Index (Apache Commons Math (Legacy) 4.0-SNAPSHOT API)

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A

aarstAndVanLaarhoven(double) - Static method in interface org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing.CoolingSchedule: Aarst and van Laarhoven (1985) scheme: \[ T_{i + 1} = \frac{T_{i}}{1 + \frac{T_i \ln(1 + \delta)}{3 \sigma}} \]
ABOVE_SIDE - org.apache.commons.math4.legacy.analysis.solvers.AllowedSolution: Only solutions for which values are greater than or equal to zero are acceptable as solutions for root-finding.
abs() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
abs() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
Abs - Class in org.apache.commons.math4.legacy.analysis.function: Absolute value function.
Abs() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Abs
AbstractConvergenceChecker<PAIR> - Class in org.apache.commons.math4.legacy.optim: Base class for all convergence checker implementations.
AbstractConvergenceChecker(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.AbstractConvergenceChecker: Build an instance with a specified thresholds.
AbstractCurveFitter - Class in org.apache.commons.math4.legacy.fitting: Base class that contains common code for fitting parametric univariate real functions y = f(p_i;x), where x is the independent variable and the p_i are the parameters.
AbstractCurveFitter() - Constructor for class org.apache.commons.math4.legacy.fitting.AbstractCurveFitter
AbstractCurveFitter.TheoreticalValuesFunction - Class in org.apache.commons.math4.legacy.fitting: Vector function for computing function theoretical values.
AbstractEvaluation - Class in org.apache.commons.math4.legacy.fitting.leastsquares: An implementation of LeastSquaresProblem.Evaluation that is designed for extension.
AbstractFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: Base class managing common boilerplate for all integrators.
AbstractFieldIntegrator(Field<T>, String) - Constructor for class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Build an instance.
AbstractFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Basic implementation of FieldMatrix methods regardless of the underlying storage.
AbstractFieldMatrix() - Constructor for class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Constructor for use with Serializable.
AbstractFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Creates a matrix with no data.
AbstractFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Create a new FieldMatrix<T> with the supplied row and column dimensions.
AbstractFieldStepInterpolator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.sampling: This abstract class represents an interpolator over the last step during an ODE integration.
AbstractFieldStepInterpolator(boolean, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Simple constructor.
AbstractIntegerDistribution - Class in org.apache.commons.math4.legacy.distribution: Base class for integer-valued discrete distributions.
AbstractIntegerDistribution() - Constructor for class org.apache.commons.math4.legacy.distribution.AbstractIntegerDistribution
AbstractIntegrator - Class in org.apache.commons.math4.legacy.ode: Base class managing common boilerplate for all integrators.
AbstractIntegrator() - Constructor for class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Build an instance with a null name.
AbstractIntegrator(String) - Constructor for class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Build an instance.
AbstractListChromosome<T> - Class in org.apache.commons.math4.legacy.genetics: Chromosome represented by an immutable list of a fixed length.
AbstractListChromosome(List<T>) - Constructor for class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Constructor, copying the input representation.
AbstractListChromosome(List<T>, boolean) - Constructor for class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Constructor.
AbstractListChromosome(T[]) - Constructor for class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Constructor, copying the input representation.
AbstractMultipleLinearRegression - Class in org.apache.commons.math4.legacy.stat.regression: Abstract base class for implementations of MultipleLinearRegression.
AbstractMultipleLinearRegression() - Constructor for class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression
AbstractMultivariateRealDistribution - Class in org.apache.commons.math4.legacy.distribution: Base class for multivariate probability distributions.
AbstractMultivariateRealDistribution(int) - Constructor for class org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution
AbstractOptimizationProblem<PAIR> - Class in org.apache.commons.math4.legacy.optim: Base class for implementing optimization problems.
AbstractOptimizationProblem(int, int, ConvergenceChecker<PAIR>) - Constructor for class org.apache.commons.math4.legacy.optim.AbstractOptimizationProblem: Create an AbstractOptimizationProblem from the given data.
AbstractParameterizable - Class in org.apache.commons.math4.legacy.ode: This abstract class provides boilerplate parameters list.
AbstractParameterizable(String...) - Constructor for class org.apache.commons.math4.legacy.ode.AbstractParameterizable: Simple constructor.
AbstractParameterizable(Collection<String>) - Constructor for class org.apache.commons.math4.legacy.ode.AbstractParameterizable: Simple constructor.
AbstractPolynomialSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Base class for solvers.
AbstractPolynomialSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractPolynomialSolver: Construct a solver with given absolute accuracy.
AbstractPolynomialSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractPolynomialSolver: Construct a solver with given accuracies.
AbstractPolynomialSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractPolynomialSolver: Construct a solver with given accuracies.
AbstractRealDistribution - Class in org.apache.commons.math4.legacy.distribution: Base class for probability distributions on the reals.
AbstractRealDistribution() - Constructor for class org.apache.commons.math4.legacy.distribution.AbstractRealDistribution
AbstractRealMatrix - Class in org.apache.commons.math4.legacy.linear: Basic implementation of RealMatrix methods regardless of the underlying storage.
AbstractRealMatrix() - Constructor for class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Creates a matrix with no data.
AbstractRealMatrix(int, int) - Constructor for class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Create a new RealMatrix with the supplied row and column dimensions.
AbstractStepInterpolator - Class in org.apache.commons.math4.legacy.ode.sampling: This abstract class represents an interpolator over the last step during an ODE integration.
AbstractStepInterpolator() - Constructor for class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Simple constructor.
AbstractStepInterpolator(double[], boolean, EquationsMapper, EquationsMapper[]) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Simple constructor.
AbstractStepInterpolator(AbstractStepInterpolator) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Copy constructor.
AbstractStorelessUnivariateStatistic - Class in org.apache.commons.math4.legacy.stat.descriptive: Abstract base class for implementations of the StorelessUnivariateStatistic interface.
AbstractStorelessUnivariateStatistic() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic
AbstractUnivariateDifferentiableSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Provide a default implementation for several functions useful to generic solvers.
AbstractUnivariateDifferentiableSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateDifferentiableSolver: Construct a solver with given absolute accuracy.
AbstractUnivariateDifferentiableSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateDifferentiableSolver: Construct a solver with given accuracies.
AbstractUnivariateSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Base class for solvers.
AbstractUnivariateSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateSolver: Construct a solver with given absolute accuracy.
AbstractUnivariateSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateSolver: Construct a solver with given accuracies.
AbstractUnivariateSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateSolver: Construct a solver with given accuracies.
AbstractUnivariateStatistic - Class in org.apache.commons.math4.legacy.stat.descriptive: Abstract base class for implementations of the UnivariateStatistic interface.
AbstractUnivariateStatistic() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic
acceptStep(AbstractFieldStepInterpolator<T>, T) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Accept a step, triggering events and step handlers.
acceptStep(AbstractStepInterpolator, double[], double[], double) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Accept a step, triggering events and step handlers.
acos() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
acos() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
acos(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute arc cosine of a derivative structure.
Acos - Class in org.apache.commons.math4.legacy.analysis.function: Arc-cosine function.
Acos() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Acos
acosh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
acosh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
acosh(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute inverse hyperbolic cosine of a derivative structure.
Acosh - Class in org.apache.commons.math4.legacy.analysis.function: Hyperbolic arc-cosine function.
Acosh() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Acosh
Action - Enum in org.apache.commons.math4.legacy.ode.events: Enumerate for actions to be performed when an event occurs during ODE integration.
AdamsBashforthFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements explicit Adams-Bashforth integrators for Ordinary Differential Equations.
AdamsBashforthFieldIntegrator(Field<T>, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsBashforthFieldIntegrator: Build an Adams-Bashforth integrator with the given order and step control parameters.
AdamsBashforthFieldIntegrator(Field<T>, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsBashforthFieldIntegrator: Build an Adams-Bashforth integrator with the given order and step control parameters.
AdamsBashforthIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements explicit Adams-Bashforth integrators for Ordinary Differential Equations.
AdamsBashforthIntegrator(int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsBashforthIntegrator: Build an Adams-Bashforth integrator with the given order and step control parameters.
AdamsBashforthIntegrator(int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsBashforthIntegrator: Build an Adams-Bashforth integrator with the given order and step control parameters.
AdamsFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: Base class for Adams-Bashforth and Adams-Moulton integrators.
AdamsFieldIntegrator(Field<T>, String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsFieldIntegrator: Build an Adams integrator with the given order and step control parameters.
AdamsFieldIntegrator(Field<T>, String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsFieldIntegrator: Build an Adams integrator with the given order and step control parameters.
AdamsIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: Base class for Adams-Bashforth and Adams-Moulton integrators.
AdamsIntegrator(String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsIntegrator: Build an Adams integrator with the given order and step control parameters.
AdamsIntegrator(String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsIntegrator: Build an Adams integrator with the given order and step control parameters.
AdamsMoultonFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements implicit Adams-Moulton integrators for Ordinary Differential Equations.
AdamsMoultonFieldIntegrator(Field<T>, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsMoultonFieldIntegrator: Build an Adams-Moulton integrator with the given order and error control parameters.
AdamsMoultonFieldIntegrator(Field<T>, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsMoultonFieldIntegrator: Build an Adams-Moulton integrator with the given order and error control parameters.
AdamsMoultonIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements implicit Adams-Moulton integrators for Ordinary Differential Equations.
AdamsMoultonIntegrator(int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsMoultonIntegrator: Build an Adams-Moulton integrator with the given order and error control parameters.
AdamsMoultonIntegrator(int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdamsMoultonIntegrator: Build an Adams-Moulton integrator with the given order and error control parameters.
AdamsNordsieckFieldTransformer<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: Transformer to Nordsieck vectors for Adams integrators.
AdamsNordsieckTransformer - Class in org.apache.commons.math4.legacy.ode.nonstiff: Transformer to Nordsieck vectors for Adams integrators.
AdaptiveStepsizeFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This abstract class holds the common part of all adaptive stepsize integrators for Ordinary Differential Equations.
AdaptiveStepsizeFieldIntegrator(Field<T>, String, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Build an integrator with the given stepsize bounds.
AdaptiveStepsizeFieldIntegrator(Field<T>, String, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Build an integrator with the given stepsize bounds.
AdaptiveStepsizeIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This abstract class holds the common part of all adaptive stepsize integrators for Ordinary Differential Equations.
AdaptiveStepsizeIntegrator(String, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Build an integrator with the given stepsize bounds.
AdaptiveStepsizeIntegrator(String, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Build an integrator with the given stepsize bounds.
add(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
add(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
add(double[], boolean) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Replace i-th facet of the microsphere.
add(double[], int, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Perform addition of two derivative structures.
add(double, double) - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoints: Adds a point to the sample.
add(double, double, double) - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoints: Adds a point to the sample.
add(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
add(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
add(UnivariateDifferentiableFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Adds functions.
add(PolynomialFunction) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Add a polynomial to the instance.
add(UnivariateFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Adds functions.
add(FieldDenseMatrix<T>) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Addition.
add(WeightedObservedPoint) - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoints: Adds a point to the sample.
add(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Add m to this matrix.
add(Array2DRowRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Compute the sum of this and m.
add(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute the sum of this and v.
add(BigReal) - Method in class org.apache.commons.math4.legacy.linear.BigReal
add(BlockFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Compute the sum of this and m.
add(BlockRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Compute the sum of this matrix and m.
add(DiagonalMatrix) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Compute the sum of this and m.
add(FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Compute the sum of this and m.
add(FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Compute the sum of this and m.
add(FieldMatrix<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Compute the sum of this and m.
add(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute the sum of this and v.
add(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Compute the sum of this and v.
add(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Compute the sum of this and v.
add(OpenMapRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Compute the sum of this matrix and m.
add(OpenMapRealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Optimized method to add two OpenMapRealVectors.
add(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the sum of this and m.
add(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the sum of this and m.
add(RealMatrix) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the sum of this and m.
add(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Compute the sum of this vector and v.
add(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Compute the sum of this vector and v.
add(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Compute the sum of this vector and v.
add(SparseFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Optimized method to add sparse vectors.
Add - Class in org.apache.commons.math4.legacy.analysis.function: Add the two operands.
Add() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Add
addChromosome(Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Add the given chromosome to the population.
addChromosome(Chromosome) - Method in interface org.apache.commons.math4.legacy.genetics.Population: Add the given chromosome to the population.
addChromosomes(Collection<Chromosome>) - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Add a Collection of chromosomes to this Population.
addData(double[][]) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Adds the observations represented by the elements in data.
addData(double, double) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Adds the observation (x,y) to the regression data set.
addEventHandler(EventHandler, double, double, int) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int) - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int, UnivariateSolver) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int, UnivariateSolver) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Add an event handler to the integrator.
addEventHandler(EventHandler, double, double, int, UnivariateSolver) - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Add an event handler to the integrator.
addEventHandler(FieldEventHandler<T>, double, double, int) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Add an event handler to the integrator.
addEventHandler(FieldEventHandler<T>, double, double, int) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Add an event handler to the integrator.
addEventHandler(FieldEventHandler<T>, double, double, int, BracketedRealFieldUnivariateSolver<T>) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Add an event handler to the integrator.
addEventHandler(FieldEventHandler<T>, double, double, int, BracketedRealFieldUnivariateSolver<T>) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Add an event handler to the integrator.
addInPlace(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Add in place.
addIterationListener(IterationListener) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Attaches a listener to this manager.
addObservation(double[], double) - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Adds an observation to the regression model.
addObservation(double[], double) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Adds one observation to the regression model.
addObservation(double[], double) - Method in interface org.apache.commons.math4.legacy.stat.regression.UpdatingMultipleLinearRegression: Adds one observation to the regression model.
addObservations(double[][], double[]) - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Adds multiple observations to the model.
addObservations(double[][], double[]) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Adds a series of observations to the regression model.
addObservations(double[][], double[]) - Method in interface org.apache.commons.math4.legacy.stat.regression.UpdatingMultipleLinearRegression: Adds a series of observations to the regression model.
addObserver(SimplexOptimizer.Observer) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.SimplexOptimizer: Register a callback.
addParameterJacobianProvider(ParameterJacobianProvider) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Add a parameter Jacobian provider.
addPoint(T) - Method in class org.apache.commons.math4.legacy.ml.clustering.Cluster: Add a point to this cluster.
addRule(Pair<T[], T[]>) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.BaseRuleFactory: Stores a rule.
addSamplePoint(double, double[]...) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.HermiteInterpolator: Add a sample point.
addSamplePoint(T, T[]...) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.FieldHermiteInterpolator: Add a sample point.
addSecondaryEquations(FieldSecondaryEquations<T>) - Method in class org.apache.commons.math4.legacy.ode.FieldExpandableODE: Add a set of secondary equations to be integrated along with the primary set.
addSecondaryEquations(SecondaryEquations) - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Add a set of secondary equations to be integrated along with the primary set.
addStepHandler(FieldStepHandler<T>) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Add a step handler to this integrator.
addStepHandler(FieldStepHandler<T>) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Add a step handler to this integrator.
addStepHandler(StepHandler) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Add a step handler to this integrator.
addStepHandler(StepHandler) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Add a step handler to this integrator.
addStepHandler(StepHandler) - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Add a step handler to this integrator.
addToEntry(int, double) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Change an entry at the specified index.
addToEntry(int, double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Change an entry at the specified index.
addToEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, double) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Adds (in place) the specified value to the specified entry of this matrix.
addToEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Change an entry in the specified row and column.
addToEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Change an entry in the specified row and column.
addValue(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Adds the value to the dataset.
addValue(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Add a value to the data.
addValue(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Adds the value to the dataset.
addValue(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Add a value to the data.
addValue(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Add an n-tuple to the data.
addValue(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Add an n-tuple to the data.
addValue(T) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Adds 1 to the frequency count for v.
advance(RealVector.Entry) - Method in class org.apache.commons.math4.legacy.linear.RealVector.SparseEntryIterator: Advance an entry up to the next nonzero one.
aggregate(Collection<? extends StatisticalSummary>) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Computes aggregate summary statistics.
AggregateSummaryStatistics - Class in org.apache.commons.math4.legacy.stat.descriptive: An aggregator for SummaryStatistics from several data sets or data set partitions.
AggregateSummaryStatistics() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Initializes a new AggregateSummaryStatistics with default statistics implementations.
AggregateSummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Initializes a new AggregateSummaryStatistics with the specified statistics object as a prototype for contributing statistics and for the internal aggregate statistics.
AggregateSummaryStatistics(SummaryStatistics, SummaryStatistics) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Initializes a new AggregateSummaryStatistics with the specified statistics object as a prototype for contributing statistics and for the internal aggregate statistics.
AgrestiCoullInterval - Class in org.apache.commons.math4.legacy.stat.interval: Implements the Agresti-Coull method for creating a binomial proportion confidence interval.
AgrestiCoullInterval() - Constructor for class org.apache.commons.math4.legacy.stat.interval.AgrestiCoullInterval
AkimaSplineInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Computes a cubic spline interpolation for the data set using the Akima algorithm, as originally formulated by Hiroshi Akima in his 1970 paper "A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures." J.
AkimaSplineInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.AkimaSplineInterpolator: Uses the original Akima algorithm.
AkimaSplineInterpolator(boolean) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.AkimaSplineInterpolator
AllowedSolution - Enum in org.apache.commons.math4.legacy.analysis.solvers: The kinds of solutions that a (bracketed univariate real) root-finding algorithm may accept as solutions.
alongAxes(double[]) - Static method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: The start configuration for simplex is built from a box parallel to the canonical axes of the space.
AlternativeHypothesis - Enum in org.apache.commons.math4.legacy.stat.inference: Represents an alternative hypothesis for a hypothesis test.
anovaFValue(Collection<double[]>) - Method in class org.apache.commons.math4.legacy.stat.inference.OneWayAnova: Computes the ANOVA F-value for a collection of double[] arrays.
anovaPValue(Collection<double[]>) - Method in class org.apache.commons.math4.legacy.stat.inference.OneWayAnova: Computes the ANOVA P-value for a collection of double[] arrays.
anovaPValue(Collection<SummaryStatistics>, boolean) - Method in class org.apache.commons.math4.legacy.stat.inference.OneWayAnova: Computes the ANOVA P-value for a collection of SummaryStatistics.
anovaTest(Collection<double[]>, double) - Method in class org.apache.commons.math4.legacy.stat.inference.OneWayAnova: Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.
ANY_SIDE - org.apache.commons.math4.legacy.analysis.solvers.AllowedSolution: There are no additional side restriction on the solutions for root-finding.
AnyMatrix - Interface in org.apache.commons.math4.legacy.linear: Interface defining very basic matrix operations.
append(double) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a new vector by appending a double to this vector.
append(double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Construct a new vector by appending a double to this vector.
append(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Construct a new vector by appending a double to this vector.
append(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending a vector to this vector.
append(ArrayRealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending a vector to this vector.
append(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending a vector to this vector.
append(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Construct a vector by appending a vector to this vector.
append(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Construct a vector by appending a vector to this vector.
append(OpenMapRealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Optimized method to append a OpenMapRealVector.
append(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a new vector by appending a vector to this vector.
append(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Construct a new vector by appending a vector to this vector.
append(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Construct a new vector by appending a vector to this vector.
append(SparseFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Construct a vector by appending a vector to this vector.
append(ContinuousOutputFieldModel<T>) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputFieldModel: Append another model at the end of the instance.
append(ContinuousOutputModel) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Append another model at the end of the instance.
append(StorelessCovariance) - Method in class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Appends sc to this, effectively aggregating the computations in sc with this.
append(SimpleRegression) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Appends data from another regression calculation to this one.
append(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending a T to this vector.
append(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Construct a vector by appending a T to this vector.
append(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Construct a vector by appending a T to this vector.
apply(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Apply the given statistic to the data associated with this set of statistics.
apply(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Apply the given statistic to the data associated with this set of statistics.
applyAsDouble(double) - Method in interface org.apache.commons.math4.legacy.analysis.UnivariateFunction
applyAsDouble(double, double) - Method in interface org.apache.commons.math4.legacy.analysis.BivariateFunction
approximateP(double, int, int) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
approximateP(double, int, int) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Uses the Kolmogorov-Smirnov distribution to approximate \(P(D_{n,m} > d)\) where \(D_{n,m}\) is the 2-sample Kolmogorov-Smirnov statistic.
Array2DRowFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Implementation of FieldMatrix<T> using a FieldElement[][] array to store entries.
Array2DRowFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Creates a matrix with no data.
Array2DRowFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> with the supplied row and column dimensions.
Array2DRowFieldMatrix(Field<T>, T[]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new (column) FieldMatrix<T> using v as the data for the unique column of the created matrix.
Array2DRowFieldMatrix(Field<T>, T[][]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> using the input array as the underlying data array.
Array2DRowFieldMatrix(Field<T>, T[][], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> using the input array as the underlying data array.
Array2DRowFieldMatrix(T[]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new (column) FieldMatrix<T> using v as the data for the unique column of the created matrix.
Array2DRowFieldMatrix(T[][]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> using the input array as the underlying data array.
Array2DRowFieldMatrix(T[][], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> using the input array as the underlying data array.
Array2DRowRealMatrix - Class in org.apache.commons.math4.legacy.linear: Implementation of RealMatrix using a double[][] array to store entries.
Array2DRowRealMatrix() - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Creates a matrix with no data.
Array2DRowRealMatrix(double[]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Create a new (column) RealMatrix using v as the data for the unique column of the created matrix.
Array2DRowRealMatrix(double[][]) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Create a new RealMatrix using the input array as the underlying data array.
Array2DRowRealMatrix(double[][], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Create a new RealMatrix using the input array as the underlying data array.
Array2DRowRealMatrix(int, int) - Constructor for class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Create a new RealMatrix with the supplied row and column dimensions.
ArrayFieldVector<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: This class implements the FieldVector interface with a FieldElement array.
ArrayFieldVector(int, T) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector with preset values.
ArrayFieldVector(Field<T>) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Build a 0-length vector.
ArrayFieldVector(Field<T>, int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector of zeroes.
ArrayFieldVector(Field<T>, T[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from an array, copying the input array.
ArrayFieldVector(Field<T>, T[], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Create a new ArrayFieldVector using the input array as the underlying data array.
ArrayFieldVector(Field<T>, T[], int, int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from part of a array.
ArrayFieldVector(Field<T>, T[], T[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending one vector to another vector.
ArrayFieldVector(ArrayFieldVector<T>) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from another vector, using a deep copy.
ArrayFieldVector(ArrayFieldVector<T>, boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from another vector.
ArrayFieldVector(FieldVector<T>) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from another vector, using a deep copy.
ArrayFieldVector(FieldVector<T>, FieldVector<T>) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending one vector to another vector.
ArrayFieldVector(FieldVector<T>, T[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending one vector to another vector.
ArrayFieldVector(T[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from an array, copying the input array.
ArrayFieldVector(T[], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Create a new ArrayFieldVector using the input array as the underlying data array.
ArrayFieldVector(T[], int, int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector from part of a array.
ArrayFieldVector(T[], FieldVector<T>) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending one vector to another vector.
ArrayFieldVector(T[], T[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Construct a vector by appending one vector to another vector.
ArrayRealVector - Class in org.apache.commons.math4.legacy.linear: This class implements the RealVector interface with a double array.
ArrayRealVector() - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Build a 0-length vector.
ArrayRealVector(double[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from an array, copying the input array.
ArrayRealVector(double[], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Create a new ArrayRealVector using the input array as the underlying data array.
ArrayRealVector(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
ArrayRealVector(double[], int, int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from part of a array.
ArrayRealVector(double[], ArrayRealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
ArrayRealVector(int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector of zeroes.
ArrayRealVector(int, double) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector with preset values.
ArrayRealVector(Double[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from an array.
ArrayRealVector(Double[], int, int) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from part of an array.
ArrayRealVector(ArrayRealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from another vector, using a deep copy.
ArrayRealVector(ArrayRealVector, boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from another vector.
ArrayRealVector(ArrayRealVector, double[]) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
ArrayRealVector(ArrayRealVector, ArrayRealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
ArrayRealVector(ArrayRealVector, RealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
ArrayRealVector(RealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector from another vector, using a deep copy.
ArrayRealVector(RealVector, ArrayRealVector) - Constructor for class org.apache.commons.math4.legacy.linear.ArrayRealVector: Construct a vector by appending one vector to another vector.
asin() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
asin() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
asin(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute arc sine of a derivative structure.
Asin - Class in org.apache.commons.math4.legacy.analysis.function: Arc-sine function.
Asin() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Asin
asinh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
asinh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
asinh(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute inverse hyperbolic sine of a derivative structure.
Asinh - Class in org.apache.commons.math4.legacy.analysis.function: Hyperbolic arc-sine function.
Asinh() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Asinh
asList() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Creates a (deep) copy of the simplex points.
atan() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
atan() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
atan(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute arc tangent of a derivative structure.
Atan - Class in org.apache.commons.math4.legacy.analysis.function: Arc-tangent function.
Atan() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Atan
atan2(double[], int, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute two arguments arc tangent of a derivative structure.
atan2(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
atan2(DerivativeStructure, DerivativeStructure) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Two arguments arc tangent operation.
atan2(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
atan2(SparseGradient, SparseGradient) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Two arguments arc tangent operation.
Atan2 - Class in org.apache.commons.math4.legacy.analysis.function: Arc-tangent function.
Atan2() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Atan2
atanh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
atanh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
atanh(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute inverse hyperbolic tangent of a derivative structure.
Atanh - Class in org.apache.commons.math4.legacy.analysis.function: Hyperbolic arc-tangent function.
Atanh() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Atanh
AVERAGE - org.apache.commons.math4.legacy.stat.ranking.TiesStrategy: Ties get the average of applicable ranks.

B

BaseAbstractUnivariateIntegrator - Class in org.apache.commons.math4.legacy.analysis.integration: Provide a default implementation for several generic functions.
BaseAbstractUnivariateIntegrator(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Construct an integrator with given accuracies.
BaseAbstractUnivariateIntegrator(double, double, int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Construct an integrator with given accuracies and iteration counts.
BaseAbstractUnivariateIntegrator(int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Construct an integrator with given iteration counts.
BaseAbstractUnivariateSolver<FUNC extends UnivariateFunction> - Class in org.apache.commons.math4.legacy.analysis.solvers: Provide a default implementation for several functions useful to generic solvers.
BaseAbstractUnivariateSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Construct a solver with given absolute accuracy.
BaseAbstractUnivariateSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Construct a solver with given accuracies.
BaseAbstractUnivariateSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Construct a solver with given accuracies.
BaseMultiStartMultivariateOptimizer<PAIR> - Class in org.apache.commons.math4.legacy.optim: Base class multi-start optimizer for a multivariate function.
BaseMultiStartMultivariateOptimizer(BaseMultivariateOptimizer<PAIR>, int, Supplier<double[]>) - Constructor for class org.apache.commons.math4.legacy.optim.BaseMultiStartMultivariateOptimizer: Create a multi-start optimizer from a single-start optimizer.
BaseMultivariateOptimizer<PAIR> - Class in org.apache.commons.math4.legacy.optim: Base class for implementing optimizers for multivariate functions.
BaseMultivariateOptimizer(ConvergenceChecker<PAIR>) - Constructor for class org.apache.commons.math4.legacy.optim.BaseMultivariateOptimizer
BaseOptimizer<PAIR> - Class in org.apache.commons.math4.legacy.optim: Base class for implementing optimizers.
BaseOptimizer(ConvergenceChecker<PAIR>) - Constructor for class org.apache.commons.math4.legacy.optim.BaseOptimizer
BaseOptimizer(ConvergenceChecker<PAIR>, int, int) - Constructor for class org.apache.commons.math4.legacy.optim.BaseOptimizer
BaseRuleFactory<T extends Number> - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: Base class for rules that determines the integration nodes and their weights.
BaseRuleFactory() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.BaseRuleFactory
BaseSecantSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Base class for all bracketing Secant-based methods for root-finding (approximating a zero of a univariate real function).
BaseSecantSolver(double, double, double, BaseSecantSolver.Method) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Construct a solver.
BaseSecantSolver(double, double, BaseSecantSolver.Method) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Construct a solver.
BaseSecantSolver(double, BaseSecantSolver.Method) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Construct a solver.
BaseSecantSolver.Method - Enum in org.apache.commons.math4.legacy.analysis.solvers: Secant-based root-finding methods.
BaseUnivariateSolver<FUNC extends UnivariateFunction> - Interface in org.apache.commons.math4.legacy.analysis.solvers: Interface for (univariate real) rootfinding algorithms.
BELOW_SIDE - org.apache.commons.math4.legacy.analysis.solvers.AllowedSolution: Only solutions for which values are less than or equal to zero are acceptable as solutions for root-finding.
BesselJ - Class in org.apache.commons.math4.legacy.special: This class provides computation methods related to Bessel functions of the first kind.
BesselJ(double) - Constructor for class org.apache.commons.math4.legacy.special.BesselJ: Create a new BesselJ with the given order.
BesselJ.BesselJResult - Class in org.apache.commons.math4.legacy.special: Encapsulates the results returned by BesselJ.rjBesl(double, double, int).
BesselJResult(double[], int) - Constructor for class org.apache.commons.math4.legacy.special.BesselJ.BesselJResult: Create a new BesselJResult with the given values and valid value count.
BicubicInterpolatingFunction - Class in org.apache.commons.math4.legacy.analysis.interpolation: Function that implements the bicubic spline interpolation.
BicubicInterpolatingFunction(double[], double[], double[][], double[][], double[][], double[][]) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction
BicubicInterpolatingFunction(double[], double[], double[][], double[][], double[][], double[][], boolean) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction
BicubicInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Generates a bicubic interpolating function.
BicubicInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolator: Default constructor.
BicubicInterpolator(boolean) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolator: Creates an interpolator.
bigDecimalValue() - Method in class org.apache.commons.math4.legacy.linear.BigReal: Get the BigDecimal value corresponding to the instance.
BigReal - Class in org.apache.commons.math4.legacy.linear: Arbitrary precision decimal number.
BigReal(char[]) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a characters representation.
BigReal(char[], int, int) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a characters representation.
BigReal(char[], int, int, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a characters representation.
BigReal(char[], MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a characters representation.
BigReal(double) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a double.
BigReal(double, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a double.
BigReal(int) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from an int.
BigReal(int, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from an int.
BigReal(long) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a long.
BigReal(long, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a long.
BigReal(String) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a String representation.
BigReal(String, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a String representation.
BigReal(BigDecimal) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a BigDecimal.
BigReal(BigInteger) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a BigInteger.
BigReal(BigInteger, int) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from an unscaled BigInteger.
BigReal(BigInteger, int, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from an unscaled BigInteger.
BigReal(BigInteger, MathContext) - Constructor for class org.apache.commons.math4.legacy.linear.BigReal: Build an instance from a BigInteger.
BigRealField - Class in org.apache.commons.math4.legacy.linear: Representation of real numbers with arbitrary precision field.
BinaryChromosome - Class in org.apache.commons.math4.legacy.genetics: Chromosome represented by a vector of 0s and 1s.
BinaryChromosome(Integer[]) - Constructor for class org.apache.commons.math4.legacy.genetics.BinaryChromosome: Constructor.
BinaryChromosome(List<Integer>) - Constructor for class org.apache.commons.math4.legacy.genetics.BinaryChromosome: Constructor.
BinaryMutation - Class in org.apache.commons.math4.legacy.genetics: Mutation for BinaryChromosomes.
BinaryMutation() - Constructor for class org.apache.commons.math4.legacy.genetics.BinaryMutation
BinomialConfidenceInterval - Interface in org.apache.commons.math4.legacy.stat.interval: Interface to generate confidence intervals for a binomial proportion.
binomialTest(int, int, double, AlternativeHypothesis) - Method in class org.apache.commons.math4.legacy.stat.inference.BinomialTest: Returns the observed significance level, or p-value, associated with a Binomial test.
binomialTest(int, int, double, AlternativeHypothesis, double) - Method in class org.apache.commons.math4.legacy.stat.inference.BinomialTest: Returns whether the null hypothesis can be rejected with the given confidence level.
BinomialTest - Class in org.apache.commons.math4.legacy.stat.inference: Implements binomial test statistics.
BinomialTest() - Constructor for class org.apache.commons.math4.legacy.stat.inference.BinomialTest
BisectionSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Implements the bisection algorithm for finding zeros of univariate real functions.
BisectionSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BisectionSolver: Construct a solver with default accuracy (1e-6).
BisectionSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BisectionSolver: Construct a solver.
BisectionSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BisectionSolver: Construct a solver.
BivariateFunction - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a bivariate real function.
BivariateGridInterpolator - Interface in org.apache.commons.math4.legacy.analysis.interpolation: Interface representing a bivariate real interpolating function where the sample points must be specified on a regular grid.
BLAND - org.apache.commons.math4.legacy.optim.linear.PivotSelectionRule: The first variable with a negative coefficient in the objective function row will be chosen as entering variable.
BLOCK_SIZE - Static variable in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Block size.
BLOCK_SIZE - Static variable in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Block size.
BlockFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Cache-friendly implementation of FieldMatrix using a flat arrays to store square blocks of the matrix.
BlockFieldMatrix(int, int, T[][], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Create a new dense matrix copying entries from block layout data.
BlockFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Create a new matrix with the supplied row and column dimensions.
BlockFieldMatrix(T[][]) - Constructor for class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Create a new dense matrix copying entries from raw layout data.
blockInverse(RealMatrix, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Computes the inverse of the given matrix by splitting it into 4 sub-matrices.
BlockRealMatrix - Class in org.apache.commons.math4.legacy.linear: Cache-friendly implementation of RealMatrix using a flat arrays to store square blocks of the matrix.
BlockRealMatrix(double[][]) - Constructor for class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Create a new dense matrix copying entries from raw layout data.
BlockRealMatrix(int, int) - Constructor for class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Create a new matrix with the supplied row and column dimensions.
BlockRealMatrix(int, int, double[][], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Create a new dense matrix copying entries from block layout data.
BOBYQAOptimizer - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: Powell's BOBYQA algorithm.
BOBYQAOptimizer(int) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer
BOBYQAOptimizer(int, double, double) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer
bootstrap(double[], double[], int, boolean, UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Estimates the p-value of a two-sample Kolmogorov-Smirnov test evaluating the null hypothesis that x and y are samples drawn from the same probability distribution.
BOTH - org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Include both the first and last points.
boundedToUnbounded(double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateFunctionMappingAdapter: Maps an array from bounded to unbounded.
bracket(UnivariateFunction, double, double, double) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: This method simply calls bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations) with q and r set to 1.0 and maximumIterations set to Integer.MAX_VALUE.
bracket(UnivariateFunction, double, double, double, double, double, int) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: This method attempts to find two values a and b satisfying lowerBound <= a < initial < b <= upperBound f(a) * f(b) <= 0 If f is continuous on [a,b], this means that a and b bracket a root of f.
bracket(UnivariateFunction, double, double, double, int) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: This method simply calls bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations) with q and r set to 1.0.
BracketedRealFieldUnivariateSolver<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.analysis.solvers: Interface for (univariate real) root-finding algorithms that maintain a bracketed solution.
BracketedUnivariateSolver<FUNC extends UnivariateFunction> - Interface in org.apache.commons.math4.legacy.analysis.solvers: Interface for (univariate real) root-finding algorithms that maintain a bracketed solution.
BracketFinder - Class in org.apache.commons.math4.legacy.optim.univariate: Provide an interval that brackets a local optimum of a function.
BracketFinder() - Constructor for class org.apache.commons.math4.legacy.optim.univariate.BracketFinder: Constructor with default values 100, 500 (see the other constructor).
BracketFinder(double, int) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.BracketFinder: Create a bracketing interval finder.
BracketingNthOrderBrentSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: This class implements a modification of the Brent algorithm.
BracketingNthOrderBrentSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Construct a solver with default accuracy and maximal order (1e-6 and 5 respectively).
BracketingNthOrderBrentSolver(double, double, double, int) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Construct a solver.
BracketingNthOrderBrentSolver(double, double, int) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Construct a solver.
BracketingNthOrderBrentSolver(double, int) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Construct a solver.
BrentOptimizer - Class in org.apache.commons.math4.legacy.optim.univariate: For a function defined on some interval (lo, hi), this class finds an approximation x to the point at which the function attains its minimum.
BrentOptimizer(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.BrentOptimizer: The arguments are used for implementing the original stopping criterion of Brent's algorithm.
BrentOptimizer(double, double, ConvergenceChecker<UnivariatePointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.BrentOptimizer: The arguments are used implement the original stopping criterion of Brent's algorithm.
BrentSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: This class implements the Brent algorithm for finding zeros of real univariate functions.
BrentSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BrentSolver: Construct a solver with default absolute accuracy (1e-6).
BrentSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BrentSolver: Construct a solver.
BrentSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BrentSolver: Construct a solver.
BrentSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.BrentSolver: Construct a solver.
build() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Construct a LeastSquaresProblem from the data in this builder.

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calculateAdjustedRSquared() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Returns the adjusted R-squared statistic, defined by the formula R²_adj = 1 - [SSR (n - 1)] / [SSTO (n - p)] where SSR is the sum of squared residuals, SSTO is the total sum of squares, n is the number of observations and p is the number of parameters estimated (including the intercept).
calculateBeta() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Calculates the beta of multiple linear regression in matrix notation.
calculateBeta() - Method in class org.apache.commons.math4.legacy.stat.regression.GLSMultipleLinearRegression: Calculates beta by GLS.
calculateBeta() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Calculates the regression coefficients using OLS.
calculateBetaVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Calculates the beta variance of multiple linear regression in matrix notation.
calculateBetaVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.GLSMultipleLinearRegression: Calculates the variance on the beta.
calculateBetaVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Calculates the variance-covariance matrix of the regression parameters.
calculateErrorVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Calculates the variance of the error term.
calculateErrorVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.GLSMultipleLinearRegression: Calculates the estimated variance of the error term using the formula
calculateHat() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Compute the "hat" matrix.
calculateResiduals() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Calculates the residuals of multiple linear regression in matrix notation.
calculateResidualSumOfSquares() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Returns the sum of squared residuals.
calculateRSquared() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Returns the R-Squared statistic, defined by the formula R² = 1 - SSR / SSTO where SSR is the sum of squared residuals and SSTO is the total sum of squares
calculateTotalSumOfSquares() - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Returns the sum of squared deviations of Y from its mean.
calculateYVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Calculates the variance of the y values.
CalinskiHarabasz - Class in org.apache.commons.math4.legacy.ml.clustering.evaluation: Compute the Calinski and Harabasz score.
CalinskiHarabasz() - Constructor for class org.apache.commons.math4.legacy.ml.clustering.evaluation.CalinskiHarabasz
canAdd(AnyMatrix) - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Checks that this matrix and the other matrix can be added.
CanberraDistance - Class in org.apache.commons.math4.legacy.ml.distance: Calculates the Canberra distance between two points.
CanberraDistance() - Constructor for class org.apache.commons.math4.legacy.ml.distance.CanberraDistance
canMultiply(AnyMatrix) - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Checks that this matrix can be multiplied by the other matrix.
cbrt() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
cbrt() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
Cbrt - Class in org.apache.commons.math4.legacy.analysis.function: Cube root function.
Cbrt() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Cbrt
cdf(double, int) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Calculates \(P(D_n < d)\) using the method described in [1] with quick decisions for extreme values given in [2] (see above).
cdf(double, int, boolean) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Calculates P(D_n < d) using method described in [1] with quick decisions for extreme values given in [2] (see above).
cdfExact(double, int) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Calculates P(D_n < d).
ceil() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
ceil() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
Ceil - Class in org.apache.commons.math4.legacy.analysis.function: ceil function.
Ceil() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Ceil
CentralPivotingStrategy - Class in org.apache.commons.math4.legacy.stat.descriptive.rank: A mid point strategy based on the average of begin and end indices.
CentralPivotingStrategy() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.CentralPivotingStrategy
centroid() - Method in class org.apache.commons.math4.legacy.ml.clustering.Cluster: Computes the centroid of the cluster.
CentroidCluster<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: A Cluster used by centroid-based clustering algorithms.
CentroidCluster(Clusterable) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.CentroidCluster: Build a cluster centered at a specified point.
ChebyshevDistance - Class in org.apache.commons.math4.legacy.ml.distance: Calculates the L_∞ (max of abs) distance between two points.
ChebyshevDistance() - Constructor for class org.apache.commons.math4.legacy.ml.distance.ChebyshevDistance
checkAdd(AnyMatrix) - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Checks that this matrix and the other matrix can be added.
checkAdditionCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if matrices are addition compatible.
checkColumnIndex(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Check if a column index is valid.
checkColumnIndex(AnyMatrix, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if a column index is valid.
checkCompatibility(DSCompiler) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Check rules set compatibility.
checker(ConvergenceChecker<LeastSquaresProblem.Evaluation>) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the convergence checker.
checkerPair(ConvergenceChecker<PointVectorValuePair>) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the convergence checker.
checkIndex(int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Check if an index is valid.
checkIndices(int, int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Checks that the indices of a subvector are valid.
checkMatrixIndex(AnyMatrix, int, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if matrix indices are valid.
checkMultiplicationCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if matrices are multiplication compatible.
checkMultiply(AnyMatrix) - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Checks that this matrix can be multiplied by the other matrix.
checkParameters(RealLinearOperator, RealLinearOperator, RealVector, RealVector) - Static method in class org.apache.commons.math4.legacy.linear.PreconditionedIterativeLinearSolver: Performs all dimension checks on the parameters of solve and solveInPlace, and throws an exception if one of the checks fails.
checkParameters(RealLinearOperator, RealVector, RealVector) - Static method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolver: Performs all dimension checks on the parameters of solve and solveInPlace, and throws an exception if one of the checks fails.
checkRowIndex(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Check if a row index is valid.
checkRowIndex(AnyMatrix, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if a row index is valid.
checkSubMatrixIndex(int[], int[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Check if submatrix ranges indices are valid.
checkSubMatrixIndex(int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Check if submatrix ranges indices are valid.
checkSubMatrixIndex(AnyMatrix, int[], int[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if submatrix ranges indices are valid.
checkSubMatrixIndex(AnyMatrix, int, int, int, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if submatrix ranges indices are valid.
checkSubtractionCompatible(AnyMatrix, AnyMatrix) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Check if matrices are subtraction compatible.
checkSymmetric(RealMatrix, double) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Checks whether a matrix is symmetric.
checkValidity(List<Double>) - Method in class org.apache.commons.math4.legacy.genetics.RandomKey: Asserts that representation can represent a valid chromosome.
checkValidity(List<Integer>) - Method in class org.apache.commons.math4.legacy.genetics.BinaryChromosome: Asserts that representation can represent a valid chromosome.
checkValidity(List<T>) - Method in class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Asserts that representation can represent a valid chromosome.
checkVectorDimensions(int) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Check if instance dimension is equal to some expected value.
checkVectorDimensions(int) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Check if instance dimension is equal to some expected value.
checkVectorDimensions(int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Check if instance dimension is equal to some expected value.
checkVectorDimensions(int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Check if instance dimension is equal to some expected value.
checkVectorDimensions(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Check if instance and specified vectors have the same dimension.
checkVectorDimensions(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Check if instance and specified vectors have the same dimension.
checkVectorDimensions(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Check if instance and specified vectors have the same dimension.
chiSquare(double[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Computes the Chi-Square statistic comparing observed and expected frequency counts.
chiSquare(double[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquare(long[][]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Computes the Chi-Square statistic associated with a chi-square test of independence based on the input counts array, viewed as a two-way table.
chiSquare(long[][]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Computes a Chi-Square two sample test statistic comparing bin frequency counts in observed1 and observed2.
chiSquareDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareTest(double[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the observed frequency counts to those in the expected array.
chiSquareTest(double[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareTest(double[], long[], double) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha.
chiSquareTest(double[], long[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareTest(long[][]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input counts array, viewed as a two-way table.
chiSquareTest(long[][]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareTest(long[][], double) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level alpha.
chiSquareTest(long[][], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
ChiSquareTest - Class in org.apache.commons.math4.legacy.stat.inference: Implements Chi-Square test statistics.
ChiSquareTest() - Constructor for class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Construct a ChiSquareTest.
chiSquareTestDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts in observed1 and observed2.
chiSquareTestDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
chiSquareTestDataSetsComparison(long[], long[], double) - Method in class org.apache.commons.math4.legacy.stat.inference.ChiSquareTest: Performs a Chi-Square two sample test comparing two binned data sets.
chiSquareTestDataSetsComparison(long[], long[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
CHOLESKY - org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer.Decomposition: Solve by forming the normal equations (J^TJx=J^Tr) and using the CholeskyDecomposition.
CholeskyDecomposition - Class in org.apache.commons.math4.legacy.linear: Calculates the Cholesky decomposition of a matrix.
CholeskyDecomposition(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Calculates the Cholesky decomposition of the given matrix.
CholeskyDecomposition(RealMatrix, double, double) - Constructor for class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Calculates the Cholesky decomposition of the given matrix.
Chromosome - Class in org.apache.commons.math4.legacy.genetics: Individual in a population.
Chromosome() - Constructor for class org.apache.commons.math4.legacy.genetics.Chromosome
ChromosomePair - Class in org.apache.commons.math4.legacy.genetics: A pair of Chromosome objects.
ChromosomePair(Chromosome, Chromosome) - Constructor for class org.apache.commons.math4.legacy.genetics.ChromosomePair: Create a chromosome pair.
ClampedSplineInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Computes a clamped cubic spline interpolation for the data set.
ClampedSplineInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.ClampedSplineInterpolator
ClassicalRungeKuttaFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the classical fourth order Runge-Kutta integrator for Ordinary Differential Equations (it is the most often used Runge-Kutta method).
ClassicalRungeKuttaFieldIntegrator(Field<T>, T) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaFieldIntegrator: Simple constructor.
ClassicalRungeKuttaIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the classical fourth order Runge-Kutta integrator for Ordinary Differential Equations (it is the most often used Runge-Kutta method).
ClassicalRungeKuttaIntegrator(double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaIntegrator: Simple constructor.
clear() - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoints: Removes all observations from this container.
clear() - Method in class org.apache.commons.math4.legacy.optim.BaseMultiStartMultivariateOptimizer: Method that will called in order to clear all stored optima.
clear() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultiStartMultivariateOptimizer: Method that will called in order to clear all stored optima.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialCovariance: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Clears the internal state of the Statistic.
clear() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StorelessUnivariateStatistic: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Clears the internal state of the Statistic.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Resets all statistics and storage.
clear() - Method in class org.apache.commons.math4.legacy.stat.Frequency: Clears the frequency table.
clear() - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: As the name suggests, clear wipes the internals and reorders everything in the canonical order.
clear() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Clears all data from the model.
clear() - Method in interface org.apache.commons.math4.legacy.stat.regression.UpdatingMultipleLinearRegression: Clears internal buffers and resets the regression model.
clearEventHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Remove all the event handlers that have been added to the integrator.
clearEventHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Remove all the event handlers that have been added to the integrator.
clearEventHandlers() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Remove all the event handlers that have been added to the integrator.
clearEventHandlers() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Remove all the event handlers that have been added to the integrator.
clearStepHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Remove all the step handlers that have been added to the integrator.
clearStepHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Remove all the step handlers that have been added to the integrator.
clearStepHandlers() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Remove all the step handlers that have been added to the integrator.
clearStepHandlers() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Remove all the step handlers that have been added to the integrator.
ClopperPearsonInterval - Class in org.apache.commons.math4.legacy.stat.interval: Implements the Clopper-Pearson method for creating a binomial proportion confidence interval.
ClopperPearsonInterval() - Constructor for class org.apache.commons.math4.legacy.stat.interval.ClopperPearsonInterval
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.Clusterer: Perform a cluster analysis on the given set of Clusterable instances.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.DBSCANClusterer: Performs DBSCAN cluster analysis.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.ElkanKMeansPlusPlusClusterer: Runs the K-means++ clustering algorithm.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Performs Fuzzy K-Means cluster analysis.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer: Runs the K-means++ clustering algorithm.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.MiniBatchKMeansClusterer: Runs the MiniBatch K-means clustering algorithm.
cluster(Collection<T>) - Method in class org.apache.commons.math4.legacy.ml.clustering.MultiKMeansPlusPlusClusterer: Runs the K-means++ clustering algorithm.
Cluster<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: Cluster holding a set of Clusterable points.
Cluster() - Constructor for class org.apache.commons.math4.legacy.ml.clustering.Cluster: Build a cluster centered at a specified point.
Clusterable - Interface in org.apache.commons.math4.legacy.ml.clustering: Interface for n-dimensional points that can be clustered together.
Clusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: Base class for clustering algorithms.
Clusterer(DistanceMeasure) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.Clusterer: Build a new clusterer with the given DistanceMeasure.
ClusterEvaluator - Interface in org.apache.commons.math4.legacy.ml.clustering: Defines a measure of the quality of clusters.
ClusterRanking - Interface in org.apache.commons.math4.legacy.ml.clustering: Evaluates the quality of a set of clusters.
CMAESOptimizer - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: An implementation of the active Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for non-linear, non-convex, non-smooth, global function minimization.
CMAESOptimizer(int, double, boolean, int, int, UniformRandomProvider, boolean, ConvergenceChecker<PointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.CMAESOptimizer
collector(BivariateFunction, double) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Returns a MultivariateFunction h(x[]).
collector(BivariateFunction, UnivariateFunction, double) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Returns a MultivariateFunction h(x[]).
combine(double, double, RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Returns a new vector representing a * this + b * y, the linear combination of this and y.
combine(double, double, RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Returns a new vector representing a * this + b * y, the linear combination of this and y.
combine(BivariateFunction, UnivariateFunction, UnivariateFunction) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Returns the univariate function h(x) = combiner(f(x), g(x)).
combineToSelf(double, double, RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Updates this with the linear combination of this and y.
combineToSelf(double, double, RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Updates this with the linear combination of this and y.
comparatorPermutation(List<S>, Comparator<S>) - Static method in class org.apache.commons.math4.legacy.genetics.RandomKey: Generates a representation of a permutation corresponding to the data sorted by comparator.
compareTo(Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.Chromosome: Compares two chromosomes based on their fitness.
compareTo(BigReal) - Method in class org.apache.commons.math4.legacy.linear.BigReal
complainIfNotSupported(String) - Method in class org.apache.commons.math4.legacy.ode.AbstractParameterizable: Check if a parameter is supported and throw an IllegalArgumentException if not.
ComplexFormat - Class in org.apache.commons.math4.legacy.util: Formats a Complex number in cartesian format "Re(c) + Im(c)i".
ComplexFormat() - Constructor for class org.apache.commons.math4.legacy.util.ComplexFormat: Create an instance with the default imaginary character, 'i', and the default number format for both real and imaginary parts.
ComplexFormat(String) - Constructor for class org.apache.commons.math4.legacy.util.ComplexFormat: Create an instance with a custom imaginary character, and the default number format for both real and imaginary parts.
ComplexFormat(String, NumberFormat) - Constructor for class org.apache.commons.math4.legacy.util.ComplexFormat: Create an instance with a custom imaginary character, and a custom number format for both real and imaginary parts.
ComplexFormat(String, NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math4.legacy.util.ComplexFormat: Create an instance with a custom imaginary character, a custom number format for the real part, and a custom number format for the imaginary part.
ComplexFormat(NumberFormat) - Constructor for class org.apache.commons.math4.legacy.util.ComplexFormat: Create an instance with a custom number format for both real and imaginary parts.
ComplexFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math4.legacy.util.ComplexFormat: Create an instance with a custom number format for the real part and a custom number format for the imaginary part.
compose(double...) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Compute composition of the instance by a univariate function.
compose(double[], int, double[], double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute composition of a derivative structure by a function.
compose(double, double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Compute composition of the instance by a univariate function.
compose(UnivariateDifferentiableFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Composes functions.
compose(UnivariateFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Composes functions.
CompositeFormat - Class in org.apache.commons.math4.legacy.util: Base class for formatters of composite objects (complex numbers, vectors ...).
compute(double[], double[]) - Method in class org.apache.commons.math4.legacy.ml.distance.CanberraDistance: Compute the distance between two n-dimensional vectors.
compute(double[], double[]) - Method in class org.apache.commons.math4.legacy.ml.distance.ChebyshevDistance: Compute the distance between two n-dimensional vectors.
compute(double[], double[]) - Method in interface org.apache.commons.math4.legacy.ml.distance.DistanceMeasure: Compute the distance between two n-dimensional vectors.
compute(double[], double[]) - Method in class org.apache.commons.math4.legacy.ml.distance.EarthMoversDistance: Compute the distance between two n-dimensional vectors.
compute(double[], double[]) - Method in class org.apache.commons.math4.legacy.ml.distance.EuclideanDistance: Compute the distance between two n-dimensional vectors.
compute(double[], double[]) - Method in class org.apache.commons.math4.legacy.ml.distance.ManhattanDistance: Compute the distance between two n-dimensional vectors.
compute(List<? extends Cluster<? extends Clusterable>>) - Method in interface org.apache.commons.math4.legacy.ml.clustering.ClusterRanking: Computes the rank (higher is better).
computeCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Calculate the coefficients of Lagrange polynomial from the interpolation data.
computeCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Calculate the normal polynomial coefficients given the Newton form.
computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Computes the Kendall's Tau rank correlation matrix for the columns of the input rectangular array.
computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Computes the correlation matrix for the columns of the input rectangular array.
computeCorrelationMatrix(double[][]) - Method in class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Computes the Spearman's rank correlation matrix for the columns of the input rectangular array.
computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Computes the Kendall's Tau rank correlation matrix for the columns of the input matrix.
computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Computes the correlation matrix for the columns of the input matrix, using PearsonsCorrelation.correlation(double[], double[]).
computeCorrelationMatrix(RealMatrix) - Method in class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Computes the Spearman's rank correlation matrix for the columns of the input matrix.
computeCovarianceMatrix(double[][]) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a covariance matrix from a rectangular array whose columns represent covariates.
computeCovarianceMatrix(double[][], boolean) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Compute a covariance matrix from a rectangular array whose columns represent covariates.
computeCovarianceMatrix(RealMatrix) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a covariance matrix from a matrix whose columns represent covariates.
computeCovarianceMatrix(RealMatrix, boolean) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Compute a covariance matrix from a matrix whose columns represent covariates.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Compute the derivatives and check the number of evaluations.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get the current time derivative of the complete state vector.
computeDerivatives(double, double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.FirstOrderConverter: Get the current time derivative of the state vector.
computeDerivatives(double, double[], double[]) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderDifferentialEquations: Get the current time derivative of the state vector.
computeDerivatives(double, double[], double[], double[], double[]) - Method in interface org.apache.commons.math4.legacy.ode.SecondaryEquations: Compute the derivatives related to the secondary state parameters.
computeDerivatives(T, T[]) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Compute the derivatives and check the number of evaluations.
computeDerivatives(T, T[]) - Method in class org.apache.commons.math4.legacy.ode.FieldExpandableODE: Get the current time derivative of the complete state vector.
computeDerivatives(T, T[]) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldDifferentialEquations: Get the current time derivative of the state vector.
computeDerivatives(T, T[], T[], T[]) - Method in interface org.apache.commons.math4.legacy.ode.FieldSecondaryEquations: Compute the derivatives related to the secondary state parameters.
computeDividedDifference(double[], double[]) - Static method in class org.apache.commons.math4.legacy.analysis.interpolation.DividedDifferenceInterpolator: Return a copy of the divided difference array.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(double, double) - Method in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: Compute the state and derivatives at the interpolated time.
computeInterpolatedStateAndDerivatives(FieldEquationsMapper<T>, T, T, T, T) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Compute the state and derivatives at the interpolated time.
computeJacobian(double[]) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.ValueAndJacobianFunction: Compute the Jacobian.
computeMainStateJacobian(double, double[], double[], double[][]) - Method in interface org.apache.commons.math4.legacy.ode.MainStateJacobianProvider: Compute the jacobian matrix of ODE with respect to main state.
computeObjectiveGradient(double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.GradientMultivariateOptimizer: Compute the gradient vector.
computeObjectiveValue(double) - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Compute the objective function value.
computeObjectiveValue(double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Compute the objective function value.
computeObjectiveValue(double) - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer: Deprecated.
Use UnivariateOptimizer.getObjectiveFunction() instead.
computeObjectiveValue(double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateOptimizer: Deprecated.
Use MultivariateOptimizer.getObjectiveFunction() instead.
computeObjectiveValueAndDerivative(double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateDifferentiableSolver: Compute the objective function value.
computeParameterJacobian(double, double[], double[], String, double[]) - Method in interface org.apache.commons.math4.legacy.ode.ParameterJacobianProvider: Compute the Jacobian matrix of ODE with respect to one parameter.
computeRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.BaseRuleFactory: Computes the rule for the given order.
computeRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.HermiteRuleFactory: Computes the rule for the given order.
computeRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.LaguerreRuleFactory: Computes the rule for the given order.
computeRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.LegendreHighPrecisionRuleFactory: Computes the rule for the given order.
computeRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.LegendreRuleFactory: Computes the rule for the given order.
computeSecondDerivatives(double, double[], double[], double[]) - Method in interface org.apache.commons.math4.legacy.ode.SecondOrderDifferentialEquations: Get the current time derivative of the state vector.
computeStepGrowShrinkFactor(double) - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Compute step grow/shrink factor according to normalized error.
computeStepGrowShrinkFactor(T) - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Compute step grow/shrink factor according to normalized error.
computeValue(double[]) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.ValueAndJacobianFunction: Compute the value.
ConfidenceInterval - Class in org.apache.commons.math4.legacy.stat.interval: Represents an interval estimate of a population parameter.
ConfidenceInterval(double, double, double) - Constructor for class org.apache.commons.math4.legacy.stat.interval.ConfidenceInterval: Create a confidence interval with the given bounds and confidence level.
ConjugateGradient - Class in org.apache.commons.math4.legacy.linear: This is an implementation of the conjugate gradient method for RealLinearOperator.
ConjugateGradient(int, double, boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ConjugateGradient: Creates a new instance of this class, with default stopping criterion.
ConjugateGradient(IterationManager, double, boolean) - Constructor for class org.apache.commons.math4.legacy.linear.ConjugateGradient: Creates a new instance of this class, with default stopping criterion and custom iteration manager.
Constant - Class in org.apache.commons.math4.legacy.analysis.function: Constant function.
Constant(double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Constant
CONTINUE - org.apache.commons.math4.legacy.ode.events.Action: Continue indicator.
CONTINUE - org.apache.commons.math4.legacy.ode.events.EventHandler.Action: Continue indicator.
ContinuousOutputFieldModel<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: This class stores all information provided by an ODE integrator during the integration process and build a continuous model of the solution from this.
ContinuousOutputFieldModel() - Constructor for class org.apache.commons.math4.legacy.ode.ContinuousOutputFieldModel: Simple constructor.
ContinuousOutputModel - Class in org.apache.commons.math4.legacy.ode: This class stores all information provided by an ODE integrator during the integration process and build a continuous model of the solution from this.
ContinuousOutputModel() - Constructor for class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Simple constructor.
converged(int, LeastSquaresProblem.Evaluation, LeastSquaresProblem.Evaluation) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.EvaluationRmsChecker: Check if the optimization algorithm has converged.
converged(int, PointValuePair, PointValuePair) - Method in class org.apache.commons.math4.legacy.optim.SimpleValueChecker: Check if the optimization algorithm has converged considering the last two points.
converged(int, PointVectorValuePair, PointVectorValuePair) - Method in class org.apache.commons.math4.legacy.optim.SimpleVectorValueChecker: Check if the optimization algorithm has converged considering the last two points.
converged(int, UnivariatePointValuePair, UnivariatePointValuePair) - Method in class org.apache.commons.math4.legacy.optim.univariate.SimpleUnivariateValueChecker: Check if the optimization algorithm has converged considering the last two points.
converged(int, PAIR, PAIR) - Method in class org.apache.commons.math4.legacy.optim.AbstractConvergenceChecker: Check if the optimization algorithm has converged.
converged(int, PAIR, PAIR) - Method in interface org.apache.commons.math4.legacy.optim.ConvergenceChecker: Check if the optimization algorithm has converged.
converged(int, PAIR, PAIR) - Method in class org.apache.commons.math4.legacy.optim.SimplePointChecker: Check if the optimization algorithm has converged considering the last two points.
ConvergenceChecker<PAIR> - Interface in org.apache.commons.math4.legacy.optim: This interface specifies how to check if an optimization algorithm has converged.
copy() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Perform a copy.
copy() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere2D: Perform a copy.
copy() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Copies this matrix.
copy() - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Make a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Make a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Returns a (deep) copy of this vector.
copy() - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Make a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns a (deep) copy of this.
copy() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Make a (deep) copy of this.
copy() - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Returns a (deep) copy of this vector.
copy() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Returns a (deep) copy of this vector.
copy() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Make a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Copy the instance.
copy() - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Copy the instance.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns a copy of this DescriptiveStatistics instance with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Returns a copy of the statistic with the same internal state.
copy() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StorelessUnivariateStatistic: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Returns a copy of the statistic with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns a copy of this SummaryStatistics instance with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Returns a copy of this SynchronizedDescriptiveStatistics instance with the same internal state.
copy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns a copy of this SynchronizedSummaryStatistics instance with the same internal state.
copy() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.UnivariateStatistic: Returns a copy of the statistic with the same internal state.
copy(Field<T>, T[][]) - Method in class org.apache.commons.math4.legacy.ode.FieldODEState: Copy a two-dimensions array.
copy(DescriptiveStatistics, DescriptiveStatistics) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Copies source to dest.
copy(GeometricMean, GeometricMean) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Copies source to dest.
copy(Kurtosis, Kurtosis) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Copies source to dest.
copy(Mean, Mean) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Copies source to dest.
copy(SecondMoment, SecondMoment) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: Copies source to dest.
copy(SemiVariance, SemiVariance) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Copies source to dest.
copy(Skewness, Skewness) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Copies source to dest.
copy(StandardDeviation, StandardDeviation) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Copies source to dest.
copy(Variance, Variance) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Copies source to dest.
copy(Max, Max) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Copies source to dest.
copy(Min, Min) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Copies source to dest.
copy(Product, Product) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Copies source to dest.
copy(SumOfLogs, SumOfLogs) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Copies source to dest.
copy(SumOfSquares, SumOfSquares) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Copies source to dest.
copy(Sum, Sum) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Copies source to dest.
copy(SummaryStatistics, SummaryStatistics) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Copies source to dest.
copy(SynchronizedDescriptiveStatistics, SynchronizedDescriptiveStatistics) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Copies source to dest.
copy(SynchronizedSummaryStatistics, SynchronizedSummaryStatistics) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Copies source to dest.
copySign(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
copySign(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
copySign(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
copySign(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
copySubMatrix(int[], int[], double[][]) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Copy a submatrix.
copySubMatrix(int[], int[], double[][]) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Copy a submatrix.
copySubMatrix(int[], int[], T[][]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Copy a submatrix.
copySubMatrix(int[], int[], T[][]) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Copy a submatrix.
copySubMatrix(int, int, int, int, double[][]) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Copy a submatrix.
copySubMatrix(int, int, int, int, double[][]) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Copy a submatrix.
copySubMatrix(int, int, int, int, T[][]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Copy a submatrix.
copySubMatrix(int, int, int, int, T[][]) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Copy a submatrix.
correct(double[]) - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Correct the current state estimate with an actual measurement.
correct(RealVector) - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Correct the current state estimate with an actual measurement.
CorrelatedVectorFactory - Class in org.apache.commons.math4.legacy.random: Generates vectors with with correlated components.
CorrelatedVectorFactory(double[], RealMatrix, double) - Constructor for class org.apache.commons.math4.legacy.random.CorrelatedVectorFactory: Correlated vector factory.
CorrelatedVectorFactory(RealMatrix, double) - Constructor for class org.apache.commons.math4.legacy.random.CorrelatedVectorFactory: Null mean correlated vector factory.
correlation(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Computes the Kendall's Tau rank correlation coefficient between the two arrays.
correlation(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Computes the Pearson's product-moment correlation coefficient between two arrays.
correlation(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Computes the Spearman's rank correlation coefficient between the two arrays.
cos() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
cos() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
cos(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute cosine of a derivative structure.
Cos - Class in org.apache.commons.math4.legacy.analysis.function: Cosine function.
Cos() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Cos
cosh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
cosh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
cosh(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute hyperbolic cosine of a derivative structure.
Cosh - Class in org.apache.commons.math4.legacy.analysis.function: Hyperbolic cosine function.
Cosh() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Cosh
cosine(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Computes the cosine of the angle between this vector and the argument.
countEvaluations(LeastSquaresProblem, IntegerSequence.Incrementor) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Count the evaluations of a particular problem.
covariance(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Computes the covariance between the two arrays, using the bias-corrected formula.
covariance(double[], double[], boolean) - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Computes the covariance between the two arrays.
Covariance - Class in org.apache.commons.math4.legacy.stat.correlation: Computes covariances for pairs of arrays or columns of a matrix.
Covariance() - Constructor for class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a Covariance with no data.
Covariance(double[][]) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a Covariance matrix from a rectangular array whose columns represent covariates.
Covariance(double[][], boolean) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a Covariance matrix from a rectangular array whose columns represent covariates.
Covariance(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a covariance matrix from a matrix whose columns represent covariates.
Covariance(RealMatrix, boolean) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.Covariance: Create a covariance matrix from a matrix whose columns represent covariates.
covarianceToCorrelation(RealMatrix) - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Derives a correlation matrix from a covariance matrix.
create() - Static method in class org.apache.commons.math4.legacy.fitting.GaussianCurveFitter: Creates a default curve fitter.
create() - Static method in class org.apache.commons.math4.legacy.fitting.HarmonicCurveFitter: Creates a default curve fitter.
create(boolean, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Create a new instance.
create(int) - Static method in class org.apache.commons.math4.legacy.fitting.PolynomialCurveFitter: Creates a default curve fitter.
create(MultivariateFunction, Comparator<PointValuePair>, DoublePredicate) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.HedarFukushimaTransform: Creates a simplex transformation.
create(MultivariateFunction, Comparator<PointValuePair>, DoublePredicate) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.MultiDirectionalTransform: Creates a simplex transformation.
create(MultivariateFunction, Comparator<PointValuePair>, DoublePredicate) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.NelderMeadTransform: Creates a simplex transformation.
create(MultivariateFunction, Comparator<PointValuePair>, DoublePredicate) - Method in interface org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex.TransformFactory: Creates a simplex transformation.
create(MultivariateVectorFunction, MultivariateMatrixFunction, double[], double[], RealMatrix, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Create a LeastSquaresProblem from the given elements.
create(ParametricUnivariateFunction, double[]) - Static method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter: Creates a curve fitter.
create(ParametricUnivariateFunction, SimpleCurveFitter.ParameterGuesser) - Static method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter: Creates a curve fitter.
create(MultivariateJacobianFunction, RealVector, RealVector, RealMatrix, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Create a LeastSquaresProblem from the given elements.
create(MultivariateJacobianFunction, RealVector, RealVector, RealMatrix, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int, boolean, ParameterValidator) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Create a LeastSquaresProblem from the given elements.
create(MultivariateJacobianFunction, RealVector, RealVector, ConvergenceChecker<LeastSquaresProblem.Evaluation>, int, int) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Create a LeastSquaresProblem from the given elements.
create(RealLinearOperator) - Static method in class org.apache.commons.math4.legacy.linear.JacobiPreconditioner: Creates a new instance of this class.
create(Field<T>, int, int) - Static method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Factory method.
createBlocksLayout(int, int) - Static method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Create a data array in blocks layout.
createBlocksLayout(Field<T>, int, int) - Static method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Create a data array in blocks layout.
createChebyshevPolynomial(int) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Create a Chebyshev polynomial of the first kind.
createColumnFieldMatrix(T[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a column FieldMatrix using the data from the input array.
createColumnRealMatrix(double[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a column RealMatrix using the data from the input array.
createConstant(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Create a constant compatible with instance order and number of parameters.
createConstant(double) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Factory method creating a constant.
createContributingStatistics() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Creates and returns a SummaryStatistics whose data will be aggregated with those of this AggregateSummaryStatistics.
createFieldDiagonalMatrix(T[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns a diagonal matrix with specified elements.
createFieldIdentityMatrix(Field<T>, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns dimension x dimension identity matrix.
createFieldMatrix(Field<T>, int, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns a FieldMatrix with specified dimensions.
createFieldMatrix(T[][]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns a FieldMatrix whose entries are the values in the the input array.
createFieldVector(T[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a FieldVector using the data from the input array.
createHermitePolynomial(int) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Create a Hermite polynomial.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EulerFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GillFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.LutherFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.MidpointFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.RungeKuttaFieldIntegrator: Create an interpolator.
createInterpolator(boolean, T[][], FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ThreeEighthesFieldIntegrator: Create an interpolator.
createInterval(int, int, double) - Method in class org.apache.commons.math4.legacy.stat.interval.AgrestiCoullInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
createInterval(int, int, double) - Method in interface org.apache.commons.math4.legacy.stat.interval.BinomialConfidenceInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
createInterval(int, int, double) - Method in class org.apache.commons.math4.legacy.stat.interval.ClopperPearsonInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
createInterval(int, int, double) - Method in class org.apache.commons.math4.legacy.stat.interval.NormalApproximationInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
createInterval(int, int, double) - Method in class org.apache.commons.math4.legacy.stat.interval.WilsonScoreInterval: Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
createJacobiPolynomial(int, int, int) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Create a Jacobi polynomial.
createLaguerrePolynomial(int) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Create a Laguerre polynomial.
createLegendrePolynomial(int) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Create a Legendre polynomial.
createLineSearch() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateOptimizer: Intantiate the line search implementation.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
createMatrix(int, int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Create a new FieldMatrix<T> of the same type as the instance with the supplied row and column dimensions.
createRealDiagonalMatrix(double[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a diagonal matrix with the specified diagonal elements.
createRealIdentityMatrix(int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns dimension x dimension identity matrix.
createRealMatrix(double[][]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns a RealMatrix whose entries are the values in the the input array.
createRealMatrix(int, int) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Returns a RealMatrix with specified dimensions.
createRealMatrixWithDiagonal(double[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a dense matrix with the specified diagonal elements.
createRealVector(double[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Creates a RealVector using the data from the input array.
createRowFieldMatrix(T[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Create a row FieldMatrix using the data from the input array.
createRowRealMatrix(double[]) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Create a row RealMatrix using the data from the input array.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.AbstractIntegerDistribution
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.AbstractRealDistribution
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedDistribution: Creates a EnumeratedDistribution.Sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution: Refer to EnumeratedDistribution.Sampler for implementation details.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.distribution.MultivariateNormalDistribution: Creates a sampler.
createSampler(UniformRandomProvider) - Method in interface org.apache.commons.math4.legacy.distribution.MultivariateRealDistribution: Creates a sampler.
createVariable(int, double) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Factory method creating an independent variable.
crossover(Chromosome, Chromosome) - Method in interface org.apache.commons.math4.legacy.genetics.CrossoverPolicy: Perform a crossover operation on the given chromosomes.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.CycleCrossover: Perform a crossover operation on the given chromosomes.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.NPointCrossover: Performs a N-point crossover.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.OnePointCrossover: Performs one point crossover.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.OrderedCrossover: Perform a crossover operation on the given chromosomes.
crossover(Chromosome, Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.UniformCrossover: Perform a crossover operation on the given chromosomes.
CrossoverPolicy - Interface in org.apache.commons.math4.legacy.genetics: Policy used to create a pair of new chromosomes by performing a crossover operation on a source pair of chromosomes.
cumulativeProbability(double) - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Algorithm description: Find the bin B that x belongs to. Compute P(B) = the mass of B and P(B-) = the combined mass of the bins below B. Compute K(B) = the probability mass of B with respect to the within-bin kernel and K(B-) = the kernel distribution evaluated at the lower endpoint of B Return P(B-) + P(B) * [K(x) - K(B-)] / K(B) where K(x) is the within-bin kernel distribution function evaluated at x. If K is a constant distribution, we return P(B-) + P(B) (counting the full mass of B).
cumulativeProbability(double) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution
cumulativeProbability(int) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution
currentState - Variable in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: current state.
CycleCrossover<T> - Class in org.apache.commons.math4.legacy.genetics: Cycle Crossover [CX] builds offspring from ordered chromosomes by identifying cycles between two parent chromosomes.
CycleCrossover() - Constructor for class org.apache.commons.math4.legacy.genetics.CycleCrossover: Creates a new CycleCrossover policy.
CycleCrossover(boolean) - Constructor for class org.apache.commons.math4.legacy.genetics.CycleCrossover: Creates a new CycleCrossover policy using the given randomStart behavior.

D

DANTZIG - org.apache.commons.math4.legacy.optim.linear.PivotSelectionRule: The classical rule, the variable with the most negative coefficient in the objective function row will be chosen as entering variable.
DBSCANClusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: DBSCAN (density-based spatial clustering of applications with noise) algorithm.
DBSCANClusterer(double, int) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.DBSCANClusterer: Creates a new instance of a DBSCANClusterer.
DBSCANClusterer(double, int, DistanceMeasure) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.DBSCANClusterer: Creates a new instance of a DBSCANClusterer.
decode(List<T>) - Method in interface org.apache.commons.math4.legacy.genetics.PermutationChromosome: Permutes the sequence of objects of type T according to the permutation this chromosome represents.
decode(List<T>) - Method in class org.apache.commons.math4.legacy.genetics.RandomKey: Permutes the sequence of objects of type T according to the permutation this chromosome represents.
decompose(double[][]) - Method in class org.apache.commons.math4.legacy.linear.QRDecomposition: Decompose matrix.
decompose(double[][]) - Method in class org.apache.commons.math4.legacy.linear.RRQRDecomposition: Decompose matrix.
DecompositionSolver - Interface in org.apache.commons.math4.legacy.linear: Interface handling decomposition algorithms that can solve A × X = B.
decreasingExponential(double) - Static method in interface org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing.CoolingSchedule: Power-law cooling scheme: \[ T_i = T_0 * f^i \], where \( i \) is the current iteration.
DEFAULT_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Default absolute accuracy.
DEFAULT_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Default absolute accuracy.
DEFAULT_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math4.legacy.analysis.solvers.SecantSolver: Default absolute accuracy.
DEFAULT_ABSOLUTE_POSITIVITY_THRESHOLD - Static variable in class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Default threshold below which diagonal elements are considered null and matrix not positive definite.
DEFAULT_ACCURACY - Static variable in class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Default value for accuracy.
DEFAULT_BANDWIDTH - Static variable in class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Default value of the bandwidth parameter.
DEFAULT_EXTEND - Static variable in class org.apache.commons.math4.legacy.analysis.interpolation.UnivariatePeriodicInterpolator: Default number of extension points of the samples array.
DEFAULT_FORMAT - Static variable in class org.apache.commons.math4.legacy.linear.MatrixUtils: The default format for RealMatrix objects.
DEFAULT_INITIAL_RADIUS - Static variable in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer: Default value for BOBYQAOptimizer.initialTrustRegionRadius: 10.0.
DEFAULT_MAX_ITERATIONS_COUNT - Static variable in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Default maximal iteration count.
DEFAULT_MIN_ITERATIONS_COUNT - Static variable in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Default minimal iteration count.
DEFAULT_NAN_STRATEGY - Static variable in class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: default NaN strategy.
DEFAULT_RELATIVE_ACCURACY - Static variable in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Default relative accuracy.
DEFAULT_RELATIVE_SYMMETRY_THRESHOLD - Static variable in class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Default threshold above which off-diagonal elements are considered too different and matrix not symmetric.
DEFAULT_ROBUSTNESS_ITERS - Static variable in class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Default value of the number of robustness iterations.
DEFAULT_STOPPING_RADIUS - Static variable in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer: Default value for BOBYQAOptimizer.stoppingTrustRegionRadius: 1.0E-8.
DEFAULT_TIES_STRATEGY - Static variable in class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: default ties strategy.
DEFAULT_ZERO_TOLERANCE - Static variable in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Default Tolerance for having a value considered zero.
DefaultFieldMatrixChangingVisitor<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Default implementation of the FieldMatrixChangingVisitor interface.
DefaultFieldMatrixChangingVisitor(T) - Constructor for class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixChangingVisitor: Build a new instance.
DefaultFieldMatrixPreservingVisitor<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Default implementation of the FieldMatrixPreservingVisitor interface.
DefaultFieldMatrixPreservingVisitor(T) - Constructor for class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixPreservingVisitor: Build a new instance.
DefaultIterativeLinearSolverEvent - Class in org.apache.commons.math4.legacy.linear: A default concrete implementation of the abstract class IterativeLinearSolverEvent.
DefaultIterativeLinearSolverEvent(Object, int, RealVector, RealVector, double) - Constructor for class org.apache.commons.math4.legacy.linear.DefaultIterativeLinearSolverEvent: Creates a new instance of this class.
DefaultIterativeLinearSolverEvent(Object, int, RealVector, RealVector, RealVector, double) - Constructor for class org.apache.commons.math4.legacy.linear.DefaultIterativeLinearSolverEvent: Creates a new instance of this class.
DefaultMeasurementModel - Class in org.apache.commons.math4.legacy.filter: Default implementation of a MeasurementModel for the use with a KalmanFilter.
DefaultMeasurementModel(double[][], double[][]) - Constructor for class org.apache.commons.math4.legacy.filter.DefaultMeasurementModel: Create a new MeasurementModel, taking double arrays as input parameters for the respective measurement matrix and noise.
DefaultMeasurementModel(RealMatrix, RealMatrix) - Constructor for class org.apache.commons.math4.legacy.filter.DefaultMeasurementModel: Create a new MeasurementModel, taking RealMatrix objects as input parameters for the respective measurement matrix and noise.
DefaultProcessModel - Class in org.apache.commons.math4.legacy.filter: Default implementation of a ProcessModel for the use with a KalmanFilter.
DefaultProcessModel(double[][], double[][], double[][]) - Constructor for class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Create a new ProcessModel, taking double arrays as input parameters.
DefaultProcessModel(double[][], double[][], double[][], double[], double[][]) - Constructor for class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Create a new ProcessModel, taking double arrays as input parameters.
DefaultProcessModel(RealMatrix, RealMatrix, RealMatrix, RealVector, RealMatrix) - Constructor for class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Create a new ProcessModel, taking double arrays as input parameters.
DefaultRealMatrixChangingVisitor - Class in org.apache.commons.math4.legacy.linear: Default implementation of the RealMatrixChangingVisitor interface.
DefaultRealMatrixChangingVisitor() - Constructor for class org.apache.commons.math4.legacy.linear.DefaultRealMatrixChangingVisitor
DefaultRealMatrixPreservingVisitor - Class in org.apache.commons.math4.legacy.linear: Default implementation of the RealMatrixPreservingVisitor interface.
DefaultRealMatrixPreservingVisitor() - Constructor for class org.apache.commons.math4.legacy.linear.DefaultRealMatrixPreservingVisitor
degree() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Returns the degree of the polynomial.
degree() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Returns the degree of the polynomial.
degree() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Returns the degree of the polynomial.
density(double) - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Returns the kernel density normalized so that its integral over each bin equals the bin mass.
density(double) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution: For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
density(double[]) - Method in class org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution: Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
density(double[]) - Method in class org.apache.commons.math4.legacy.distribution.MultivariateNormalDistribution: Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
density(double[]) - Method in interface org.apache.commons.math4.legacy.distribution.MultivariateRealDistribution: Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
derivative(MultivariateDifferentiableFunction, int[]) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Convert an MultivariateDifferentiableFunction to an MultivariateFunction computing n^th order derivative.
derivative(UnivariateDifferentiableFunction, int) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Convert an UnivariateDifferentiableFunction to an UnivariateFunction computing n^th order derivative.
derivatives(T, int) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.FieldHermiteInterpolator: Interpolate value and first derivatives at a specified abscissa.
DerivativeStructure - Class in org.apache.commons.math4.legacy.analysis.differentiation: Class representing both the value and the differentials of a function.
DerivativeStructure(double, DerivativeStructure, double, DerivativeStructure) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Linear combination constructor.
DerivativeStructure(double, DerivativeStructure, double, DerivativeStructure, double, DerivativeStructure) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Linear combination constructor.
DerivativeStructure(double, DerivativeStructure, double, DerivativeStructure, double, DerivativeStructure, double, DerivativeStructure) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Linear combination constructor.
DerivativeStructure(int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Build an instance with all values and derivatives set to 0.
DerivativeStructure(int, int, double) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Build an instance representing a constant value.
DerivativeStructure(int, int, double...) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Build an instance from all its derivatives.
DerivativeStructure(int, int, int, double) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Build an instance representing a variable.
DescriptiveStatistics - Class in org.apache.commons.math4.legacy.stat.descriptive: Maintains a dataset of values of a single variable and computes descriptive statistics based on stored data.
DescriptiveStatistics() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Construct a DescriptiveStatistics instance with an infinite window.
DescriptiveStatistics(double[]) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Construct a DescriptiveStatistics instance with an infinite window and the initial data values in initialDoubleArray.
DescriptiveStatistics(int) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Construct a DescriptiveStatistics instance with the specified window.
DescriptiveStatistics(Double[]) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Construct a DescriptiveStatistics instance with an infinite window and the initial data values in initialDoubleArray.
DescriptiveStatistics(DescriptiveStatistics) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Copy constructor.
deserializeRealMatrix(Object, String, ObjectInputStream) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Deserialize a RealMatrix field in a class.
deserializeRealVector(Object, String, ObjectInputStream) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Deserialize a RealVector field in a class.
df(double, double, double, double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes approximate degrees of freedom for 2-sample t-test.
DiagonalMatrix - Class in org.apache.commons.math4.legacy.linear: Implementation of a diagonal matrix.
DiagonalMatrix(double[]) - Constructor for class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Creates a matrix using the input array as the underlying data.
DiagonalMatrix(double[], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Creates a matrix using the input array as the underlying data.
DiagonalMatrix(int) - Constructor for class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Creates a matrix with the supplied dimension.
differentiate(double[]) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Returns the coefficients of the derivative of the polynomial with the given coefficients.
differentiate(UnivariateFunction) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Create an implementation of a differential from a regular function.
differentiate(UnivariateFunction) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.UnivariateFunctionDifferentiator: Create an implementation of a differential from a regular function.
differentiate(UnivariateMatrixFunction) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Create an implementation of a differential from a regular matrix function.
differentiate(UnivariateMatrixFunction) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.UnivariateMatrixFunctionDifferentiator: Create an implementation of a differential from a regular matrix function.
differentiate(UnivariateVectorFunction) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Create an implementation of a differential from a regular vector function.
differentiate(UnivariateVectorFunction) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.UnivariateVectorFunctionDifferentiator: Create an implementation of a differential from a regular vector function.
DifferentiatorVectorMultivariateJacobianFunction - Class in org.apache.commons.math4.legacy.fitting.leastsquares: A MultivariateJacobianFunction (a thing that requires a derivative) combined with the thing that can find derivatives.
DifferentiatorVectorMultivariateJacobianFunction(MultivariateVectorFunction, UnivariateVectorFunctionDifferentiator) - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.DifferentiatorVectorMultivariateJacobianFunction: Build the jacobian function using a differentiator.
distance(Clusterable, Clusterable) - Method in class org.apache.commons.math4.legacy.ml.clustering.Clusterer: Calculates the distance between two Clusterable instances with the configured DistanceMeasure.
DistanceMeasure - Interface in org.apache.commons.math4.legacy.ml.distance: Interface for distance measures of n-dimensional vectors.
divide(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
divide(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
divide(double[], int, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Perform division of two derivative structures.
divide(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
divide(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
divide(BigReal) - Method in class org.apache.commons.math4.legacy.linear.BigReal
Divide - Class in org.apache.commons.math4.legacy.analysis.function: Divide the first operand by the second.
Divide() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Divide
DividedDifferenceInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Implements the Divided Difference Algorithm for interpolation of real univariate functions.
DividedDifferenceInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.DividedDifferenceInterpolator
doCopy() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Really copy the finalized instance.
doCopy() - Method in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: Really copy the finalized instance.
doFinalize() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Really finalize the step.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Method for implementing actual integration algorithms in derived classes.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.IterativeLegendreGaussIntegrator: Method for implementing actual integration algorithms in derived classes.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.MidPointIntegrator: Method for implementing actual integration algorithms in derived classes.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.RombergIntegrator: Method for implementing actual integration algorithms in derived classes.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.SimpsonIntegrator: Method for implementing actual integration algorithms in derived classes.
doIntegrate() - Method in class org.apache.commons.math4.legacy.analysis.integration.TrapezoidIntegrator: Method for implementing actual integration algorithms in derived classes.
doIteration(SimplexTableau) - Method in class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Runs one iteration of the Simplex method on the given model.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.BaseMultiStartMultivariateOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.CMAESOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.PowellOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.SimplexOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.univariate.BrentOptimizer: Performs the bulk of the optimization algorithm.
doOptimize() - Method in class org.apache.commons.math4.legacy.optim.univariate.MultiStartUnivariateOptimizer: Performs the bulk of the optimization algorithm.
DormandPrince54FieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 5(4) Dormand-Prince integrator for Ordinary Differential Equations.
DormandPrince54FieldIntegrator(Field<T>, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Simple constructor.
DormandPrince54FieldIntegrator(Field<T>, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Simple constructor.
DormandPrince54Integrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 5(4) Dormand-Prince integrator for Ordinary Differential Equations.
DormandPrince54Integrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54Integrator: Simple constructor.
DormandPrince54Integrator(double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54Integrator: Simple constructor.
DormandPrince853FieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 8(5,3) Dormand-Prince integrator for Ordinary Differential Equations.
DormandPrince853FieldIntegrator(Field<T>, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Simple constructor.
DormandPrince853FieldIntegrator(Field<T>, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Simple constructor.
DormandPrince853Integrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 8(5,3) Dormand-Prince integrator for Ordinary Differential Equations.
DormandPrince853Integrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853Integrator: Simple constructor.
DormandPrince853Integrator(double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853Integrator: Simple constructor.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BisectionSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BrentSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.LaguerreSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.MullerSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.MullerSolver2: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.NewtonRaphsonSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.RiddersSolver: Method for implementing actual optimization algorithms in derived classes.
doSolve() - Method in class org.apache.commons.math4.legacy.analysis.solvers.SecantSolver: Method for implementing actual optimization algorithms in derived classes.
dotProduct(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute the dot product.
dotProduct(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute the dot product.
dotProduct(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Compute the dot product.
dotProduct(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Compute the dot product.
dotProduct(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Compute the dot product of this vector with v.
dotProduct(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Compute the dot product of this vector with v.
DoublePoint - Class in org.apache.commons.math4.legacy.ml.clustering: A simple implementation of Clusterable for points with double coordinates.
DoublePoint(double[]) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.DoublePoint: Build an instance wrapping an double array.
DoublePoint(int[]) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.DoublePoint: Build an instance wrapping an integer array.
doubleValue() - Method in class org.apache.commons.math4.legacy.linear.BigReal: Get the double value corresponding to the instance.
DOWNSIDE - org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance.Direction: The DOWNSIDE Direction is used to specify that the observations below.
DOWNSIDE_VARIANCE - Static variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: The DOWNSIDE Direction is used to specify that the observations below.
DSCompiler - Class in org.apache.commons.math4.legacy.analysis.differentiation: Class holding "compiled" computation rules for derivative structures.
DummyStepHandler - Class in org.apache.commons.math4.legacy.ode.sampling: This class is a step handler that does nothing.

E

EarthMoversDistance - Class in org.apache.commons.math4.legacy.ml.distance: Calculates the Earh Mover's distance (also known as Wasserstein metric) between two distributions.
EarthMoversDistance() - Constructor for class org.apache.commons.math4.legacy.ml.distance.EarthMoversDistance
ebeDivide(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Element-by-element division.
ebeDivide(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Element-by-element division.
ebeDivide(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Element-by-element division.
ebeDivide(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Element-by-element division.
ebeDivide(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Element-by-element division.
ebeDivide(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Element-by-element division.
ebeDivide(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Element-by-element division.
ebeMultiply(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Element-by-element multiplication.
ebeMultiply(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Element-by-element multiplication.
ebeMultiply(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Element-by-element multiplication.
ebeMultiply(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Element-by-element multiplication.
ebeMultiply(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Element-by-element multiplication.
ebeMultiply(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Element-by-element multiplication.
ebeMultiply(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Element-by-element multiplication.
EigenDecomposition - Class in org.apache.commons.math4.legacy.linear: Calculates the eigen decomposition of a real matrix.
EigenDecomposition(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.linear.EigenDecomposition: Calculates the eigen decomposition of the symmetric tridiagonal matrix.
EigenDecomposition(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.linear.EigenDecomposition: Calculates the eigen decomposition of the given real matrix.
ElitisticListPopulation - Class in org.apache.commons.math4.legacy.genetics: Population of chromosomes which uses elitism (certain percentage of the best chromosomes is directly copied to the next generation).
ElitisticListPopulation(int, double) - Constructor for class org.apache.commons.math4.legacy.genetics.ElitisticListPopulation: Creates a new ElitisticListPopulation instance and initializes its inner chromosome list.
ElitisticListPopulation(List<Chromosome>, int, double) - Constructor for class org.apache.commons.math4.legacy.genetics.ElitisticListPopulation: Creates a new ElitisticListPopulation instance.
ElkanKMeansPlusPlusClusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: Implementation of k-means++ algorithm.
ElkanKMeansPlusPlusClusterer(int) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.ElkanKMeansPlusPlusClusterer
ElkanKMeansPlusPlusClusterer(int, int, DistanceMeasure, UniformRandomProvider) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.ElkanKMeansPlusPlusClusterer
ElkanKMeansPlusPlusClusterer(int, int, DistanceMeasure, UniformRandomProvider, KMeansPlusPlusClusterer.EmptyClusterStrategy) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.ElkanKMeansPlusPlusClusterer
EmbeddedRungeKuttaFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the common part of all embedded Runge-Kutta integrators for Ordinary Differential Equations.
EmbeddedRungeKuttaFieldIntegrator(Field<T>, String, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Build a Runge-Kutta integrator with the given Butcher array.
EmbeddedRungeKuttaFieldIntegrator(Field<T>, String, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Build a Runge-Kutta integrator with the given Butcher array.
EmbeddedRungeKuttaIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the common part of all embedded Runge-Kutta integrators for Ordinary Differential Equations.
EmbeddedRungeKuttaIntegrator(String, boolean, double[], double[][], double[], RungeKuttaStepInterpolator, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Build a Runge-Kutta integrator with the given Butcher array.
EmbeddedRungeKuttaIntegrator(String, boolean, double[], double[][], double[], RungeKuttaStepInterpolator, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Build a Runge-Kutta integrator with the given Butcher array.
EmpiricalDistribution - Class in org.apache.commons.math4.legacy.distribution: Represents an empirical probability distribution: Probability distribution derived from observed data without making any assumptions about the functional form of the population distribution that the data come from.
end() - Method in class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixChangingVisitor: End visiting a matrix.
end() - Method in class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixPreservingVisitor: End visiting a matrix.
end() - Method in class org.apache.commons.math4.legacy.linear.DefaultRealMatrixChangingVisitor: End visiting a matrix.
end() - Method in class org.apache.commons.math4.legacy.linear.DefaultRealMatrixPreservingVisitor: End visiting a matrix.
end() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrixChangingVisitor: End visiting a matrix.
end() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrixPreservingVisitor: End visiting a matrix.
end() - Method in interface org.apache.commons.math4.legacy.linear.FieldVectorChangingVisitor: End visiting a vector.
end() - Method in interface org.apache.commons.math4.legacy.linear.FieldVectorPreservingVisitor: End visiting a vector.
end() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrixChangingVisitor: End visiting a matrix.
end() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrixPreservingVisitor: End visiting a matrix.
end() - Method in interface org.apache.commons.math4.legacy.linear.RealVectorChangingVisitor: End visiting a vector.
end() - Method in interface org.apache.commons.math4.legacy.linear.RealVectorPreservingVisitor: End visiting a vector.
Entry() - Constructor for class org.apache.commons.math4.legacy.linear.RealVector.Entry: Simple constructor.
entrySetIterator() - Method in class org.apache.commons.math4.legacy.stat.Frequency: Return an Iterator over the set of keys and values that have been added.
EnumeratedDistribution<T> - Class in org.apache.commons.math4.legacy.distribution: A generic implementation of a discrete probability distribution (Wikipedia) over a finite sample space, based on an enumerated list of <value, probability> pairs.
EnumeratedDistribution(List<Pair<T, Double>>) - Constructor for class org.apache.commons.math4.legacy.distribution.EnumeratedDistribution: Create an enumerated distribution using the given random number generator and probability mass function enumeration.
EnumeratedDistribution.Sampler - Class in org.apache.commons.math4.legacy.distribution: Sampler functionality.
EnumeratedIntegerDistribution - Class in org.apache.commons.math4.legacy.distribution: Implementation of an integer-valued EnumeratedDistribution.
EnumeratedIntegerDistribution(int[]) - Constructor for class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution: Create a discrete integer-valued distribution from the input data.
EnumeratedIntegerDistribution(int[], double[]) - Constructor for class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution: Create a discrete distribution.
EnumeratedRealDistribution - Class in org.apache.commons.math4.legacy.distribution: Implementation of a real-valued EnumeratedDistribution.
EnumeratedRealDistribution(double[]) - Constructor for class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution: Creates a discrete real-valued distribution from the input data.
EnumeratedRealDistribution(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution: Create a discrete real-valued distribution using the given random number generator and probability mass function enumeration.
EQ - org.apache.commons.math4.legacy.optim.linear.Relationship: Equality relationship.
equals(Object) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Test for the equality of two derivative structures.
equals(Object) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Test for the equality of two sparse gradients.
equals(Object) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction
equals(Object) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns true iff object is a FieldMatrix instance with the same dimensions as this and all corresponding matrix entries are equal.
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns true iff object is a RealMatrix instance with the same dimensions as this and all corresponding matrix entries are equal.
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Test for the equality of two vectors.
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Test for the equality of two real vectors.
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.BigReal
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Test for the equality of two real vectors.
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Test for the equality of two real vectors.
equals(Object) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector
equals(Object) - Method in class org.apache.commons.math4.legacy.ml.clustering.DoublePoint
equals(Object) - Method in class org.apache.commons.math4.legacy.optim.linear.LinearConstraint
equals(Object) - Method in class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction
equals(Object) - Method in class org.apache.commons.math4.legacy.optim.PointValuePair
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: Returns true iff object is the same type of StorelessUnivariateStatistic (the object's class equals this instance) returning the same values as this for getResult() and getN().
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialCovariance
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialMean
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns true iff object is a MultivariateSummaryStatistics instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Returns true iff o is a PSquarePercentile returning the.
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues: Returns true iff object is a StatisticalSummaryValues instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns true iff object is a SummaryStatistics instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns true iff object is a MultivariateSummaryStatistics instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns true iff object is a SummaryStatistics instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math4.legacy.stat.Frequency
equalSidesAlongAxes(int, double) - Static method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Builds simplex with the given side length.
EquationsMapper - Class in org.apache.commons.math4.legacy.ode: Class mapping the part of a complete state or derivative that pertains to a specific differential equation.
EquationsMapper(int, int) - Constructor for class org.apache.commons.math4.legacy.ode.EquationsMapper: simple constructor.
ERROR - org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer.EmptyClusterStrategy: Generate an error.
estimate(double[][], int) - Static method in class org.apache.commons.math4.legacy.distribution.fitting.MultivariateNormalMixtureExpectationMaximization: Helper method to create a multivariate normal mixture model which can be used to initialize MultivariateNormalMixtureExpectationMaximization.fit(MixtureMultivariateNormalDistribution).
estimate(double[], int[], double, int, KthSelector) - Method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Estimation based on K^th selection.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54Integrator: Compute the error ratio.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853Integrator: Compute the error ratio.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Compute the error ratio.
estimateError(double[][], double[], double[], double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54Integrator: Compute the error ratio.
estimateError(T[][], T[], T[], T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Compute the error ratio.
estimateError(T[][], T[], T[], T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Compute the error ratio.
estimateError(T[][], T[], T[], T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Compute the error ratio.
estimateError(T[][], T[], T[], T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Compute the error ratio.
estimateErrorVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Estimates the variance of the error.
estimateRegressandVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Returns the variance of the regressand, ie Var(y).
estimateRegressandVariance() - Method in interface org.apache.commons.math4.legacy.stat.regression.MultipleLinearRegression: Returns the variance of the regressand, ie Var(y).
estimateRegressionParameters() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Estimates the regression parameters b.
estimateRegressionParameters() - Method in interface org.apache.commons.math4.legacy.stat.regression.MultipleLinearRegression: Estimates the regression parameters b.
estimateRegressionParametersStandardErrors() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Returns the standard errors of the regression parameters.
estimateRegressionParametersStandardErrors() - Method in interface org.apache.commons.math4.legacy.stat.regression.MultipleLinearRegression: Returns the standard errors of the regression parameters.
estimateRegressionParametersVariance() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Estimates the variance of the regression parameters, ie Var(b).
estimateRegressionParametersVariance() - Method in interface org.apache.commons.math4.legacy.stat.regression.MultipleLinearRegression: Estimates the variance of the regression parameters, ie Var(b).
estimateRegressionStandardError() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Estimates the standard error of the regression.
estimateResiduals() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Estimates the residuals, ie u = y - X*b.
estimateResiduals() - Method in interface org.apache.commons.math4.legacy.stat.regression.MultipleLinearRegression: Estimates the residuals, ie u = y - X*b.
EuclideanDistance - Class in org.apache.commons.math4.legacy.ml.distance: Calculates the L₂ (Euclidean) distance between two points.
EuclideanDistance() - Constructor for class org.apache.commons.math4.legacy.ml.distance.EuclideanDistance
EulerFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements a simple Euler integrator for Ordinary Differential Equations.
EulerFieldIntegrator(Field<T>, T) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.EulerFieldIntegrator: Simple constructor.
EulerIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements a simple Euler integrator for Ordinary Differential Equations.
EulerIntegrator(double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.EulerIntegrator: Simple constructor.
evaluate() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Returns the result of evaluating the statistic over the stored data.
evaluate(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns the result of evaluating the statistic over the stored data.
evaluate(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: This default implementation creates a copy of this StorelessUnivariateStatistic instance, calls AbstractStorelessUnivariateStatistic.clear() on it, then calls AbstractStorelessUnivariateStatistic.incrementAll(double[]) with the specified portion of the input array, and then uses AbstractStorelessUnivariateStatistic.getResult() to compute the return value.
evaluate(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Returns the result of evaluating the statistic over the input array.
evaluate(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Returns the Standard Deviation of the entries in the input array, or Double.NaN if the array is empty.
evaluate(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the variance of the entries in the input array, or Double.NaN if the array is empty.
evaluate(double[]) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.UnivariateStatistic: Returns the result of evaluating the statistic over the input array.
evaluate(double[], double) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Uses Horner's Method to evaluate the polynomial with the given coefficients at the argument.
evaluate(double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Returns the SemiVariance of the designated values against the cutoff, using instance properties variancDirection and biasCorrection.
evaluate(double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Returns the Standard Deviation of the entries in the input array, using the precomputed mean value.
evaluate(double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the variance of the entries in the input array, using the precomputed mean value.
evaluate(double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the pth percentile of the values in the values array.
evaluate(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Returns the weighted arithmetic mean of the entries in the input array.
evaluate(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the weighted variance of the entries in the input array.
evaluate(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Returns the weighted product of the entries in the input array.
evaluate(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: The weighted sum of the entries in the input array.
evaluate(double[], double[]) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.WeightedEvaluation: Returns the result of evaluating the statistic over the input array, using the supplied weights.
evaluate(double[], double[], double) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Evaluate the Lagrange polynomial using Neville's Algorithm.
evaluate(double[], double[], double) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Evaluate the Newton polynomial using nested multiplication.
evaluate(double[], double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the weighted variance of the values in the input array, using the precomputed weighted mean value.
evaluate(double[], double[], double) - Method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Evaluate weighted percentile by estimation rule specified in Percentile.EstimationType.
evaluate(double[], double[], double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the pth percentile of the values in the values array with their weights.
evaluate(double[], double[], double, int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the weighted variance of the entries in the specified portion of the input array, using the precomputed weighted mean value.
evaluate(double[], double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Returns the weighted arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the weighted variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the weighted quantileth percentile of the designated values in the values array.
evaluate(double[], double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Returns the weighted product of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: The weighted sum of the entries in the specified portion of the input array, or 0 if the designated subarray is empty.
evaluate(double[], double[], int, int) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.WeightedEvaluation: Returns the result of evaluating the statistic over the specified entries in the input array, using corresponding entries in the supplied weights array.
evaluate(double[], double[], int, int, double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the pth percentile of the values in the values array with sampleWeights, starting with the element in (0-based) position begin in the array and including length values.
evaluate(double[], double, int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Returns the Standard Deviation of the entries in the specified portion of the input array, using the precomputed mean value.
evaluate(double[], double, int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the variance of the entries in the specified portion of the input array, using the precomputed mean value.
evaluate(double[], double, SemiVariance.Direction) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Returns the SemiVariance of the designated values against the cutoff in the given direction, using the current value of the biasCorrection instance property.
evaluate(double[], double, SemiVariance.Direction, boolean, int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Returns the SemiVariance of the designated values against the cutoff in the given direction with the provided bias correction.
evaluate(double[], double, KthSelector) - Method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Evaluate method to compute the percentile for a given bounded array.
evaluate(double[], int[], double, KthSelector) - Method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Evaluate method to compute the percentile for a given bounded array using earlier computed pivots heap.
This basically calls the index and then estimate functions to return the estimated percentile value.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: This default implementation creates a copy of this StorelessUnivariateStatistic instance, calls AbstractStorelessUnivariateStatistic.clear() on it, then calls AbstractStorelessUnivariateStatistic.incrementAll(double[]) with the specified portion of the input array, and then uses AbstractStorelessUnivariateStatistic.getResult() to compute the return value.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Returns the result of evaluating the statistic over the specified entries in the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Returns the geometric mean of the entries in the specified portion of the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Returns the kurtosis of the entries in the specified portion of the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Returns the arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Returns the SemiVariance of the designated values against the mean, using instance properties varianceDirection and biasCorrection.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Returns the Skewness of the entries in the specified portion of the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Returns the Standard Deviation of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Returns the maximum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Returns the minimum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the quantileth percentile of the designated values in the values array.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Returns the product of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: The sum of the entries in the specified portion of the input array, or 0 if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Returns the sum of the natural logs of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Returns the sum of the squares of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
evaluate(double[], int, int) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.UnivariateStatistic: Returns the result of evaluating the statistic over the specified entries in the input array.
evaluate(double[], int, int, double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns an estimate of the pth percentile of the values in the values array, starting with the element in (0-based) position begin in the array and including length values.
evaluate(double[], SemiVariance.Direction) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: This method calculates SemiVariance for the entire array against the mean, using the current value of the biasCorrection instance property.
evaluate(MultivariateFunction, Comparator<PointValuePair>) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Evaluates the (non-evaluated) simplex points and returns a new instance with vertices sorted from best to worst.
evaluate(RealVector) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresAdapter: Evaluate the model at the specified point.
evaluate(RealVector) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem: Evaluate the model at the specified point.
evaluateStep(FieldStepInterpolator<T>) - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Evaluate the impact of the proposed step on the event handler.
evaluateStep(StepInterpolator) - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Evaluate the impact of the proposed step on the event handler.
evaluationChecker(ConvergenceChecker<PointVectorValuePair>) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: View a convergence checker specified for a PointVectorValuePair as one specified for an LeastSquaresProblem.Evaluation.
EvaluationRmsChecker - Class in org.apache.commons.math4.legacy.fitting.leastsquares: Check if an optimization has converged based on the change in computed RMS.
EvaluationRmsChecker(double) - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.EvaluationRmsChecker: Create a convergence checker for the RMS with the same relative and absolute tolerance.
EvaluationRmsChecker(double, double) - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.EvaluationRmsChecker: Create a convergence checker for the RMS with a relative and absolute tolerance.
EventFilter - Class in org.apache.commons.math4.legacy.ode.events: Wrapper used to detect only increasing or decreasing events.
EventFilter(EventHandler, FilterType) - Constructor for class org.apache.commons.math4.legacy.ode.events.EventFilter: Wrap an event handler.
EventHandler - Interface in org.apache.commons.math4.legacy.ode.events: This interface represents a handler for discrete events triggered during ODE integration.
EventHandler.Action - Enum in org.apache.commons.math4.legacy.ode.events: Enumerate for actions to be performed when an event occurs.
eventOccurred(double, double[], boolean) - Method in class org.apache.commons.math4.legacy.ode.events.EventFilter: Handle an event and choose what to do next.
eventOccurred(double, double[], boolean) - Method in interface org.apache.commons.math4.legacy.ode.events.EventHandler: Handle an event and choose what to do next.
eventOccurred(FieldODEStateAndDerivative<T>, boolean) - Method in interface org.apache.commons.math4.legacy.ode.events.FieldEventHandler: Handle an event and choose what to do next.
EventState - Class in org.apache.commons.math4.legacy.ode.events: This class handles the state for one event handler during integration steps.
EventState(EventHandler, double, double, int, UnivariateSolver) - Constructor for class org.apache.commons.math4.legacy.ode.events.EventState: Simple constructor.
evolve(Population, StoppingCondition) - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Evolve the given population.
exactP(double, int, int, boolean) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
exactP(double, int, int, boolean) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Computes \(P(D_{n,m} > d)\) if strict is true; otherwise \(P(D_{n,m} \ge d)\), where \(D_{n,m}\) is the 2-sample Kolmogorov-Smirnov statistic.
exp() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
exp() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
exp(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute exponential of a derivative structure.
Exp - Class in org.apache.commons.math4.legacy.analysis.function: Exponential function.
Exp() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Exp
ExpandableStatefulODE - Class in org.apache.commons.math4.legacy.ode: This class represents a combined set of first order differential equations, with at least a primary set of equations expandable by some sets of secondary equations.
ExpandableStatefulODE(FirstOrderDifferentialEquations) - Constructor for class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Build an expandable set from its primary ODE set.
expm1() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
expm1() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
expm1(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute exp(x) - 1 of a derivative structure.
Expm1 - Class in org.apache.commons.math4.legacy.analysis.function: e^x-1 function.
Expm1() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Expm1
extractEquationData(double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.EquationsMapper: Extract equation data from a complete state or derivative array.
extractEquationData(int, T[]) - Method in class org.apache.commons.math4.legacy.ode.FieldEquationsMapper: Extract equation data from a complete state or derivative array.
extractField(T[]) - Static method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the elements type from an array.
extractField(T[][]) - Static method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the elements type from an array.

F

FAILED - org.apache.commons.math4.legacy.stat.ranking.NaNStrategy: NaNs result in an exception.
FARTHEST_POINT - org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer.EmptyClusterStrategy: Create a cluster around the point farthest from its centroid.
FieldBracketingNthOrderBrentSolver<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.analysis.solvers: This class implements a modification of the Brent algorithm.
FieldBracketingNthOrderBrentSolver(T, T, T, int) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Construct a solver.
FieldButcherArrayProvider<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode.nonstiff: This interface represents an integrator based on Butcher arrays.
FieldDecompositionSolver<T> - Interface in org.apache.commons.math4.legacy.field.linalg: Interface handling decomposition algorithms that can solve A X = B.
FieldDecompositionSolver<T extends FieldElement<T>> - Interface in org.apache.commons.math4.legacy.linear: Interface handling decomposition algorithms that can solve A × X = B.
FieldDenseMatrix<T> - Class in org.apache.commons.math4.legacy.field.linalg: Square matrix whose elements define a Field.
FieldEquationsMapper<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: Class mapping the part of a complete state or derivative that pertains to a set of differential equations.
FieldEventHandler<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode.events: This interface represents a handler for discrete events triggered during ODE integration.
FieldEventState<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.events: This class handles the state for one event handler during integration steps.
FieldEventState(FieldEventHandler<T>, double, T, int, BracketedRealFieldUnivariateSolver<T>) - Constructor for class org.apache.commons.math4.legacy.ode.events.FieldEventState: Simple constructor.
FieldExpandableODE<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: This class represents a combined set of first order differential equations, with at least a primary set of equations expandable by some sets of secondary equations.
FieldExpandableODE(FirstOrderFieldDifferentialEquations<T>) - Constructor for class org.apache.commons.math4.legacy.ode.FieldExpandableODE: Build an expandable set from its primary ODE set.
FieldFixedStepHandler<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode.sampling: This interface represents a handler that should be called after each successful fixed step.
FieldHermiteInterpolator<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.analysis.interpolation: Polynomial interpolator using both sample values and sample derivatives.
FieldHermiteInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.FieldHermiteInterpolator: Create an empty interpolator.
FieldLUDecomposition<T> - Class in org.apache.commons.math4.legacy.field.linalg: Calculates the LUP-decomposition of a square matrix.
FieldLUDecomposition<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Calculates the LUP-decomposition of a square matrix.
FieldLUDecomposition(FieldMatrix<T>) - Constructor for class org.apache.commons.math4.legacy.linear.FieldLUDecomposition: Calculates the LU-decomposition of the given matrix.
FieldMatrix<T extends FieldElement<T>> - Interface in org.apache.commons.math4.legacy.linear: Interface defining field-valued matrix with basic algebraic operations.
FieldMatrixChangingVisitor<T extends FieldElement<?>> - Interface in org.apache.commons.math4.legacy.linear: Interface defining a visitor for matrix entries.
FieldMatrixPreservingVisitor<T extends FieldElement<?>> - Interface in org.apache.commons.math4.legacy.linear: Interface defining a visitor for matrix entries.
FieldODEState<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: Container for time, main and secondary state vectors.
FieldODEState(T, T[]) - Constructor for class org.apache.commons.math4.legacy.ode.FieldODEState: Simple constructor.
FieldODEState(T, T[], T[][]) - Constructor for class org.apache.commons.math4.legacy.ode.FieldODEState: Simple constructor.
FieldODEStateAndDerivative<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: Container for time, main and secondary state vectors as well as their derivatives.
FieldODEStateAndDerivative(T, T[], T[]) - Constructor for class org.apache.commons.math4.legacy.ode.FieldODEStateAndDerivative: Simple constructor.
FieldODEStateAndDerivative(T, T[], T[], T[][], T[][]) - Constructor for class org.apache.commons.math4.legacy.ode.FieldODEStateAndDerivative: Simple constructor.
FieldSecondaryEquations<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode: This interface allows users to add secondary differential equations to a primary set of differential equations.
FieldStepHandler<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode.sampling: This interface represents a handler that should be called after each successful step.
FieldStepInterpolator<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode.sampling: This interface represents an interpolator over the last step during an ODE integration.
FieldStepNormalizer<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.sampling: This class wraps an object implementing FieldFixedStepHandler into a FieldStepHandler.
FieldStepNormalizer(double, FieldFixedStepHandler<T>) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.FieldStepNormalizer: Simple constructor.
FieldStepNormalizer(double, FieldFixedStepHandler<T>, StepNormalizerBounds) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.FieldStepNormalizer: Simple constructor.
FieldStepNormalizer(double, FieldFixedStepHandler<T>, StepNormalizerMode) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.FieldStepNormalizer: Simple constructor.
FieldStepNormalizer(double, FieldFixedStepHandler<T>, StepNormalizerMode, StepNormalizerBounds) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.FieldStepNormalizer: Simple constructor.
FieldVector<T extends FieldElement<T>> - Interface in org.apache.commons.math4.legacy.linear: Interface defining a field-valued vector with basic algebraic operations.
FieldVectorChangingVisitor<T extends FieldElement<?>> - Interface in org.apache.commons.math4.legacy.linear: This interface defines a visitor for the entries of a vector.
FieldVectorPreservingVisitor<T extends FieldElement<?>> - Interface in org.apache.commons.math4.legacy.linear: This interface defines a visitor for the entries of a vector.
fill(T) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Sets all elements to the given value.
filterStep(double, boolean, boolean) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Filter the integration step.
filterStep(T, boolean, boolean) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Filter the integration step.
FilterType - Enum in org.apache.commons.math4.legacy.ode.events: Enumerate for filtering events.
finalizeStep() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Finalize the step.
findMaxY(WeightedObservedPoint[]) - Method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter.ParameterGuesser: Finds index of point in specified points with the largest Y.
findSameChromosome(Population) - Method in class org.apache.commons.math4.legacy.genetics.Chromosome: Searches the population for another chromosome with the same representation.
FiniteDifferencesDifferentiator - Class in org.apache.commons.math4.legacy.analysis.differentiation: Univariate functions differentiator using finite differences.
FiniteDifferencesDifferentiator(int, double) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Build a differentiator with number of points and step size when independent variable is unbounded.
FiniteDifferencesDifferentiator(int, double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Build a differentiator with number of points and step size when independent variable is bounded.
fireInitializationEvent(IterationEvent) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Informs all registered listeners that the initial phase (prior to the main iteration loop) has been completed.
fireIterationPerformedEvent(IterationEvent) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Informs all registered listeners that a new iteration (in the main iteration loop) has been performed.
fireIterationStartedEvent(IterationEvent) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Informs all registered listeners that a new iteration (in the main iteration loop) has been started.
fireTerminationEvent(IterationEvent) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Informs all registered listeners that the final phase (post-iterations) has been completed.
FIRST - org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Include the first point, but not the last point.
firstIncluded() - Method in enum org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Returns a value indicating whether the first point should be passed to the underlying fixed step size step handler.
FirstOrderConverter - Class in org.apache.commons.math4.legacy.ode: This class converts second order differential equations to first order ones.
FirstOrderConverter(SecondOrderDifferentialEquations) - Constructor for class org.apache.commons.math4.legacy.ode.FirstOrderConverter: Simple constructor.
FirstOrderDifferentialEquations - Interface in org.apache.commons.math4.legacy.ode: This interface represents a first order differential equations set.
FirstOrderFieldDifferentialEquations<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode: This interface represents a first order differential equations set.
FirstOrderFieldIntegrator<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.ode: This interface represents a first order integrator for differential equations.
FirstOrderIntegrator - Interface in org.apache.commons.math4.legacy.ode: This interface represents a first order integrator for differential equations.
fit(Collection<WeightedObservedPoint>) - Method in class org.apache.commons.math4.legacy.fitting.AbstractCurveFitter: Fits a curve.
fit(MixtureMultivariateNormalDistribution) - Method in class org.apache.commons.math4.legacy.distribution.fitting.MultivariateNormalMixtureExpectationMaximization: Fit a mixture model to the data supplied to the constructor.
fit(MixtureMultivariateNormalDistribution, int, double) - Method in class org.apache.commons.math4.legacy.distribution.fitting.MultivariateNormalMixtureExpectationMaximization: Fit a mixture model to the data supplied to the constructor.
fitness() - Method in interface org.apache.commons.math4.legacy.genetics.Fitness: Compute the fitness.
Fitness - Interface in org.apache.commons.math4.legacy.genetics: Fitness of a chromosome.
fix1stArgument(BivariateFunction, double) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Creates a unary function by fixing the first argument of a binary function.
fix2ndArgument(BivariateFunction, double) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Creates a unary function by fixing the second argument of a binary function.
FIXED - org.apache.commons.math4.legacy.stat.ranking.NaNStrategy: NaNs are left in place.
FixedElapsedTime - Class in org.apache.commons.math4.legacy.genetics: Stops after a fixed amount of time has elapsed.
FixedElapsedTime(long) - Constructor for class org.apache.commons.math4.legacy.genetics.FixedElapsedTime: Create a new FixedElapsedTime instance.
FixedElapsedTime(long, TimeUnit) - Constructor for class org.apache.commons.math4.legacy.genetics.FixedElapsedTime: Create a new FixedElapsedTime instance.
FixedGenerationCount - Class in org.apache.commons.math4.legacy.genetics: Stops after a fixed number of generations.
FixedGenerationCount(int) - Constructor for class org.apache.commons.math4.legacy.genetics.FixedGenerationCount: Create a new FixedGenerationCount instance.
FixedStepHandler - Interface in org.apache.commons.math4.legacy.ode.sampling: This interface represents a handler that should be called after each successful fixed step.
FLETCHER_REEVES - org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer.Formula: Fletcher-Reeves formula.
floor() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
floor() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
Floor - Class in org.apache.commons.math4.legacy.analysis.function: floor function.
Floor() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Floor
forceSide(int, UnivariateFunction, BracketedUnivariateSolver<UnivariateFunction>, double, double, double, AllowedSolution) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: Force a root found by a non-bracketing solver to lie on a specified side, as if the solver were a bracketing one.
format(Double) - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: This method calls ComplexFormat.format(Object,StringBuffer,FieldPosition).
format(Object, StringBuffer, FieldPosition) - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: Formats a object to produce a string.
format(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: This method calls RealMatrixFormat.format(RealMatrix,StringBuffer,FieldPosition).
format(RealMatrix, StringBuffer, FieldPosition) - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Formats a RealMatrix object to produce a string.
format(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: This method calls RealVectorFormat.format(RealVector,StringBuffer,FieldPosition).
format(RealVector, StringBuffer, FieldPosition) - Method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Formats a RealVector object to produce a string.
format(Complex) - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: This method calls ComplexFormat.format(Object,StringBuffer,FieldPosition).
format(Complex, StringBuffer, FieldPosition) - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: Formats a Complex object to produce a string.
formatDouble(double, NumberFormat, StringBuffer, FieldPosition) - Static method in class org.apache.commons.math4.legacy.util.CompositeFormat: Formats a double value to produce a string.
fraction(double, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Create a fraction.
fraction(int, int) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Create a fraction.
fraction(int, int) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.RungeKuttaFieldIntegrator: Create a fraction.
Frequency<T extends Comparable<T>> - Class in org.apache.commons.math4.legacy.stat: Maintains a frequency distribution.
Frequency() - Constructor for class org.apache.commons.math4.legacy.stat.Frequency: Default constructor.
Frequency(Comparator<T>) - Constructor for class org.apache.commons.math4.legacy.stat.Frequency: Constructor allowing values Comparator to be specified.
from(int, double[]) - Static method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Factory that creates a new instance from the specified data.
from(int, double[], Function<SummaryStatistics, ContinuousDistribution>) - Static method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Factory that creates a new instance from the specified data.
FunctionUtils - Class in org.apache.commons.math4.legacy.analysis: Utilities for manipulating function objects.
FuzzyKMeansClusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: Fuzzy K-Means clustering algorithm.
FuzzyKMeansClusterer(int, double) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Creates a new instance of a FuzzyKMeansClusterer.
FuzzyKMeansClusterer(int, double, int, DistanceMeasure) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Creates a new instance of a FuzzyKMeansClusterer.
FuzzyKMeansClusterer(int, double, int, DistanceMeasure, double, UniformRandomProvider) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Creates a new instance of a FuzzyKMeansClusterer.

G

g(double[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.GTest: Computes the G statistic for Goodness of Fit comparing observed and expected frequency counts.
g(double[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
g(double, double[]) - Method in class org.apache.commons.math4.legacy.ode.events.EventFilter: Compute the value of the switching function.
g(double, double[]) - Method in interface org.apache.commons.math4.legacy.ode.events.EventHandler: Compute the value of the switching function.
g(FieldODEStateAndDerivative<T>) - Method in interface org.apache.commons.math4.legacy.ode.events.FieldEventHandler: Compute the value of the switching function.
gaussian(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.random.CorrelatedVectorFactory
Gaussian - Class in org.apache.commons.math4.legacy.analysis.function: Gaussian function.
Gaussian() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Gaussian: Normalized gaussian with zero mean and unit standard deviation.
Gaussian(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Gaussian: Normalized gaussian with given mean and standard deviation.
Gaussian(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Gaussian: Gaussian with given normalization factor, mean and standard deviation.
Gaussian.Parametric - Class in org.apache.commons.math4.legacy.analysis.function: Parametric function where the input array contains the parameters of the Gaussian.
GaussianCurveFitter - Class in org.apache.commons.math4.legacy.fitting: Fits points to a Gaussian function.
GaussianCurveFitter.ParameterGuesser - Class in org.apache.commons.math4.legacy.fitting: Guesses the parameters norm, mean, and sigma of a Gaussian.Parametric based on the specified observed points.
GaussIntegrator - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: Class that implements the Gaussian rule for integrating a weighted function.
GaussIntegrator(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegrator: Creates an integrator from the given points and weights.
GaussIntegrator(Pair<double[], double[]>) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegrator: Creates an integrator from the given pair of points (first element of the pair) and weights (second element of the pair.
GaussIntegratorFactory - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: Class that provides different ways to compute the nodes and weights to be used by the Gaussian integration rule.
GaussIntegratorFactory() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegratorFactory
GaussNewtonOptimizer - Class in org.apache.commons.math4.legacy.fitting.leastsquares: Gauss-Newton least-squares solver.
GaussNewtonOptimizer() - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer: Creates a Gauss Newton optimizer.
GaussNewtonOptimizer(GaussNewtonOptimizer.Decomposition) - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer: Create a Gauss Newton optimizer that uses the given decomposition algorithm to solve the normal equations.
GaussNewtonOptimizer.Decomposition - Enum in org.apache.commons.math4.legacy.fitting.leastsquares: The decomposition algorithm to use to solve the normal equations.
gDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.GTest: Computes a G (Log-Likelihood Ratio) two sample test statistic for independence comparing frequency counts in observed1 and observed2.
gDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
GeneticAlgorithm - Class in org.apache.commons.math4.legacy.genetics: Implementation of a genetic algorithm.
GeneticAlgorithm(CrossoverPolicy, double, MutationPolicy, double, SelectionPolicy) - Constructor for class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Create a new genetic algorithm.
geometricMean(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the geometric mean of the entries in the input array, or Double.NaN if the array is empty.
geometricMean(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the geometric mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
GeometricMean - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Returns the geometric mean of the available values.
GeometricMean() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Create a GeometricMean instance.
GeometricMean(GeometricMean) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Copy constructor, creates a new GeometricMean identical to the original.
GeometricMean(SumOfLogs) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Create a GeometricMean instance using the given SumOfLogs instance.
GEQ - org.apache.commons.math4.legacy.optim.linear.Relationship: Greater than or equal relationship.
get() - Method in class org.apache.commons.math4.legacy.random.HaltonSequenceGenerator
get() - Method in class org.apache.commons.math4.legacy.random.SobolSequenceGenerator
get(int) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Retrieves a copy of the simplex point stored at index.
get(int, int) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Gets an element.
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EulerFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in interface org.apache.commons.math4.legacy.ode.nonstiff.FieldButcherArrayProvider: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GillFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.LutherFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.MidpointFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getA() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ThreeEighthesFieldIntegrator: Get the internal weights from Butcher array (without the first empty row).
getAbsoluteAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Get the absolute accuracy.
getAbsoluteAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.integration.UnivariateIntegrator: Get the absolute accuracy.
getAbsoluteAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Get the absolute accuracy of the solver.
getAbsoluteAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BaseUnivariateSolver: Get the absolute accuracy of the solver.
getAbsoluteAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BracketedRealFieldUnivariateSolver: Get the absolute accuracy of the solver.
getAbsoluteAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Get the absolute accuracy.
getAbsoluteThreshold() - Method in class org.apache.commons.math4.legacy.optim.AbstractConvergenceChecker
getAbsoluteTolerance() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer
getAbsoluteTolerance() - Method in class org.apache.commons.math4.legacy.optim.Tolerance
getAdjustedRSquared() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the adjusted R-squared statistic, defined by the formula R²_adj = 1 - [SSR (n - 1)] / [SSTO (n - p)] where SSR is the sum of squared residuals}, SSTO is the total sum of squares}, n is the number of observations and p is the number of parameters estimated (including the intercept).
getAgrestiCoullInterval(int, int, double) - Static method in class org.apache.commons.math4.legacy.stat.interval.IntervalUtils: Create an Agresti-Coull binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
getAllDerivatives() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Get all partial derivatives.
getArity() - Method in class org.apache.commons.math4.legacy.genetics.TournamentSelection: Gets the arity (number of chromosomes drawn to the tournament).
getAvailableLocales() - Static method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Get the set of locales for which real vectors formats are available.
getAvailableLocales() - Static method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Get the set of locales for which real vectors formats are available.
getAvailableLocales() - Static method in class org.apache.commons.math4.legacy.util.ComplexFormat: Get the set of locales for which complex formats are available.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaFieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EulerFieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in interface org.apache.commons.math4.legacy.ode.nonstiff.FieldButcherArrayProvider: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GillFieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.LutherFieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.MidpointFieldIntegrator: Get the external weights for the high order method from Butcher array.
getB() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ThreeEighthesFieldIntegrator: Get the external weights for the high order method from Butcher array.
getBinCount() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Returns the number of bins.
getBinStats() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Returns a copy of the SummaryStatistics instances containing statistics describing the values in each of the bins.
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ClassicalRungeKuttaFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EulerFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in interface org.apache.commons.math4.legacy.ode.nonstiff.FieldButcherArrayProvider: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GillFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.LutherFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.MidpointFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getC() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.ThreeEighthesFieldIntegrator: Get the time steps from Butcher array (without the first zero).
getCenters() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Returns a copy of the centers array.
getCheck() - Method in class org.apache.commons.math4.legacy.linear.ConjugateGradient: Returns true if positive-definiteness should be checked for both matrix and preconditioner.
getCheck() - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns true if symmetry of the matrix, and symmetry as well as positive definiteness of the preconditioner should be checked.
getChiSquare() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.AbstractEvaluation: Get the sum of the squares of the residuals.
getChiSquare() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the sum of the squares of the residuals.
getChromosomeList() - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Access the list of chromosomes.
getChromosomes() - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Returns an unmodifiable list of the chromosomes in this population.
getClopperPearsonInterval(int, int, double) - Static method in class org.apache.commons.math4.legacy.stat.interval.IntervalUtils: Create a Clopper-Pearson binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
getClusters() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Returns the list of clusters resulting from the last call to FuzzyKMeansClusterer.cluster(Collection).
getCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Returns a copy of the coefficients array.
getCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Returns a copy of the coefficients array.
getCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Returns a copy of the coefficients array.
getCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.solvers.AbstractPolynomialSolver
getCoefficients() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearConstraint: Gets the coefficients of the constraint (left hand side).
getCoefficients() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction: Gets the coefficients of the linear equation being optimized.
getColumn() - Method in exception org.apache.commons.math4.legacy.linear.NonPositiveDefiniteMatrixException
getColumn() - Method in exception org.apache.commons.math4.legacy.linear.NonSymmetricMatrixException
getColumn(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the entries in column number col as an array.
getColumn(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get the entries at the given column index as an array.
getColumn(int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Get the entries in column number col as an array.
getColumn(int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Get the entries at the given column index as an array.
getColumn(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Get the entries in column number col as an array.
getColumn(int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Get the entries at the given column index as an array.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Gets the number of columns.
getColumnDimension() - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Gets the number of columns.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Gets the number of columns.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Gets the number of columns.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.JacobiPreconditioner: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.RealLinearOperator: Returns the dimension of the domain of this operator.
getColumnDimension() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Gets the number of columns.
getColumnMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the entries in column number column as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get the entries at the given column index as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Get the entries in column number column as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Get the entries at the given column index as a column matrix.
getColumnMatrix(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Get the entries in column number column as a column matrix.
getColumnMatrix(int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Get the entries at the given column index as a column matrix.
getColumnSeparator() - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Get the format separator between components.
getColumnVector(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the entries in column number column as a vector.
getColumnVector(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get the entries at the given column index as a vector.
getColumnVector(int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Returns the entries in column number column as a vector.
getColumnVector(int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Get the entries at the given column index as a vector.
getColumnVector(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns the entries in column number column as a vector.
getColumnVector(int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Get the entries at the given column index as a vector.
getCompiler(int, int) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Get the compiler for number of free parameters and order.
getCompleteState() - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get the complete current state.
getComponents() - Method in class org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution: Gets the distributions that make up the mixture model.
getConditionNumber() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Return the condition number of the matrix.
getConfidenceLevel() - Method in class org.apache.commons.math4.legacy.stat.interval.ConfidenceInterval
getConstantTerm() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction: Gets the constant of the linear equation being optimized.
getConstraints() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearConstraintSet: Gets the set of linear constraints.
getConstraints() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearOptimizer
getControlMatrix() - Method in class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Returns the control matrix.
getControlMatrix() - Method in interface org.apache.commons.math4.legacy.filter.ProcessModel: Returns the control matrix.
getConvergence() - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Get the convergence threshold for event localization.
getConvergence() - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Get the convergence threshold for event localization.
getConvergenceChecker() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresAdapter: Gets the convergence checker.
getConvergenceChecker() - Method in class org.apache.commons.math4.legacy.optim.AbstractOptimizationProblem: Gets the convergence checker.
getConvergenceChecker() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Gets the convergence checker.
getConvergenceChecker() - Method in interface org.apache.commons.math4.legacy.optim.OptimizationProblem: Gets the convergence checker.
getCoolingSchedule() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing
getCorrelationMatrix() - Method in class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Returns the correlation matrix.
getCorrelationMatrix() - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Returns the correlation matrix.
getCorrelationMatrix() - Method in class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Calculate the Spearman Rank Correlation Matrix.
getCorrelationPValues() - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Returns a matrix of p-values associated with the (two-sided) null hypothesis that the corresponding correlation coefficient is zero.
getCorrelationStandardErrors() - Method in class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Returns a matrix of standard errors associated with the estimates in the correlation matrix.
getCorrelationStandardErrors().getEntry(i,j) is the standard error associated with getCorrelationMatrix.getEntry(i,j)
getCost() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.AbstractEvaluation: Get the cost.
getCost() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the cost.
getCostRelativeTolerance() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer: Gets the value of a tuning parameter.
getCount(T) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns the number of values equal to v.
getCounter() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get the evaluations counter.
getCovariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the covariance matrix of the values that have been added.
getCovariance() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns the covariance of the available values.
getCovariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the covariance matrix of the values that have been added.
getCovariance(double) - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Returns the n × n covariance matrix.
getCovariance(int, int) - Method in class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Get the covariance for an individual element of the covariance matrix.
getCovarianceMatrix() - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Returns the covariance matrix.
getCovarianceMatrix() - Method in class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Returns the covariance matrix.
getCovarianceOfParameters(int, int) - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the covariance between regression parameters i and j.
getCovariances() - Method in class org.apache.commons.math4.legacy.distribution.MultivariateNormalDistribution: Gets the covariance matrix.
getCovariances(double) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.AbstractEvaluation: Get the covariance matrix of the optimized parameters.
getCovariances(double) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the covariance matrix of the optimized parameters.
getCrossoverPoints() - Method in class org.apache.commons.math4.legacy.genetics.NPointCrossover: Returns the number of crossover points used by this CrossoverPolicy.
getCrossoverPolicy() - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Returns the crossover policy.
getCrossoverRate() - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Returns the crossover rate.
getCumFreq(T) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns the cumulative frequency of values less than or equal to v.
getCumPct(T) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns the cumulative percentage of values less than or equal to v (as a proportion between 0 and 1).
getCurrentMainSetJacobian(double[][]) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Get the current value of the Jacobian matrix with respect to state.
getCurrentParameterJacobian(String, double[]) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Get the current value of the Jacobian matrix with respect to one parameter.
getCurrentSignedStepsize() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the current signed value of the integration stepsize.
getCurrentSignedStepsize() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get the current signed value of the integration stepsize.
getCurrentSignedStepsize() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Get the current signed value of the integration stepsize.
getCurrentSignedStepsize() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Get the current signed value of the integration stepsize.
getCurrentState() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Get the state at current grid point time.
getCurrentState() - Method in interface org.apache.commons.math4.legacy.ode.sampling.FieldStepInterpolator: Get the state at current grid point time.
getCurrentStepStart() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the current value of the step start time t_i.
getCurrentStepStart() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get the current value of the step start time t_i.
getCurrentStepStart() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Get the current value of the step start time t_i.
getCurrentStepStart() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Get the current value of the step start time t_i.
getCurrentStepStart() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Get the current value of the step start time t_i.
getCurrentTime() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Get the current soft grid point time.
getCurrentTime() - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Get the current grid point time.
getD() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Gets the block diagonal matrix D of the decomposition.
getData() - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Return the covariance matrix as two-dimensional array.
getData() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Get a copy of the stored data array.
getDataPoints() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Returns an unmodifiable list of the data points used in the last call to FuzzyKMeansClusterer.cluster(Collection).
getDataRef() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Get a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Get a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Returns a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Get a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Gets a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Get a reference to the stored data array.
getDecomposition() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer: Get the matrix decomposition algorithm used to solve the normal equations.
getDefaultNumberFormat() - Static method in class org.apache.commons.math4.legacy.util.CompositeFormat: Create a default number format.
getDefaultNumberFormat(Locale) - Static method in class org.apache.commons.math4.legacy.util.CompositeFormat: Create a default number format.
getDerivative() - Method in class org.apache.commons.math4.legacy.ode.FieldODEStateAndDerivative: Get derivative of the main state at time.
getDerivative(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Get the derivative with respect to a particular index variable.
getDeterminant() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldLUDecomposition: Return the determinant of the matrix.
getDeterminant() - Method in class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Return the determinant of the matrix.
getDeterminant() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Computes the determinant of the matrix.
getDeterminant() - Method in class org.apache.commons.math4.legacy.linear.FieldLUDecomposition: Return the determinant of the matrix.
getDeterminant() - Method in class org.apache.commons.math4.legacy.linear.LUDecomposition: Return the determinant of the matrix.
getDiagonalOfHatMatrix(double[]) - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Gets the diagonal of the Hat matrix also known as the leverage matrix.
getDimension() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Get the space dimensionality.
getDimension() - Method in class org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution: Gets the number of random variables of the distribution.
getDimension() - Method in interface org.apache.commons.math4.legacy.distribution.MultivariateRealDistribution: Gets the number of random variables of the distribution.
getDimension() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Returns the size of the vector.
getDimension() - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Returns the size of the vector.
getDimension() - Method in class org.apache.commons.math4.legacy.ode.EquationsMapper: Get the dimension of the secondary state parameters.
getDimension() - Method in interface org.apache.commons.math4.legacy.ode.FieldSecondaryEquations: Get the dimension of the secondary state parameters.
getDimension() - Method in class org.apache.commons.math4.legacy.ode.FirstOrderConverter: Get the dimension of the problem.
getDimension() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderDifferentialEquations: Get the dimension of the problem.
getDimension() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldDifferentialEquations: Get the dimension of the problem.
getDimension() - Method in interface org.apache.commons.math4.legacy.ode.SecondaryEquations: Get the dimension of the secondary state parameters.
getDimension() - Method in interface org.apache.commons.math4.legacy.ode.SecondOrderDifferentialEquations: Get the dimension of the problem.
getDimension() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Returns the space dimension.
getDimension() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the dimension of the data.
getDimension() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns the dimension of the data.
getDimension() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the dimension of the data.
getDistance(OpenMapRealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Optimized method to compute distance.
getDistance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Distance between two vectors.
getDistance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Distance between two vectors.
getDistance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Distance between two vectors.
getDistanceMeasure() - Method in class org.apache.commons.math4.legacy.ml.clustering.Clusterer: Returns the DistanceMeasure instance used by this clusterer.
getEigenvector(int) - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Gets a copy of the i^th eigenvector of the original matrix.
getElement(int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the element at the specified index.
getElement(int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Returns the element at the specified index.
getElitismRate() - Method in class org.apache.commons.math4.legacy.genetics.ElitisticListPopulation: Access the elitism rate.
getEndProbability() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing
getEntry(int) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Returns the entry in the specified index.
getEntry(int) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Return the entry at the specified index.
getEntry(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Returns the entry in the specified index.
getEntry(int) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Return the entry at the specified index.
getEntry(int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Return the entry at the specified index.
getEntry(int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Returns the entry in the specified index.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Get the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Get the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Get the entry in the specified row and column.
getEntry(int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Get the entry in the specified row and column.
getEntry(int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Get the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Returns the entry in the specified row and column.
getEpochDuration() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing
getEps() - Method in class org.apache.commons.math4.legacy.ml.clustering.DBSCANClusterer: Returns the maximum radius of the neighborhood to be considered.
getEpsilon() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Returns the convergence criteria used by this instance.
getEquations() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the differential equations to integrate.
getErrorCovariance() - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Returns the current error covariance matrix.
getErrorCovarianceMatrix() - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Returns a copy of the current error covariance matrix.
getErrorSumSquares() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the sum of squared errors (SSE) associated with the regression model.
getEstimationType() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Get the estimation type used for computation.
getEvaluationCounter() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresAdapter: Get a independent Incrementor that counts up to the maximum number of evaluations and then throws an exception.
getEvaluationCounter() - Method in class org.apache.commons.math4.legacy.optim.AbstractOptimizationProblem: Get a independent Incrementor that counts up to the maximum number of evaluations and then throws an exception.
getEvaluationCounter() - Method in interface org.apache.commons.math4.legacy.optim.OptimizationProblem: Get a independent Incrementor that counts up to the maximum number of evaluations and then throws an exception.
getEvaluations() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Get the number of function evaluations of the last run of the integrator.
getEvaluations() - Method in interface org.apache.commons.math4.legacy.analysis.integration.UnivariateIntegrator: Get the number of function evaluations of the last run of the integrator.
getEvaluations() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Get the number of evaluations of the objective function.
getEvaluations() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BaseUnivariateSolver: Get the number of evaluations of the objective function.
getEvaluations() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BracketedRealFieldUnivariateSolver: Get the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Get the number of evaluations of the objective function.
getEvaluations() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresOptimizer.Optimum: Get the number of times the model was evaluated in order to produce this optimum.
getEvaluations() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the number of evaluations of the differential equations function.
getEvaluations() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get the number of evaluations of the differential equations function.
getEvaluations() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Get the number of evaluations of the differential equations function.
getEvaluations() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Get the number of evaluations of the differential equations function.
getEvaluations() - Method in class org.apache.commons.math4.legacy.optim.BaseMultiStartMultivariateOptimizer: Gets the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Gets the number of evaluations of the objective function.
getEvaluations() - Method in class org.apache.commons.math4.legacy.optim.univariate.BracketFinder
getEvaluations() - Method in class org.apache.commons.math4.legacy.optim.univariate.MultiStartUnivariateOptimizer: Gets the number of evaluations of the objective function.
getEvaluationsCounter() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the evaluations counter.
getEventHandler() - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Get the underlying event handler.
getEventHandler() - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Get the underlying event handler.
getEventHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get all the event handlers that have been added to the integrator.
getEventHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get all the event handlers that have been added to the integrator.
getEventHandlers() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Get all the event handlers that have been added to the integrator.
getEventHandlers() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Get all the event handlers that have been added to the integrator.
getEventTime() - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Get the occurrence time of the event triggered in the current step.
getEventTime() - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Get the occurrence time of the event triggered in the current step.
getExpandable() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get the differential equations to integrate.
getExpectedColumnDimension() - Method in exception org.apache.commons.math4.legacy.linear.MatrixDimensionMismatchException
getExpectedRowDimension() - Method in exception org.apache.commons.math4.legacy.linear.MatrixDimensionMismatchException
getExponent() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Return the exponent of the instance value, removing the bias.
getFHi() - Method in class org.apache.commons.math4.legacy.optim.univariate.BracketFinder: Get function value at BracketFinder.getHi().
getField() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
getField() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
getField() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix
getField() - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the type of field elements of the matrix.
getField() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Get the type of field elements of the vector.
getField() - Method in class org.apache.commons.math4.legacy.linear.BigReal
getField() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Get the type of field elements of the matrix.
getField() - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Get the type of field elements of the vector.
getField() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Get the type of field elements of the vector.
getField() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the field to which state vector elements belong.
getFinalTime() - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputFieldModel: Get the final integration time.
getFinalTime() - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Get the final integration time.
getFirst() - Method in class org.apache.commons.math4.legacy.genetics.ChromosomePair: Access the first chromosome.
getFirstIndex() - Method in class org.apache.commons.math4.legacy.ode.EquationsMapper: Get the index of the first equation element in complete state arrays.
getFitness() - Method in class org.apache.commons.math4.legacy.genetics.Chromosome: Access the fitness of this chromosome.
getFittedModel() - Method in class org.apache.commons.math4.legacy.distribution.fitting.MultivariateNormalMixtureExpectationMaximization: Gets the fitted model.
getFittestChromosome() - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Access the fittest chromosome in this population.
getFittestChromosome() - Method in interface org.apache.commons.math4.legacy.genetics.Population: Access the fittest chromosome in this population.
getFLo() - Method in class org.apache.commons.math4.legacy.optim.univariate.BracketFinder: Get function value at BracketFinder.getLo().
getFMid() - Method in class org.apache.commons.math4.legacy.optim.univariate.BracketFinder: Get function value at BracketFinder.getMid().
getFormat() - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Get the components format.
getFormat() - Method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Get the components format.
getFreeParameters() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Get the number of free parameters.
getFreeParameters() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Get the number of free parameters.
getFrobeniusNorm() - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the Frobenius norm of the matrix.
getFrobeniusNorm() - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the Frobenius norm of the matrix.
getFrobeniusNorm() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the Frobenius norm of the matrix.
getFunction() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearOptimizer
getFunctionValueAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Get the function value accuracy of the solver.
getFunctionValueAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BaseUnivariateSolver: Get the function value accuracy of the solver.
getFunctionValueAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BracketedRealFieldUnivariateSolver: Get the function value accuracy of the solver.
getFunctionValueAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Get the function accuracy.
getFuzziness() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Returns the fuzziness factor used by this instance.
getGenerationsEvolved() - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Returns the number of generations evolved to reach StoppingCondition in the last run.
getGeneratorUpperBounds() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Returns the upper bounds of the subintervals of [0, 1] used in generating data from the empirical distribution.
getGeoMeanImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the currently configured geometric mean implementation.
getGeoMeanImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the currently configured geometric mean implementation.
getGeoMeanImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the currently configured geometric mean implementation.
getGeoMeanImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the currently configured geometric mean implementation.
getGeometricMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns the geometric mean of all the aggregated data.
getGeometricMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the geometric mean of the available values.
getGeometricMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns an array whose i^th entry is the geometric mean of the.
getGeometricMean() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns an array whose i^th entry is the.
getGeometricMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the geometric mean of the values that have been added.
getGeometricMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns an array whose i^th entry is the geometric mean of the.
getGeometricMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the geometric mean of the values that have been added.
getGeometricMeanImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the currently configured geometric mean implementation.
getGlobalCurrentState() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Get the current global grid point state.
getGlobalCurrentTime() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Get the current global grid point time.
getGlobalPreviousState() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Get the previous global grid point state.
getGlobalPreviousTime() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Get the previous global grid point time.
getGoalType() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateOptimizer
getGoalType() - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer
getH() - Method in class org.apache.commons.math4.legacy.linear.QRDecomposition: Returns the Householder reflector vectors.
getHi() - Method in class org.apache.commons.math4.legacy.optim.univariate.BracketFinder
getImagEigenvalue(int) - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Gets the imaginary part of the i^th eigenvalue of the original matrix.
getImagEigenvalues() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Gets a copy of the imaginary parts of the eigenvalues of the original matrix.
getImaginaryCharacter() - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: Access the imaginaryCharacter.
getImaginaryFormat() - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: Access the imaginaryFormat.
getIndex() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector.OpenMapEntry: Get the index of the entry.
getIndex() - Method in class org.apache.commons.math4.legacy.linear.RealVector.Entry: Get the index of the entry.
getInitialBracketingRange() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.LineSearchTolerance
getInitialErrorCovariance() - Method in class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Returns the initial error covariance matrix.
getInitialErrorCovariance() - Method in interface org.apache.commons.math4.legacy.filter.ProcessModel: Returns the initial error covariance matrix.
getInitialGuess() - Method in class org.apache.commons.math4.legacy.optim.InitialGuess: Gets the initial guess.
getInitialStateEstimate() - Method in class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Returns the initial state estimation vector.
getInitialStateEstimate() - Method in interface org.apache.commons.math4.legacy.filter.ProcessModel: Returns the initial state estimation vector.
getInitialStepBoundFactor() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer: Gets the value of a tuning parameter.
getInitialTime() - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputFieldModel: Get the initial integration time.
getInitialTime() - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Get the initial integration time.
getInstance() - Static method in class org.apache.commons.math4.legacy.linear.BigRealField: Get the unique instance.
getInstance() - Static method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Returns the default real vector format for the current locale.
getInstance() - Static method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Returns the default real vector format for the current locale.
getInstance() - Static method in class org.apache.commons.math4.legacy.ode.sampling.DummyStepHandler: Get the only instance.
getInstance() - Static method in class org.apache.commons.math4.legacy.util.ComplexFormat: Returns the default complex format for the current locale.
getInstance(int) - Static method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsNordsieckTransformer: Get the Nordsieck transformer for a given number of steps.
getInstance(String, Locale) - Static method in class org.apache.commons.math4.legacy.util.ComplexFormat: Returns the default complex format for the given locale.
getInstance(Locale) - Static method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Returns the default real vector format for the given locale.
getInstance(Locale) - Static method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Returns the default real vector format for the given locale.
getInstance(Locale) - Static method in class org.apache.commons.math4.legacy.util.ComplexFormat: Returns the default complex format for the given locale.
getInstance(Field<T>, int) - Static method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsNordsieckFieldTransformer: Get the Nordsieck transformer for a given field and number of steps.
getIntercept() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the intercept of the estimated regression line, if SimpleRegression.hasIntercept() is true; otherwise 0.
getInterceptStdErr() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the standard error of the intercept estimate, usually denoted s(b0).
getInterpolatedDerivatives() - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Get the derivatives of the state vector of the interpolated point.
getInterpolatedDerivatives() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Get the derivatives of the state vector of the interpolated point.
getInterpolatedDerivatives() - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Get the derivatives of the state vector of the interpolated point.
getInterpolatedSecondaryDerivatives(int) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Get the interpolated secondary derivatives corresponding to the secondary equations.
getInterpolatedSecondaryDerivatives(int) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Get the interpolated secondary derivatives corresponding to the secondary equations.
getInterpolatedSecondaryDerivatives(int) - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Get the interpolated secondary derivatives corresponding to the secondary equations.
getInterpolatedSecondaryState(int) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Get the interpolated secondary state corresponding to the secondary equations.
getInterpolatedSecondaryState(int) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Get the interpolated secondary state corresponding to the secondary equations.
getInterpolatedSecondaryState(int) - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Get the interpolated secondary state corresponding to the secondary equations.
getInterpolatedState() - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Get the state vector of the interpolated point.
getInterpolatedState() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Get the state vector of the interpolated point.
getInterpolatedState() - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Get the state vector of the interpolated point.
getInterpolatedState(T) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputFieldModel: Get the state at interpolated time.
getInterpolatedState(T) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Get the state at interpolated time.
getInterpolatedState(T) - Method in interface org.apache.commons.math4.legacy.ode.sampling.FieldStepInterpolator: Get the state at interpolated time.
getInterpolatedStateVariation() - Method in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: Get the state vector variation from current to interpolated state.
getInterpolatedTime() - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Get the time of the interpolated point.
getInterpolatedTime() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Get the time of the interpolated point.
getInterpolatedTime() - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Get the time of the interpolated point.
getInterpolatingPoints() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Returns a copy of the interpolating points array.
getInterpolatingValues() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Returns a copy of the interpolating values array.
getInverse() - Method in interface org.apache.commons.math4.legacy.field.linalg.FieldDecompositionSolver: Computes the inverse of a decomposed (square) matrix.
getInverse() - Method in interface org.apache.commons.math4.legacy.linear.DecompositionSolver: Get the pseudo-inverse of the decomposed matrix.
getInverse() - Method in interface org.apache.commons.math4.legacy.linear.FieldDecompositionSolver: Get the inverse (or pseudo-inverse) of the decomposed matrix.
getInverseConditionNumber() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Computes the inverse of the condition number.
getIterationCounter() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresAdapter: Get a independent Incrementor that counts up to the maximum number of iterations and then throws an exception.
getIterationCounter() - Method in class org.apache.commons.math4.legacy.optim.AbstractOptimizationProblem: Get a independent Incrementor that counts up to the maximum number of iterations and then throws an exception.
getIterationCounter() - Method in interface org.apache.commons.math4.legacy.optim.OptimizationProblem: Get a independent Incrementor that counts up to the maximum number of iterations and then throws an exception.
getIterationManager() - Method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolver: Returns the iteration manager attached to this solver.
getIterations() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Get the number of iterations of the last run of the integrator.
getIterations() - Method in interface org.apache.commons.math4.legacy.analysis.integration.UnivariateIntegrator: Get the number of iterations of the last run of the integrator.
getIterations() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresOptimizer.Optimum: Get the number of times the algorithm iterated in order to produce this optimum.
getIterations() - Method in class org.apache.commons.math4.legacy.linear.IterationEvent: Returns the number of iterations performed at the time this event is created.
getIterations() - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Returns the number of iterations of this solver, 0 if no iterations has been performed yet.
getIterations() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Gets the number of iterations performed by the algorithm.
getJacobian() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the weighted Jacobian matrix.
getK() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Return the number of clusters this instance will use.
getKnots() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialSplineFunction: Get an array copy of the knot points.
getKthSelector() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Get the kthSelector used for computation.
getKurtosis() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the Kurtosis of the available values.
getKurtosisImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the currently configured kurtosis implementation.
getL() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldLUDecomposition: Builds the "L" matrix of the decomposition.
getL() - Method in class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Returns the matrix L of the decomposition.
getL() - Method in class org.apache.commons.math4.legacy.linear.FieldLUDecomposition: Returns the matrix L of the decomposition.
getL() - Method in class org.apache.commons.math4.legacy.linear.LUDecomposition: Returns the matrix L of the decomposition.
getL1Distance(OpenMapRealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Distance between two vectors.
getL1Distance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Distance between two vectors.
getL1Distance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Distance between two vectors.
getL1Distance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Distance between two vectors.
getL1Norm() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Returns the L₁ norm of the vector.
getL1Norm() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Returns the L₁ norm of the vector.
getLength() - Method in class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Returns the length of the chromosome.
getLInfDistance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Distance between two vectors.
getLInfDistance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Distance between two vectors.
getLInfDistance(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Distance between two vectors.
getLInfNorm() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Returns the L_∞ norm of the vector.
getLInfNorm() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Returns the L_∞ norm of the vector.
getLo() - Method in class org.apache.commons.math4.legacy.optim.univariate.BracketFinder
getLogLikelihood() - Method in class org.apache.commons.math4.legacy.distribution.fitting.MultivariateNormalMixtureExpectationMaximization: Gets the log likelihood of the data under the fitted model.
getLower() - Method in class org.apache.commons.math4.legacy.optim.SimpleBounds: Gets the lower bounds.
getLowerBound() - Method in class org.apache.commons.math4.legacy.optim.BaseMultivariateOptimizer
getLowerBound() - Method in class org.apache.commons.math4.legacy.stat.interval.ConfidenceInterval
getLT() - Method in class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Returns the transpose of the matrix L of the decomposition.
getMapper() - Method in class org.apache.commons.math4.legacy.ode.FieldExpandableODE: Get the mapper for the set of equations.
getMax() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator
getMax() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver
getMax() - Method in class org.apache.commons.math4.legacy.optim.univariate.SearchInterval: Gets the upper bound.
getMax() - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer
getMax() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns the maximum of the available values.
getMax() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the maximum of the available values.
getMax() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns an array whose i^th entry is the maximum of the.
getMax() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns an array whose i^th entry is the.
getMax() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummary: Returns the maximum of the available values.
getMax() - Method in class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues
getMax() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the maximum of the values that have been added.
getMax() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns an array whose i^th entry is the maximum of the.
getMax() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the maximum of the values that have been added.
getMaxCheckInterval() - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Get the maximal time interval between events handler checks.
getMaxCheckInterval() - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Get the maximal time interval between events handler checks.
getMaxEval() - Method in class org.apache.commons.math4.legacy.optim.MaxEval: Gets the maximum number of evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Get the maximum number of function evaluations.
getMaxEvaluations() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BaseUnivariateSolver: Get the maximum number of function evaluations.
getMaxEvaluations() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BracketedRealFieldUnivariateSolver: Get the maximum number of function evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Get the maximal number of function evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Get the maximal number of functions evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Gets the maximal number of function evaluations.
getMaxEvaluations() - Method in class org.apache.commons.math4.legacy.optim.univariate.BracketFinder
getMaxGrowth() - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Get the maximal growth factor for stepsize control.
getMaxGrowth() - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Get the maximal growth factor for stepsize control.
getMaxGrowth() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Get the maximal growth factor for stepsize control.
getMaxGrowth() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Get the maximal growth factor for stepsize control.
getMaximalIterationCount() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Get the upper limit for the number of iterations.
getMaximalIterationCount() - Method in interface org.apache.commons.math4.legacy.analysis.integration.UnivariateIntegrator: Get the upper limit for the number of iterations.
getMaximalOrder() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Get the maximal order.
getMaximalOrder() - Method in class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Get the maximal order.
getMaxImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the currently configured maximum implementation.
getMaxImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the currently configured maximum implementation.
getMaxImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the currently configured maximum implementation.
getMaxImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the currently configured maximum implementation.
getMaxImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the currently configured maximum implementation.
getMaxIndex() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Get the index of the maximum entry.
getMaxIter() - Method in class org.apache.commons.math4.legacy.optim.MaxIter: Gets the maximum number of evaluations.
getMaxIterationCount() - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Get the upper limit in the iteration count for event localization.
getMaxIterationCount() - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Get the upper limit in the iteration count for event localization.
getMaxIterations() - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Returns the maximum number of iterations.
getMaxIterations() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Returns the maximum number of iterations this instance will use.
getMaxIterations() - Method in class org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer: Returns the maximum number of iterations this instance will use.
getMaxIterations() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Gets the maximal number of iterations.
getMaxStep() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Get the maximal step.
getMaxStep() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Get the maximal step.
getMaxValue() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Get the value of the maximum entry.
getMean() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution
getMean() - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution
getMean() - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution
getMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns the arithmetic mean of the available values.
getMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the arithmetic mean of the available values.
getMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns an array whose i^th entry is the mean of the.
getMean() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns an array whose i^th entry is the.
getMean() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummary: Returns the arithmetic mean of the available values.
getMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues
getMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the mean of the values that have been added.
getMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns an array whose i^th entry is the mean of the.
getMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the mean of the values that have been added.
getMeanImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the currently configured mean implementation.
getMeanImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the currently configured mean implementation.
getMeanImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the currently configured mean implementation.
getMeanImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the currently configured mean implementation.
getMeanImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the currently configured mean implementation.
getMeans() - Method in class org.apache.commons.math4.legacy.distribution.MultivariateNormalDistribution: Gets the mean vector.
getMeanSquareError() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the sum of squared errors divided by the degrees of freedom, usually abbreviated MSE.
getMeanSquareError() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the sum of squared errors divided by the degrees of freedom, usually abbreviated MSE.
getMeasurementDimension() - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Returns the dimension of the measurement vector.
getMeasurementMatrix() - Method in class org.apache.commons.math4.legacy.filter.DefaultMeasurementModel: Returns the measurement matrix.
getMeasurementMatrix() - Method in interface org.apache.commons.math4.legacy.filter.MeasurementModel: Returns the measurement matrix.
getMeasurementNoise() - Method in class org.apache.commons.math4.legacy.filter.DefaultMeasurementModel: Returns the measurement noise matrix.
getMeasurementNoise() - Method in interface org.apache.commons.math4.legacy.filter.MeasurementModel: Returns the measurement noise matrix.
getMembershipMatrix() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Returns the nxk membership matrix, where n is the number of data points and k the number of clusters.
getMid() - Method in class org.apache.commons.math4.legacy.optim.univariate.BracketFinder
getMin() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator
getMin() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver
getMin() - Method in class org.apache.commons.math4.legacy.optim.univariate.SearchInterval: Gets the lower bound.
getMin() - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer
getMin() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns the minimum of the available values.
getMin() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the minimum of the available values.
getMin() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns an array whose i^th entry is the minimum of the.
getMin() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns an array whose i^th entry is the.
getMin() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummary: Returns the minimum of the available values.
getMin() - Method in class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues
getMin() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the minimum of the values that have been added.
getMin() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns an array whose i^th entry is the minimum of the.
getMin() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the minimum of the values that have been added.
getMinimalIterationCount() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Get the min limit for the number of iterations.
getMinimalIterationCount() - Method in interface org.apache.commons.math4.legacy.analysis.integration.UnivariateIntegrator: Get the min limit for the number of iterations.
getMinImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the currently configured minimum implementation.
getMinImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the currently configured minimum implementation.
getMinImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the currently configured minimum implementation.
getMinImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the currently configured minimum implementation.
getMinImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the currently configured minimum implementation.
getMinIndex() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Get the index of the minimum entry.
getMinPts() - Method in class org.apache.commons.math4.legacy.ml.clustering.DBSCANClusterer: Returns the minimum number of points needed for a cluster.
getMinReduction() - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Get the minimal reduction factor for stepsize control.
getMinReduction() - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Get the minimal reduction factor for stepsize control.
getMinReduction() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Get the minimal reduction factor for stepsize control.
getMinReduction() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Get the minimal reduction factor for stepsize control.
getMinStep() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Get the minimal step.
getMinStep() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Get the minimal step.
getMinValue() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Get the value of the minimum entry.
getMode() - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns the mode value(s) in comparator order.
getModelFunction() - Method in class org.apache.commons.math4.legacy.fitting.AbstractCurveFitter.TheoreticalValuesFunction
getModelFunctionJacobian() - Method in class org.apache.commons.math4.legacy.fitting.AbstractCurveFitter.TheoreticalValuesFunction
getMutationPolicy() - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Returns the mutation policy.
getMutationRate() - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Returns the mutation rate.
getN() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialSplineFunction: Get the number of spline segments.
getN() - Method in class org.apache.commons.math4.legacy.stat.correlation.Covariance: Returns the number of observations (length of covariate vectors).
getN() - Method in class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: This Covariance method is not supported by a StorelessCovariance, since the number of bivariate observations does not have to be the same for different pairs of covariates - i.e., N as defined in Covariance.getN() is undefined.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns the number of available values.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the number of available values.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialCovariance: Get the number of vectors in the sample.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialMean: Get the number of vectors in the sample.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the number of available values.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Returns the number of values that have been added.
getN() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns the number of available values.
getN() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummary: Returns the number of available values.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues
getN() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StorelessUnivariateStatistic: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the number of available values.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Returns the number of available values.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the number of available values.
getN() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the number of available values.
getN() - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Gets the number of observations added to the regression model.
getN() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the number of observations added to the regression model.
getN() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the number of observations that have been added to the model.
getN() - Method in interface org.apache.commons.math4.legacy.stat.regression.UpdatingMultipleLinearRegression: Returns the number of observations added to the regression model.
getName() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the name of the method.
getName() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get the name of the method.
getName() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Get the name of the method.
getName() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Get the name of the method.
getName() - Method in exception org.apache.commons.math4.legacy.ode.UnknownParameterException
getNanStrategy() - Method in class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: Return the NaNStrategy.
getNaNStrategy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Get the NaN Handling strategy used for computation.
getNbPoints() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Get the number of points to use.
getNewtonCoefficients() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Returns a copy of coefficients in Newton form formula.
getNextIndex() - Method in class org.apache.commons.math4.legacy.random.HaltonSequenceGenerator: Returns the index i of the next point in the Halton sequence that will be returned by calling HaltonSequenceGenerator.get().
getNextIndex() - Method in class org.apache.commons.math4.legacy.random.SobolSequenceGenerator: Returns the index i of the next point in the Sobol sequence that will be returned by calling SobolSequenceGenerator.get().
getNorm() - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Returns the L₂ norm of the vector.
getNorm() - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Returns the L₂ norm of the vector.
getNorm() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Returns the L₂ norm of the matrix.
getNormalApproximationInterval(int, int, double) - Static method in class org.apache.commons.math4.legacy.stat.interval.IntervalUtils: Create a binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level using the Normal approximation to the binomial distribution.
getNormOfResidual() - Method in class org.apache.commons.math4.legacy.linear.DefaultIterativeLinearSolverEvent: Returns the norm of the residual.
getNormOfResidual() - Method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolverEvent: Returns the norm of the residual.
getNSteps() - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Get the number of steps of the multistep method (excluding the one being computed).
getNSteps() - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Get the number of steps of the multistep method (excluding the one being computed).
getNSteps() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsNordsieckTransformer: Deprecated.
as of 3.6, this method is not used anymore
getNumberOfClusters() - Method in class org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer: Return the number of clusters this instance will use.
getNumberOfEquations() - Method in class org.apache.commons.math4.legacy.ode.FieldEquationsMapper: Get the number of equations mapped.
getNumberOfParameters() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the number of parameters estimated in the model.
getNumberOfPoints() - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegrator
getNumberOfSecondaryStates() - Method in class org.apache.commons.math4.legacy.ode.FieldODEState: Get the number of secondary states.
getNumGenerations() - Method in class org.apache.commons.math4.legacy.genetics.FixedGenerationCount: Returns the number of generations that have already passed.
getnVals() - Method in class org.apache.commons.math4.legacy.special.BesselJ.BesselJResult
getObjectiveFunction() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateOptimizer
getObjectiveFunction() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.ObjectiveFunction: Gets the function to be optimized.
getObjectiveFunction() - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariateObjectiveFunction: Gets the function to be optimized.
getObjectiveFunction() - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer
getObjectiveFunctionGradient() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.ObjectiveFunctionGradient: Gets the gradient of the function to be optimized.
getObjectiveFunctionValue() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Get the value of the objective function.
getObservationSize() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresAdapter: Get the number of observations (rows in the Jacobian) in this problem.
getObservationSize() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem: Get the number of observations (rows in the Jacobian) in this problem.
getOmegaInverse() - Method in class org.apache.commons.math4.legacy.stat.regression.GLSMultipleLinearRegression: Get the inverse of the covariance.
getOne() - Method in class org.apache.commons.math4.legacy.linear.BigRealField
getOptima() - Method in class org.apache.commons.math4.legacy.optim.BaseMultiStartMultivariateOptimizer: Gets all the optima found during the last call to optimize.
getOptima() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultiStartMultivariateOptimizer: Gets all the optima found during the last call to optimize.
getOptima() - Method in class org.apache.commons.math4.legacy.optim.univariate.MultiStartUnivariateOptimizer: Gets all the optima found during the last call to optimize.
getOptimizer() - Method in class org.apache.commons.math4.legacy.fitting.AbstractCurveFitter: Creates an optimizer set up to fit the appropriate curve.
getOrder() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Get the derivation order.
getOrder() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Get the derivation order.
getOrder() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54FieldIntegrator: Get the order of the method.
getOrder() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince54Integrator: Get the order of the method.
getOrder() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853FieldIntegrator: Get the order of the method.
getOrder() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.DormandPrince853Integrator: Get the order of the method.
getOrder() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Get the order of the method.
getOrder() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Get the order of the method.
getOrder() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Get the order of the method.
getOrder() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54Integrator: Get the order of the method.
getOrderOfRegressors() - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Gets the order of the regressors, useful if some type of reordering has been called.
getOrthoTolerance() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer: Gets the value of a tuning parameter.
getP() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldLUDecomposition: Builds the "P" matrix.
getP() - Method in class org.apache.commons.math4.legacy.linear.FieldLUDecomposition: Returns the P rows permutation matrix.
getP() - Method in class org.apache.commons.math4.legacy.linear.LUDecomposition: Returns the P rows permutation matrix.
getP() - Method in class org.apache.commons.math4.legacy.linear.RRQRDecomposition: Returns the pivot matrix, P, used in the QR Decomposition of matrix A such that AP = QR.
getParameter(String) - Method in interface org.apache.commons.math4.legacy.ode.ParameterizedODE: Get parameter value from its name.
getParameterEstimate(int) - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the parameter estimate for the regressor at the given index.
getParameterEstimates() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns a copy of the regression parameters estimates.
getParameterRelativeTolerance() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer: Gets the value of a tuning parameter.
getParameterSize() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresAdapter: Get the number of parameters (columns in the Jacobian) in this problem.
getParameterSize() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem: Get the number of parameters (columns in the Jacobian) in this problem.
getParametersNames() - Method in class org.apache.commons.math4.legacy.ode.AbstractParameterizable: Get the names of the supported parameters.
getParametersNames() - Method in interface org.apache.commons.math4.legacy.ode.Parameterizable: Get the names of the supported parameters.
getPartialCorrelations(int) - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: In the original algorithm only the partial correlations of the regressors is returned to the user.
getPartialDerivative(int...) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Get a partial derivative.
getPartialDerivativeIndex(int...) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Get the index of a partial derivative in the array.
getPartialDerivativeOrders(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Get the derivation orders for a specific index in the array.
getPct(T) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns the percentage of values that are equal to v (as a proportion between 0 and 1).
getPercentile(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns an estimate for the pth percentile of the stored values.
getPercentileImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the currently configured percentile implementation.
getPivot() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldLUDecomposition: Gets the pivot permutation vector.
getPivot() - Method in class org.apache.commons.math4.legacy.linear.FieldLUDecomposition: Returns the pivot permutation vector.
getPivot() - Method in class org.apache.commons.math4.legacy.linear.LUDecomposition: Returns the pivot permutation vector.
getPivotingStrategy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.KthSelector: Get the pivoting strategy.
getPivotingStrategy() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Get the PivotingStrategy used in KthSelector for computation.
getPmf() - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedDistribution: Return the probability mass function as a list of <value, probability> pairs.
getPoint() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the abscissa (independent variables) of this evaluation.
getPoint() - Method in interface org.apache.commons.math4.legacy.ml.clustering.Clusterable: Gets the n-dimensional point.
getPoint() - Method in class org.apache.commons.math4.legacy.ml.clustering.DoublePoint: Gets the n-dimensional point.
getPoint() - Method in class org.apache.commons.math4.legacy.optim.PointValuePair: Gets the point.
getPoint() - Method in class org.apache.commons.math4.legacy.optim.PointVectorValuePair: Gets the point.
getPoint() - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariatePointValuePair: Get the point.
getPoint(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegrator: Gets the integration point at the given index.
getPointRef() - Method in class org.apache.commons.math4.legacy.optim.PointValuePair: Gets a reference to the point.
getPointRef() - Method in class org.apache.commons.math4.legacy.optim.PointVectorValuePair: Gets a reference to the point.
getPoints() - Method in class org.apache.commons.math4.legacy.ml.clustering.Cluster: Get the points contained in the cluster.
getPolynomials() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.HermiteInterpolator: Compute the interpolation polynomials.
getPolynomials() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialSplineFunction: Get a copy of the interpolating polynomials array.
getPopulationLimit() - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Access the maximum population size.
getPopulationLimit() - Method in interface org.apache.commons.math4.legacy.genetics.Population: Access the maximum population size.
getPopulationSize() - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Access the current population size.
getPopulationSize() - Method in interface org.apache.commons.math4.legacy.genetics.Population: Access the current population size.
getPopulationSize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.PopulationSize
getPopulationVariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the population variance of the available values.
getPopulationVariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the population variance of the values that have been added.
getPopulationVariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the population variance of the values that have been added.
getPrefix() - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Get the format prefix.
getPrefix() - Method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Get the format prefix.
getPreviousState() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Get the state at previous grid point time.
getPreviousState() - Method in interface org.apache.commons.math4.legacy.ode.sampling.FieldStepInterpolator: Get the state at previous grid point time.
getPreviousTime() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Get the previous soft grid point time.
getPreviousTime() - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Get the previous grid point time.
getPrimary() - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get the primary set of differential equations.
getPrimaryMapper() - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get an equations mapper for the primary equations set.
getPrimaryState() - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get primary part of the current state.
getPrimaryStateDot() - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get primary part of the current state derivative.
getProblem(Collection<WeightedObservedPoint>) - Method in class org.apache.commons.math4.legacy.fitting.AbstractCurveFitter: Creates a least squares problem corresponding to the appropriate curve.
getProblem(Collection<WeightedObservedPoint>) - Method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter: Creates a least squares problem corresponding to the appropriate curve.
getProcessNoise() - Method in class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Returns the process noise matrix.
getProcessNoise() - Method in interface org.apache.commons.math4.legacy.filter.ProcessModel: Returns the process noise matrix.
getQ() - Method in class org.apache.commons.math4.legacy.linear.QRDecomposition: Returns the matrix Q of the decomposition.
getQT() - Method in class org.apache.commons.math4.legacy.linear.QRDecomposition: Returns the transpose of the matrix Q of the decomposition.
getQuadraticMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the quadratic mean, a.k.a.
getQuadraticMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the quadratic mean, a.k.a.
getQuadraticMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Returns the quadratic mean, a.k.a.
getQuadraticMean() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the quadratic mean, a.k.a.
getQuantile() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Returns the value of the quantile field (determines what percentile is computed when evaluate() is called with no quantile argument).
getR() - Method in class org.apache.commons.math4.legacy.linear.QRDecomposition: Returns the matrix R of the decomposition.
getR() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns Pearson's product moment correlation coefficient, usually denoted r.
getRandomGenerator() - Static method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Returns the (static) random generator.
getRandomGenerator() - Method in class org.apache.commons.math4.legacy.ml.clustering.FuzzyKMeansClusterer: Returns the random generator this instance will use.
getRank() - Method in class org.apache.commons.math4.legacy.linear.RectangularCholeskyDecomposition: Get the rank of the symmetric positive semidefinite matrix.
getRank() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Return the effective numerical matrix rank.
getRank(double) - Method in class org.apache.commons.math4.legacy.linear.RRQRDecomposition: Return the effective numerical matrix rank.
getRankCorrelation() - Method in class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Returns a PearsonsCorrelation instance constructed from the ranked input data.
getRankingThreshold() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer: Gets the value of a tuning parameter.
getRatio() - Method in class org.apache.commons.math4.legacy.genetics.UniformCrossover: Returns the mixing ratio used by this CrossoverPolicy.
getReal() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
getReal() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
getRealEigenvalue(int) - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Returns the real part of the i^th eigenvalue of the original matrix.
getRealEigenvalues() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Gets a copy of the real parts of the eigenvalues of the original matrix.
getRealFormat() - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: Access the realFormat.
getReducedChiSquare(int) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.AbstractEvaluation: Get the reduced chi-square.
getReducedChiSquare(int) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the reduced chi-square.
getRegressionSumSquares() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the sum of squared deviations of the predicted y values about their mean (which equals the mean of y).
getRegressionSumSquares() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the sum of squared deviations of the predicted y values about their mean (which equals the mean of y).
getRelationship() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearConstraint: Gets the relationship between left and right hand sides.
getRelativeAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Get the relative accuracy.
getRelativeAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.integration.UnivariateIntegrator: Get the relative accuracy.
getRelativeAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Get the relative accuracy of the solver.
getRelativeAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BaseUnivariateSolver: Get the relative accuracy of the solver.
getRelativeAccuracy() - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BracketedRealFieldUnivariateSolver: Get the relative accuracy of the solver.
getRelativeAccuracy() - Method in class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Get the relative accuracy.
getRelativeThreshold() - Method in class org.apache.commons.math4.legacy.optim.AbstractConvergenceChecker
getRelativeTolerance() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer
getRelativeTolerance() - Method in class org.apache.commons.math4.legacy.optim.Tolerance
getRepresentation() - Method in class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Returns the (immutable) inner representation of the chromosome.
getResidual() - Method in class org.apache.commons.math4.legacy.linear.DefaultIterativeLinearSolverEvent: Returns the residual.
getResidual() - Method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolverEvent: Returns the residual.
getResiduals() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the weighted residuals.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Returns the value of the statistic based on the values that have been added.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialCovariance: Get the covariance matrix.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialMean: Get the mean vector.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Returns the current value of the Statistic.
getResult() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StorelessUnivariateStatistic: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Returns the current value of the Statistic.
getRightHandSideVector() - Method in class org.apache.commons.math4.legacy.linear.DefaultIterativeLinearSolverEvent: Returns the current right-hand side of the linear system to be solved.
getRightHandSideVector() - Method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolverEvent: Returns the current right-hand side of the linear system to be solved.
getRMS() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.AbstractEvaluation: Get the normalized cost.
getRMS() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get the normalized cost.
getRootMatrix() - Method in class org.apache.commons.math4.legacy.linear.RectangularCholeskyDecomposition: Get the root of the covariance matrix.
getRoundingMode() - Method in class org.apache.commons.math4.legacy.linear.BigReal: Gets the rounding mode for division operations.
getRow() - Method in exception org.apache.commons.math4.legacy.linear.NonPositiveDefiniteMatrixException
getRow() - Method in exception org.apache.commons.math4.legacy.linear.NonSymmetricMatrixException
getRow(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the entries in row number row as an array.
getRow(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get the entries at the given row index.
getRow(int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Get the entries at the given row index.
getRow(int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Get the entries in row number row as an array.
getRow(int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Get the entries at the given row index.
getRow(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Get the entries in row number row as an array.
getRow(int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Get the entries at the given row index.
getRowDimension() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Gets the number of rows.
getRowDimension() - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Gets the number of rows.
getRowDimension() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Gets the number of rows.
getRowDimension() - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns the dimension of the codomain of this operator.
getRowDimension() - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Gets the number of rows.
getRowDimension() - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the dimension of the codomain of this operator.
getRowDimension() - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns the dimension of the codomain of this operator.
getRowDimension() - Method in class org.apache.commons.math4.legacy.linear.JacobiPreconditioner: Returns the dimension of the codomain of this operator.
getRowDimension() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Returns the dimension of the codomain of this operator.
getRowDimension() - Method in class org.apache.commons.math4.legacy.linear.RealLinearOperator: Returns the dimension of the codomain of this operator.
getRowDimension() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Gets the number of rows.
getRowMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the entries in row number row as a row matrix.
getRowMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get the entries at the given row index as a row matrix.
getRowMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Get the entries in row number row as a row matrix.
getRowMatrix(int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Get the entries at the given row index as a row matrix.
getRowMatrix(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Get the entries in row number row as a row matrix.
getRowMatrix(int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Get the entries at the given row index as a row matrix.
getRowPrefix() - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Get the format prefix.
getRowSeparator() - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Get the format separator between rows of the matrix.
getRowSuffix() - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Get the format suffix.
getRowVector(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get the entries in row number row as a vector.
getRowVector(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the entries in row number row as a vector.
getRowVector(int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Get the entries in row number row as a vector.
getRowVector(int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the entries in row number row as a vector.
getRowVector(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Get the entries in row number row as a vector.
getRowVector(int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the entries in row number row as a vector.
getRSquare() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the coefficient of determination, usually denoted r-square.
getRSquared() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the coefficient of multiple determination, usually denoted r-square.
getRule(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.BaseRuleFactory: Gets a copy of the quadrature rule with the given number of integration points.
getRuleInternal(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.BaseRuleFactory: Gets a rule.
getRuntimeClass() - Method in class org.apache.commons.math4.legacy.linear.BigRealField
getS() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Returns the diagonal matrix Σ of the decomposition.
getSafety() - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Get the safety factor for stepsize control.
getSafety() - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Get the safety factor for stepsize control.
getSafety() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Get the safety factor for stepsize control.
getSafety() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Get the safety factor for stepsize control.
getSampleStats() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Returns a StatisticalSummary describing this distribution.
getScale() - Method in class org.apache.commons.math4.legacy.linear.BigReal: Sets the scale for division operations.
getSecond() - Method in class org.apache.commons.math4.legacy.genetics.ChromosomePair: Access the second chromosome.
getSecondaryDerivative(int) - Method in class org.apache.commons.math4.legacy.ode.FieldODEStateAndDerivative: Get derivative of the secondary state at time.
getSecondaryMappers() - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get the equations mappers for the secondary equations sets.
getSecondaryState(int) - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get secondary part of the current state.
getSecondaryState(int) - Method in class org.apache.commons.math4.legacy.ode.FieldODEState: Get secondary state at time.
getSecondaryStateDimension(int) - Method in class org.apache.commons.math4.legacy.ode.FieldODEState: Get secondary state dimension.
getSecondaryStateDot(int) - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get secondary part of the current state derivative.
getSecondMoment() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns a statistic related to the Second Central Moment.
getSecondMoment() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns a statistic related to the Second Central Moment.
getSelectionPolicy() - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Returns the selection policy.
getSeparator() - Method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Get the format separator between components.
getSigma() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.Sigma
getSigma(double) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.AbstractEvaluation: Get an estimate of the standard deviation of the parameters.
getSigma(double) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem.Evaluation: Get an estimate of the standard deviation of the parameters.
getSignificance() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the significance level of the slope (equiv) correlation.
getSingularValues() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Returns the diagonal elements of the matrix Σ of the decomposition.
getSize() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Get the array size required for holding partial derivatives data.
getSize() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Get the size of the sphere.
getSize() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Returns the number of vertices.
getSkewness() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the skewness of the available values.
getSkewnessImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the currently configured skewness implementation.
getSlope() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the slope of the estimated regression line.
getSlopeConfidenceInterval() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the half-width of a 95% confidence interval for the slope estimate.
getSlopeConfidenceInterval(double) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the half-width of a (100-100*alpha)% confidence interval for the slope estimate.
getSlopeStdErr() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the standard error of the slope estimate, usually denoted s(b1).
getSolution() - Method in class org.apache.commons.math4.legacy.linear.DefaultIterativeLinearSolverEvent: Returns the current estimate of the solution to the linear system to be solved.
getSolution() - Method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolverEvent: Returns the current estimate of the solution to the linear system to be solved.
getSolution() - Method in class org.apache.commons.math4.legacy.optim.linear.SolutionCallback: Retrieve the best solution found so far.
getSolver() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldLUDecomposition: Creates a solver for finding the solution X of the linear system of equations A X = B.
getSolver() - Method in class org.apache.commons.math4.legacy.linear.CholeskyDecomposition: Get a solver for finding the A × X = B solution in least square sense.
getSolver() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Gets a solver for finding the A × X = B solution in exact linear sense.
getSolver() - Method in class org.apache.commons.math4.legacy.linear.FieldLUDecomposition: Get a solver for finding the A × X = B solution in exact linear sense.
getSolver() - Method in class org.apache.commons.math4.legacy.linear.LUDecomposition: Get a solver for finding the A × X = B solution in exact linear sense.
getSolver() - Method in class org.apache.commons.math4.legacy.linear.QRDecomposition: Get a solver for finding the A × X = B solution in least square sense.
getSolver() - Method in class org.apache.commons.math4.legacy.linear.RRQRDecomposition: Get a solver for finding the A × X = B solution in least square sense.
getSolver() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Get a solver for finding the A × X = B solution in least square sense.
getSolverAbsoluteAccuracy() - Method in class org.apache.commons.math4.legacy.distribution.AbstractRealDistribution: Returns the solver absolute accuracy for inverse cumulative computation.
getSortedValues() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the current set of values in an array of double primitives, sorted in ascending order.
getSparsity() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector
getSquareRoot() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Computes the square-root of the matrix.
getStandardDeviation() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns the standard deviation of the available values.
getStandardDeviation() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the standard deviation of the available values.
getStandardDeviation() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns an array whose i^th entry is the standard deviation of the.
getStandardDeviation() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns an array whose i^th entry is the.
getStandardDeviation() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummary: Returns the standard deviation of the available values.
getStandardDeviation() - Method in class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues
getStandardDeviation() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the standard deviation of the values that have been added.
getStandardDeviation() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Returns the standard deviation of the available values.
getStandardDeviation() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns an array whose i^th entry is the standard deviation of the.
getStandardDeviation() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the standard deviation of the values that have been added.
getStandardDeviations() - Method in class org.apache.commons.math4.legacy.distribution.MultivariateNormalDistribution: Gets the square root of each element on the diagonal of the covariance matrix.
getStart() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresAdapter: Gets the initial guess.
getStart() - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresProblem: Gets the initial guess.
getStarterIntegrator() - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Get the starter integrator.
getStarterIntegrator() - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Get the starter integrator.
getStartPoint() - Method in class org.apache.commons.math4.legacy.optim.BaseMultivariateOptimizer: Gets the initial guess.
getStartProbability() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing
getStartValue() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver
getStartValue() - Method in class org.apache.commons.math4.legacy.optim.univariate.SearchInterval: Gets the start value.
getStartValue() - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer
getState() - Method in class org.apache.commons.math4.legacy.ode.FieldODEState: Get main state at time.
getStateDimension() - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Returns the dimension of the state estimation vector.
getStateDimension() - Method in class org.apache.commons.math4.legacy.ode.FieldODEState: Get main state dimension.
getStateEstimation() - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Returns the current state estimation vector.
getStateEstimationVector() - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Returns a copy of the current state estimation vector.
getStateTransitionMatrix() - Method in class org.apache.commons.math4.legacy.filter.DefaultProcessModel: Returns the state transition matrix.
getStateTransitionMatrix() - Method in interface org.apache.commons.math4.legacy.filter.ProcessModel: Returns the state transition matrix.
getStatisticsDHistory() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.CMAESOptimizer
getStatisticsFitnessHistory() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.CMAESOptimizer
getStatisticsMeanHistory() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.CMAESOptimizer
getStatisticsSigmaHistory() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.CMAESOptimizer
getStdErrorOfEstimate(int) - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the standard error of the parameter estimate at index, usually denoted s(b_index).
getStdErrorOfEstimates() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the standard error of the parameter estimates, usually denoted s(b_i).
getStepHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get all the step handlers that have been added to the integrator.
getStepHandlers() - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Get all the step handlers that have been added to the integrator.
getStepHandlers() - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Get all the step handlers that have been added to the integrator.
getStepHandlers() - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Get all the step handlers that have been added to the integrator.
getStepSize() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.FiniteDifferencesDifferentiator: Get the step size.
getStepSize() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Get the current step size.
getStepStart() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Getcurrent step start.
getSubMatrix(int[], int[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get a submatrix.
getSubMatrix(int[], int[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Gets a submatrix.
getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Get a submatrix.
getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Get a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Get a submatrix.
getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Gets a submatrix.
getSubVector(int, int) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Get a subvector from consecutive elements.
getSubVector(int, int) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Get a subvector from consecutive elements.
getSubVector(int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Get a subvector from consecutive elements.
getSubVector(int, int) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Get a subvector from consecutive elements.
getSubVector(int, int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Get a subvector from consecutive elements.
getSubVector(int, int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Get a subvector from consecutive elements.
getSuffix() - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Get the format suffix.
getSuffix() - Method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Get the format suffix.
getSum() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns the sum of the values that have been added to Univariate.
getSum() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the sum of the values that have been added to Univariate.
getSum() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns an array whose i^th entry is the sum of the.
getSum() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns an array whose i^th entry is the.
getSum() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummary: Returns the sum of the values that have been added to Univariate.
getSum() - Method in class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues
getSum() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the sum of the values that have been added.
getSum() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns an array whose i^th entry is the sum of the.
getSum() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the sum of the values that have been added.
getSumFreq() - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns the sum of all frequencies.
getSumImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the currently configured sum implementation.
getSumImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the currently configured Sum implementation.
getSumImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the currently configured Sum implementation.
getSumImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the currently configured Sum implementation.
getSumImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the currently configured Sum implementation.
getSumLog() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns an array whose i^th entry is the sum of logs of the.
getSumLog() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns an array whose i^th entry is the.
getSumLog() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns an array whose i^th entry is the sum of logs of the.
getSumLogImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Returns the currently configured sum of logs implementation.
getSumLogImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the currently configured sum of logs implementation.
getSumLogImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the currently configured sum of logs implementation.
getSumLogImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the currently configured sum of logs implementation.
getSumLogImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the currently configured sum of logs implementation.
getSummary() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Return a StatisticalSummaryValues instance reporting current aggregate statistics.
getSummary() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Return a StatisticalSummaryValues instance reporting current statistics.
getSummary() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Return a StatisticalSummaryValues instance reporting current statistics.
getSumOfCrossProducts() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the sum of crossproducts, x_i*y_i.
getSumOfLogs() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns the sum of the logs of all the aggregated data.
getSumOfLogs() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the sum of the logs of the values that have been added.
getSumsq() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns the sum of the squares of all the aggregated data.
getSumsq() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the sum of the squares of the available values.
getSumsq() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the sum of the squares of the values that have been added.
getSumsq() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the sum of the squares of the values that have been added.
getSumSq() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns an array whose i^th entry is the sum of squares of the.
getSumSq() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalMultivariateSummary: Returns an array whose i^th entry is the.
getSumSq() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns an array whose i^th entry is the sum of squares of the.
getSumsqImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the currently configured sum of squares implementation.
getSumsqImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns the currently configured sum of squares implementation.
getSumsqImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the currently configured sum of squares implementation.
getSumsqImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns the currently configured sum of squares implementation.
getSumsqImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the currently configured sum of squares implementation.
getSumSquaredErrors() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the sum of squared errors (SSE) associated with the regression model.
getSupportLowerBound() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution
getSupportLowerBound() - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution: Returns the lowest value with non-zero probability.
getSupportLowerBound() - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution: Returns the lowest value with non-zero probability.
getSupportUpperBound() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution
getSupportUpperBound() - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution: Returns the highest value with non-zero probability.
getSupportUpperBound() - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution: Returns the highest value with non-zero probability.
getThreshold() - Method in exception org.apache.commons.math4.legacy.linear.NonPositiveDefiniteMatrixException
getThreshold() - Method in exception org.apache.commons.math4.legacy.linear.NonSymmetricMatrixException
getTiesStrategy() - Method in class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: Return the TiesStrategy.
getTime() - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Get current time.
getTime() - Method in class org.apache.commons.math4.legacy.ode.FieldODEState: Get time.
getTotalDimension() - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Return the dimension of the complete set of equations.
getTotalDimension() - Method in class org.apache.commons.math4.legacy.ode.FieldEquationsMapper: Return the dimension of the complete set of equations.
getTotalSumSquares() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns the sum of squared deviations of the y values about their mean.
getTotalSumSquares() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the sum of squared deviations of the y values about their mean.
getTrace() - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTriggeredIncreasing() - Method in enum org.apache.commons.math4.legacy.ode.events.FilterType: Get the increasing status of triggered events.
getU() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldLUDecomposition: Builds the "U" matrix of the decomposition.
getU() - Method in class org.apache.commons.math4.legacy.linear.FieldLUDecomposition: Returns the matrix U of the decomposition.
getU() - Method in class org.apache.commons.math4.legacy.linear.LUDecomposition: Returns the matrix U of the decomposition.
getU() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Returns the matrix U of the decomposition.
getUniqueCount() - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns the number of values in the frequency table.
getUpper() - Method in class org.apache.commons.math4.legacy.optim.SimpleBounds: Gets the upper bounds.
getUpperBound() - Method in class org.apache.commons.math4.legacy.optim.BaseMultivariateOptimizer
getUpperBound() - Method in class org.apache.commons.math4.legacy.stat.interval.ConfidenceInterval
getUpperBounds() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: Returns the upper bounds of the bins.
getUT() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Returns the transpose of the matrix U of the decomposition.
getV() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Gets the matrix V of the decomposition.
getV() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Returns the matrix V of the decomposition.
getVals() - Method in class org.apache.commons.math4.legacy.special.BesselJ.BesselJResult
getValue() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Get the value part of the derivative structure.
getValue() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Get the value of the function.
getValue() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector.OpenMapEntry: Get the value of the entry.
getValue() - Method in class org.apache.commons.math4.legacy.linear.RealVector.Entry: Get the value of the entry.
getValue() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearConstraint: Gets the value of the constraint (right hand side).
getValue() - Method in class org.apache.commons.math4.legacy.optim.PointVectorValuePair: Gets the value of the objective function.
getValue() - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariatePointValuePair: Get the value of the objective function.
getValueRef() - Method in class org.apache.commons.math4.legacy.optim.PointVectorValuePair: Gets a reference to the value of the objective function.
getValues() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the current set of values in an array of double primitives.
getValues() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Returns the current set of values in an array of double primitives.
getVariance() - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution
getVariance() - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution
getVariance() - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution
getVariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AggregateSummaryStatistics: Returns the variance of the available values.
getVariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the (sample) variance of the available values.
getVariance() - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummary: Returns the variance of the available values.
getVariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues
getVariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the (sample) variance of the available values.
getVariance() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the (sample) variance of the available values.
getVarianceDirection() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Returns the varianceDirection property.
getVarianceImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the currently configured variance implementation.
getVarianceImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns the currently configured variance implementation.
getVarianceImpl() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns the currently configured variance implementation.
getVT() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Gets the transpose of the matrix V of the decomposition.
getVT() - Method in class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Returns the transpose of the matrix V of the decomposition.
getWeight() - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoint: Gets the weight of the measurement in the fitting process.
getWeight(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegrator: Gets the weight of the integration point at the given index.
getWilsonScoreInterval(int, int, double) - Static method in class org.apache.commons.math4.legacy.stat.interval.IntervalUtils: Create a Wilson score binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
getWindowSize() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Returns the maximum number of values that can be stored in the dataset, or INFINITE_WINDOW (-1) if there is no limit.
getWindowSize() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Returns the maximum number of values that can be stored in the dataset, or INFINITE_WINDOW (-1) if there is no limit.
getWorkArray(double[], double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Get the work arrays of weights to operate.
getWrongColumnDimension() - Method in exception org.apache.commons.math4.legacy.linear.MatrixDimensionMismatchException
getWrongRowDimension() - Method in exception org.apache.commons.math4.legacy.linear.MatrixDimensionMismatchException
getX() - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoint: Gets the abscissa of the point.
getX() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression
getXSumSquares() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the sum of squared deviations of the x values about their mean.
getY() - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoint: Gets the observed value of the function at x.
getY() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression
getZero() - Method in class org.apache.commons.math4.legacy.linear.BigRealField
GillFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the Gill fourth order Runge-Kutta integrator for Ordinary Differential Equations .
GillFieldIntegrator(Field<T>, T) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.GillFieldIntegrator: Simple constructor.
GillIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the Gill fourth order Runge-Kutta integrator for Ordinary Differential Equations .
GillIntegrator(double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.GillIntegrator: Simple constructor.
GLSMultipleLinearRegression - Class in org.apache.commons.math4.legacy.stat.regression: The GLS implementation of multiple linear regression.
GLSMultipleLinearRegression() - Constructor for class org.apache.commons.math4.legacy.stat.regression.GLSMultipleLinearRegression
GoalType - Enum in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Goal type for an optimization problem (minimization or maximization of a scalar function.
gradient(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.function.Gaussian.Parametric: Computes the value of the gradient at x.
gradient(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.function.HarmonicOscillator.Parametric: Computes the value of the gradient at x.
gradient(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.function.Logistic.Parametric: Computes the value of the gradient at x.
gradient(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.function.Logit.Parametric: Computes the value of the gradient at x.
gradient(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.function.Sigmoid.Parametric: Computes the value of the gradient at x.
gradient(double, double...) - Method in interface org.apache.commons.math4.legacy.analysis.ParametricUnivariateFunction: Compute the gradient of the function with respect to its parameters.
gradient(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction.Parametric: Compute the gradient of the function with respect to its parameters.
GradientFunction - Class in org.apache.commons.math4.legacy.analysis.differentiation: Class representing the gradient of a multivariate function.
GradientFunction(MultivariateDifferentiableFunction) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.GradientFunction: Simple constructor.
GradientMultivariateOptimizer - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Base class for implementing optimizers for multivariate scalar differentiable functions.
GradientMultivariateOptimizer(ConvergenceChecker<PointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.GradientMultivariateOptimizer
GraggBulirschStoerIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements a Gragg-Bulirsch-Stoer integrator for Ordinary Differential Equations.
GraggBulirschStoerIntegrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Simple constructor.
GraggBulirschStoerIntegrator(double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Simple constructor.
GREATER_THAN - org.apache.commons.math4.legacy.stat.inference.AlternativeHypothesis: Represents a right-sided test.
gTest(double[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.GTest: Returns the observed significance level, or p-value, associated with a G-Test for goodness of fit comparing the observed frequency counts to those in the expected array.
gTest(double[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
gTest(double[], long[], double) - Method in class org.apache.commons.math4.legacy.stat.inference.GTest: Performs a G-Test (Log-Likelihood Ratio Test) for goodness of fit evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha.
gTest(double[], long[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
GTest - Class in org.apache.commons.math4.legacy.stat.inference: Implements G Test statistics.
GTest() - Constructor for class org.apache.commons.math4.legacy.stat.inference.GTest
gTestDataSetsComparison(long[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.GTest: Returns the observed significance level, or p-value, associated with a G-Value (Log-Likelihood Ratio) for two sample test comparing bin frequency counts in observed1 and observed2.
gTestDataSetsComparison(long[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
gTestDataSetsComparison(long[], long[], double) - Method in class org.apache.commons.math4.legacy.stat.inference.GTest: Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned data sets.
gTestDataSetsComparison(long[], long[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
gTestIntrinsic(double[], long[]) - Method in class org.apache.commons.math4.legacy.stat.inference.GTest: Returns the intrinsic (Hardy-Weinberg proportions) p-Value, as described in p64-69 of McDonald, J.H.
gTestIntrinsic(double[], long[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
guess(Collection<WeightedObservedPoint>) - Method in class org.apache.commons.math4.legacy.fitting.GaussianCurveFitter.ParameterGuesser: Computes an estimation of the parameters.
guess(Collection<WeightedObservedPoint>) - Method in class org.apache.commons.math4.legacy.fitting.HarmonicCurveFitter.ParameterGuesser: Computes an estimation of the parameters.
guess(Collection<WeightedObservedPoint>) - Method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter.ParameterGuesser: Computes an estimation of the parameters.

H

h - Variable in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: current time step.
HaltonSequenceGenerator - Class in org.apache.commons.math4.legacy.random: Implementation of a Halton sequence.
HaltonSequenceGenerator(int) - Constructor for class org.apache.commons.math4.legacy.random.HaltonSequenceGenerator: Construct a new Halton sequence generator for the given space dimension.
HaltonSequenceGenerator(int, int[], int[]) - Constructor for class org.apache.commons.math4.legacy.random.HaltonSequenceGenerator: Construct a new Halton sequence generator with the given base numbers and weights for each dimension.
handleStep(double, double[], double[], boolean) - Method in interface org.apache.commons.math4.legacy.ode.sampling.FixedStepHandler: Handle the last accepted step.
handleStep(FieldODEStateAndDerivative<T>, boolean) - Method in interface org.apache.commons.math4.legacy.ode.sampling.FieldFixedStepHandler: Handle the last accepted step.
handleStep(FieldStepInterpolator<T>, boolean) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputFieldModel: Handle the last accepted step.
handleStep(FieldStepInterpolator<T>, boolean) - Method in interface org.apache.commons.math4.legacy.ode.sampling.FieldStepHandler: Handle the last accepted step.
handleStep(FieldStepInterpolator<T>, boolean) - Method in class org.apache.commons.math4.legacy.ode.sampling.FieldStepNormalizer: Handle the last accepted step.
handleStep(StepInterpolator, boolean) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Handle the last accepted step.
handleStep(StepInterpolator, boolean) - Method in class org.apache.commons.math4.legacy.ode.sampling.DummyStepHandler: Handle the last accepted step.
handleStep(StepInterpolator, boolean) - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepHandler: Handle the last accepted step.
handleStep(StepInterpolator, boolean) - Method in class org.apache.commons.math4.legacy.ode.sampling.StepNormalizer: Handle the last accepted step.
HarmonicCurveFitter - Class in org.apache.commons.math4.legacy.fitting: Fits points to a harmonic oscillator function.
HarmonicCurveFitter.ParameterGuesser - Class in org.apache.commons.math4.legacy.fitting: This class guesses harmonic coefficients from a sample.
HarmonicOscillator - Class in org.apache.commons.math4.legacy.analysis.function: simple harmonic oscillator function.
HarmonicOscillator(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.HarmonicOscillator: Harmonic oscillator function.
HarmonicOscillator.Parametric - Class in org.apache.commons.math4.legacy.analysis.function: Parametric function where the input array contains the parameters of the harmonic oscillator function.
hasComplexEigenvalues() - Method in class org.apache.commons.math4.legacy.linear.EigenDecomposition: Returns whether the calculated eigen values are complex or real.
hashCode() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Get a hashCode for the derivative structure.
hashCode() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Get a hashCode for the derivative structure.
hashCode() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction
hashCode() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix
hashCode() - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Computes a hash code for the matrix.
hashCode() - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Computes a hash code for the matrix.
hashCode() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Get a hashCode for the real vector.
hashCode() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: .
hashCode() - Method in class org.apache.commons.math4.legacy.linear.BigReal
hashCode() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: .
hashCode() - Method in class org.apache.commons.math4.legacy.linear.RealVector: .
hashCode() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector
hashCode() - Method in class org.apache.commons.math4.legacy.ml.clustering.DoublePoint
hashCode() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearConstraint
hashCode() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction
hashCode() - Method in class org.apache.commons.math4.legacy.optim.PointValuePair
hashCode() - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: Returns hash code based on getResult() and getN().
hashCode() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialCovariance
hashCode() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialMean
hashCode() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Returns hash code based on values of statistics.
hashCode() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Returns hash code based on getResult() and getN().
hashCode() - Method in class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues: Returns hash code based on values of statistics.
hashCode() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Returns hash code based on values of statistics.
hashCode() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Returns hash code based on values of statistics.
hashCode() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Returns hash code based on values of statistics.
hashCode() - Method in class org.apache.commons.math4.legacy.stat.Frequency
hasIntercept() - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: A getter method which determines whether a constant is included.
hasIntercept() - Method in class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Returns true if the regression model has been computed including an intercept.
hasIntercept() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns true if the model includes an intercept term.
hasIntercept() - Method in interface org.apache.commons.math4.legacy.stat.regression.UpdatingMultipleLinearRegression: Returns true if a constant has been included false otherwise.
hasNext() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector.OpenMapSparseIterator
hasNext() - Method in class org.apache.commons.math4.legacy.linear.RealVector.SparseEntryIterator
HedarFukushimaTransform - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: DSSA algorithm.
HedarFukushimaTransform() - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.HedarFukushimaTransform: Disable shrinking of the simplex (as mandated by DSSA).
HedarFukushimaTransform(double) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.HedarFukushimaTransform
HedarFukushimaTransform(double, UniformRandomProvider) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.HedarFukushimaTransform
hermite(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegratorFactory: Creates a Gauss-Hermite integrator of the given order.
HermiteInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Polynomial interpolator using both sample values and sample derivatives.
HermiteInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.HermiteInterpolator: Create an empty interpolator.
HermiteRuleFactory - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: Factory that creates a Gauss-type quadrature rule using Hermite polynomials of the first kind.
HermiteRuleFactory() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.HermiteRuleFactory
HighamHall54FieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 5(4) Higham and Hall integrator for Ordinary Differential Equations.
HighamHall54FieldIntegrator(Field<T>, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Simple constructor.
HighamHall54FieldIntegrator(Field<T>, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54FieldIntegrator: Simple constructor.
HighamHall54Integrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 5(4) Higham and Hall integrator for Ordinary Differential Equations.
HighamHall54Integrator(double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54Integrator: Simple constructor.
HighamHall54Integrator(double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.HighamHall54Integrator: Simple constructor.
homoscedasticT(double[], double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
homoscedasticT(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances.
homoscedasticT(double, double, double, double, double, double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes t test statistic for 2-sample t-test under the hypothesis of equal subpopulation variances.
homoscedasticT(StatisticalSummary, StatisticalSummary) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
homoscedasticT(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes a 2-sample t statistic, comparing the means of the datasets described by two StatisticalSummary instances, under the assumption of equal subpopulation variances.
homoscedasticTTest(double[], double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
homoscedasticTTest(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances.
homoscedasticTTest(double[], double[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
homoscedasticTTest(double[], double[], double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Performs a two-sided t-test evaluating the null hypothesis that sample1 and sample2 are drawn from populations with the same mean, with significance level alpha, assuming that the subpopulation variances are equal.
homoscedasticTTest(double, double, double, double, double, double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes p-value for 2-sided, 2-sample t-test, under the assumption of equal subpopulation variances.
homoscedasticTTest(StatisticalSummary, StatisticalSummary) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
homoscedasticTTest(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.
hypot(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
hypot(DerivativeStructure, DerivativeStructure) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Returns the hypotenuse of a triangle with sides x and y - sqrt(x² +y²) avoiding intermediate overflow or underflow.
hypot(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
hypot(SparseGradient, SparseGradient) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Returns the hypotenuse of a triangle with sides x and y - sqrt(x² +y²) avoiding intermediate overflow or underflow.

I

identity(Field<T>, int) - Static method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Factory method.
Identity - Class in org.apache.commons.math4.legacy.analysis.function: Identity function.
Identity() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Identity
identityPermutation(int) - Static method in class org.apache.commons.math4.legacy.genetics.RandomKey: Generates a representation corresponding to an identity permutation of length l which can be passed to the RandomKey constructor.
IdentityPreconditioner() - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer.IdentityPreconditioner
IllConditionedOperatorException - Exception in org.apache.commons.math4.legacy.linear: An exception to be thrown when the condition number of a RealLinearOperator is too high.
IllConditionedOperatorException(double) - Constructor for exception org.apache.commons.math4.legacy.linear.IllConditionedOperatorException: Creates a new instance of this class.
ILLINOIS - org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver.Method: The Illinois method.
IllinoisSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Implements the Illinois method for root-finding (approximating a zero of a univariate real function).
IllinoisSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.IllinoisSolver: Construct a solver with default accuracy (1e-6).
IllinoisSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.IllinoisSolver: Construct a solver.
IllinoisSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.IllinoisSolver: Construct a solver.
IllinoisSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.IllinoisSolver: Construct a solver.
incMoment - Variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Determines whether or not this statistic can be incremented or cleared.
incMoment - Variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Determines whether or not this statistic can be incremented or cleared.
incMoment - Variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Determines whether or not this statistic can be incremented or cleared.
incMoment - Variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Whether or not Variance.increment(double) should increment the internal second moment.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StorelessUnivariateStatistic: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Updates the internal state of the statistic to reflect the addition of the new value.
increment(double[]) - Method in class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Increment the covariance matrix with one row of data.
increment(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialCovariance: Add a new vector to the sample.
increment(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialMean: Add a new vector to the sample.
INCREMENT - org.apache.commons.math4.legacy.ode.sampling.StepNormalizerMode: Steps are fixed increments of the start value.
incrementAll(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: This default implementation just calls AbstractStorelessUnivariateStatistic.increment(double) in a loop over the input array.
incrementAll(double[]) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StorelessUnivariateStatistic: Updates the internal state of the statistic to reflect addition of all values in the values array.
incrementAll(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractStorelessUnivariateStatistic: This default implementation just calls AbstractStorelessUnivariateStatistic.increment(double) in a loop over the specified portion of the input array.
incrementAll(double[], int, int) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.StorelessUnivariateStatistic: Updates the internal state of the statistic to reflect addition of the values in the designated portion of the values array.
incrementEvaluationCount() - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Increment the evaluation count by one.
incrementEvaluationCount() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Increment the evaluation count.
incrementIterationCount() - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Increments the iteration count by one, and throws an exception if the maximum number of iterations is reached.
incrementIterationCount() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Increment the iteration count.
incrementValue(T, long) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Increments the frequency count for v.
index(double, int) - Method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Finds the index of array that can be used as starting index to estimate percentile.
inducedPermutation(List<S>, List<S>) - Static method in class org.apache.commons.math4.legacy.genetics.RandomKey: Generates a representation of a permutation corresponding to a permutation which yields permutedData when applied to originalData.
InferenceTestUtils - Class in org.apache.commons.math4.legacy.stat.inference: A collection of static methods to create inference test instances or to perform inference tests.
INFINITE_WINDOW - Static variable in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Represents an infinite window size.
init(double, double[], double) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Initialize step handler at the start of an ODE integration.
init(double, double[], double) - Method in class org.apache.commons.math4.legacy.ode.events.EventFilter: Initialize event handler at the start of an ODE integration.
init(double, double[], double) - Method in interface org.apache.commons.math4.legacy.ode.events.EventHandler: Initialize event handler at the start of an ODE integration.
init(double, double[], double) - Method in class org.apache.commons.math4.legacy.ode.sampling.DummyStepHandler: Initialize step handler at the start of an ODE integration.
init(double, double[], double) - Method in interface org.apache.commons.math4.legacy.ode.sampling.FixedStepHandler: Initialize step handler at the start of an ODE integration.
init(double, double[], double) - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepHandler: Initialize step handler at the start of an ODE integration.
init(double, double[], double) - Method in class org.apache.commons.math4.legacy.ode.sampling.StepNormalizer: Initialize step handler at the start of an ODE integration.
init(FieldODEStateAndDerivative<T>, T) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputFieldModel: Initialize step handler at the start of an ODE integration.
init(FieldODEStateAndDerivative<T>, T) - Method in interface org.apache.commons.math4.legacy.ode.events.FieldEventHandler: Initialize event handler at the start of an ODE integration.
init(FieldODEStateAndDerivative<T>, T) - Method in interface org.apache.commons.math4.legacy.ode.sampling.FieldFixedStepHandler: Initialize step handler at the start of an ODE integration.
init(FieldODEStateAndDerivative<T>, T) - Method in interface org.apache.commons.math4.legacy.ode.sampling.FieldStepHandler: Initialize step handler at the start of an ODE integration.
init(FieldODEStateAndDerivative<T>, T) - Method in class org.apache.commons.math4.legacy.ode.sampling.FieldStepNormalizer: Initialize step handler at the start of an ODE integration.
init(T, T[], T) - Method in class org.apache.commons.math4.legacy.ode.FieldExpandableODE: Initialize equations at the start of an ODE integration.
init(T, T[], T) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldDifferentialEquations: Initialize equations at the start of an ODE integration.
init(T, T[], T[], T) - Method in interface org.apache.commons.math4.legacy.ode.FieldSecondaryEquations: Initialize equations at the start of an ODE integration.
InitialGuess - Class in org.apache.commons.math4.legacy.optim: Starting point (first guess) of the optimization procedure.
InitialGuess(double[]) - Constructor for class org.apache.commons.math4.legacy.optim.InitialGuess
initializationPerformed(IterationEvent) - Method in interface org.apache.commons.math4.legacy.linear.IterationListener: Invoked after completion of the initial phase of the iterative algorithm (prior to the main iteration loop).
initializeHighOrderDerivatives(double, double[], double[][], double[][]) - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Initialize the high order scaled derivatives at step start.
initializeHighOrderDerivatives(double, double[], double[][], double[][]) - Method in interface org.apache.commons.math4.legacy.ode.MultistepIntegrator.NordsieckTransformer: Deprecated.

Initialize the high order scaled derivatives at step start.
initializeHighOrderDerivatives(double, double[], double[][], double[][]) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsIntegrator: Initialize the high order scaled derivatives at step start.
initializeHighOrderDerivatives(double, double[], double[][], double[][]) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsNordsieckTransformer: Initialize the high order scaled derivatives at step start.
initializeHighOrderDerivatives(T, T[], T[][], T[][]) - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Initialize the high order scaled derivatives at step start.
initializeHighOrderDerivatives(T, T[], T[][], T[][]) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsFieldIntegrator: Initialize the high order scaled derivatives at step start.
initializeHighOrderDerivatives(T, T[], T[][], T[][]) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsNordsieckFieldTransformer: Initialize the high order scaled derivatives at step start.
initializeStep(boolean, int, double[], double, double[], double[], double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Initialize the integration step.
initializeStep(boolean, int, T[], FieldODEStateAndDerivative<T>, FieldEquationsMapper<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Initialize the integration step.
initIntegration(double, double[], double) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Prepare the start of an integration.
initIntegration(FieldExpandableODE<T>, T, T[], T) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Prepare the start of an integration.
innerDistribution - Variable in class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution: EnumeratedDistribution instance (using the Integer wrapper) used to generate the pmf.
innerDistribution - Variable in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution: EnumeratedDistribution (using the Double wrapper) used to generate the pmf.
insertEquationData(double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.EquationsMapper: Insert equation data into a complete state or derivative array.
insertEquationData(int, T[], T[]) - Method in class org.apache.commons.math4.legacy.ode.FieldEquationsMapper: Insert equation data into a complete state or derivative array.
integrate(int, UnivariateFunction, double, double) - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Integrate the function in the given interval.
integrate(int, UnivariateFunction, double, double) - Method in interface org.apache.commons.math4.legacy.analysis.integration.UnivariateIntegrator: Integrate the function in the given interval.
integrate(UnivariateFunction) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegrator: Returns an estimate of the integral of f(x) * w(x), where w is a weight function that depends on the actual flavor of the Gauss integration scheme.
integrate(UnivariateFunction) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.SymmetricGaussIntegrator: Returns an estimate of the integral of f(x) * w(x), where w is a weight function that depends on the actual flavor of the Gauss integration scheme.
integrate(ExpandableStatefulODE, double) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Integrate a set of differential equations up to the given time.
integrate(ExpandableStatefulODE, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsBashforthIntegrator: Integrate a set of differential equations up to the given time.
integrate(ExpandableStatefulODE, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsIntegrator: Integrate a set of differential equations up to the given time.
integrate(ExpandableStatefulODE, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsMoultonIntegrator: Integrate a set of differential equations up to the given time.
integrate(ExpandableStatefulODE, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Integrate a set of differential equations up to the given time.
integrate(ExpandableStatefulODE, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Integrate a set of differential equations up to the given time.
integrate(ExpandableStatefulODE, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Integrate a set of differential equations up to the given time.
integrate(ExpandableStatefulODE, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.RungeKuttaIntegrator: Integrate a set of differential equations up to the given time.
integrate(FieldExpandableODE<T>, FieldODEState<T>, T) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Integrate the differential equations up to the given time.
integrate(FieldExpandableODE<T>, FieldODEState<T>, T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsBashforthFieldIntegrator: Integrate the differential equations up to the given time.
integrate(FieldExpandableODE<T>, FieldODEState<T>, T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsFieldIntegrator: Integrate the differential equations up to the given time.
integrate(FieldExpandableODE<T>, FieldODEState<T>, T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsMoultonFieldIntegrator: Integrate the differential equations up to the given time.
integrate(FieldExpandableODE<T>, FieldODEState<T>, T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Integrate the differential equations up to the given time.
integrate(FieldExpandableODE<T>, FieldODEState<T>, T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.RungeKuttaFieldIntegrator: Integrate the differential equations up to the given time.
integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Integrate the differential equations up to the given time.
integrate(FirstOrderDifferentialEquations, double, double[], double, double[]) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderIntegrator: Integrate the differential equations up to the given time.
integrate(SecondOrderDifferentialEquations, double, double[], double[], double, double[], double[]) - Method in interface org.apache.commons.math4.legacy.ode.SecondOrderIntegrator: Integrate the differential equations up to the given time.
interpolate(double[][], double[]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.MicrosphereProjectionInterpolator: Computes an interpolating function for the data set.
interpolate(double[][], double[]) - Method in interface org.apache.commons.math4.legacy.analysis.interpolation.MultivariateInterpolator: Computes an interpolating function for the data set.
interpolate(double[], double[]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.AkimaSplineInterpolator: Computes an interpolating function for the data set.
interpolate(double[], double[]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.DividedDifferenceInterpolator: Compute an interpolating function for the dataset.
interpolate(double[], double[]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.LinearInterpolator: Computes a linear interpolating function for the data set.
interpolate(double[], double[]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Compute an interpolating function by performing a loess fit on the data at the original abscissae and then building a cubic spline with a SplineInterpolator on the resulting fit.
interpolate(double[], double[]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.NevilleInterpolator: Computes an interpolating function for the data set.
interpolate(double[], double[]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.SplineInterpolator: Computes an interpolating function for the data set.
interpolate(double[], double[]) - Method in interface org.apache.commons.math4.legacy.analysis.interpolation.UnivariateInterpolator: Computes an interpolating function for the dataset.
interpolate(double[], double[]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.UnivariatePeriodicInterpolator: Computes an interpolating function for the dataset.
interpolate(double[], double[], double[][]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolator: Compute an interpolating function for the dataset.
interpolate(double[], double[], double[][]) - Method in interface org.apache.commons.math4.legacy.analysis.interpolation.BivariateGridInterpolator: Compute an interpolating function for the dataset.
interpolate(double[], double[], double[][]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.PiecewiseBicubicSplineInterpolator: Compute an interpolating function for the dataset.
interpolate(double[], double[], double[], double[][][]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.TricubicInterpolator: Compute an interpolating function for the dataset.
interpolate(double[], double[], double[], double[][][]) - Method in interface org.apache.commons.math4.legacy.analysis.interpolation.TrivariateGridInterpolator: Compute an interpolating function for the dataset.
interpolate(double[], double[], double, double) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.ClampedSplineInterpolator: Computes an interpolating function for the data set.
interpolatedDerivatives - Variable in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: interpolated derivatives.
interpolatedPrimaryDerivatives - Variable in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: interpolated primary derivatives.
interpolatedPrimaryState - Variable in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: interpolated primary state.
interpolatedSecondaryDerivatives - Variable in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: interpolated secondary derivatives.
interpolatedSecondaryState - Variable in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: interpolated secondary state.
interpolatedState - Variable in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: interpolated state.
interpolatedTime - Variable in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: interpolated time.
interpolateXAtY(WeightedObservedPoint[], int, int, double) - Method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter.ParameterGuesser: Interpolates using the specified points to determine X at the specified Y.
InterpolatingMicrosphere - Class in org.apache.commons.math4.legacy.analysis.interpolation: Utility class for the MicrosphereProjectionInterpolator algorithm.
InterpolatingMicrosphere(int, int, double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Create an uninitialized sphere.
InterpolatingMicrosphere(int, int, double, double, double, UnitSphereSampler) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Create a sphere from randomly sampled vectors.
InterpolatingMicrosphere(InterpolatingMicrosphere) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Copy constructor.
InterpolatingMicrosphere2D - Class in org.apache.commons.math4.legacy.analysis.interpolation: Utility class for the MicrosphereProjectionInterpolator algorithm.
InterpolatingMicrosphere2D(int, double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere2D: Create a sphere from vectors regularly sampled around a circle.
InterpolatingMicrosphere2D(InterpolatingMicrosphere2D) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere2D: Copy constructor.
IntervalUtils - Class in org.apache.commons.math4.legacy.stat.interval: Factory methods to generate confidence intervals for a binomial proportion.
InvalidRepresentationException - Exception in org.apache.commons.math4.legacy.genetics: Exception indicating that the representation of a chromosome is not valid.
InvalidRepresentationException(Localizable, Object...) - Constructor for exception org.apache.commons.math4.legacy.genetics.InvalidRepresentationException: Construct an InvalidRepresentationException with a specialized message.
inverse() - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Computes the inverse of this diagonal matrix.
inverse(double) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Computes the inverse of this diagonal matrix.
inverse(RealMatrix) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Computes the inverse of the given matrix.
inverse(RealMatrix, double) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Computes the inverse of the given matrix.
Inverse - Class in org.apache.commons.math4.legacy.analysis.function: Inverse function.
Inverse() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Inverse
inverseCumulativeProbability(double) - Method in class org.apache.commons.math4.legacy.distribution.AbstractIntegerDistribution: The default implementation returns DiscreteDistribution.getSupportLowerBound() for p = 0, DiscreteDistribution.getSupportUpperBound() for p = 1, and AbstractIntegerDistribution.solveInverseCumulativeProbability(double, int, int) for 0 < p < 1.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math4.legacy.distribution.AbstractRealDistribution: The default implementation returns ContinuousDistribution.getSupportLowerBound() for p = 0, ContinuousDistribution.getSupportUpperBound() for p = 1.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math4.legacy.distribution.EmpiricalDistribution: The default implementation returns ContinuousDistribution.getSupportLowerBound() for p = 0, ContinuousDistribution.getSupportUpperBound() for p = 1.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedRealDistribution
isBetterScore(double, double) - Method in interface org.apache.commons.math4.legacy.ml.clustering.ClusterEvaluator: Provides a means to interpret the score value.
isBetterScore(double, double) - Method in class org.apache.commons.math4.legacy.ml.clustering.evaluation.CalinskiHarabasz: Provides a means to interpret the score value.
isBetterScore(double, double) - Method in class org.apache.commons.math4.legacy.ml.clustering.evaluation.SumOfClusterVariances: Provides a means to interpret the score value.
isBiasCorrected() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Returns true iff biasCorrected property is set to true.
isBiasCorrected() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation
isBiasCorrected() - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance
isBracketing(double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Check whether the function takes opposite signs at the endpoints.
isBracketing(UnivariateFunction, double, double) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: Check whether the interval bounds bracket a root.
isDefaultValue(double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Determine if this value is within epsilon of zero.
isForward() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Check if the natural integration direction is forward.
isForward() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Check if the natural integration direction is forward.
isForward() - Method in interface org.apache.commons.math4.legacy.ode.sampling.FieldStepInterpolator: Check if the natural integration direction is forward.
isForward() - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Check if the natural integration direction is forward.
isInfinite() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Check whether any coordinate of this vector is infinite and none are NaN.
isInfinite() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Check whether any coordinate of this vector is infinite and none are NaN.
isInfinite() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Check whether any coordinate of this vector is infinite and none are NaN.
isLastStep - Variable in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Indicator for last step.
isLastStep() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Check if this step is the last one.
isNaN() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Check if any coordinate of this vector is NaN.
isNaN() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Check whether any coordinate of this vector is NaN.
isNaN() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Check whether any coordinate of this vector is NaN.
isNoIntercept() - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression
isNonSingular() - Method in interface org.apache.commons.math4.legacy.linear.DecompositionSolver: Check if the decomposed matrix is non-singular.
isNonSingular() - Method in interface org.apache.commons.math4.legacy.linear.FieldDecompositionSolver: Check if the decomposed matrix is non-singular.
isRandomStart() - Method in class org.apache.commons.math4.legacy.genetics.CycleCrossover: Returns whether the starting index is chosen randomly or set to zero.
isRestrictedToNonNegative() - Method in class org.apache.commons.math4.legacy.optim.linear.LinearOptimizer
isRestrictedToNonNegative() - Method in class org.apache.commons.math4.legacy.optim.linear.NonNegativeConstraint: Indicates whether all the variables must be restricted to non-negative values.
isSame(Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.BinaryChromosome: Returns true iff another has the same representation and therefore the same fitness.
isSame(Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.Chromosome: Returns true iff another has the same representation and therefore the same fitness.
isSame(Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.RandomKey: Returns true iff another is a RandomKey and encodes the same permutation.
isSatisfied(Population) - Method in class org.apache.commons.math4.legacy.genetics.FixedElapsedTime: Determine whether or not the maximum allowed time has passed.
isSatisfied(Population) - Method in class org.apache.commons.math4.legacy.genetics.FixedGenerationCount: Determine whether or not the given number of generations have passed.
isSatisfied(Population) - Method in interface org.apache.commons.math4.legacy.genetics.StoppingCondition: Determine whether or not the given population satisfies the stopping condition.
isSequence(double, double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Check whether the arguments form a (strictly) increasing sequence.
isSequence(double, double, double) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: Check whether the arguments form a (strictly) increasing sequence.
isSingular() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldLUDecomposition
isSingular(double) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns whether this diagonal matrix is singular, i.e.
isSolutionOptimal() - Method in class org.apache.commons.math4.legacy.optim.linear.SolutionCallback: Returns if the found solution is optimal.
isSquare() - Method in interface org.apache.commons.math4.legacy.linear.AnyMatrix: Indicates whether this is a square matrix.
isSupported(String) - Method in class org.apache.commons.math4.legacy.ode.AbstractParameterizable: Check if a parameter is supported.
isSupported(String) - Method in interface org.apache.commons.math4.legacy.ode.Parameterizable: Check if a parameter is supported.
isSymmetric(RealMatrix, double) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Checks whether a matrix is symmetric.
isTransposable() - Method in class org.apache.commons.math4.legacy.linear.RealLinearOperator: Returns true if this operator supports RealLinearOperator.operateTranspose(RealVector).
isValidPoint(double) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialSplineFunction: Indicates whether a point is within the interpolation range.
isValidPoint(double, double) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction: Indicates whether a point is within the interpolation range.
isValidPoint(double, double) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.PiecewiseBicubicSplineInterpolatingFunction: Indicates whether a point is within the interpolation range.
isValidPoint(double, double, double) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.TricubicInterpolatingFunction: Indicates whether a point is within the interpolation range.
IterationEvent - Class in org.apache.commons.math4.legacy.linear: The root class from which all events occurring while running an IterationManager should be derived.
IterationEvent(Object, int) - Constructor for class org.apache.commons.math4.legacy.linear.IterationEvent: Creates a new instance of this class.
IterationListener - Interface in org.apache.commons.math4.legacy.linear: The listener interface for receiving events occurring in an iterative algorithm.
IterationManager - Class in org.apache.commons.math4.legacy.linear: This abstract class provides a general framework for managing iterative algorithms.
IterationManager(int) - Constructor for class org.apache.commons.math4.legacy.linear.IterationManager: Creates a new instance of this class.
IterationManager(int, IntegerSequence.Incrementor.MaxCountExceededCallback) - Constructor for class org.apache.commons.math4.legacy.linear.IterationManager: Creates a new instance of this class.
iterationPerformed(IterationEvent) - Method in interface org.apache.commons.math4.legacy.linear.IterationListener: Invoked each time an iteration is completed (in the main iteration loop).
iterations - Variable in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: The iteration count.
iterationStarted(IterationEvent) - Method in interface org.apache.commons.math4.legacy.linear.IterationListener: Invoked each time a new iteration is completed (in the main iteration loop).
IterativeLegendreGaussIntegrator - Class in org.apache.commons.math4.legacy.analysis.integration: This algorithm divides the integration interval into equally-sized sub-interval and on each of them performs a Legendre-Gauss quadrature.
IterativeLegendreGaussIntegrator(int, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.IterativeLegendreGaussIntegrator: Builds an integrator with given accuracies.
IterativeLegendreGaussIntegrator(int, double, double, int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.IterativeLegendreGaussIntegrator: Builds an integrator with given accuracies and iterations counts.
IterativeLegendreGaussIntegrator(int, int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.IterativeLegendreGaussIntegrator: Builds an integrator with given iteration counts.
IterativeLinearSolver - Class in org.apache.commons.math4.legacy.linear: This abstract class defines an iterative solver for the linear system A · x = b.
IterativeLinearSolver(int) - Constructor for class org.apache.commons.math4.legacy.linear.IterativeLinearSolver: Creates a new instance of this class, with default iteration manager.
IterativeLinearSolver(IterationManager) - Constructor for class org.apache.commons.math4.legacy.linear.IterativeLinearSolver: Creates a new instance of this class, with custom iteration manager.
IterativeLinearSolverEvent - Class in org.apache.commons.math4.legacy.linear: This is the base class for all events occurring during the iterations of a IterativeLinearSolver.
IterativeLinearSolverEvent(Object, int) - Constructor for class org.apache.commons.math4.legacy.linear.IterativeLinearSolverEvent: Creates a new instance of this class.
iterator() - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Returns an iterator over the unmodifiable list of chromosomes.
iterator() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Generic dense iterator.

J

JacobianFunction - Class in org.apache.commons.math4.legacy.analysis.differentiation: Class representing the Jacobian of a multivariate vector function.
JacobianFunction(MultivariateDifferentiableVectorFunction) - Constructor for class org.apache.commons.math4.legacy.analysis.differentiation.JacobianFunction: Simple constructor.
JacobianMatrices - Class in org.apache.commons.math4.legacy.ode: This class defines a set of secondary equations to compute the Jacobian matrices with respect to the initial state vector and, if any, to some parameters of the primary ODE set.
JacobianMatrices(FirstOrderDifferentialEquations, double[], String...) - Constructor for class org.apache.commons.math4.legacy.ode.JacobianMatrices: Simple constructor for a secondary equations set computing Jacobian matrices.
JacobianMatrices(MainStateJacobianProvider, String...) - Constructor for class org.apache.commons.math4.legacy.ode.JacobianMatrices: Simple constructor for a secondary equations set computing Jacobian matrices.
JacobianMatrices.MismatchedEquations - Exception in org.apache.commons.math4.legacy.ode: Special exception for equations mismatch.
JacobiPreconditioner - Class in org.apache.commons.math4.legacy.linear: This class implements the standard Jacobi (diagonal) preconditioner.
JacobiPreconditioner(double[], boolean) - Constructor for class org.apache.commons.math4.legacy.linear.JacobiPreconditioner: Creates a new instance of this class.

K

KalmanFilter - Class in org.apache.commons.math4.legacy.filter: Implementation of a Kalman filter to estimate the state x_k of a discrete-time controlled process that is governed by the linear stochastic difference equation:
KalmanFilter(ProcessModel, MeasurementModel) - Constructor for class org.apache.commons.math4.legacy.filter.KalmanFilter: Creates a new Kalman filter with the given process and measurement models.
KendallsCorrelation - Class in org.apache.commons.math4.legacy.stat.correlation: Implementation of Kendall's Tau-b rank correlation.
KendallsCorrelation() - Constructor for class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Create a KendallsCorrelation instance without data.
KendallsCorrelation(double[][]) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Create a KendallsCorrelation from a rectangular array whose columns represent values of variables to be correlated.
KendallsCorrelation(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.KendallsCorrelation: Create a KendallsCorrelation from a RealMatrix whose columns represent variables to be correlated.
KMeansPlusPlusClusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: Clustering algorithm based on David Arthur and Sergei Vassilvitski k-means++ algorithm.
KMeansPlusPlusClusterer(int) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer: Build a clusterer.
KMeansPlusPlusClusterer(int, int) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer: Build a clusterer.
KMeansPlusPlusClusterer(int, int, DistanceMeasure) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer: Build a clusterer.
KMeansPlusPlusClusterer(int, int, DistanceMeasure, UniformRandomProvider) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer: Build a clusterer.
KMeansPlusPlusClusterer(int, int, DistanceMeasure, UniformRandomProvider, KMeansPlusPlusClusterer.EmptyClusterStrategy) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer: Build a clusterer.
KMeansPlusPlusClusterer.EmptyClusterStrategy - Enum in org.apache.commons.math4.legacy.ml.clustering: Strategies to use for replacing an empty cluster.
kolmogorovSmirnovStatistic(double[], double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
kolmogorovSmirnovStatistic(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Computes the two-sample Kolmogorov-Smirnov test statistic, \(D_{n,m}=\sup_x |F_n(x)-F_m(x)|\) where \(n\) is the length of x, \(m\) is the length of y, \(F_n\) is the empirical distribution that puts mass \(1/n\) at each of the values in x and \(F_m\) is the empirical distribution of the y values.
kolmogorovSmirnovStatistic(ContinuousDistribution, double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
kolmogorovSmirnovStatistic(ContinuousDistribution, double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Computes the one-sample Kolmogorov-Smirnov test statistic, \(D_n=\sup_x |F_n(x)-F(x)|\) where \(F\) is the distribution (cdf) function associated with distribution, \(n\) is the length of data and \(F_n\) is the empirical distribution that puts mass \(1/n\) at each of the values in data.
kolmogorovSmirnovTest(double[], double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
kolmogorovSmirnovTest(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Computes the p-value, or observed significance level, of a two-sample Kolmogorov-Smirnov test evaluating the null hypothesis that x and y are samples drawn from the same probability distribution.
kolmogorovSmirnovTest(double[], double[], boolean) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
kolmogorovSmirnovTest(double[], double[], boolean) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Computes the p-value, or observed significance level, of a two-sample Kolmogorov-Smirnov test evaluating the null hypothesis that x and y are samples drawn from the same probability distribution.
kolmogorovSmirnovTest(ContinuousDistribution, double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
kolmogorovSmirnovTest(ContinuousDistribution, double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Computes the p-value, or observed significance level, of a one-sample Kolmogorov-Smirnov test evaluating the null hypothesis that data conforms to distribution.
kolmogorovSmirnovTest(ContinuousDistribution, double[], boolean) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
kolmogorovSmirnovTest(ContinuousDistribution, double[], boolean) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Computes the p-value, or observed significance level, of a one-sample Kolmogorov-Smirnov test evaluating the null hypothesis that data conforms to distribution.
kolmogorovSmirnovTest(ContinuousDistribution, double[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
kolmogorovSmirnovTest(ContinuousDistribution, double[], double) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Performs a Kolmogorov-Smirnov test evaluating the null hypothesis that data conforms to distribution.
KolmogorovSmirnovTest - Class in org.apache.commons.math4.legacy.stat.inference: Implementation of the Kolmogorov-Smirnov (K-S) test for equality of continuous distributions.
KolmogorovSmirnovTest() - Constructor for class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest
ksSum(double, double, int) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Computes \( 1 + 2 \sum_{i=1}^\infty (-1)^i e^{-2 i^2 t^2} \) stopping when successive partial sums are within tolerance of one another, or when maxIterations partial sums have been computed.
KthSelector - Class in org.apache.commons.math4.legacy.stat.descriptive.rank: A Simple K^th selector implementation to pick up the K^th ordered element from a work array containing the input numbers.
KthSelector() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.KthSelector: Constructor with default median of 3 pivoting strategy.
KthSelector(PivotingStrategy) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.KthSelector: Constructor with specified pivoting strategy.
Kurtosis - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Computes the Kurtosis of the available values.
Kurtosis() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Construct a Kurtosis.
Kurtosis(FourthMoment) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Construct a Kurtosis from an external moment.
Kurtosis(Kurtosis) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Copy constructor, creates a new Kurtosis identical to the original.

L

laguerre(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegratorFactory: Creates a Gauss-Laguerre integrator of the given order.
LaguerreRuleFactory - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: Factory that creates Gauss-type quadrature rule using Laguerre polynomials.
LaguerreRuleFactory() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.LaguerreRuleFactory
LaguerreSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Implements the Laguerre's Method for root finding of real coefficient polynomials.
LaguerreSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.LaguerreSolver: Construct a solver with default accuracy (1e-6).
LaguerreSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.LaguerreSolver: Construct a solver.
LaguerreSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.LaguerreSolver: Construct a solver.
LaguerreSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.LaguerreSolver: Construct a solver.
LARGEST_POINTS_NUMBER - org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer.EmptyClusterStrategy: Split the cluster with largest number of points.
LARGEST_VARIANCE - org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer.EmptyClusterStrategy: Split the cluster with largest distance variance.
LAST - org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Include the last point, but not the first point.
lastIncluded() - Method in enum org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Returns a value indicating whether the last point should be passed to the underlying fixed step size step handler.
lazyEvaluation(boolean) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure whether evaluation will be lazy or not.
LeastSquaresAdapter - Class in org.apache.commons.math4.legacy.fitting.leastsquares: An adapter that delegates to another implementation of LeastSquaresProblem.
LeastSquaresAdapter(LeastSquaresProblem) - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresAdapter: Delegate the LeastSquaresProblem interface to the given implementation.
LeastSquaresBuilder - Class in org.apache.commons.math4.legacy.fitting.leastsquares: A mutable builder for LeastSquaresProblems.
LeastSquaresBuilder() - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder
LeastSquaresConverter - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: This class converts vectorial objective functions to scalar objective functions when the goal is to minimize them.
LeastSquaresConverter(MultivariateVectorFunction, double[]) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.LeastSquaresConverter: Builds a simple converter for uncorrelated residuals with identical weights.
LeastSquaresConverter(MultivariateVectorFunction, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.LeastSquaresConverter: Builds a simple converter for uncorrelated residuals with the specified weights.
LeastSquaresConverter(MultivariateVectorFunction, double[], RealMatrix) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.LeastSquaresConverter: Builds a simple converter for correlated residuals with the specified weights.
LeastSquaresFactory - Class in org.apache.commons.math4.legacy.fitting.leastsquares: A Factory for creating LeastSquaresProblems.
LeastSquaresOptimizer - Interface in org.apache.commons.math4.legacy.fitting.leastsquares: An algorithm that can be applied to a non-linear least squares problem.
LeastSquaresOptimizer.Optimum - Interface in org.apache.commons.math4.legacy.fitting.leastsquares: The optimum found by the optimizer.
LeastSquaresProblem - Interface in org.apache.commons.math4.legacy.fitting.leastsquares: The data necessary to define a non-linear least squares problem.
LeastSquaresProblem.Evaluation - Interface in org.apache.commons.math4.legacy.fitting.leastsquares: An evaluation of a LeastSquaresProblem at a particular point.
LEFT_SIDE - org.apache.commons.math4.legacy.analysis.solvers.AllowedSolution: Only solutions that are less than or equal to the actual root are acceptable as solutions for root-finding.
LEGACY - org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: This is the default type used in the Percentile.This method.
legendre(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegratorFactory: Creates a Gauss-Legendre integrator of the given order.
legendre(int, double, double) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegratorFactory: Creates a Gauss-Legendre integrator of the given order.
legendreHighPrecision(int) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegratorFactory: Creates a Gauss-Legendre integrator of the given order.
legendreHighPrecision(int, double, double) - Method in class org.apache.commons.math4.legacy.analysis.integration.gauss.GaussIntegratorFactory: Creates an integrator of the given order, and whose call to the integrate method will perform an integration on the given interval.
LegendreHighPrecisionRuleFactory - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: Factory that creates Gauss-type quadrature rule using Legendre polynomials.
LegendreHighPrecisionRuleFactory() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.LegendreHighPrecisionRuleFactory: Default precision is DECIMAL128.
LegendreHighPrecisionRuleFactory(MathContext) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.LegendreHighPrecisionRuleFactory
LegendreRuleFactory - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: Factory that creates Gauss-type quadrature rule using Legendre polynomials.
LegendreRuleFactory() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.LegendreRuleFactory
LEQ - org.apache.commons.math4.legacy.optim.linear.Relationship: Lesser than or equal relationship.
LESS_THAN - org.apache.commons.math4.legacy.stat.inference.AlternativeHypothesis: Represents a left-sided test.
LevenbergMarquardtOptimizer - Class in org.apache.commons.math4.legacy.fitting.leastsquares: This class solves a least-squares problem using the Levenberg-Marquardt algorithm.
LevenbergMarquardtOptimizer() - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer: Default constructor.
LevenbergMarquardtOptimizer(double, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer: Construct an instance with all parameters specified.
linearCombination(double[], DerivativeStructure[]) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
linearCombination(double[], SparseGradient[]) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
linearCombination(double, double[], int, double, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute linear combination.
linearCombination(double, double[], int, double, double[], int, double, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute linear combination.
linearCombination(double, double[], int, double, double[], int, double, double[], int, double, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute linear combination.
linearCombination(double, DerivativeStructure, double, DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
linearCombination(double, DerivativeStructure, double, DerivativeStructure, double, DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
linearCombination(double, DerivativeStructure, double, DerivativeStructure, double, DerivativeStructure, double, DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
linearCombination(double, SparseGradient, double, SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
linearCombination(double, SparseGradient, double, SparseGradient, double, SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
linearCombination(double, SparseGradient, double, SparseGradient, double, SparseGradient, double, SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
linearCombination(DerivativeStructure[], DerivativeStructure[]) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
linearCombination(DerivativeStructure, DerivativeStructure, DerivativeStructure, DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
linearCombination(DerivativeStructure, DerivativeStructure, DerivativeStructure, DerivativeStructure, DerivativeStructure, DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
linearCombination(DerivativeStructure, DerivativeStructure, DerivativeStructure, DerivativeStructure, DerivativeStructure, DerivativeStructure, DerivativeStructure, DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
linearCombination(SparseGradient[], SparseGradient[]) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
linearCombination(SparseGradient, SparseGradient, SparseGradient, SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
linearCombination(SparseGradient, SparseGradient, SparseGradient, SparseGradient, SparseGradient, SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
linearCombination(SparseGradient, SparseGradient, SparseGradient, SparseGradient, SparseGradient, SparseGradient, SparseGradient, SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
LinearConstraint - Class in org.apache.commons.math4.legacy.optim.linear: A linear constraint for a linear optimization problem.
LinearConstraint(double[], double, Relationship, double[], double) - Constructor for class org.apache.commons.math4.legacy.optim.linear.LinearConstraint: Build a constraint involving two linear equations.
LinearConstraint(double[], Relationship, double) - Constructor for class org.apache.commons.math4.legacy.optim.linear.LinearConstraint: Build a constraint involving a single linear equation.
LinearConstraint(RealVector, double, Relationship, RealVector, double) - Constructor for class org.apache.commons.math4.legacy.optim.linear.LinearConstraint: Build a constraint involving two linear equations.
LinearConstraint(RealVector, Relationship, double) - Constructor for class org.apache.commons.math4.legacy.optim.linear.LinearConstraint: Build a constraint involving a single linear equation.
LinearConstraintSet - Class in org.apache.commons.math4.legacy.optim.linear: Class that represents a set of linear constraints.
LinearConstraintSet(Collection<LinearConstraint>) - Constructor for class org.apache.commons.math4.legacy.optim.linear.LinearConstraintSet: Creates a set containing the given constraints.
LinearConstraintSet(LinearConstraint...) - Constructor for class org.apache.commons.math4.legacy.optim.linear.LinearConstraintSet: Creates a set containing the given constraints.
LinearInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Implements a linear function for interpolation of real univariate functions.
LinearInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.LinearInterpolator
LinearObjectiveFunction - Class in org.apache.commons.math4.legacy.optim.linear: An objective function for a linear optimization problem.
LinearObjectiveFunction(double[], double) - Constructor for class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction
LinearObjectiveFunction(RealVector, double) - Constructor for class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction
LinearOptimizer - Class in org.apache.commons.math4.legacy.optim.linear: Base class for implementing linear optimizers.
LinearOptimizer() - Constructor for class org.apache.commons.math4.legacy.optim.linear.LinearOptimizer: Simple constructor with default settings.
lineSearch(double[], double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateOptimizer: Finds the number alpha that optimizes f(startPoint + alpha * direction).
LineSearch - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Deprecated.
as of 4.0-beta2. Class is now encapsulated in MultivariateOptimizer. Subclasses should call MultivariateOptimizer.createLineSearch() and MultivariateOptimizer.lineSearch(double[],double[]) instead.
LineSearch(MultivariateOptimizer, double, double, double) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.LineSearch: Deprecated.

The BrentOptimizer default stopping criterion uses the tolerances to check the domain (point) values, not the function values.
LineSearchTolerance - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Tolerances for line search.
LineSearchTolerance(double, double, double) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.LineSearchTolerance
ListPopulation - Class in org.apache.commons.math4.legacy.genetics: Population of chromosomes represented by a List.
ListPopulation(int) - Constructor for class org.apache.commons.math4.legacy.genetics.ListPopulation: Creates a new ListPopulation instance and initializes its inner chromosome list.
ListPopulation(List<Chromosome>, int) - Constructor for class org.apache.commons.math4.legacy.genetics.ListPopulation: Creates a new ListPopulation instance.
LoessInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Implements the Local Regression Algorithm (also Loess, Lowess) for interpolation of real univariate functions.
LoessInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Constructs a new LoessInterpolator with a bandwidth of LoessInterpolator.DEFAULT_BANDWIDTH, LoessInterpolator.DEFAULT_ROBUSTNESS_ITERS robustness iterations and an accuracy of {#link #DEFAULT_ACCURACY}.
LoessInterpolator(double, int) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Construct a new LoessInterpolator with given bandwidth and number of robustness iterations.
LoessInterpolator(double, int, double) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Construct a new LoessInterpolator with given bandwidth, number of robustness iterations and accuracy.
log() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
log() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
log(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute natural logarithm of a derivative structure.
Log - Class in org.apache.commons.math4.legacy.analysis.function: Natural logarithm function.
Log() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Log
log10() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Base 10 logarithm.
log10() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Base 10 logarithm.
log10(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Computes base 10 logarithm of a derivative structure.
Log10 - Class in org.apache.commons.math4.legacy.analysis.function: Base 10 logarithm function.
Log10() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Log10
log1p() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
log1p() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
log1p(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Computes shifted logarithm of a derivative structure.
Log1p - Class in org.apache.commons.math4.legacy.analysis.function: log(1 + p) function.
Log1p() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Log1p
logDensity(double) - Method in class org.apache.commons.math4.legacy.distribution.AbstractRealDistribution
Logistic - Class in org.apache.commons.math4.legacy.analysis.function: Generalised logistic function.
Logistic(double, double, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Logistic
Logistic.Parametric - Class in org.apache.commons.math4.legacy.analysis.function: Parametric function where the input array contains the parameters of the logistic function.
Logit - Class in org.apache.commons.math4.legacy.analysis.function: Logit function.
Logit() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Logit: Usual logit function, where the lower bound is 0 and the higher bound is 1.
Logit(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Logit: Logit function.
Logit.Parametric - Class in org.apache.commons.math4.legacy.analysis.function: Parametric function where the input array contains the parameters of the logit function.
logProbability(int) - Method in class org.apache.commons.math4.legacy.distribution.AbstractIntegerDistribution
LU - org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer.Decomposition: Solve by forming the normal equations (J^TJx=J^Tr) and using the LUDecomposition.
LUDecomposition - Class in org.apache.commons.math4.legacy.linear: Calculates the LUP-decomposition of a square matrix.
LUDecomposition(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.linear.LUDecomposition: Calculates the LU-decomposition of the given matrix.
LUDecomposition(RealMatrix, double) - Constructor for class org.apache.commons.math4.legacy.linear.LUDecomposition: Calculates the LU-decomposition of the given matrix.
LutherFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the Luther sixth order Runge-Kutta integrator for Ordinary Differential Equations.
LutherFieldIntegrator(Field<T>, T) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.LutherFieldIntegrator: Simple constructor.
LutherIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the Luther sixth order Runge-Kutta integrator for Ordinary Differential Equations.
LutherIntegrator(double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.LutherIntegrator: Simple constructor.

M

m2 - Variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: second moment of values that have been added.
mainSetDimension - Variable in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Main set dimension.
mainSetDimension - Variable in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Main set dimension.
MainStateJacobianProvider - Interface in org.apache.commons.math4.legacy.ode: Interface expanding first order differential equations in order to compute exactly the main state jacobian matrix for partial derivatives equations.
ManhattanDistance - Class in org.apache.commons.math4.legacy.ml.distance: Calculates the L₁ (sum of abs) distance between two points.
ManhattanDistance() - Constructor for class org.apache.commons.math4.legacy.ml.distance.ManhattanDistance
mannWhitneyU(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.MannWhitneyUTest: Computes the Mann-Whitney U statistic comparing mean for two independent samples possibly of different length.
mannWhitneyUTest(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.MannWhitneyUTest: Returns the asymptotic observed significance level, or p-value, associated with a Mann-Whitney U statistic comparing mean for two independent samples.
MannWhitneyUTest - Class in org.apache.commons.math4.legacy.stat.inference: An implementation of the Mann-Whitney U test (also called Wilcoxon rank-sum test).
MannWhitneyUTest() - Constructor for class org.apache.commons.math4.legacy.stat.inference.MannWhitneyUTest: Create a test instance using where NaN's are left in place and ties get the average of applicable ranks.
MannWhitneyUTest(NaNStrategy, TiesStrategy) - Constructor for class org.apache.commons.math4.legacy.stat.inference.MannWhitneyUTest: Create a test instance using the given strategies for NaN's and ties.
map(UnivariateFunction) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Acts as if implemented as:
map(UnivariateFunction) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Acts as if implemented as:
mapAdd(double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Add a value to each entry.
mapAdd(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Add a value to each entry.
mapAdd(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Map an addition operation to each entry.
mapAdd(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Map an addition operation to each entry.
mapAdd(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Map an addition operation to each entry.
mapAddToSelf(double) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Add a value to each entry.
mapAddToSelf(double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Add a value to each entry.
mapAddToSelf(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Add a value to each entry.
mapAddToSelf(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Map an addition operation to each entry.
mapAddToSelf(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Map an addition operation to each entry.
mapAddToSelf(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Map an addition operation to each entry.
mapDerivative(FieldODEStateAndDerivative<T>) - Method in class org.apache.commons.math4.legacy.ode.FieldEquationsMapper: Map a state derivative to a complete flat array.
mapDivide(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Divide each entry by the argument.
mapDivide(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Map a division operation to each entry.
mapDivide(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Map a division operation to each entry.
mapDivide(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Map a division operation to each entry.
mapDivideToSelf(double) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Divide each entry by the argument.
mapDivideToSelf(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Divide each entry by the argument.
mapDivideToSelf(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Map a division operation to each entry.
mapDivideToSelf(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Map a division operation to each entry.
mapDivideToSelf(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Map a division operation to each entry.
mapInv() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Map the 1/x function to each entry.
mapInv() - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Map the 1/x function to each entry.
mapInv() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Map the 1/x function to each entry.
mapInvToSelf() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Map the 1/x function to each entry.
mapInvToSelf() - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Map the 1/x function to each entry.
mapInvToSelf() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Map the 1/x function to each entry.
mapMultiply(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Multiply each entry by the argument.
mapMultiply(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Map a multiplication operation to each entry.
mapMultiply(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Map a multiplication operation to each entry.
mapMultiply(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Map a multiplication operation to each entry.
mapMultiplyToSelf(double) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Multiply each entry.
mapMultiplyToSelf(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Multiply each entry.
mapMultiplyToSelf(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Map a multiplication operation to each entry.
mapMultiplyToSelf(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Map a multiplication operation to each entry.
mapMultiplyToSelf(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Map a multiplication operation to each entry.
mapState(FieldODEState<T>) - Method in class org.apache.commons.math4.legacy.ode.FieldEquationsMapper: Map a state to a complete flat array.
mapStateAndDerivative(T, T[], T[]) - Method in class org.apache.commons.math4.legacy.ode.FieldEquationsMapper: Map flat arrays to a state and derivative.
mapSubtract(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Subtract a value from each entry.
mapSubtract(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Map a subtraction operation to each entry.
mapSubtract(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Map a subtraction operation to each entry.
mapSubtract(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Map a subtraction operation to each entry.
mapSubtractToSelf(double) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Subtract a value from each entry.
mapSubtractToSelf(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Subtract a value from each entry.
mapSubtractToSelf(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Map a subtraction operation to each entry.
mapSubtractToSelf(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Map a subtraction operation to each entry.
mapSubtractToSelf(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Map a subtraction operation to each entry.
mapToSelf(UnivariateFunction) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Acts as if it is implemented as: Entry e = null; for(Iterator<Entry> it = iterator(); it.hasNext(); e = it.next()) { e.setValue(function.value(e.getValue())); } Entries of this vector are modified in-place by this method.
mapToSelf(UnivariateFunction) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Acts as if it is implemented as: Entry e = null; for(Iterator<Entry> it = iterator(); it.hasNext(); e = it.next()) { e.setValue(function.value(e.getValue())); } Entries of this vector are modified in-place by this method.
mate(AbstractListChromosome<T>, AbstractListChromosome<T>) - Method in class org.apache.commons.math4.legacy.genetics.CycleCrossover: Helper for CycleCrossover.crossover(Chromosome, Chromosome).
mate(AbstractListChromosome<T>, AbstractListChromosome<T>) - Method in class org.apache.commons.math4.legacy.genetics.OrderedCrossover: Helper for OrderedCrossover.crossover(Chromosome, Chromosome).
MatrixDimensionMismatchException - Exception in org.apache.commons.math4.legacy.linear: Exception to be thrown when either the number of rows or the number of columns of a matrix do not match the expected values.
MatrixDimensionMismatchException(int, int, int, int) - Constructor for exception org.apache.commons.math4.legacy.linear.MatrixDimensionMismatchException: Construct an exception from the mismatched dimensions.
MatrixUtils - Class in org.apache.commons.math4.legacy.linear: A collection of static methods that operate on or return matrices.
max(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the maximum of the entries in the input array, or Double.NaN if the array is empty.
max(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the maximum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
Max - Class in org.apache.commons.math4.legacy.analysis.function: Maximum function.
Max - Class in org.apache.commons.math4.legacy.stat.descriptive.rank: Returns the maximum of the available values.
Max() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Max
Max() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Create a Max instance.
Max(Max) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.Max: Copy constructor, creates a new Max identical to the original.
MaxEval - Class in org.apache.commons.math4.legacy.optim: Maximum number of evaluations of the function to be optimized.
MaxEval(int) - Constructor for class org.apache.commons.math4.legacy.optim.MaxEval
maxEvaluations(int) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the max evaluations.
MAXIMAL - org.apache.commons.math4.legacy.stat.ranking.NaNStrategy: NaNs are considered maximal in the ordering.
MAXIMIZE - org.apache.commons.math4.legacy.optim.nonlinear.scalar.GoalType: Maximization.
MAXIMUM - org.apache.commons.math4.legacy.stat.ranking.TiesStrategy: Ties get the maximum applicable rank.
MaxIter - Class in org.apache.commons.math4.legacy.optim: Maximum number of iterations performed by an (iterative) algorithm.
MaxIter(int) - Constructor for class org.apache.commons.math4.legacy.optim.MaxIter
maxIterations(int) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the max iterations.
mean(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the arithmetic mean of the entries in the input array, or Double.NaN if the array is empty.
mean(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the arithmetic mean of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
Mean - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Computes the arithmetic mean of a set of values.
Mean() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Constructs a Mean.
Mean(FirstMoment) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Constructs a Mean with an External Moment.
Mean(Mean) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: Copy constructor, creates a new Mean identical to the original.
meanDifference(double[], double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the mean of the (signed) differences between corresponding elements of the input arrays -- i.e., sum(sample1[i] - sample2[i]) / sample1.length.
MeasurementModel - Interface in org.apache.commons.math4.legacy.filter: Defines the measurement model for the use with a KalmanFilter.
Median - Class in org.apache.commons.math4.legacy.stat.descriptive.rank: Returns the median of the available values.
Median() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.Median: Default constructor.
Median(Median) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.Median: Copy constructor, creates a new Median identical.
MedianOf3PivotingStrategy - Class in org.apache.commons.math4.legacy.stat.descriptive.rank: Classic median of 3 strategy given begin and end indices.
MedianOf3PivotingStrategy() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.MedianOf3PivotingStrategy
merge(Collection<Frequency<T>>) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Merge a Collection of Frequency objects into this instance.
merge(Frequency<T>) - Method in class org.apache.commons.math4.legacy.stat.Frequency: Merge another Frequency object's counts into this instance.
metropolis(double) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing: Factory for the Metropolis check for accepting a worse state.
MicrosphereProjectionInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Interpolator that implements the algorithm described in William Dudziak's MS thesis.
MicrosphereProjectionInterpolator(int, int, double, double, double, double, boolean, double) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.MicrosphereProjectionInterpolator: Create a microsphere interpolator.
MicrosphereProjectionInterpolator(InterpolatingMicrosphere, double, boolean, double) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.MicrosphereProjectionInterpolator: Create a microsphere interpolator.
midpoint(double, double) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: Compute the midpoint of two values.
MidpointFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements a second order Runge-Kutta integrator for Ordinary Differential Equations.
MidpointFieldIntegrator(Field<T>, T) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.MidpointFieldIntegrator: Simple constructor.
MidpointIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements a second order Runge-Kutta integrator for Ordinary Differential Equations.
MidpointIntegrator(double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.MidpointIntegrator: Simple constructor.
MidPointIntegrator - Class in org.apache.commons.math4.legacy.analysis.integration: Implements the Midpoint Rule for integration of real univariate functions.
MidPointIntegrator() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.MidPointIntegrator: Construct a midpoint integrator with default settings.
MidPointIntegrator(double, double, int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.MidPointIntegrator: Build a midpoint integrator with given accuracies and iterations counts.
MidPointIntegrator(int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.MidPointIntegrator: Build a midpoint integrator with given iteration counts.
MillerUpdatingRegression - Class in org.apache.commons.math4.legacy.stat.regression: This class is a concrete implementation of the UpdatingMultipleLinearRegression interface.
MillerUpdatingRegression(int, boolean) - Constructor for class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Primary constructor for the MillerUpdatingRegression.
MillerUpdatingRegression(int, boolean, double) - Constructor for class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: This is the augmented constructor for the MillerUpdatingRegression class.
min(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the minimum of the entries in the input array, or Double.NaN if the array is empty.
min(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the minimum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
Min - Class in org.apache.commons.math4.legacy.analysis.function: Minimum function.
Min - Class in org.apache.commons.math4.legacy.stat.descriptive.rank: Returns the minimum of the available values.
Min() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Min
Min() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Create a Min instance.
Min(Min) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.Min: Copy constructor, creates a new Min identical to the original.
MiniBatchKMeansClusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: Clustering algorithm based on KMeans.
MiniBatchKMeansClusterer(int, int, int, int, int, int, DistanceMeasure, UniformRandomProvider, KMeansPlusPlusClusterer.EmptyClusterStrategy) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.MiniBatchKMeansClusterer: Build a clusterer.
MINIMAL - org.apache.commons.math4.legacy.stat.ranking.NaNStrategy: NaNs are considered minimal in the ordering.
MINIMIZE - org.apache.commons.math4.legacy.optim.nonlinear.scalar.GoalType: Minimization.
MINIMUM - org.apache.commons.math4.legacy.stat.ranking.TiesStrategy: Ties get the minimum applicable rank.
MINIMUM_PROBLEM_DIMENSION - Static variable in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.BOBYQAOptimizer: Minimum dimension of the problem: 2.
Minus - Class in org.apache.commons.math4.legacy.analysis.function: Minus function.
Minus() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Minus
MismatchedEquations() - Constructor for exception org.apache.commons.math4.legacy.ode.JacobianMatrices.MismatchedEquations: Simple constructor.
MixtureMultivariateNormalDistribution - Class in org.apache.commons.math4.legacy.distribution: Multivariate normal mixture distribution.
MixtureMultivariateNormalDistribution(double[], double[][], double[][][]) - Constructor for class org.apache.commons.math4.legacy.distribution.MixtureMultivariateNormalDistribution: Creates a multivariate normal mixture distribution.
MixtureMultivariateNormalDistribution(List<Pair<Double, MultivariateNormalDistribution>>) - Constructor for class org.apache.commons.math4.legacy.distribution.MixtureMultivariateNormalDistribution: Creates a mixture model from a list of distributions and their associated weights.
MixtureMultivariateRealDistribution<T extends MultivariateRealDistribution> - Class in org.apache.commons.math4.legacy.distribution: Class for representing mixture model distributions.
MixtureMultivariateRealDistribution(List<Pair<Double, T>>) - Constructor for class org.apache.commons.math4.legacy.distribution.MixtureMultivariateRealDistribution: Creates a mixture model from a list of distributions and their associated weights.
mode(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the sample mode(s).
mode(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the sample mode(s).
model(MultivariateVectorFunction, MultivariateMatrixFunction) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the model function.
model(MultivariateVectorFunction, MultivariateMatrixFunction) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Combine a MultivariateVectorFunction with a MultivariateMatrixFunction to produce a MultivariateJacobianFunction.
model(MultivariateJacobianFunction) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the model function.
ModelSpecificationException - Exception in org.apache.commons.math4.legacy.stat.regression: Exception thrown when a regression model is not correctly specified.
ModelSpecificationException(Localizable, Object...) - Constructor for exception org.apache.commons.math4.legacy.stat.regression.ModelSpecificationException
moment - Variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.Kurtosis: Fourth Moment on which this statistic is based.
moment - Variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.Mean: First moment on which this statistic is based.
moment - Variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Third moment on which this statistic is based.
moment - Variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: SecondMoment is used in incremental calculation of Variance.
monteCarloP(double, int, int, boolean, int, UniformRandomProvider) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
monteCarloP(double, int, int, boolean, int, UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Uses Monte Carlo simulation to approximate \(P(D_{n,m} > d)\) where \(D_{n,m}\) is the 2-sample Kolmogorov-Smirnov statistic.
MullerSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: This class implements the Muller's Method for root finding of real univariate functions.
MullerSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.MullerSolver: Construct a solver with default accuracy (1e-6).
MullerSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.MullerSolver: Construct a solver.
MullerSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.MullerSolver: Construct a solver.
MullerSolver2 - Class in org.apache.commons.math4.legacy.analysis.solvers: This class implements the Muller's Method for root finding of real univariate functions.
MullerSolver2() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.MullerSolver2: Construct a solver with default accuracy (1e-6).
MullerSolver2(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.MullerSolver2: Construct a solver.
MullerSolver2(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.MullerSolver2: Construct a solver.
MultiDirectionalTransform - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: Multi-directional search method.
MultiDirectionalTransform() - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.MultiDirectionalTransform: Transform with default values.
MultiDirectionalTransform(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.MultiDirectionalTransform
MultiKMeansPlusPlusClusterer<T extends Clusterable> - Class in org.apache.commons.math4.legacy.ml.clustering: A wrapper around a k-means++ clustering algorithm which performs multiple trials and returns the best solution.
MultiKMeansPlusPlusClusterer(KMeansPlusPlusClusterer<T>, int) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.MultiKMeansPlusPlusClusterer: Build a clusterer.
MultiKMeansPlusPlusClusterer(KMeansPlusPlusClusterer<T>, int, ClusterRanking) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.MultiKMeansPlusPlusClusterer: Build a clusterer.
MultipleLinearRegression - Interface in org.apache.commons.math4.legacy.stat.regression: The multiple linear regression can be represented in matrix-notation.
MULTIPLES - org.apache.commons.math4.legacy.ode.sampling.StepNormalizerMode: Steps are multiples of a fixed value.
multiply(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
multiply(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
multiply(double[], int, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Perform multiplication of two derivative structures.
multiply(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
multiply(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
multiply(int) - Method in class org.apache.commons.math4.legacy.linear.BigReal
multiply(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
multiply(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
multiply(UnivariateDifferentiableFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Multiplies functions.
multiply(PolynomialFunction) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Multiply the instance by a polynomial.
multiply(UnivariateFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Multiplies functions.
multiply(FieldDenseMatrix<T>) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Multiplication.
multiply(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Postmultiplying this matrix by m.
multiply(Array2DRowRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns the result of postmultiplying this by m.
multiply(BigReal) - Method in class org.apache.commons.math4.legacy.linear.BigReal
multiply(BlockFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Returns the result of postmultiplying this by m.
multiply(BlockRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the result of postmultiplying this by m.
multiply(DiagonalMatrix) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns the result of postmultiplying this by m.
multiply(FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Postmultiply this matrix by m.
multiply(FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Postmultiply this matrix by m.
multiply(FieldMatrix<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Postmultiply this matrix by m.
multiply(OpenMapRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Postmultiply this matrix by m.
multiply(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the result of postmultiplying this by m.
multiply(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the result of postmultiplying this by m.
multiply(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns the result of postmultiplying this by m.
multiply(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Returns the result of postmultiplying this by m.
multiply(RealMatrix) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the result of postmultiplying this by m.
Multiply - Class in org.apache.commons.math4.legacy.analysis.function: Multiply the two operands.
Multiply() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Multiply
multiplyEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Multiplies (in place) the specified entry of this matrix by the specified value.
multiplyEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Multiplies (in place) the specified entry of this matrix by the specified value.
multiplyEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Multiplies (in place) the specified entry of this matrix by the specified value.
multiplyEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Multiplies (in place) the specified entry of this matrix by the specified value.
multiplyEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Multiplies (in place) the specified entry of this matrix by the specified value.
multiplyEntry(int, int, double) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Multiplies (in place) the specified entry of this matrix by the specified value.
multiplyEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Change an entry in the specified row and column.
multiplyEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Change an entry in the specified row and column.
multiplyEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Change an entry in the specified row and column.
multiplyEntry(int, int, T) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Change an entry in the specified row and column.
multiplyEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Change an entry in the specified row and column.
multiplyInPlace(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Multiply in place.
MultiStartMultivariateOptimizer - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Multi-start optimizer.
MultiStartMultivariateOptimizer(MultivariateOptimizer, int, Supplier<double[]>) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultiStartMultivariateOptimizer: Create a multi-start optimizer from a single-start optimizer.
MultiStartUnivariateOptimizer - Class in org.apache.commons.math4.legacy.optim.univariate: Special implementation of the UnivariateOptimizer interface adding multi-start features to an existing optimizer.
MultiStartUnivariateOptimizer(UnivariateOptimizer, int, UniformRandomProvider) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.MultiStartUnivariateOptimizer: Create a multi-start optimizer from a single-start optimizer.
MultistepFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode: This class is the base class for multistep integrators for Ordinary Differential Equations.
MultistepFieldIntegrator(Field<T>, String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Build a multistep integrator with the given stepsize bounds.
MultistepFieldIntegrator(Field<T>, String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Build a multistep integrator with the given stepsize bounds.
MultistepIntegrator - Class in org.apache.commons.math4.legacy.ode: This class is the base class for multistep integrators for Ordinary Differential Equations.
MultistepIntegrator(String, int, int, double, double, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Build a multistep integrator with the given stepsize bounds.
MultistepIntegrator(String, int, int, double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Build a multistep integrator with the given stepsize bounds.
MultistepIntegrator.NordsieckTransformer - Interface in org.apache.commons.math4.legacy.ode: Deprecated.
as of 3.6 this unused interface is deprecated
MultivariateDifferentiableFunction - Interface in org.apache.commons.math4.legacy.analysis.differentiation: Extension of MultivariateFunction representing a multivariate differentiable real function.
MultivariateDifferentiableVectorFunction - Interface in org.apache.commons.math4.legacy.analysis.differentiation: Extension of MultivariateVectorFunction representing a multivariate differentiable vectorial function.
MultivariateFunction - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a multivariate real function.
MultivariateFunctionMappingAdapter - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Adapter for mapping bounded MultivariateFunction to unbounded ones.
MultivariateFunctionMappingAdapter(MultivariateFunction, double[], double[]) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateFunctionMappingAdapter: Simple constructor.
MultivariateFunctionPenaltyAdapter - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Adapter extending bounded MultivariateFunction to an unbouded domain using a penalty function.
MultivariateFunctionPenaltyAdapter(MultivariateFunction, double[], double[], double, double[]) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateFunctionPenaltyAdapter: Simple constructor.
MultivariateInterpolator - Interface in org.apache.commons.math4.legacy.analysis.interpolation: Interface representing a univariate real interpolating function.
MultivariateJacobianFunction - Interface in org.apache.commons.math4.legacy.fitting.leastsquares: A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).
MultivariateMatrixFunction - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a multivariate matrix function.
MultivariateNormalDistribution - Class in org.apache.commons.math4.legacy.distribution: Implementation of the multivariate normal (Gaussian) distribution.
MultivariateNormalDistribution(double[], double[][]) - Constructor for class org.apache.commons.math4.legacy.distribution.MultivariateNormalDistribution: Creates a multivariate normal distribution with the given mean vector and covariance matrix.
MultivariateNormalMixtureExpectationMaximization - Class in org.apache.commons.math4.legacy.distribution.fitting: Expectation-Maximization algorithm for fitting the parameters of multivariate normal mixture model distributions.
MultivariateNormalMixtureExpectationMaximization(double[][]) - Constructor for class org.apache.commons.math4.legacy.distribution.fitting.MultivariateNormalMixtureExpectationMaximization: Creates an object to fit a multivariate normal mixture model to data.
MultivariateOptimizer - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Base class for a multivariate scalar function optimizer.
MultivariateOptimizer(ConvergenceChecker<PointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateOptimizer
MultivariateRealDistribution - Interface in org.apache.commons.math4.legacy.distribution: Base interface for multivariate distributions on the reals.
MultivariateRealDistribution.Sampler - Interface in org.apache.commons.math4.legacy.distribution: Sampling functionality.
MultivariateSummaryStatistics - Class in org.apache.commons.math4.legacy.stat.descriptive: Computes summary statistics for a stream of n-tuples added using the addValue method.
MultivariateSummaryStatistics(int, boolean) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Construct a MultivariateSummaryStatistics instance.
MultivariateVectorFunction - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a multivariate vectorial function.
mutate(Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.BinaryMutation: Mutate the given chromosome.
mutate(Chromosome) - Method in interface org.apache.commons.math4.legacy.genetics.MutationPolicy: Mutate the given chromosome.
mutate(Chromosome) - Method in class org.apache.commons.math4.legacy.genetics.RandomKeyMutation: Mutate the given chromosome.
MutationPolicy - Interface in org.apache.commons.math4.legacy.genetics: Algorithm used to mutate a chromosome.

N

NaNStrategy - Enum in org.apache.commons.math4.legacy.stat.ranking: Strategies for handling NaN values in rank transformations.
NaturalRanking - Class in org.apache.commons.math4.legacy.stat.ranking: Ranking based on the natural ordering on doubles.
NaturalRanking() - Constructor for class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: Create a NaturalRanking with default strategies for handling ties and NaNs.
NaturalRanking(NaNStrategy) - Constructor for class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: Create a NaturalRanking with the given NaNStrategy.
NaturalRanking(NaNStrategy, TiesStrategy) - Constructor for class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: Create a NaturalRanking with the given NaNStrategy and TiesStrategy.
NaturalRanking(NaNStrategy, UniformRandomProvider) - Constructor for class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: Create a NaturalRanking with the given NaNStrategy, TiesStrategy.RANDOM and the given source of random data.
NaturalRanking(TiesStrategy) - Constructor for class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: Create a NaturalRanking with the given TiesStrategy.
NaturalRanking(UniformRandomProvider) - Constructor for class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: Create a NaturalRanking with TiesStrategy.RANDOM and the given random generator as the source of random data.
negate() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
negate() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
negate() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Negate the instance.
negate() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Negate.
negate() - Method in class org.apache.commons.math4.legacy.linear.BigReal
NEITHER - org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Do not include the first and last points.
NelderMeadTransform - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: Nelder-Mead method.
NelderMeadTransform() - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.NelderMeadTransform: Transform with default values.
NelderMeadTransform(double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.NelderMeadTransform
NevilleInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Implements the Neville's Algorithm for interpolation of real univariate functions.
NevilleInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.NevilleInterpolator
newCovarianceData(double[][]) - Method in class org.apache.commons.math4.legacy.stat.regression.GLSMultipleLinearRegression: Add the covariance data.
newFixedLengthChromosome(List<T>) - Method in class org.apache.commons.math4.legacy.genetics.AbstractListChromosome: Creates a new instance of the same class as this is, with a given arrayRepresentation.
newMarkers(List<Double>, double) - Static method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: A creation method to build Markers.
newSampleData(double[], double[][]) - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Loads model x and y sample data, overriding any previous sample.
newSampleData(double[], double[][], double[][]) - Method in class org.apache.commons.math4.legacy.stat.regression.GLSMultipleLinearRegression: Replace sample data, overriding any previous sample.
newSampleData(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Loads model x and y sample data from a flat input array, overriding any previous sample.
newSampleData(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Loads model x and y sample data from a flat input array, overriding any previous sample.
NewtonRaphsonSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Implements Newton's Method for finding zeros of real univariate differentiable functions.
NewtonRaphsonSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.NewtonRaphsonSolver: Construct a solver.
NewtonRaphsonSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.NewtonRaphsonSolver: Construct a solver.
newXSampleData(double[][]) - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Loads new x sample data, overriding any previous data.
newXSampleData(double[][]) - Method in class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Loads new x sample data, overriding any previous data.
newYSampleData(double[]) - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Loads new y sample data, overriding any previous data.
next() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector.OpenMapSparseIterator
next() - Method in class org.apache.commons.math4.legacy.linear.RealVector.SparseEntryIterator
nextGeneration() - Method in class org.apache.commons.math4.legacy.genetics.ElitisticListPopulation: Start the population for the next generation.
nextGeneration() - Method in interface org.apache.commons.math4.legacy.genetics.Population: Start the population for the next generation.
nextGeneration(Population) - Method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Evolve the given population into the next generation.
NoFeasibleSolutionException - Exception in org.apache.commons.math4.legacy.optim.linear: This class represents exceptions thrown by optimizers when no solution fulfills the constraints.
NoFeasibleSolutionException() - Constructor for exception org.apache.commons.math4.legacy.optim.linear.NoFeasibleSolutionException: Simple constructor using a default message.
NonLinearConjugateGradientOptimizer - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient: Non-linear conjugate gradient optimizer.
NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula, ConvergenceChecker<PointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer: Constructor with default preconditioner.
NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula, ConvergenceChecker<PointValuePair>, Preconditioner) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer
NonLinearConjugateGradientOptimizer.Formula - Enum in org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient: Available choices of update formulas for the updating the parameter that is used to compute the successive conjugate search directions.
NonLinearConjugateGradientOptimizer.IdentityPreconditioner - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient: Default identity preconditioner.
NonNegativeConstraint - Class in org.apache.commons.math4.legacy.optim.linear: A constraint for a linear optimization problem indicating whether all variables must be restricted to non-negative values.
NonNegativeConstraint(boolean) - Constructor for class org.apache.commons.math4.legacy.optim.linear.NonNegativeConstraint
NonPositiveDefiniteMatrixException - Exception in org.apache.commons.math4.legacy.linear: Exception to be thrown when a positive definite matrix is expected.
NonPositiveDefiniteMatrixException(double, int, double) - Constructor for exception org.apache.commons.math4.legacy.linear.NonPositiveDefiniteMatrixException: Construct an exception.
NonPositiveDefiniteOperatorException - Exception in org.apache.commons.math4.legacy.linear: Exception to be thrown when a symmetric, definite positive RealLinearOperator is expected.
NonPositiveDefiniteOperatorException() - Constructor for exception org.apache.commons.math4.legacy.linear.NonPositiveDefiniteOperatorException: Creates a new instance of this class.
NonSelfAdjointOperatorException - Exception in org.apache.commons.math4.legacy.linear: Exception to be thrown when a self-adjoint RealLinearOperator is expected.
NonSelfAdjointOperatorException() - Constructor for exception org.apache.commons.math4.legacy.linear.NonSelfAdjointOperatorException: Creates a new instance of this class.
NonSquareMatrixException - Exception in org.apache.commons.math4.legacy.linear: Exception to be thrown when a square matrix is expected.
NonSquareMatrixException(int, int) - Constructor for exception org.apache.commons.math4.legacy.linear.NonSquareMatrixException: Construct an exception from the mismatched dimensions.
NonSquareOperatorException - Exception in org.apache.commons.math4.legacy.linear: Exception to be thrown when a square linear operator is expected.
NonSquareOperatorException(int, int) - Constructor for exception org.apache.commons.math4.legacy.linear.NonSquareOperatorException: Construct an exception from the mismatched dimensions.
NonSymmetricMatrixException - Exception in org.apache.commons.math4.legacy.linear: Exception to be thrown when a symmetric matrix is expected.
NonSymmetricMatrixException(int, int, double) - Constructor for exception org.apache.commons.math4.legacy.linear.NonSymmetricMatrixException: Construct an exception.
nordsieck - Variable in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Nordsieck matrix of the higher scaled derivatives.
nordsieck - Variable in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Nordsieck matrix of the higher scaled derivatives.
NordsieckStepInterpolator - Class in org.apache.commons.math4.legacy.ode.sampling: This class implements an interpolator for integrators using Nordsieck representation.
NordsieckStepInterpolator() - Constructor for class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: Simple constructor.
NordsieckStepInterpolator(NordsieckStepInterpolator) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: Copy constructor.
NormalApproximationInterval - Class in org.apache.commons.math4.legacy.stat.interval: Implements the normal approximation method for creating a binomial proportion confidence interval.
NormalApproximationInterval() - Constructor for class org.apache.commons.math4.legacy.stat.interval.NormalApproximationInterval
normalize(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Normalize (standardize) the sample, so it is has a mean of 0 and a standard deviation of 1.
NPointCrossover<T> - Class in org.apache.commons.math4.legacy.genetics: N-point crossover policy.
NPointCrossover(int) - Constructor for class org.apache.commons.math4.legacy.genetics.NPointCrossover: Creates a new NPointCrossover policy using the given number of points.
numVars() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Find the number of variables.

O

ObjectiveFunction - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Scalar function to be optimized.
ObjectiveFunction(MultivariateFunction) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.ObjectiveFunction
ObjectiveFunctionGradient - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Gradient of the scalar function to be optimized.
ObjectiveFunctionGradient(MultivariateVectorFunction) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.ObjectiveFunctionGradient
OCTAVE_FORMAT - Static variable in class org.apache.commons.math4.legacy.linear.MatrixUtils: A format for RealMatrix objects compatible with octave.
ODEIntegrator - Interface in org.apache.commons.math4.legacy.ode: This interface defines the common parts shared by integrators for first and second order differential equations.
of(double[][]) - Static method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.Simplex: Builds from a given set of coordinates.
of(FieldDenseMatrix<T>) - Static method in class org.apache.commons.math4.legacy.field.linalg.FieldLUDecomposition: Factory method.
OLSMultipleLinearRegression - Class in org.apache.commons.math4.legacy.stat.regression: Implements ordinary least squares (OLS) to estimate the parameters of a multiple linear regression model.
OLSMultipleLinearRegression() - Constructor for class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Create an empty OLSMultipleLinearRegression instance.
OLSMultipleLinearRegression(double) - Constructor for class org.apache.commons.math4.legacy.stat.regression.OLSMultipleLinearRegression: Create an empty OLSMultipleLinearRegression instance, using the given singularity threshold for the QR decomposition.
ONE - Static variable in class org.apache.commons.math4.legacy.linear.BigReal: A big real representing 1.
OnePointCrossover<T> - Class in org.apache.commons.math4.legacy.genetics: One point crossover policy.
OnePointCrossover() - Constructor for class org.apache.commons.math4.legacy.genetics.OnePointCrossover
OneWayAnova - Class in org.apache.commons.math4.legacy.stat.inference: Implements one-way ANOVA (analysis of variance) statistics.
OneWayAnova() - Constructor for class org.apache.commons.math4.legacy.stat.inference.OneWayAnova: Default constructor.
oneWayAnovaFValue(Collection<double[]>) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
oneWayAnovaPValue(Collection<double[]>) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
oneWayAnovaTest(Collection<double[]>, double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
OpenMapEntry(OpenIntToDoubleHashMap.Iterator) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector.OpenMapEntry: Build an entry from an iterator point to an element.
OpenMapRealMatrix - Class in org.apache.commons.math4.legacy.linear: Sparse matrix implementation based on an open addressed map.
OpenMapRealMatrix(int, int) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Build a sparse matrix with the supplied row and column dimensions.
OpenMapRealMatrix(OpenMapRealMatrix) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Build a matrix by copying another one.
OpenMapRealVector - Class in org.apache.commons.math4.legacy.linear: This class implements the RealVector interface with a OpenIntToDoubleHashMap backing store.
OpenMapRealVector() - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Build a 0-length vector.
OpenMapRealVector(double[]) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Create from an array.
OpenMapRealVector(double[], double) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Create from an array, specifying zero tolerance.
OpenMapRealVector(int) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Construct a vector of zeroes.
OpenMapRealVector(int, double) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Construct a vector of zeroes, specifying zero tolerance.
OpenMapRealVector(int, int) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Build a vector with known the sparseness (for advanced use only).
OpenMapRealVector(int, int, double) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Build a vector with known the sparseness and zero tolerance setting (for advanced use only).
OpenMapRealVector(Double[]) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Create from an array.
OpenMapRealVector(Double[], double) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Create from an array.
OpenMapRealVector(OpenMapRealVector) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Copy constructor.
OpenMapRealVector(OpenMapRealVector, int) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Build a resized vector, for use with append.
OpenMapRealVector(RealVector) - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Generic copy constructor.
OpenMapRealVector.OpenMapEntry - Class in org.apache.commons.math4.legacy.linear: Implementation of Entry optimized for OpenMap.
OpenMapRealVector.OpenMapSparseIterator - Class in org.apache.commons.math4.legacy.linear: Iterator class to do iteration over just the non-zero elements.
OpenMapSparseIterator() - Constructor for class org.apache.commons.math4.legacy.linear.OpenMapRealVector.OpenMapSparseIterator: Simple constructor.
operate(double[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the result of multiplying this by the vector v.
operate(double[]) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns the result of multiplying this by the vector v.
operate(double[]) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the result of multiplying this by the vector v.
operate(double[]) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns the result of multiplying this by the vector v.
operate(double[]) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the result of multiplying this by the vector v.
operate(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the result of multiplying this by the vector v.
operate(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns the result of multiplying this by the vector v.
operate(RealVector) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the result of multiplying this by the vector x.
operate(RealVector) - Method in class org.apache.commons.math4.legacy.linear.JacobiPreconditioner: Returns the result of multiplying this by the vector x.
operate(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealLinearOperator: Returns the result of multiplying this by the vector x.
operate(RealVector) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the result of multiplying this by the vector v.
operate(T[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the result of multiplying this by the vector v.
operate(T[]) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Returns the result of multiplying this by the vector v.
operate(T[]) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Returns the result of multiplying this by the vector v.
operate(T[]) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns the result of multiplying this by the vector v.
operateTranspose(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealLinearOperator: Returns the result of multiplying the transpose of this operator by the vector x (optional operation).
OPERATOR - Static variable in class org.apache.commons.math4.legacy.linear.ConjugateGradient: Key for the exception context.
oppositeRelationship() - Method in enum org.apache.commons.math4.legacy.optim.linear.Relationship: Gets the relationship obtained when multiplying all coefficients by -1.
OptimizationData - Interface in org.apache.commons.math4.legacy.optim: Marker interface.
OptimizationProblem<PAIR> - Interface in org.apache.commons.math4.legacy.optim: Common settings for all optimization problems.
optimize() - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Performs the optimization.
optimize(LeastSquaresProblem) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer: Solve the non-linear least squares problem.
optimize(LeastSquaresProblem) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresOptimizer: Solve the non-linear least squares problem.
optimize(LeastSquaresProblem) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer: Solve the non-linear least squares problem.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.BaseMultiStartMultivariateOptimizer: Stores data and performs the optimization.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.BaseMultivariateOptimizer: Stores data and performs the optimization.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Stores data and performs the optimization.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.linear.LinearOptimizer: Stores data and performs the optimization.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Stores data and performs the optimization.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer: Stores data and performs the optimization.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.GradientMultivariateOptimizer: Stores data and performs the optimization.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateOptimizer: Stores data and performs the optimization.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.CMAESOptimizer: Stores data and performs the optimization.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.univariate.MultiStartUnivariateOptimizer: Stores data and performs the optimization.
optimize(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer: Stores data and performs the optimization.
OrderedCrossover<T> - Class in org.apache.commons.math4.legacy.genetics: Order 1 Crossover [OX1] builds offspring from ordered chromosomes by copying a consecutive slice from one parent, and filling up the remaining genes from the other parent as they appear.
OrderedCrossover() - Constructor for class org.apache.commons.math4.legacy.genetics.OrderedCrossover
org.apache.commons.math4.legacy.analysis - package org.apache.commons.math4.legacy.analysis: Parent package for common numerical analysis procedures, including root finding, function interpolation and integration.
org.apache.commons.math4.legacy.analysis.differentiation - package org.apache.commons.math4.legacy.analysis.differentiation: This package holds the main interfaces and basic building block classes dealing with differentiation.
org.apache.commons.math4.legacy.analysis.function - package org.apache.commons.math4.legacy.analysis.function: The function package contains function objects that wrap the methods contained in Math, as well as common mathematical functions such as the gaussian and sinc functions.
org.apache.commons.math4.legacy.analysis.integration - package org.apache.commons.math4.legacy.analysis.integration: Numerical integration (quadrature) algorithms for univariate real functions.
org.apache.commons.math4.legacy.analysis.integration.gauss - package org.apache.commons.math4.legacy.analysis.integration.gauss: Gauss family of quadrature schemes.
org.apache.commons.math4.legacy.analysis.interpolation - package org.apache.commons.math4.legacy.analysis.interpolation: Univariate real functions interpolation algorithms.
org.apache.commons.math4.legacy.analysis.polynomials - package org.apache.commons.math4.legacy.analysis.polynomials: Univariate real polynomials implementations, seen as differentiable univariate real functions.
org.apache.commons.math4.legacy.analysis.solvers - package org.apache.commons.math4.legacy.analysis.solvers: Root finding algorithms, for univariate real functions.
org.apache.commons.math4.legacy.distribution - package org.apache.commons.math4.legacy.distribution: Implementations of probability distributions.
org.apache.commons.math4.legacy.distribution.fitting - package org.apache.commons.math4.legacy.distribution.fitting: Fitting of parameters against distributions.
org.apache.commons.math4.legacy.field - package org.apache.commons.math4.legacy.field: Utilities based on the Field functionality defined in Commons Numbers.
org.apache.commons.math4.legacy.field.linalg - package org.apache.commons.math4.legacy.field.linalg: Linear algebra defined in term of matrices whose entries are elements of a field.
org.apache.commons.math4.legacy.filter - package org.apache.commons.math4.legacy.filter: Implementations of common discrete-time linear filters.
org.apache.commons.math4.legacy.fitting - package org.apache.commons.math4.legacy.fitting: Classes to perform curve fitting.
org.apache.commons.math4.legacy.fitting.leastsquares - package org.apache.commons.math4.legacy.fitting.leastsquares: This package provides algorithms that minimize the residuals between observations and model values.
org.apache.commons.math4.legacy.genetics - package org.apache.commons.math4.legacy.genetics: This package provides Genetic Algorithms components and implementations.
org.apache.commons.math4.legacy.linear - package org.apache.commons.math4.legacy.linear: Linear algebra support.
org.apache.commons.math4.legacy.ml - package org.apache.commons.math4.legacy.ml: Base package for machine learning algorithms.
org.apache.commons.math4.legacy.ml.clustering - package org.apache.commons.math4.legacy.ml.clustering: Clustering algorithms.
org.apache.commons.math4.legacy.ml.clustering.evaluation - package org.apache.commons.math4.legacy.ml.clustering.evaluation: Cluster evaluation methods.
org.apache.commons.math4.legacy.ml.distance - package org.apache.commons.math4.legacy.ml.distance: Common distance measures.
org.apache.commons.math4.legacy.ode - package org.apache.commons.math4.legacy.ode: This package provides classes to solve Ordinary Differential Equations problems.
org.apache.commons.math4.legacy.ode.events - package org.apache.commons.math4.legacy.ode.events: This package provides classes to handle discrete events occurring during Ordinary Differential Equations integration.
org.apache.commons.math4.legacy.ode.nonstiff - package org.apache.commons.math4.legacy.ode.nonstiff: This package provides classes to solve non-stiff Ordinary Differential Equations problems.
org.apache.commons.math4.legacy.ode.sampling - package org.apache.commons.math4.legacy.ode.sampling: This package provides classes to handle sampling steps during Ordinary Differential Equations integration.
org.apache.commons.math4.legacy.optim - package org.apache.commons.math4.legacy.optim: Generally, optimizers are algorithms that will either minimize or maximize a scalar function, called the objective function.
org.apache.commons.math4.legacy.optim.linear - package org.apache.commons.math4.legacy.optim.linear: Optimization algorithms for linear constrained problems.
org.apache.commons.math4.legacy.optim.nonlinear.scalar - package org.apache.commons.math4.legacy.optim.nonlinear.scalar: Algorithms for optimizing a scalar function.
org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient - package org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient: This package provides optimization algorithms that require derivatives.
org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv - package org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: This package provides optimization algorithms that do not require derivatives.
org.apache.commons.math4.legacy.optim.univariate - package org.apache.commons.math4.legacy.optim.univariate: One-dimensional optimization algorithms.
org.apache.commons.math4.legacy.random - package org.apache.commons.math4.legacy.random: This package contains functionality related to random numbers.
org.apache.commons.math4.legacy.special - package org.apache.commons.math4.legacy.special: Implementations of special functions.
org.apache.commons.math4.legacy.stat - package org.apache.commons.math4.legacy.stat: Data storage, manipulation and summary routines.
org.apache.commons.math4.legacy.stat.correlation - package org.apache.commons.math4.legacy.stat.correlation: Correlations/Covariance computations.
org.apache.commons.math4.legacy.stat.descriptive - package org.apache.commons.math4.legacy.stat.descriptive: Generic univariate summary statistic objects.
org.apache.commons.math4.legacy.stat.descriptive.moment - package org.apache.commons.math4.legacy.stat.descriptive.moment: Summary statistics based on moments.
org.apache.commons.math4.legacy.stat.descriptive.rank - package org.apache.commons.math4.legacy.stat.descriptive.rank: Summary statistics based on ranks.
org.apache.commons.math4.legacy.stat.descriptive.summary - package org.apache.commons.math4.legacy.stat.descriptive.summary: Other summary statistics.
org.apache.commons.math4.legacy.stat.inference - package org.apache.commons.math4.legacy.stat.inference: Classes providing hypothesis testing.
org.apache.commons.math4.legacy.stat.interval - package org.apache.commons.math4.legacy.stat.interval: Classes providing binomial proportion confidence interval construction.
org.apache.commons.math4.legacy.stat.ranking - package org.apache.commons.math4.legacy.stat.ranking: Classes providing rank transformations.
org.apache.commons.math4.legacy.stat.regression - package org.apache.commons.math4.legacy.stat.regression: Statistical routines involving multivariate data.
org.apache.commons.math4.legacy.util - package org.apache.commons.math4.legacy.util: Convenience routines and common data structures used throughout the commons-math library.
outerProduct(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute the outer product.
outerProduct(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute the outer product.
outerProduct(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Compute the outer product.
outerProduct(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Compute the outer product.
outerProduct(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Compute the outer product.
outerProduct(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Compute the outer product.
outerProduct(SparseFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Optimized method to compute outer product when both vectors are sparse.

P

pairedT(double[], double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
pairedT(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes a paired, 2-sample t-statistic based on the data in the input arrays.
pairedTTest(double[], double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
pairedTTest(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays.
pairedTTest(double[], double[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
pairedTTest(double[], double[], double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between sample1 and sample2 is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance level alpha.
ParameterGuesser() - Constructor for class org.apache.commons.math4.legacy.fitting.GaussianCurveFitter.ParameterGuesser
ParameterGuesser() - Constructor for class org.apache.commons.math4.legacy.fitting.HarmonicCurveFitter.ParameterGuesser
ParameterGuesser() - Constructor for class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter.ParameterGuesser
Parameterizable - Interface in org.apache.commons.math4.legacy.ode: This interface enables to process any parameterizable object.
ParameterizedODE - Interface in org.apache.commons.math4.legacy.ode: Interface to compute by finite difference Jacobian matrix for some parameter when computing partial derivatives equations.
ParameterJacobianProvider - Interface in org.apache.commons.math4.legacy.ode: Interface to compute exactly Jacobian matrix for some parameter when computing partial derivatives equations.
parameterValidator(ParameterValidator) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the validator of the model parameters.
ParameterValidator - Interface in org.apache.commons.math4.legacy.fitting.leastsquares: Interface for validating a set of model parameters.
Parametric() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Gaussian.Parametric
Parametric() - Constructor for class org.apache.commons.math4.legacy.analysis.function.HarmonicOscillator.Parametric
Parametric() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Logistic.Parametric
Parametric() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Logit.Parametric
Parametric() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Sigmoid.Parametric
Parametric() - Constructor for class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction.Parametric
ParametricUnivariateFunction - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a real function that depends on one independent variable plus some extra parameters.
parse(String) - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Parse a string to produce a RealMatrix object.
parse(String) - Method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Parse a string to produce a RealVector object.
parse(String) - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: Parses a string to produce a Complex object.
parse(String, ParsePosition) - Method in class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Parse a string to produce a RealMatrix object.
parse(String, ParsePosition) - Method in class org.apache.commons.math4.legacy.linear.RealVectorFormat: Parse a string to produce a RealVector object.
parse(String, ParsePosition) - Method in class org.apache.commons.math4.legacy.util.ComplexFormat: Parses a string to produce a Complex object.
parseAndIgnoreWhitespace(String, ParsePosition) - Static method in class org.apache.commons.math4.legacy.util.CompositeFormat: Parses source until a non-whitespace character is found.
parseFixedstring(String, String, ParsePosition) - Static method in class org.apache.commons.math4.legacy.util.CompositeFormat: Parse source for an expected fixed string.
parseNextCharacter(String, ParsePosition) - Static method in class org.apache.commons.math4.legacy.util.CompositeFormat: Parses source until a non-whitespace character is found.
parseNumber(String, NumberFormat, ParsePosition) - Static method in class org.apache.commons.math4.legacy.util.CompositeFormat: Parses source for a number.
parseOptimizationData(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.BaseMultivariateOptimizer: Scans the list of (required and optional) optimization data that characterize the problem.
parseOptimizationData(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.BaseOptimizer: Scans the list of (required and optional) optimization data that characterize the problem.
parseOptimizationData(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.linear.LinearOptimizer: Scans the list of (required and optional) optimization data that characterize the problem.
parseOptimizationData(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Scans the list of (required and optional) optimization data that characterize the problem.
parseOptimizationData(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer: Scans the list of (required and optional) optimization data that characterize the problem.
parseOptimizationData(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.GradientMultivariateOptimizer: Scans the list of (required and optional) optimization data that characterize the problem.
parseOptimizationData(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateOptimizer: Scans the list of (required and optional) optimization data that characterize the problem.
parseOptimizationData(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.CMAESOptimizer: Scans the list of (required and optional) optimization data that characterize the problem.
parseOptimizationData(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.SimplexOptimizer: Scans the list of (required and optional) optimization data that characterize the problem.
parseOptimizationData(OptimizationData...) - Method in class org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer: Scans the list of (required and optional) optimization data that characterize the problem.
partialDerivativeX() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction
partialDerivativeXX() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction
partialDerivativeXY() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction
partialDerivativeY() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction
partialDerivativeYY() - Method in class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction
PearsonsCorrelation - Class in org.apache.commons.math4.legacy.stat.correlation: Computes Pearson's product-moment correlation coefficients for pairs of arrays or columns of a matrix.
PearsonsCorrelation() - Constructor for class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Create a PearsonsCorrelation instance without data.
PearsonsCorrelation(double[][]) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Create a PearsonsCorrelation from a rectangular array whose columns represent values of variables to be correlated.
PearsonsCorrelation(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Create a PearsonsCorrelation from a RealMatrix whose columns represent variables to be correlated.
PearsonsCorrelation(RealMatrix, int) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Create a PearsonsCorrelation from a covariance matrix.
PearsonsCorrelation(Covariance) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.PearsonsCorrelation: Create a PearsonsCorrelation from a Covariance.
PEGASUS - org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver.Method: The Pegasus method.
PegasusSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Implements the Pegasus method for root-finding (approximating a zero of a univariate real function).
PegasusSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.PegasusSolver: Construct a solver with default accuracy (1e-6).
PegasusSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.PegasusSolver: Construct a solver.
PegasusSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.PegasusSolver: Construct a solver.
PegasusSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.PegasusSolver: Construct a solver.
pelzGood(double, int) - Method in class org.apache.commons.math4.legacy.stat.inference.KolmogorovSmirnovTest: Computes the Pelz-Good approximation for \(P(D_n < d)\) as described in [2] in the class javadoc.
percentile(double[], double) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns an estimate of the pth percentile of the values in the values array.
percentile(double[], int, int, double) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns an estimate of the pth percentile of the values in the values array, starting with the element in (0-based) position begin in the array and including length values.
Percentile - Class in org.apache.commons.math4.legacy.stat.descriptive.rank: Provides percentile computation.
Percentile() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Constructs a Percentile with the following defaults.
Percentile(double) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Constructs a Percentile with the specific quantile value and the following.
Percentile(double, Percentile.EstimationType, NaNStrategy, KthSelector) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Constructs a Percentile with the specific quantile value, Percentile.EstimationType, NaNStrategy and KthSelector.
Percentile(Percentile) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Copy constructor, creates a new Percentile identical.
Percentile.EstimationType - Enum in org.apache.commons.math4.legacy.stat.descriptive.rank: An enum for various estimation strategies of a percentile referred in wikipedia on quantile with the names of enum matching those of types mentioned in wikipedia.
performHouseholderReflection(int, double[][]) - Method in class org.apache.commons.math4.legacy.linear.QRDecomposition: Perform Householder reflection for a minor A(minor, minor) of A.
performHouseholderReflection(int, double[][]) - Method in class org.apache.commons.math4.legacy.linear.RRQRDecomposition: Perform Householder reflection for a minor A(minor, minor) of A.
PermutationChromosome<T> - Interface in org.apache.commons.math4.legacy.genetics: Interface indicating that the chromosome represents a permutation of objects.
PiecewiseBicubicSplineInterpolatingFunction - Class in org.apache.commons.math4.legacy.analysis.interpolation: Function that implements the bicubic spline interpolation.
PiecewiseBicubicSplineInterpolatingFunction(double[], double[], double[][]) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.PiecewiseBicubicSplineInterpolatingFunction
PiecewiseBicubicSplineInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Generates a piecewise-bicubic interpolating function.
PiecewiseBicubicSplineInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.PiecewiseBicubicSplineInterpolator
pivotIndex(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.CentralPivotingStrategy: Find pivot index of the array so that partition and K^th element selection can be made.
pivotIndex(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.MedianOf3PivotingStrategy: Find pivot index of the array so that partition and K^th element selection can be made.
pivotIndex(double[], int, int) - Method in interface org.apache.commons.math4.legacy.stat.descriptive.rank.PivotingStrategy: Find pivot index of the array so that partition and K^th element selection can be made.
pivotIndex(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.RandomPivotingStrategy: Find pivot index of the array so that partition and K^th element selection can be made.
PivotingStrategy - Interface in org.apache.commons.math4.legacy.stat.descriptive.rank: A strategy to pick a pivoting index of an array for doing partitioning.
PivotSelectionRule - Enum in org.apache.commons.math4.legacy.optim.linear: Pivot selection rule to the use for a Simplex solver.
PointValuePair - Class in org.apache.commons.math4.legacy.optim: This class holds a point and the value of an objective function at that point.
PointValuePair(double[], double) - Constructor for class org.apache.commons.math4.legacy.optim.PointValuePair: Builds a point/objective function value pair.
PointValuePair(double[], double, boolean) - Constructor for class org.apache.commons.math4.legacy.optim.PointValuePair: Builds a point/objective function value pair.
PointVectorValuePair - Class in org.apache.commons.math4.legacy.optim: This class holds a point and the vectorial value of an objective function at that point.
PointVectorValuePair(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.optim.PointVectorValuePair: Builds a point/objective function value pair.
PointVectorValuePair(double[], double[], boolean) - Constructor for class org.apache.commons.math4.legacy.optim.PointVectorValuePair: Build a point/objective function value pair.
POLAK_RIBIERE - org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer.Formula: Polak-Ribière formula.
PolynomialCurveFitter - Class in org.apache.commons.math4.legacy.fitting: Fits points to a polynomial function.
polynomialDerivative() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Returns the derivative as a PolynomialFunction.
PolynomialFunction - Class in org.apache.commons.math4.legacy.analysis.polynomials: Immutable representation of a real polynomial function with real coefficients.
PolynomialFunction(double[]) - Constructor for class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Construct a polynomial with the given coefficients.
PolynomialFunction.Parametric - Class in org.apache.commons.math4.legacy.analysis.polynomials: Dedicated parametric polynomial class.
PolynomialFunctionLagrangeForm - Class in org.apache.commons.math4.legacy.analysis.polynomials: Implements the representation of a real polynomial function in Lagrange Form.
PolynomialFunctionLagrangeForm(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Construct a Lagrange polynomial with the given abscissas and function values.
PolynomialFunctionNewtonForm - Class in org.apache.commons.math4.legacy.analysis.polynomials: Implements the representation of a real polynomial function in Newton Form.
PolynomialFunctionNewtonForm(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Construct a Newton polynomial with the given a[] and c[].
PolynomialSolver - Interface in org.apache.commons.math4.legacy.analysis.solvers: Interface for (polynomial) root-finding algorithms.
polynomialSplineDerivative() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialSplineFunction: Get the derivative of the polynomial spline function.
PolynomialSplineFunction - Class in org.apache.commons.math4.legacy.analysis.polynomials: Represents a polynomial spline function.
PolynomialSplineFunction(double[], PolynomialFunction[]) - Constructor for class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialSplineFunction: Construct a polynomial spline function with the given segment delimiters and interpolating polynomials.
PolynomialsUtils - Class in org.apache.commons.math4.legacy.analysis.polynomials: A collection of static methods that operate on or return polynomials.
Population - Interface in org.apache.commons.math4.legacy.genetics: A collection of chromosomes that facilitates generational evolution.
PopulationSize - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Population size.
PopulationSize(int) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.PopulationSize
populationVariance(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the population variance of the entries in the input array, or Double.NaN if the array is empty.
populationVariance(double[], double) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the population variance of the entries in the input array, using the precomputed mean value.
populationVariance(double[], double, int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the population variance of the entries in the specified portion of the input array, using the precomputed mean value.
populationVariance(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the population variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
pow(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
pow(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
pow(double[], int, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute power of a derivative structure.
pow(double[], int, double, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute power of a derivative structure.
pow(double[], int, int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute integer power of a derivative structure.
pow(double, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute power of a double to a derivative structure.
pow(double, DerivativeStructure) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Compute a^x where a is a double and x a DerivativeStructure.
pow(double, SparseGradient) - Static method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Compute a^x where a is a double and x a SparseGradient.
pow(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
pow(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
pow(int) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Multiplies the matrix with itself p times.
pow(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
pow(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
Pow - Class in org.apache.commons.math4.legacy.analysis.function: Power function.
Pow() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Pow
PowellOptimizer - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: Powell's algorithm.
PowellOptimizer(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.PowellOptimizer: The parameters control the default convergence checking procedure.
PowellOptimizer(double, double, double, double) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.PowellOptimizer: Builds an instance with the default convergence checking procedure.
PowellOptimizer(double, double, double, double, ConvergenceChecker<PointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.PowellOptimizer: This constructor allows to specify a user-defined convergence checker, in addition to the parameters that control the default convergence checking procedure and the line search tolerances.
PowellOptimizer(double, double, ConvergenceChecker<PointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.PowellOptimizer: This constructor allows to specify a user-defined convergence checker, in addition to the parameters that control the default convergence checking procedure.
power(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the result multiplying this with itself p times.
power(int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the result of multiplying this with itself p times.
power(int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns the result multiplying this with itself p times.
power(int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the result of multiplying this with itself p times.
Power - Class in org.apache.commons.math4.legacy.analysis.function: Power function.
Power(double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Power
precondition(double[], double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer.IdentityPreconditioner: Precondition a search direction.
precondition(double[], double[]) - Method in interface org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.Preconditioner: Precondition a search direction.
PreconditionedIterativeLinearSolver - Class in org.apache.commons.math4.legacy.linear: This abstract class defines preconditioned iterative solvers.
PreconditionedIterativeLinearSolver(int) - Constructor for class org.apache.commons.math4.legacy.linear.PreconditionedIterativeLinearSolver: Creates a new instance of this class, with default iteration manager.
PreconditionedIterativeLinearSolver(IterationManager) - Constructor for class org.apache.commons.math4.legacy.linear.PreconditionedIterativeLinearSolver: Creates a new instance of this class, with custom iteration manager.
Preconditioner - Interface in org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient: This interface represents a preconditioner for differentiable scalar objective function optimizers.
predict() - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Predict the internal state estimation one time step ahead.
predict(double) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Returns the "predicted" y value associated with the supplied x value, based on the data that has been added to the model when this method is activated.
predict(double[]) - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Predict the internal state estimation one time step ahead.
predict(RealVector) - Method in class org.apache.commons.math4.legacy.filter.KalmanFilter: Predict the internal state estimation one time step ahead.
preMultiply(double[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(double[]) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(double[]) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(double[]) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(double[]) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Premultiply this matrix by m.
preMultiply(FieldMatrix<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Premultiply this matrix by m.
preMultiply(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the result of premultiplying this by m.
preMultiply(RealMatrix) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the result of premultiplying this by m.
preMultiply(RealVector) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(RealVector) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(RealVector) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(T[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(T[]) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(T[]) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Returns the (row) vector result of premultiplying this by the vector v.
preMultiply(T[]) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns the (row) vector result of premultiplying this by the vector v.
probability(double, double) - Method in class org.apache.commons.math4.legacy.distribution.AbstractRealDistribution: For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
probability(int) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedIntegerDistribution
probability(int, int) - Method in class org.apache.commons.math4.legacy.distribution.AbstractIntegerDistribution: The default implementation uses the identity
ProcessModel - Interface in org.apache.commons.math4.legacy.filter: Defines the process dynamics model for the use with a KalmanFilter.
product(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the product of the entries in the input array, or Double.NaN if the array is empty.
product(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the product of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
Product - Class in org.apache.commons.math4.legacy.stat.descriptive.summary: Returns the product of the available values.
Product() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Create a Product instance.
Product(Product) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.summary.Product: Copy constructor, creates a new Product identical to the original.
projection(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Find the orthogonal projection of this vector onto another vector.
projection(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Find the orthogonal projection of this vector onto another vector.
projection(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Find the orthogonal projection of this vector onto another vector.
projection(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Find the orthogonal projection of this vector onto another vector.
projection(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Find the orthogonal projection of this vector onto another vector.
providesResidual() - Method in class org.apache.commons.math4.legacy.linear.DefaultIterativeLinearSolverEvent: Returns true if IterativeLinearSolverEvent.getResidual() is supported.
providesResidual() - Method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolverEvent: Returns true if IterativeLinearSolverEvent.getResidual() is supported.
PSquarePercentile - Class in org.apache.commons.math4.legacy.stat.descriptive.rank: A StorelessUnivariateStatistic estimating percentiles using the P² Algorithm as explained by Raj Jain and Imrich Chlamtac in P² Algorithm for Dynamic Calculation of Quantiles and Histogram Without Storing Observations.
PSquarePercentile(double) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Constructs a PSquarePercentile with the specific percentile value.

Q

QR - org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer.Decomposition: Solve the linear least squares problem (Jx=r) using the QRDecomposition.
QRDecomposition - Class in org.apache.commons.math4.legacy.linear: Calculates the QR-decomposition of a matrix.
QRDecomposition(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.linear.QRDecomposition: Calculates the QR-decomposition of the given matrix.
QRDecomposition(RealMatrix, double) - Constructor for class org.apache.commons.math4.legacy.linear.QRDecomposition: Calculates the QR-decomposition of the given matrix.
quantile() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Returns the quantile estimated by this statistic in the range [0.0-1.0].

R

R_1 - org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: The method R_1 has the following formulae for index and estimates.
\( \begin{align} &index= Np + 1/2\, \\ &estimate= x_{\lceil h\,-\,1/2 \rceil} \\ &minLimit = 0 \\ \end{align}\)
R_2 - org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: The method R_2 has the following formulae for index and estimates.
\( \begin{align} &index= Np + 1/2\, \\ &estimate=\frac{x_{\lceil h\,-\,1/2 \rceil} + x_{\lfloor h\,+\,1/2 \rfloor}}{2} \\ &minLimit = 0 \\ &maxLimit = 1 \\ \end{align}\)
R_3 - org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: The method R_3 has the following formulae for index and estimates.
\( \begin{align} &index= Np \\ &estimate= x_{\lfloor h \rceil}\, \\ &minLimit = 0.5/N \\ \end{align}\)
R_4 - org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: The method R_4 has the following formulae for index and estimates.
\( \begin{align} &index= Np\, \\ &estimate= x_{\lfloor h \rfloor} + (h - \lfloor h \rfloor) (x_{\lfloor h \rfloor + 1} - x_{\lfloor h \rfloor}) \\ &minLimit = 1/N \\ &maxLimit = 1 \\ \end{align}\)
R_5 - org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: The method R_5 has the following formulae for index and estimates.
\( \begin{align} &index= Np + 1/2\\ &estimate= x_{\lfloor h \rfloor} + (h - \lfloor h \rfloor) (x_{\lfloor h \rfloor + 1} - x_{\lfloor h \rfloor}) \\ &minLimit = 0.5/N \\ &maxLimit = (N-0.5)/N \end{align}\)
R_6 - org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: The method R_6 has the following formulae for index and estimates.
\( \begin{align} &index= (N + 1)p \\ &estimate= x_{\lfloor h \rfloor} + (h - \lfloor h \rfloor) (x_{\lfloor h \rfloor + 1} - x_{\lfloor h \rfloor}) \\ &minLimit = 1/(N+1) \\ &maxLimit = N/(N+1) \\ \end{align}\)
R_7 - org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: The method R_7 implements Microsoft Excel style computation has the following formulae for index and estimates.
\( \begin{align} &index = (N-1)p + 1 \\ &estimate = x_{\lfloor h \rfloor} + (h - \lfloor h \rfloor) (x_{\lfloor h \rfloor + 1} - x_{\lfloor h \rfloor}) \\ &minLimit = 0 \\ &maxLimit = 1 \\ \end{align}\) The formula to evaluate weighted percentiles is as following.
\( \begin{align} &S_k = (k-1)w_k + (n-1)\sum_{i=1}^{k-1}w_i &Then find k s.t.
R_8 - org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: The method R_8 has the following formulae for index and estimates.
\( \begin{align} &index = (N + 1/3)p + 1/3 \\ &estimate = x_{\lfloor h \rfloor} + (h - \lfloor h \rfloor) (x_{\lfloor h \rfloor + 1} - x_{\lfloor h \rfloor}) \\ &minLimit = (2/3)/(N+1/3) \\ &maxLimit = (N-1/3)/(N+1/3) \\ \end{align}\)
R_9 - org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: The method R_9 has the following formulae for index and estimates.
\( \begin{align} &index = (N + 1/4)p + 3/8\\ &estimate = x_{\lfloor h \rfloor} + (h - \lfloor h \rfloor) (x_{\lfloor h \rfloor + 1} - x_{\lfloor h \rfloor}) \\ &minLimit = (5/8)/(N+1/4) \\ &maxLimit = (N-3/8)/(N+1/4) \\ \end{align}\)
RANDOM - org.apache.commons.math4.legacy.stat.ranking.TiesStrategy: Ties get a random integral value from among applicable ranks.
randomBinaryRepresentation(int) - Static method in class org.apache.commons.math4.legacy.genetics.BinaryChromosome: Returns a representation of a random binary array of length length.
RandomKey<T> - Class in org.apache.commons.math4.legacy.genetics: Random Key chromosome is used for permutation representation.
RandomKey(Double[]) - Constructor for class org.apache.commons.math4.legacy.genetics.RandomKey: Constructor.
RandomKey(List<Double>) - Constructor for class org.apache.commons.math4.legacy.genetics.RandomKey: Constructor.
RandomKeyMutation - Class in org.apache.commons.math4.legacy.genetics: Mutation operator for RandomKeys.
RandomKeyMutation() - Constructor for class org.apache.commons.math4.legacy.genetics.RandomKeyMutation
randomPermutation(int) - Static method in class org.apache.commons.math4.legacy.genetics.RandomKey: Generates a representation corresponding to a random permutation of length l which can be passed to the RandomKey constructor.
RandomPivotingStrategy - Class in org.apache.commons.math4.legacy.stat.descriptive.rank: A strategy of selecting random index between begin and end indices.
RandomPivotingStrategy(RandomSource, long) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.rank.RandomPivotingStrategy: Simple constructor.
rank(double[]) - Method in class org.apache.commons.math4.legacy.stat.ranking.NaturalRanking: Rank data using the natural ordering on Doubles, with NaN values handled according to nanStrategy and ties resolved using tiesStrategy.
rank(double[]) - Method in interface org.apache.commons.math4.legacy.stat.ranking.RankingAlgorithm: Performs a rank transformation on the input data, returning an array of ranks.
ranking(ClusterEvaluator) - Static method in interface org.apache.commons.math4.legacy.ml.clustering.ClusterEvaluator: Converts to a ranking function (as required by clustering implementations).
RankingAlgorithm - Interface in org.apache.commons.math4.legacy.stat.ranking: Interface representing a rank transformation.
readBaseExternal(ObjectInput) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Read the base state of the instance.
readExternal(ObjectInput) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator
readExternal(ObjectInput) - Method in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator
RealFieldUnivariateFunction<T extends RealFieldElement<T>> - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a univariate real function.
RealLinearOperator - Class in org.apache.commons.math4.legacy.linear: This class defines a linear operator operating on real (double) vector spaces.
RealLinearOperator() - Constructor for class org.apache.commons.math4.legacy.linear.RealLinearOperator
RealMatrix - Interface in org.apache.commons.math4.legacy.linear: Interface defining a real-valued matrix with basic algebraic operations.
RealMatrixChangingVisitor - Interface in org.apache.commons.math4.legacy.linear: Interface defining a visitor for matrix entries.
RealMatrixFormat - Class in org.apache.commons.math4.legacy.linear: Formats a nxm matrix in components list format "{{a₀₀,a₀₁, ..., a₀_m-1},{a₁₀, a₁₁, ..., a₁_m-1},{...},{ a_n-1₀, a_n-1₁, ..., a_n-1_m-1}}".
RealMatrixFormat() - Constructor for class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Create an instance with default settings.
RealMatrixFormat(String, String, String, String, String, String) - Constructor for class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Create an instance with custom prefix, suffix and separator.
RealMatrixFormat(String, String, String, String, String, String, NumberFormat) - Constructor for class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Create an instance with custom prefix, suffix, separator and format for components.
RealMatrixFormat(NumberFormat) - Constructor for class org.apache.commons.math4.legacy.linear.RealMatrixFormat: Create an instance with a custom number format for components.
RealMatrixPreservingVisitor - Interface in org.apache.commons.math4.legacy.linear: Interface defining a visitor for matrix entries.
RealVector - Class in org.apache.commons.math4.legacy.linear: Class defining a real-valued vector with basic algebraic operations.
RealVector() - Constructor for class org.apache.commons.math4.legacy.linear.RealVector
RealVector.Entry - Class in org.apache.commons.math4.legacy.linear: An entry in the vector.
RealVector.SparseEntryIterator - Class in org.apache.commons.math4.legacy.linear: This class should rarely be used, but is here to provide a default implementation of sparseIterator(), which is implemented by walking over the entries, skipping those that are zero.
RealVectorChangingVisitor - Interface in org.apache.commons.math4.legacy.linear: This interface defines a visitor for the entries of a vector.
RealVectorFormat - Class in org.apache.commons.math4.legacy.linear: Formats a vector in components list format "{v0; v1; ...; vk-1}".
RealVectorFormat() - Constructor for class org.apache.commons.math4.legacy.linear.RealVectorFormat: Create an instance with default settings.
RealVectorFormat(String, String, String) - Constructor for class org.apache.commons.math4.legacy.linear.RealVectorFormat: Create an instance with custom prefix, suffix and separator.
RealVectorFormat(String, String, String, NumberFormat) - Constructor for class org.apache.commons.math4.legacy.linear.RealVectorFormat: Create an instance with custom prefix, suffix, separator and format for components.
RealVectorFormat(NumberFormat) - Constructor for class org.apache.commons.math4.legacy.linear.RealVectorFormat: Create an instance with a custom number format for components.
RealVectorPreservingVisitor - Interface in org.apache.commons.math4.legacy.linear: This interface defines a visitor for the entries of a vector.
reciprocal() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
reciprocal() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
reciprocal() - Method in class org.apache.commons.math4.legacy.linear.BigReal
RectangularCholeskyDecomposition - Class in org.apache.commons.math4.legacy.linear: Calculates the rectangular Cholesky decomposition of a matrix.
RectangularCholeskyDecomposition(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.linear.RectangularCholeskyDecomposition: Decompose a symmetric positive semidefinite matrix.
RectangularCholeskyDecomposition(RealMatrix, double) - Constructor for class org.apache.commons.math4.legacy.linear.RectangularCholeskyDecomposition: Decompose a symmetric positive semidefinite matrix.
registerVariationalEquations(ExpandableStatefulODE) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Register the variational equations for the Jacobians matrices to the expandable set.
regress() - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Conducts a regression on the data in the model, using all regressors.
regress() - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Performs a regression on data present in buffers and outputs a RegressionResults object.
regress() - Method in interface org.apache.commons.math4.legacy.stat.regression.UpdatingMultipleLinearRegression: Performs a regression on data present in buffers and outputs a RegressionResults object.
regress(int) - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Conducts a regression on the data in the model, using a subset of regressors.
regress(int[]) - Method in class org.apache.commons.math4.legacy.stat.regression.MillerUpdatingRegression: Conducts a regression on the data in the model, using regressors in array Calling this method will change the internal order of the regressors and care is required in interpreting the hatmatrix.
regress(int[]) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Performs a regression on data present in buffers including only regressors.
regress(int[]) - Method in interface org.apache.commons.math4.legacy.stat.regression.UpdatingMultipleLinearRegression: Performs a regression on data present in buffers including only regressors.
RegressionResults - Class in org.apache.commons.math4.legacy.stat.regression: Results of a Multiple Linear Regression model fit.
RegressionResults(double[], double[][], boolean, long, int, double, double, double, boolean, boolean) - Constructor for class org.apache.commons.math4.legacy.stat.regression.RegressionResults: Constructor for Regression Results.
REGULA_FALSI - org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver.Method: The Regula Falsi or False Position method.
RegulaFalsiSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Implements the Regula Falsi or False position method for root-finding (approximating a zero of a univariate real function).
RegulaFalsiSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.RegulaFalsiSolver: Construct a solver with default accuracy (1e-6).
RegulaFalsiSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.RegulaFalsiSolver: Construct a solver.
RegulaFalsiSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.RegulaFalsiSolver: Construct a solver.
RegulaFalsiSolver(double, double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.RegulaFalsiSolver: Construct a solver.
reinitialize(double[], boolean, EquationsMapper, EquationsMapper[]) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Reinitialize the instance.
reinitialize(double[], boolean, EquationsMapper, EquationsMapper[]) - Method in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: Reinitialize the instance.
reinitialize(double, double, double[], Array2DRowRealMatrix) - Method in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: Reinitialize the instance.
reinitializeBegin(FieldStepInterpolator<T>) - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Reinitialize the beginning of the step.
reinitializeBegin(StepInterpolator) - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Reinitialize the beginning of the step.
Relationship - Enum in org.apache.commons.math4.legacy.optim.linear: Types of relationships between two cells in a Solver LinearConstraint.
remainder(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
remainder(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
remainder(double[], int, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Perform remainder of two derivative structures.
remainder(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
remainder(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
remove() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector.OpenMapSparseIterator
remove() - Method in class org.apache.commons.math4.legacy.linear.RealVector.SparseEntryIterator
REMOVED - org.apache.commons.math4.legacy.stat.ranking.NaNStrategy: NaNs are removed before computing ranks.
removeData(double[][]) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Removes observations represented by the elements in data.
removeData(double, double) - Method in class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Removes the observation (x,y) from the regression data set.
removeIterationListener(IterationListener) - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Removes the specified iteration listener from the list of listeners currently attached to this object.
removeMostRecentValue() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Removes the most recent value from the dataset.
replaceMostRecentValue(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Replaces the most recently stored value with the given value.
rescale(double) - Method in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: Rescale the instance.
rescale(T) - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Rescale the instance.
reset(double, double[]) - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Let the event handler reset the state if it wants.
reset(FieldODEStateAndDerivative<T>) - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Let the event handler reset the state if it wants.
RESET_DERIVATIVES - org.apache.commons.math4.legacy.ode.events.Action: Reset derivatives indicator.
RESET_DERIVATIVES - org.apache.commons.math4.legacy.ode.events.EventHandler.Action: Reset derivatives indicator.
RESET_STATE - org.apache.commons.math4.legacy.ode.events.Action: Reset state indicator.
RESET_STATE - org.apache.commons.math4.legacy.ode.events.EventHandler.Action: Reset state indicator.
resetInternalState() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Reset internal state to dummy values.
resetInternalState() - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Reset internal state to dummy values.
resetIterationCount() - Method in class org.apache.commons.math4.legacy.linear.IterationManager: Sets the iteration count to 0.
resetOccurred - Variable in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Indicator that a state or derivative reset was triggered by some event.
resetOccurred() - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Check if a reset occurred while last step was accepted.
resetState(double, double[]) - Method in class org.apache.commons.math4.legacy.ode.events.EventFilter: Reset the state prior to continue the integration.
resetState(double, double[]) - Method in interface org.apache.commons.math4.legacy.ode.events.EventHandler: Reset the state prior to continue the integration.
resetState(FieldODEStateAndDerivative<T>) - Method in interface org.apache.commons.math4.legacy.ode.events.FieldEventHandler: Reset the state prior to continue the integration.
restrictStep(FieldODEStateAndDerivative<T>, FieldODEStateAndDerivative<T>) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractFieldStepInterpolator: Create a new restricted version of the instance.
RiddersSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Implements the Ridders' Method for root finding of real univariate functions.
RiddersSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.RiddersSolver: Construct a solver with default accuracy (1e-6).
RiddersSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.RiddersSolver: Construct a solver.
RiddersSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.RiddersSolver: Construct a solver.
RIGHT_SIDE - org.apache.commons.math4.legacy.analysis.solvers.AllowedSolution: Only solutions that are greater than or equal to the actual root are acceptable as solutions for root-finding.
rint() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
rint() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
Rint - Class in org.apache.commons.math4.legacy.analysis.function: rint function.
Rint() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Rint
rjBesl(double, double, int) - Static method in class org.apache.commons.math4.legacy.special.BesselJ: Calculates Bessel functions \(J_{n+alpha}(x)\) for non-negative argument x, and non-negative order n + alpha.
ROMBERG_MAX_ITERATIONS_COUNT - Static variable in class org.apache.commons.math4.legacy.analysis.integration.RombergIntegrator: Maximal number of iterations for Romberg.
RombergIntegrator - Class in org.apache.commons.math4.legacy.analysis.integration: Implements the Romberg Algorithm for integration of real univariate functions.
RombergIntegrator() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.RombergIntegrator: Construct a Romberg integrator with default settings (max iteration count set to RombergIntegrator.ROMBERG_MAX_ITERATIONS_COUNT).
RombergIntegrator(double, double, int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.RombergIntegrator: Build a Romberg integrator with given accuracies and iterations counts.
RombergIntegrator(int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.RombergIntegrator: Build a Romberg integrator with given iteration counts.
rootLogLikelihoodRatio(long, long, long, long) - Method in class org.apache.commons.math4.legacy.stat.inference.GTest: Calculates the root log-likelihood ratio for 2 state Datasets.
rootLogLikelihoodRatio(long, long, long, long) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
rootN(double[], int, int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute n^th root of a derivative structure.
rootN(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
rootN(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
round() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
round() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
RRQRDecomposition - Class in org.apache.commons.math4.legacy.linear: Calculates the rank-revealing QR-decomposition of a matrix, with column pivoting.
RRQRDecomposition(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.linear.RRQRDecomposition: Calculates the QR-decomposition of the given matrix.
RRQRDecomposition(RealMatrix, double) - Constructor for class org.apache.commons.math4.legacy.linear.RRQRDecomposition: Calculates the QR-decomposition of the given matrix.
RungeKuttaFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the common part of all fixed step Runge-Kutta integrators for Ordinary Differential Equations.
RungeKuttaFieldIntegrator(Field<T>, String, T) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.RungeKuttaFieldIntegrator: Simple constructor.
RungeKuttaIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the common part of all fixed step Runge-Kutta integrators for Ordinary Differential Equations.
RungeKuttaIntegrator(String, double[], double[][], double[], RungeKuttaStepInterpolator, double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.RungeKuttaIntegrator: Simple constructor.

S

sample() - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedDistribution.Sampler: Generates a random value sampled from this distribution.
sample() - Method in interface org.apache.commons.math4.legacy.distribution.MultivariateRealDistribution.Sampler: Generates a random value vector sampled from this distribution.
sample(int) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedDistribution.Sampler: Generates a random sample from the distribution.
sample(int, MultivariateRealDistribution.Sampler) - Static method in class org.apache.commons.math4.legacy.distribution.AbstractMultivariateRealDistribution: Utility function for creating n vectors generated by the given sampler.
sample(int, ContinuousDistribution.Sampler) - Static method in class org.apache.commons.math4.legacy.distribution.AbstractRealDistribution: Utility function for allocating an array and filling it with n samples generated by the given sampler.
sample(int, DiscreteDistribution.Sampler) - Static method in class org.apache.commons.math4.legacy.distribution.AbstractIntegerDistribution: Utility function for allocating an array and filling it with n samples generated by the given sampler.
sample(int, T[]) - Method in class org.apache.commons.math4.legacy.distribution.EnumeratedDistribution.Sampler: Generates a random sample from the distribution.
sanityChecks(ExpandableStatefulODE, double) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Check the integration span.
sanityChecks(ExpandableStatefulODE, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Check the integration span.
sanityChecks(FieldODEState<T>, T) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Check the integration span.
sanityChecks(FieldODEState<T>, T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Check the integration span.
scalAbsoluteTolerance - Variable in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Allowed absolute scalar error.
scalAbsoluteTolerance - Variable in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Allowed absolute scalar error.
scalarAdd(double) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the result of adding d to each entry of this.
scalarAdd(double) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the result of adding d to each entry of this.
scalarAdd(double) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the result of adding d to each entry of this.
scalarAdd(T) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Increment each entry of this matrix.
scalarAdd(T) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Increment each entry of this matrix.
scalarAdd(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Increment each entry of this matrix.
scalarMultiply(double) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the result of multiplying each entry of this by d.
scalarMultiply(double) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the result of multiplying each entry of this by d.
scalarMultiply(double) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the result of multiplying each entry of this by d.
scalarMultiply(T) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Multiply each entry by d.
scalarMultiply(T) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Multiply each entry by d.
scalarMultiply(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Multiply each entry by d.
scalb(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
scalb(int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
scaled - Variable in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: First scaled derivative (h y').
scaled - Variable in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: First scaled derivative (h y').
scalRelativeTolerance - Variable in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Allowed relative scalar error.
scalRelativeTolerance - Variable in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Allowed relative scalar error.
score(List<? extends Cluster<? extends Clusterable>>) - Method in interface org.apache.commons.math4.legacy.ml.clustering.ClusterEvaluator
score(List<? extends Cluster<? extends Clusterable>>) - Method in class org.apache.commons.math4.legacy.ml.clustering.evaluation.CalinskiHarabasz
score(List<? extends Cluster<? extends Clusterable>>) - Method in class org.apache.commons.math4.legacy.ml.clustering.evaluation.SumOfClusterVariances
scramble(int, int, int, int) - Method in class org.apache.commons.math4.legacy.random.HaltonSequenceGenerator: Performs scrambling of digit d_j according to the formula:
search(double[], double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.LineSearch: Deprecated.

Finds the number alpha that optimizes f(startPoint + alpha * direction).
search(UnivariateFunction, GoalType, double, double) - Method in class org.apache.commons.math4.legacy.optim.univariate.BracketFinder: Search new points that bracket a local optimum of the function.
searchForFitnessUpdate(Population) - Method in class org.apache.commons.math4.legacy.genetics.Chromosome: Searches the population for a chromosome representing the same solution, and if it finds one, updates the fitness to its value.
SearchInterval - Class in org.apache.commons.math4.legacy.optim.univariate: Search interval and (optional) start value.
SearchInterval(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.SearchInterval
SearchInterval(double, double, double) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.SearchInterval
SecantSolver - Class in org.apache.commons.math4.legacy.analysis.solvers: Implements the Secant method for root-finding (approximating a zero of a univariate real function).
SecantSolver() - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.SecantSolver: Construct a solver with default accuracy (1e-6).
SecantSolver(double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.SecantSolver: Construct a solver.
SecantSolver(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.solvers.SecantSolver: Construct a solver.
SecondaryEquations - Interface in org.apache.commons.math4.legacy.ode: This interface allows users to add secondary differential equations to a primary set of differential equations.
SecondMoment - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Computes a statistic related to the Second Central Moment.
SecondMoment() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: Create a SecondMoment instance.
SecondMoment(SecondMoment) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.SecondMoment: Copy constructor, creates a new SecondMoment identical to the original.
SecondOrderDifferentialEquations - Interface in org.apache.commons.math4.legacy.ode: This interface represents a second order differential equations set.
SecondOrderIntegrator - Interface in org.apache.commons.math4.legacy.ode: This interface represents a second order integrator for differential equations.
select(double[], int[], int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.KthSelector: Select K^th value in the array.
select(Population) - Method in interface org.apache.commons.math4.legacy.genetics.SelectionPolicy: Select two chromosomes from the population.
select(Population) - Method in class org.apache.commons.math4.legacy.genetics.TournamentSelection: Select two chromosomes from the population.
SelectionPolicy - Interface in org.apache.commons.math4.legacy.genetics: Algorithm used to select a chromosome pair from a population.
selectTransformer(Transformer, double, boolean) - Method in enum org.apache.commons.math4.legacy.ode.events.FilterType: Get next function transformer in the specified direction.
SemiVariance - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Computes the semivariance of a set of values with respect to a given cutoff value.
SemiVariance() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Constructs a SemiVariance with default (true) biasCorrected property and default (Downside) varianceDirection property.
SemiVariance(boolean) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Constructs a SemiVariance with the specified biasCorrected property and default (Downside) varianceDirection property.
SemiVariance(boolean, SemiVariance.Direction) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Constructs a SemiVariance with the specified isBiasCorrected property and the specified Direction property.
SemiVariance(SemiVariance) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Copy constructor, creates a new SemiVariance identical to the original.
SemiVariance(SemiVariance.Direction) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Constructs a SemiVariance with the specified Direction property.
SemiVariance.Direction - Enum in org.apache.commons.math4.legacy.stat.descriptive.moment: The direction of the semivariance - either upside or downside.
SEQUENTIAL - org.apache.commons.math4.legacy.stat.ranking.TiesStrategy: Ties assigned sequential ranks in order of occurrence.
serializeRealMatrix(RealMatrix, ObjectOutputStream) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Serialize a RealMatrix.
serializeRealVector(RealVector, ObjectOutputStream) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Serialize a RealVector.
set(double) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Set all elements to a single value.
set(double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Set all elements to a single value.
set(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Set all elements to a single value.
set(int, int, T) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Sets an element.
set(int, ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Set a set of consecutive elements.
set(T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Set all elements to a single value.
set(T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Set all elements to a single value.
set(T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Set all elements to a single value.
setArity(int) - Method in class org.apache.commons.math4.legacy.genetics.TournamentSelection: Sets the arity (number of chromosomes drawn to the tournament).
setBiasCorrected(boolean) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Sets the biasCorrected property.
setBiasCorrected(boolean) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation
setBiasCorrected(boolean) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance
setColumn(int, double[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Sets the specified column of this matrix to the entries of the specified array.
setColumn(int, double[]) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Sets the specified column of this matrix to the entries of the specified array.
setColumn(int, double[]) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Sets the specified column of this matrix to the entries of the specified array.
setColumn(int, T[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Set the entries in column number column as a column matrix.
setColumn(int, T[]) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Set the entries in column number column as a column matrix.
setColumn(int, T[]) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Set the entries in column number column as a column matrix.
setColumnMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Set the entries in column number column as a column matrix.
setColumnMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Set the entries in column number column as a column matrix.
setColumnMatrix(int, FieldMatrix<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Set the entries in column number column as a column matrix.
setColumnMatrix(int, RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Sets the specified column of this matrix to the entries of the specified column matrix.
setColumnMatrix(int, RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Sets the specified column of this matrix to the entries of the specified column matrix.
setColumnMatrix(int, RealMatrix) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Sets the specified column of this matrix to the entries of the specified column matrix.
setColumnVector(int, FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Set the entries in column number column as a vector.
setColumnVector(int, FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Set the entries in column number column as a vector.
setColumnVector(int, FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Set the entries in column number column as a vector.
setColumnVector(int, RealVector) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Sets the specified column of this matrix to the entries of the specified vector.
setColumnVector(int, RealVector) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Sets the specified column of this matrix to the entries of the specified vector.
setColumnVector(int, RealVector) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Sets the specified column of this matrix to the entries of the specified vector.
setCompleteState(double[]) - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Set the complete current state.
setControlFactors(double, double, double, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Set the step size control factors.
setData(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Set the data array.
setData(double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Set the data array.
setData(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Set the data array.
setData(double[], double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Set the data and weights arrays.
setData(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.AbstractUnivariateStatistic: Set the data array.
setData(double[], int, int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Set the data array.
setElitismRate(double) - Method in class org.apache.commons.math4.legacy.genetics.ElitisticListPopulation: Sets the elitism rate, i.e.
setEntry(int, double) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Set a single element.
setEntry(int, double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Set a single element.
setEntry(int, double) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Set a single element.
setEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Set the entry in the specified row and column.
setEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Set the entry in the specified row and column.
setEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Set the entry in the specified row and column.
setEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Set the entry in the specified row and column.
setEntry(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Set the entry in the specified row and column.
setEntry(int, int, double) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Set the entry in the specified row and column.
setEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Set the entry in the specified row and column.
setEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Set the entry in the specified row and column.
setEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Set the entry in the specified row and column.
setEntry(int, int, T) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Set the entry in the specified row and column.
setEntry(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Set the entry in the specified row and column.
setEntry(int, T) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Set a single element.
setEntry(int, T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Set a single element.
setEntry(int, T) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Set a single element.
setEquations(ExpandableStatefulODE) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Set the equations.
setExpandable(ExpandableStatefulODE) - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Set the equation.
setGeoMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Sets the implementation for the geometric mean.
setGeoMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Sets the implementation for the geometric mean.
setGeoMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Sets the implementation for the geometric mean.
setGeoMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Sets the implementation for the geometric mean.
setGeometricMeanImpl(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Sets the implementation for the geometric mean.
setIndex(int) - Method in class org.apache.commons.math4.legacy.linear.RealVector.Entry: Set the index of the entry.
setInitialMainStateJacobian(double[][]) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Set the initial value of the Jacobian matrix with respect to state.
setInitialParameterJacobian(String, double[]) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Set the initial value of a column of the Jacobian matrix with respect to one parameter.
setInitialStepSize(double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Set the initial step size.
setInitialStepSize(T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Set the initial step size.
setInterpolatedTime(double) - Method in class org.apache.commons.math4.legacy.ode.ContinuousOutputModel: Set the time of the interpolated point.
setInterpolatedTime(double) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Set the time of the interpolated point.
setInterpolatedTime(double) - Method in interface org.apache.commons.math4.legacy.ode.sampling.StepInterpolator: Set the time of the interpolated point.
setInterpolationControl(boolean, int) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Set the interpolation order control parameter.
setIsLastStep(boolean) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Set the last state flag.
setKurtosisImpl(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Sets the implementation for the kurtosis.
setMaxEvaluations(int) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Set the maximal number of differential equations function evaluations.
setMaxEvaluations(int) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Set the maximal number of differential equations function evaluations.
setMaxEvaluations(int) - Method in interface org.apache.commons.math4.legacy.ode.FirstOrderFieldIntegrator: Set the maximal number of differential equations function evaluations.
setMaxEvaluations(int) - Method in interface org.apache.commons.math4.legacy.ode.ODEIntegrator: Set the maximal number of differential equations function evaluations.
setMaxGrowth(double) - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Set the maximal growth factor for stepsize control.
setMaxGrowth(double) - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Set the maximal growth factor for stepsize control.
setMaxGrowth(double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Set the maximal growth factor for stepsize control.
setMaxGrowth(T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Set the maximal growth factor for stepsize control.
setMaxImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Sets the implementation for the maximum.
setMaxImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Sets the implementation for the maximum.
setMaxImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Sets the implementation for the maximum.
setMaxImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Sets the implementation for the maximum.
setMaxImpl(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Sets the implementation for the maximum.
setMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Sets the implementation for the mean.
setMeanImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Sets the implementation for the mean.
setMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Sets the implementation for the mean.
setMeanImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Sets the implementation for the mean.
setMeanImpl(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Sets the implementation for the mean.
setMinImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Sets the implementation for the minimum.
setMinImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Sets the implementation for the minimum.
setMinImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Sets the implementation for the minimum.
setMinImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Sets the implementation for the minimum.
setMinImpl(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Sets the implementation for the minimum.
setMinReduction(double) - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Set the minimal reduction factor for stepsize control.
setMinReduction(double) - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Set the minimal reduction factor for stepsize control.
setMinReduction(double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Set the minimal reduction factor for stepsize control.
setMinReduction(T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Set the minimal reduction factor for stepsize control.
setNoIntercept(boolean) - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression
setOrderControl(int, double, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Set the order control parameters.
setParameter(String, double) - Method in interface org.apache.commons.math4.legacy.ode.ParameterizedODE: Set the value for a given parameter.
setParameterizedODE(ParameterizedODE) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Set a parameter Jacobian provider.
setParameterStep(String, double) - Method in class org.apache.commons.math4.legacy.ode.JacobianMatrices: Set the step associated to a parameter in order to compute by finite difference the Jacobian matrix.
setPercentileImpl(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Sets the implementation to be used by DescriptiveStatistics.getPercentile(double).
setPopulationLimit(int) - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation: Sets the maximal population size.
setPrimaryState(double[]) - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Set primary part of the current state.
setQuantile(double) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Sets the value of the quantile field (determines what percentile is computed when evaluate() is called with no quantile argument).
setRandomGenerator(UniformRandomProvider) - Static method in class org.apache.commons.math4.legacy.genetics.GeneticAlgorithm: Set the (static) random generator.
setRoundingMode(RoundingMode) - Method in class org.apache.commons.math4.legacy.linear.BigReal: Sets the rounding mode for decimal divisions.
setRow(int, double[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Sets the specified row of this matrix to the entries of the specified array.
setRow(int, double[]) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Sets the specified row of this matrix to the entries of the specified array.
setRow(int, double[]) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Sets the specified row of this matrix to the entries of the specified array.
setRow(int, double[]) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Sets the specified row of this matrix to the entries of the specified array.
setRow(int, T[]) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Set the entries in row number row as a row matrix.
setRow(int, T[]) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Set the entries in row number row as a row matrix.
setRow(int, T[]) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Set the entries in row number row as a row matrix.
setRowMatrix(int, BlockFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Sets the entries in row number row as a row matrix.
setRowMatrix(int, BlockRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Sets the entries in row number row as a row matrix.
setRowMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Set the entries in row number row as a row matrix.
setRowMatrix(int, FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Set the entries in row number row as a row matrix.
setRowMatrix(int, FieldMatrix<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Set the entries in row number row as a row matrix.
setRowMatrix(int, RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Sets the specified row of this matrix to the entries of the specified row matrix.
setRowMatrix(int, RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Sets the specified row of this matrix to the entries of the specified row matrix.
setRowMatrix(int, RealMatrix) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Sets the specified row of this matrix to the entries of the specified row matrix.
setRowVector(int, FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Set the entries in row number row as a vector.
setRowVector(int, FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Set the entries in row number row as a vector.
setRowVector(int, FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Set the entries in row number row as a vector.
setRowVector(int, RealVector) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Sets the specified row of this matrix to the entries of the specified vector.
setRowVector(int, RealVector) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Sets the specified row of this matrix to the entries of the specified vector.
setRowVector(int, RealVector) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Sets the specified row of this matrix to the entries of the specified vector.
setSafety(double) - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Set the safety factor for stepsize control.
setSafety(double) - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Set the safety factor for stepsize control.
setSafety(double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaIntegrator: Set the safety factor for stepsize control.
setSafety(T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.EmbeddedRungeKuttaFieldIntegrator: Set the safety factor for stepsize control.
setScale(int) - Method in class org.apache.commons.math4.legacy.linear.BigReal: Sets the scale for division operations.
setSecondaryState(int, double[]) - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Set secondary part of the current state.
setSkewnessImpl(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Sets the implementation for the skewness.
setSoftCurrentTime(double) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Restrict step range to a limited part of the global step.
setSoftPreviousTime(double) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Restrict step range to a limited part of the global step.
setStabilityCheck(boolean, int, int, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.GraggBulirschStoerIntegrator: Set the stability check controls.
setStarterIntegrator(FirstOrderFieldIntegrator<T>) - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Set the starter integrator.
setStarterIntegrator(FirstOrderIntegrator) - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Set the starter integrator.
setStateInitialized(boolean) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Set the stateInitialized flag.
setStateInitialized(boolean) - Method in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Set the stateInitialized flag.
setStepSize(T) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Set the current step size.
setStepSizeControl(double, double, double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Set the adaptive step size control parameters.
setStepSizeControl(double, double, double[], double[]) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Set the adaptive step size control parameters.
setStepSizeControl(double, double, double, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Set the adaptive step size control parameters.
setStepSizeControl(double, double, double, double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Set the adaptive step size control parameters.
setStepStart(FieldODEStateAndDerivative<T>) - Method in class org.apache.commons.math4.legacy.ode.AbstractFieldIntegrator: Set current step start.
setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Replace the submatrix starting at row, column using data in the input subMatrix array.
setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Replace the submatrix starting at row, column using data in the input subMatrix array.
setSubMatrix(double[][], int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Replace the submatrix starting at row, column using data in the input subMatrix array.
setSubMatrix(double[][], int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Replace the submatrix starting at row, column using data in the input subMatrix array.
setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Replace the submatrix starting at (row, column) using data in the input subMatrix array.
setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Replace the submatrix starting at (row, column) using data in the input subMatrix array.
setSubMatrix(T[][], int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Replace the submatrix starting at (row, column) using data in the input subMatrix array.
setSubMatrix(T[][], int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Replace the submatrix starting at (row, column) using data in the input subMatrix array.
setSubVector(int, double[]) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Set a set of consecutive elements.
setSubVector(int, FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Set a set of consecutive elements.
setSubVector(int, FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Set a set of consecutive elements.
setSubVector(int, FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Set a set of consecutive elements.
setSubVector(int, RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Set a sequence of consecutive elements.
setSubVector(int, RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Set a sequence of consecutive elements.
setSubVector(int, RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Set a sequence of consecutive elements.
setSumImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Sets the implementation for the Sum.
setSumImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Sets the implementation for the Sum.
setSumImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Sets the implementation for the Sum.
setSumImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Sets the implementation for the Sum.
setSumImpl(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Sets the implementation for the sum.
setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.GeometricMean: Sets the implementation for the sum of logs.
setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Sets the implementation for the sum of logs.
setSumLogImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Sets the implementation for the sum of logs.
setSumLogImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Sets the implementation for the sum of logs.
setSumLogImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Sets the implementation for the sum of logs.
setSumsqImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Sets the implementation for the sum of squares.
setSumsqImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Sets the implementation for the sum of squares.
setSumsqImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Sets the implementation for the sum of squares.
setSumsqImpl(StorelessUnivariateStatistic[]) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Sets the implementation for the sum of squares.
setSumsqImpl(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Sets the implementation for the sum of squares.
setTime(double) - Method in class org.apache.commons.math4.legacy.ode.ExpandableStatefulODE: Set current time.
setup(int, FUNC, double, double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Prepare for computation.
setup(int, UnivariateDifferentiableFunction, double, double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.AbstractUnivariateDifferentiableSolver: Prepare for computation.
setup(int, PolynomialFunction, double, double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.AbstractPolynomialSolver: Prepare for computation.
setup(int, UnivariateFunction, double, double) - Method in class org.apache.commons.math4.legacy.analysis.integration.BaseAbstractUnivariateIntegrator: Prepare for computation.
setValue(double) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector.OpenMapEntry: Set the value of the entry.
setValue(double) - Method in class org.apache.commons.math4.legacy.linear.RealVector.Entry: Set the value of the entry.
setVarianceDirection(SemiVariance.Direction) - Method in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: Sets the variance direction.
setVarianceImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Sets the implementation for the variance.
setVarianceImpl(StorelessUnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Sets the implementation for the variance.
setVarianceImpl(UnivariateStatistic) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Sets the implementation for the variance.
setWindowSize(int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: WindowSize controls the number of values that contribute to the reported statistics.
setWindowSize(int) - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: WindowSize controls the number of values that contribute to the reported statistics.
shift() - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Shift one step forward.
shift(double[], double) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialsUtils: Compute the coefficients of the polynomial \(P_s(x)\) whose values at point x will be the same as the those from the original polynomial \(P(x)\) when computed at x + shift.
Sigma - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Input sigma values define the initial coordinate-wise extent for sampling the solution space around the initial guess.
Sigma(double[]) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.Sigma
Sigmoid - Class in org.apache.commons.math4.legacy.analysis.function: Sigmoid function.
Sigmoid() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Sigmoid: Usual sigmoid function, where the lower asymptote is 0 and the higher asymptote is 1.
Sigmoid(double, double) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Sigmoid: Sigmoid function.
Sigmoid.Parametric - Class in org.apache.commons.math4.legacy.analysis.function: Parametric function where the input array contains the parameters of the sigmoid function.
signum() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
signum() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
Signum - Class in org.apache.commons.math4.legacy.analysis.function: signum function.
Signum() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Signum
SimpleBounds - Class in org.apache.commons.math4.legacy.optim: Simple optimization constraints: lower and upper bounds.
SimpleBounds(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.optim.SimpleBounds
SimpleCurveFitter - Class in org.apache.commons.math4.legacy.fitting: Fits points to a user-defined function.
SimpleCurveFitter(ParametricUnivariateFunction, double[], SimpleCurveFitter.ParameterGuesser, int) - Constructor for class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter: Constructor used by the factory methods.
SimpleCurveFitter.ParameterGuesser - Class in org.apache.commons.math4.legacy.fitting: Guesses the parameters.
SimplePointChecker<PAIR extends Pair<double[],? extends Object>> - Class in org.apache.commons.math4.legacy.optim: Simple implementation of the ConvergenceChecker interface using only point coordinates.
SimplePointChecker(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.SimplePointChecker: Build an instance with specified thresholds.
SimplePointChecker(double, double, int) - Constructor for class org.apache.commons.math4.legacy.optim.SimplePointChecker: Builds an instance with specified thresholds.
SimpleRegression - Class in org.apache.commons.math4.legacy.stat.regression: Estimates an ordinary least squares regression model with one independent variable.
SimpleRegression() - Constructor for class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Create an empty SimpleRegression instance.
SimpleRegression(boolean) - Constructor for class org.apache.commons.math4.legacy.stat.regression.SimpleRegression: Create a SimpleRegression instance, specifying whether or not to estimate an intercept.
SimpleUnivariateValueChecker - Class in org.apache.commons.math4.legacy.optim.univariate: Simple implementation of the ConvergenceChecker interface that uses only objective function values.
SimpleUnivariateValueChecker(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.SimpleUnivariateValueChecker: Build an instance with specified thresholds.
SimpleUnivariateValueChecker(double, double, int) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.SimpleUnivariateValueChecker: Builds an instance with specified thresholds.
SimpleValueChecker - Class in org.apache.commons.math4.legacy.optim: Simple implementation of the ConvergenceChecker interface using only objective function values.
SimpleValueChecker(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.SimpleValueChecker: Build an instance with specified thresholds.
SimpleValueChecker(double, double, int) - Constructor for class org.apache.commons.math4.legacy.optim.SimpleValueChecker: Builds an instance with specified thresholds.
SimpleVectorValueChecker - Class in org.apache.commons.math4.legacy.optim: Simple implementation of the ConvergenceChecker interface using only objective function values.
SimpleVectorValueChecker(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.SimpleVectorValueChecker: Build an instance with specified thresholds.
SimpleVectorValueChecker(double, double, int) - Constructor for class org.apache.commons.math4.legacy.optim.SimpleVectorValueChecker: Builds an instance with specified tolerance thresholds and iteration count.
Simplex - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: Represents a simplex.
Simplex.TransformFactory - Interface in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: Generator of simplex transform.
SimplexOptimizer - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: This class implements simplex-based direct search optimization.
SimplexOptimizer(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.SimplexOptimizer
SimplexOptimizer(ConvergenceChecker<PointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.SimplexOptimizer
SimplexOptimizer.Observer - Interface in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv: Callback interface for updating caller's code with the current state of the optimization.
SimplexSolver - Class in org.apache.commons.math4.legacy.optim.linear: Solves a linear problem using the "Two-Phase Simplex" method.
SimplexSolver() - Constructor for class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Builds a simplex solver with default settings.
SimplexSolver(double) - Constructor for class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Builds a simplex solver with a specified accepted amount of error.
SimplexSolver(double, int) - Constructor for class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Builds a simplex solver with a specified accepted amount of error.
SimplexSolver(double, int, double) - Constructor for class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Builds a simplex solver with a specified accepted amount of error.
SimpsonIntegrator - Class in org.apache.commons.math4.legacy.analysis.integration: Implements Simpson's Rule for integration of real univariate functions.
SimpsonIntegrator() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.SimpsonIntegrator: Construct an integrator with default settings.
SimpsonIntegrator(double, double, int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.SimpsonIntegrator: Build a Simpson integrator with given accuracies and iterations counts.
SimpsonIntegrator(int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.SimpsonIntegrator: Build a Simpson integrator with given iteration counts.
SimulatedAnnealing - Class in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Simulated annealing setup.
SimulatedAnnealing(int, double, double, SimulatedAnnealing.CoolingSchedule, UniformRandomProvider) - Constructor for class org.apache.commons.math4.legacy.optim.nonlinear.scalar.SimulatedAnnealing
SimulatedAnnealing.CoolingSchedule - Interface in org.apache.commons.math4.legacy.optim.nonlinear.scalar: Specifies the cooling schedule.
sin() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
sin() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
sin(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute sine of a derivative structure.
Sin - Class in org.apache.commons.math4.legacy.analysis.function: Sine function.
Sin() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Sin
Sinc - Class in org.apache.commons.math4.legacy.analysis.function: Sinc function, defined by
Sinc() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Sinc: The sinc function, sin(x) / x.
Sinc(boolean) - Constructor for class org.apache.commons.math4.legacy.analysis.function.Sinc: Instantiates the sinc function.
singleStep(FirstOrderDifferentialEquations, double, double[], double) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.RungeKuttaIntegrator: Fast computation of a single step of ODE integration.
singleStep(FirstOrderFieldDifferentialEquations<T>, T, T[], T) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.RungeKuttaFieldIntegrator: Fast computation of a single step of ODE integration.
SingularMatrixException - Exception in org.apache.commons.math4.legacy.linear: Exception to be thrown when a non-singular matrix is expected.
SingularMatrixException() - Constructor for exception org.apache.commons.math4.legacy.linear.SingularMatrixException: Construct an exception.
SingularOperatorException - Exception in org.apache.commons.math4.legacy.linear: Exception to be thrown when trying to invert a singular operator.
SingularOperatorException() - Constructor for exception org.apache.commons.math4.legacy.linear.SingularOperatorException: Creates a new instance of this class.
SingularValueDecomposition - Class in org.apache.commons.math4.legacy.linear: Calculates the compact Singular Value Decomposition of a matrix.
SingularValueDecomposition(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.linear.SingularValueDecomposition: Calculates the compact Singular Value Decomposition of the given matrix.
sinh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
sinh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
sinh(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute hyperbolic sine of a derivative structure.
Sinh - Class in org.apache.commons.math4.legacy.analysis.function: Hyperbolic sine function.
Sinh() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Sinh
Skewness - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Computes the skewness of the available values.
Skewness() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Constructs a Skewness.
Skewness(Skewness) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Copy constructor, creates a new Skewness identical to the original.
Skewness(ThirdMoment) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Skewness: Constructs a Skewness with an external moment.
skipTo(int) - Method in class org.apache.commons.math4.legacy.random.HaltonSequenceGenerator: Skip to the i-th point in the Halton sequence.
skipTo(int) - Method in class org.apache.commons.math4.legacy.random.SobolSequenceGenerator: Skip to the i-th point in the Sobol sequence.
smooth(double[], double[]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Compute a loess fit on the data at the original abscissae.
smooth(double[], double[], double[]) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.LoessInterpolator: Compute a weighted loess fit on the data at the original abscissae.
SobolSequenceGenerator - Class in org.apache.commons.math4.legacy.random: Implementation of a Sobol sequence.
SobolSequenceGenerator(int) - Constructor for class org.apache.commons.math4.legacy.random.SobolSequenceGenerator: Construct a new Sobol sequence generator for the given space dimension.
SobolSequenceGenerator(int, InputStream) - Constructor for class org.apache.commons.math4.legacy.random.SobolSequenceGenerator: Construct a new Sobol sequence generator for the given space dimension with direction vectors loaded from the given stream.
SolutionCallback - Class in org.apache.commons.math4.legacy.optim.linear: A callback object that can be provided to a linear optimizer to keep track of the best solution found.
SolutionCallback() - Constructor for class org.apache.commons.math4.legacy.optim.linear.SolutionCallback
solve(int, FUNC, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Solve for a zero in the vicinity of startValue.
solve(int, FUNC, double) - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BaseUnivariateSolver: Solve for a zero in the vicinity of startValue.
solve(int, FUNC, double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Solve for a zero root in the given interval.
solve(int, FUNC, double, double) - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BaseUnivariateSolver: Solve for a zero root in the given interval.
solve(int, FUNC, double, double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Solve for a zero in the given interval, start at startValue.
solve(int, FUNC, double, double, double) - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BaseUnivariateSolver: Solve for a zero in the given interval, start at startValue.
solve(int, FUNC, double, double, double, AllowedSolution) - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BracketedUnivariateSolver: Solve for a zero in the given interval, start at startValue.
solve(int, FUNC, double, double, AllowedSolution) - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BracketedUnivariateSolver: Solve for a zero in the given interval.
solve(int, UnivariateDifferentiableFunction, double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.NewtonRaphsonSolver: Find a zero near the midpoint of min and max.
solve(int, RealFieldUnivariateFunction<T>, T, T, AllowedSolution) - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BracketedRealFieldUnivariateSolver: Solve for a zero in the given interval.
solve(int, RealFieldUnivariateFunction<T>, T, T, AllowedSolution) - Method in class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Solve for a zero in the given interval.
solve(int, RealFieldUnivariateFunction<T>, T, T, T, AllowedSolution) - Method in interface org.apache.commons.math4.legacy.analysis.solvers.BracketedRealFieldUnivariateSolver: Solve for a zero in the given interval, start at startValue.
solve(int, RealFieldUnivariateFunction<T>, T, T, T, AllowedSolution) - Method in class org.apache.commons.math4.legacy.analysis.solvers.FieldBracketingNthOrderBrentSolver: Solve for a zero in the given interval, start at startValue.
solve(int, UnivariateFunction, double, double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Solve for a zero in the given interval, start at startValue.
solve(int, UnivariateFunction, double, double, double, AllowedSolution) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Solve for a zero in the given interval, start at startValue.
solve(int, UnivariateFunction, double, double, double, AllowedSolution) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Solve for a zero in the given interval, start at startValue.
solve(int, UnivariateFunction, double, double, AllowedSolution) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver: Solve for a zero in the given interval.
solve(int, UnivariateFunction, double, double, AllowedSolution) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BracketingNthOrderBrentSolver: Solve for a zero in the given interval.
solve(UnivariateFunction, double, double) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: Convenience method to find a zero of a univariate real function.
solve(UnivariateFunction, double, double, double) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: Convenience method to find a zero of a univariate real function.
solve(FieldDenseMatrix<T>) - Method in interface org.apache.commons.math4.legacy.field.linalg.FieldDecompositionSolver: Solves the linear equation A X = B.
solve(FieldMatrix<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldDecompositionSolver: Solve the linear equation A × X = B for matrices A.
solve(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldDecompositionSolver: Solve the linear equation A × X = B for matrices A.
solve(RealLinearOperator, RealLinearOperator, RealVector) - Method in class org.apache.commons.math4.legacy.linear.PreconditionedIterativeLinearSolver: Returns an estimate of the solution to the linear system A · x = b.
solve(RealLinearOperator, RealLinearOperator, RealVector) - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns an estimate of the solution to the linear system A · x = b.
solve(RealLinearOperator, RealLinearOperator, RealVector, boolean, double) - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns an estimate of the solution to the linear system (A - shift · I) · x = b.
solve(RealLinearOperator, RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.PreconditionedIterativeLinearSolver: Returns an estimate of the solution to the linear system A · x = b.
solve(RealLinearOperator, RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns an estimate of the solution to the linear system A · x = b.
solve(RealLinearOperator, RealVector) - Method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolver: Returns an estimate of the solution to the linear system A · x = b.
solve(RealLinearOperator, RealVector) - Method in class org.apache.commons.math4.legacy.linear.PreconditionedIterativeLinearSolver: Returns an estimate of the solution to the linear system A · x = b.
solve(RealLinearOperator, RealVector) - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns an estimate of the solution to the linear system A · x = b.
solve(RealLinearOperator, RealVector, boolean, double) - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns the solution to the system (A - shift · I) · x = b.
solve(RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolver: Returns an estimate of the solution to the linear system A · x = b.
solve(RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.PreconditionedIterativeLinearSolver: Returns an estimate of the solution to the linear system A · x = b.
solve(RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns an estimate of the solution to the linear system A · x = b.
solve(RealMatrix) - Method in interface org.apache.commons.math4.legacy.linear.DecompositionSolver: Solve the linear equation A × X = B for matrices A.
solve(RealMatrix, RealVector) - Method in enum org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer.Decomposition: Solve the linear least squares problem Jx=r.
solve(RealVector) - Method in interface org.apache.commons.math4.legacy.linear.DecompositionSolver: Solve the linear equation A × X = B for matrices A.
solveAllComplex(double[], double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.LaguerreSolver: Find all complex roots for the polynomial with the given coefficients, starting from the given initial value.
solveComplex(double[], double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.LaguerreSolver: Find a complex root for the polynomial with the given coefficients, starting from the given initial value.
solveInPlace(RealLinearOperator, RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.ConjugateGradient: Returns an estimate of the solution to the linear system A · x = b.
solveInPlace(RealLinearOperator, RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.PreconditionedIterativeLinearSolver: Returns an estimate of the solution to the linear system A · x = b.
solveInPlace(RealLinearOperator, RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns an estimate of the solution to the linear system A · x = b.
solveInPlace(RealLinearOperator, RealLinearOperator, RealVector, RealVector, boolean, double) - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns an estimate of the solution to the linear system (A - shift · I) · x = b.
solveInPlace(RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.IterativeLinearSolver: Returns an estimate of the solution to the linear system A · x = b.
solveInPlace(RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.PreconditionedIterativeLinearSolver: Returns an estimate of the solution to the linear system A · x = b.
solveInPlace(RealLinearOperator, RealVector, RealVector) - Method in class org.apache.commons.math4.legacy.linear.SymmLQ: Returns an estimate of the solution to the linear system A · x = b.
solveInverseCumulativeProbability(double, int, int) - Method in class org.apache.commons.math4.legacy.distribution.AbstractIntegerDistribution: This is a utility function used by AbstractIntegerDistribution.inverseCumulativeProbability(double).
solveLowerTriangularSystem(RealMatrix, RealVector) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Solve a system of composed of a Lower Triangular Matrix RealMatrix.
solvePhase1(SimplexTableau) - Method in class org.apache.commons.math4.legacy.optim.linear.SimplexSolver: Solves Phase 1 of the Simplex method.
SOLVER_DEFAULT_ABSOLUTE_ACCURACY - Static variable in class org.apache.commons.math4.legacy.distribution.AbstractRealDistribution: Default absolute accuracy for inverse cumulative computation.
solveUpperTriangularSystem(RealMatrix, RealVector) - Static method in class org.apache.commons.math4.legacy.linear.MatrixUtils: Solver a system composed of an Upper Triangular Matrix RealMatrix.
sortObservations(Collection<WeightedObservedPoint>) - Method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter.ParameterGuesser: Sort the observations.
SparseEntryIterator() - Constructor for class org.apache.commons.math4.legacy.linear.RealVector.SparseEntryIterator: Simple constructor.
SparseFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: Sparse matrix implementation based on an open addressed map.
SparseFieldMatrix(Field<T>) - Constructor for class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Create a matrix with no data.
SparseFieldMatrix(Field<T>, int, int) - Constructor for class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Create a new SparseFieldMatrix<T> with the supplied row and column dimensions.
SparseFieldMatrix(FieldMatrix<T>) - Constructor for class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Generic copy constructor.
SparseFieldMatrix(SparseFieldMatrix<T>) - Constructor for class org.apache.commons.math4.legacy.linear.SparseFieldMatrix: Copy constructor.
SparseFieldVector<T extends FieldElement<T>> - Class in org.apache.commons.math4.legacy.linear: This class implements the FieldVector interface with a OpenIntToFieldHashMap backing store.
SparseFieldVector(Field<T>) - Constructor for class org.apache.commons.math4.legacy.linear.SparseFieldVector: Build a 0-length vector.
SparseFieldVector(Field<T>, int) - Constructor for class org.apache.commons.math4.legacy.linear.SparseFieldVector: Construct a vector of zeroes.
SparseFieldVector(Field<T>, int, int) - Constructor for class org.apache.commons.math4.legacy.linear.SparseFieldVector: Build a vector with known the sparseness (for advanced use only).
SparseFieldVector(Field<T>, T[]) - Constructor for class org.apache.commons.math4.legacy.linear.SparseFieldVector: Create from a Field array.
SparseFieldVector(SparseFieldVector<T>) - Constructor for class org.apache.commons.math4.legacy.linear.SparseFieldVector: Copy constructor.
SparseFieldVector(SparseFieldVector<T>, int) - Constructor for class org.apache.commons.math4.legacy.linear.SparseFieldVector: Build a resized vector, for use with append.
SparseGradient - Class in org.apache.commons.math4.legacy.analysis.differentiation: First derivative computation with large number of variables.
sparseIterator() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Create a sparse iterator over the vector, which may omit some entries.
sparseIterator() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Create a sparse iterator over the vector, which may omit some entries.
SparseRealMatrix - Interface in org.apache.commons.math4.legacy.linear: Marker interface for RealMatrix implementations that require sparse backing storage
SparseRealVector - Class in org.apache.commons.math4.legacy.linear: Marker class for RealVectors that require sparse backing storage
SparseRealVector() - Constructor for class org.apache.commons.math4.legacy.linear.SparseRealVector
SpearmansCorrelation - Class in org.apache.commons.math4.legacy.stat.correlation: Spearman's rank correlation.
SpearmansCorrelation() - Constructor for class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Create a SpearmansCorrelation without data.
SpearmansCorrelation(RealMatrix) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Create a SpearmansCorrelation from the given data matrix.
SpearmansCorrelation(RealMatrix, RankingAlgorithm) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Create a SpearmansCorrelation with the given input data matrix and ranking algorithm.
SpearmansCorrelation(RankingAlgorithm) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.SpearmansCorrelation: Create a SpearmansCorrelation with the given ranking algorithm.
SplineInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Computes a natural (also known as "free", "unclamped") cubic spline interpolation for the data set.
SplineInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.SplineInterpolator
sqrt() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
sqrt() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
sqrt() - Method in class org.apache.commons.math4.legacy.linear.JacobiPreconditioner: Returns the square root of this diagonal operator.
Sqrt - Class in org.apache.commons.math4.legacy.analysis.function: Square-root function.
Sqrt() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Sqrt
StandardDeviation - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Computes the sample standard deviation.
StandardDeviation() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Constructs a StandardDeviation.
StandardDeviation(boolean) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Constructs a StandardDeviation with the specified value for the isBiasCorrected property.
StandardDeviation(boolean, SecondMoment) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Constructs a StandardDeviation with the specified value for the isBiasCorrected property and the supplied external moment.
StandardDeviation(SecondMoment) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Constructs a StandardDeviation from an external second moment.
StandardDeviation(StandardDeviation) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.StandardDeviation: Copy constructor, creates a new StandardDeviation identical to the original.
start(double[]) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the initial guess.
start(double, double[], double) - Method in class org.apache.commons.math4.legacy.ode.MultistepIntegrator: Start the integration.
start(int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldVectorChangingVisitor: Start visiting a vector.
start(int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldVectorPreservingVisitor: Start visiting a vector.
start(int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealVectorChangingVisitor: Start visiting a vector.
start(int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealVectorPreservingVisitor: Start visiting a vector.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixChangingVisitor: Start visiting a matrix.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixPreservingVisitor: Start visiting a matrix.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.DefaultRealMatrixChangingVisitor: Start visiting a matrix.
start(int, int, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.DefaultRealMatrixPreservingVisitor: Start visiting a matrix.
start(int, int, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrixChangingVisitor: Start visiting a matrix.
start(int, int, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrixPreservingVisitor: Start visiting a matrix.
start(int, int, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrixChangingVisitor: Start visiting a matrix.
start(int, int, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrixPreservingVisitor: Start visiting a matrix.
start(RealVector) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the initial guess.
start(FieldExpandableODE<T>, FieldODEState<T>, T) - Method in class org.apache.commons.math4.legacy.ode.MultistepFieldIntegrator: Start the integration.
stateVariation - Variable in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator: State variation.
StatisticalMultivariateSummary - Interface in org.apache.commons.math4.legacy.stat.descriptive: Reporting interface for basic multivariate statistics.
StatisticalSummary - Interface in org.apache.commons.math4.legacy.stat.descriptive: Reporting interface for basic univariate statistics.
StatisticalSummaryValues - Class in org.apache.commons.math4.legacy.stat.descriptive: Value object representing the results of a univariate statistical summary.
StatisticalSummaryValues(double, double, long, double, double, double) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues: Constructor.
StatUtils - Class in org.apache.commons.math4.legacy.stat: StatUtils provides static methods for computing statistics based on data stored in double[] arrays.
stepAccepted(double, double[]) - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Acknowledge the fact the step has been accepted by the integrator.
stepAccepted(FieldODEStateAndDerivative<T>) - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Acknowledge the fact the step has been accepted by the integrator.
StepFunction - Class in org.apache.commons.math4.legacy.analysis.function: Step function.
StepFunction(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.analysis.function.StepFunction: Builds a step function from a list of arguments and the corresponding values.
StepHandler - Interface in org.apache.commons.math4.legacy.ode.sampling: This interface represents a handler that should be called after each successful step.
stepHandlers - Variable in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Step handler.
StepInterpolator - Interface in org.apache.commons.math4.legacy.ode.sampling: This interface represents an interpolator over the last step during an ODE integration.
StepNormalizer - Class in org.apache.commons.math4.legacy.ode.sampling: This class wraps an object implementing FixedStepHandler into a StepHandler.
StepNormalizer(double, FixedStepHandler) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.StepNormalizer: Simple constructor.
StepNormalizer(double, FixedStepHandler, StepNormalizerBounds) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.StepNormalizer: Simple constructor.
StepNormalizer(double, FixedStepHandler, StepNormalizerMode) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.StepNormalizer: Simple constructor.
StepNormalizer(double, FixedStepHandler, StepNormalizerMode, StepNormalizerBounds) - Constructor for class org.apache.commons.math4.legacy.ode.sampling.StepNormalizer: Simple constructor.
StepNormalizerBounds - Enum in org.apache.commons.math4.legacy.ode.sampling: Step normalizer bounds settings.
StepNormalizerMode - Enum in org.apache.commons.math4.legacy.ode.sampling: Step normalizer modes.
stepSize - Variable in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Current stepsize.
stepStart - Variable in class org.apache.commons.math4.legacy.ode.AbstractIntegrator: Current step start time.
stop() - Method in class org.apache.commons.math4.legacy.ode.events.EventState: Check if the integration should be stopped at the end of the current step.
stop() - Method in class org.apache.commons.math4.legacy.ode.events.FieldEventState: Check if the integration should be stopped at the end of the current step.
STOP - org.apache.commons.math4.legacy.ode.events.Action: Stop indicator.
STOP - org.apache.commons.math4.legacy.ode.events.EventHandler.Action: Stop indicator.
StoppingCondition - Interface in org.apache.commons.math4.legacy.genetics: Algorithm used to determine when to stop evolution.
store(PointValuePair) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultiStartMultivariateOptimizer: Method that will be called in order to store each found optimum.
store(PAIR) - Method in class org.apache.commons.math4.legacy.optim.BaseMultiStartMultivariateOptimizer: Method that will be called in order to store each found optimum.
StorelessCovariance - Class in org.apache.commons.math4.legacy.stat.correlation: Covariance implementation that does not require input data to be stored in memory.
StorelessCovariance(int) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Create a bias corrected covariance matrix with a given dimension.
StorelessCovariance(int, boolean) - Constructor for class org.apache.commons.math4.legacy.stat.correlation.StorelessCovariance: Create a covariance matrix with a given number of rows and columns and the indicated bias correction.
StorelessUnivariateStatistic - Interface in org.apache.commons.math4.legacy.stat.descriptive: Extends the definition of UnivariateStatistic with StorelessUnivariateStatistic.increment(double) and StorelessUnivariateStatistic.incrementAll(double[]) methods for adding values and updating internal state.
storeTime(double) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Store the current step time.
subtract(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
subtract(double) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
subtract(double[], int, double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Perform subtraction of two derivative structures.
subtract(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
subtract(SparseGradient) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
subtract(PolynomialFunction) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Subtract a polynomial from the instance.
subtract(FieldDenseMatrix<T>) - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Subtraction.
subtract(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Subtract m from this matrix.
subtract(Array2DRowRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Returns this minus m.
subtract(ArrayFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute this minus v.
subtract(BigReal) - Method in class org.apache.commons.math4.legacy.linear.BigReal
subtract(BlockFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Compute this - m.
subtract(BlockRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Subtract m from this matrix.
subtract(DiagonalMatrix) - Method in class org.apache.commons.math4.legacy.linear.DiagonalMatrix: Returns this minus m.
subtract(FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Subtract m from this matrix.
subtract(FieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Subtract m from this matrix.
subtract(FieldMatrix<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Subtract m from this matrix.
subtract(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Compute this minus v.
subtract(FieldVector<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Compute this minus v.
subtract(FieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Compute this minus v.
subtract(OpenMapRealMatrix) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Subtract m from this matrix.
subtract(OpenMapRealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Optimized method to subtract OpenMapRealVectors.
subtract(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns this minus m.
subtract(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns this minus m.
subtract(RealMatrix) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealMatrix: Returns this minus m.
subtract(RealMatrix) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns this minus m.
subtract(RealVector) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Subtract v from this vector.
subtract(RealVector) - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Subtract v from this vector.
subtract(RealVector) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Subtract v from this vector.
subtract(SparseFieldVector<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Optimized method to compute this minus v.
Subtract - Class in org.apache.commons.math4.legacy.analysis.function: Subtract the second operand from the first.
Subtract() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Subtract
sum(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the sum of the values in the input array, or Double.NaN if the array is empty.
sum(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the sum of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
Sum - Class in org.apache.commons.math4.legacy.stat.descriptive.summary: Returns the sum of the available values.
Sum() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Create a Sum instance.
Sum(Sum) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.summary.Sum: Copy constructor, creates a new Sum identical to the original.
sumDifference(double[], double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the sum of the (signed) differences between corresponding elements of the input arrays -- i.e., sum(sample1[i] - sample2[i]).
sumLog(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the sum of the natural logs of the entries in the input array, or Double.NaN if the array is empty.
sumLog(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the sum of the natural logs of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
SummaryStatistics - Class in org.apache.commons.math4.legacy.stat.descriptive: Computes summary statistics for a stream of data values added using the addValue method.
SummaryStatistics() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Construct a SummaryStatistics instance.
SummaryStatistics(SummaryStatistics) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: A copy constructor.
SumOfClusterVariances - Class in org.apache.commons.math4.legacy.ml.clustering.evaluation: Computes the sum of intra-cluster distance variances according to the formula:
SumOfClusterVariances(DistanceMeasure) - Constructor for class org.apache.commons.math4.legacy.ml.clustering.evaluation.SumOfClusterVariances
SumOfLogs - Class in org.apache.commons.math4.legacy.stat.descriptive.summary: Returns the sum of the natural logs for this collection of values.
SumOfLogs() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Create a SumOfLogs instance.
SumOfLogs(SumOfLogs) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfLogs: Copy constructor, creates a new SumOfLogs identical to the original.
SumOfSquares - Class in org.apache.commons.math4.legacy.stat.descriptive.summary: Returns the sum of the squares of the available values.
SumOfSquares() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Create a SumOfSquares instance.
SumOfSquares(SumOfSquares) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.summary.SumOfSquares: Copy constructor, creates a new SumOfSquares identical to the original.
sumSq(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the sum of the squares of the entries in the input array, or Double.NaN if the array is empty.
sumSq(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the sum of the squares of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
SVD - org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer.Decomposition: Solve the linear least squares problem using the SingularValueDecomposition.
SymmetricGaussIntegrator - Class in org.apache.commons.math4.legacy.analysis.integration.gauss: This class's implements integrate method assuming that the integral is symmetric about 0.
SymmetricGaussIntegrator(double[], double[]) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.SymmetricGaussIntegrator: Creates an integrator from the given points and weights.
SymmetricGaussIntegrator(Pair<double[], double[]>) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.gauss.SymmetricGaussIntegrator: Creates an integrator from the given pair of points (first element of the pair) and weights (second element of the pair.
SymmLQ - Class in org.apache.commons.math4.legacy.linear: Implementation of the SYMMLQ iterative linear solver proposed by Paige and Saunders (1975).
SymmLQ(int, double, boolean) - Constructor for class org.apache.commons.math4.legacy.linear.SymmLQ: Creates a new instance of this class, with default stopping criterion.
SymmLQ(IterationManager, double, boolean) - Constructor for class org.apache.commons.math4.legacy.linear.SymmLQ: Creates a new instance of this class, with default stopping criterion and custom iteration manager.
SynchronizedDescriptiveStatistics - Class in org.apache.commons.math4.legacy.stat.descriptive: Implementation of DescriptiveStatistics that is safe to use in a multithreaded environment.
SynchronizedDescriptiveStatistics() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Construct an instance with infinite window.
SynchronizedDescriptiveStatistics(int) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Construct an instance with finite window.
SynchronizedDescriptiveStatistics(SynchronizedDescriptiveStatistics) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: A copy constructor.
SynchronizedMultivariateSummaryStatistics - Class in org.apache.commons.math4.legacy.stat.descriptive: Implementation of MultivariateSummaryStatistics that is safe to use in a multithreaded environment.
SynchronizedMultivariateSummaryStatistics(int, boolean) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Construct a SynchronizedMultivariateSummaryStatistics instance.
SynchronizedSummaryStatistics - Class in org.apache.commons.math4.legacy.stat.descriptive: Implementation of SummaryStatistics that is safe to use in a multithreaded environment.
SynchronizedSummaryStatistics() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Construct a SynchronizedSummaryStatistics instance.
SynchronizedSummaryStatistics(SynchronizedSummaryStatistics) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: A copy constructor.

T

t(double[], double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
t(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances.
t(double, double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
t(double, double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes a t statistic given observed values and a comparison constant.
t(double, double, double, double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes t test statistic for 1-sample t-test.
t(double, double, double, double, double, double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes t test statistic for 2-sample t-test.
t(double, StatisticalSummary) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
t(double, StatisticalSummary) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes a t statistic to use in comparing the mean of the dataset described by sampleStats to mu.
t(StatisticalSummary, StatisticalSummary) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
t(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes a 2-sample t statistic, comparing the means of the datasets described by two StatisticalSummary instances, without the assumption of equal subpopulation variances.
tan() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
tan() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
tan(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute tangent of a derivative structure.
Tan - Class in org.apache.commons.math4.legacy.analysis.function: Tangent function.
Tan() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Tan
tanh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure
tanh() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient
tanh(double[], int, double[], int) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Compute hyperbolic tangent of a derivative structure.
Tanh - Class in org.apache.commons.math4.legacy.analysis.function: Hyperbolic tangent function.
Tanh() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Tanh
target(double[]) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the observed data.
target(RealVector) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the observed data.
taylor(double...) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Evaluate Taylor expansion a derivative structure.
taylor(double...) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Evaluate Taylor expansion of a sparse gradient.
taylor(double[], int, double...) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DSCompiler: Evaluate Taylor expansion of a derivative structure.
terminationPerformed(IterationEvent) - Method in interface org.apache.commons.math4.legacy.linear.IterationListener: Invoked after completion of the operations which occur after breaking out of the main iteration loop.
TheoreticalValuesFunction(ParametricUnivariateFunction, Collection<WeightedObservedPoint>) - Constructor for class org.apache.commons.math4.legacy.fitting.AbstractCurveFitter.TheoreticalValuesFunction
ThreeEighthesFieldIntegrator<T extends RealFieldElement<T>> - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 3/8 fourth order Runge-Kutta integrator for Ordinary Differential Equations.
ThreeEighthesFieldIntegrator(Field<T>, T) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.ThreeEighthesFieldIntegrator: Simple constructor.
ThreeEighthesIntegrator - Class in org.apache.commons.math4.legacy.ode.nonstiff: This class implements the 3/8 fourth order Runge-Kutta integrator for Ordinary Differential Equations.
ThreeEighthesIntegrator(double) - Constructor for class org.apache.commons.math4.legacy.ode.nonstiff.ThreeEighthesIntegrator: Simple constructor.
TiesStrategy - Enum in org.apache.commons.math4.legacy.stat.ranking: Strategies for handling tied values in rank transformations.
toArray() - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Convert the vector to a T array.
toArray() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Convert the vector to an array of doubles.
toArray() - Method in interface org.apache.commons.math4.legacy.linear.FieldVector: Convert the vector to a T array.
toArray() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Convert the vector to an array of doubles.
toArray() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Convert the vector to an array of doubles.
toArray() - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Convert the vector to a T array.
toBlocksLayout(double[][]) - Static method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Convert a data array from raw layout to blocks layout.
toBlocksLayout(T[][]) - Static method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Convert a data array from raw layout to blocks layout.
toDegrees() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Convert radians to degrees, with error of less than 0.5 ULP.
toDegrees() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Convert radians to degrees, with error of less than 0.5 ULP.
toDifferentiable(MultivariateFunction, MultivariateVectorFunction) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Convert regular functions to MultivariateDifferentiableFunction.
toDifferentiable(UnivariateFunction, UnivariateFunction...) - Static method in class org.apache.commons.math4.legacy.analysis.FunctionUtils: Convert regular functions to UnivariateDifferentiableFunction.
Tolerance - Class in org.apache.commons.math4.legacy.optim: Default tolerances values.
Tolerance(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.Tolerance
toList() - Method in class org.apache.commons.math4.legacy.fitting.WeightedObservedPoints: Gets a snapshot of the observed points.
toRadians() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.DerivativeStructure: Convert degrees to radians, with error of less than 0.5 ULP.
toRadians() - Method in class org.apache.commons.math4.legacy.analysis.differentiation.SparseGradient: Convert degrees to radians, with error of less than 0.5 ULP.
toString() - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Returns a string representation of the polynomial.
toString() - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer
toString() - Method in class org.apache.commons.math4.legacy.genetics.AbstractListChromosome
toString() - Method in class org.apache.commons.math4.legacy.genetics.ChromosomePair
toString() - Method in class org.apache.commons.math4.legacy.genetics.ListPopulation
toString() - Method in class org.apache.commons.math4.legacy.genetics.RandomKey
toString() - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Get a string representation for this matrix.
toString() - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Get a string representation for this matrix.
toString() - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector
toString() - Method in class org.apache.commons.math4.legacy.ml.clustering.DoublePoint
toString() - Method in enum org.apache.commons.math4.legacy.optim.linear.Relationship
toString() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.HedarFukushimaTransform
toString() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.MultiDirectionalTransform
toString() - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.NelderMeadTransform
toString() - Method in class org.apache.commons.math4.legacy.optim.PointValuePair
toString() - Method in class org.apache.commons.math4.legacy.stat.descriptive.DescriptiveStatistics: Generates a text report displaying univariate statistics from values that have been added.
toString() - Method in class org.apache.commons.math4.legacy.stat.descriptive.MultivariateSummaryStatistics: Generates a text report displaying summary statistics from values that have been added.
toString() - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.PSquarePercentile: Returns a string containing the last observation, the current estimate of the quantile and all markers.
toString() - Method in class org.apache.commons.math4.legacy.stat.descriptive.StatisticalSummaryValues: Generates a text report displaying values of statistics.
toString() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SummaryStatistics: Generates a text report displaying summary statistics from values that have been added.
toString() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedDescriptiveStatistics: Generates a text report displaying univariate statistics from values that have been added.
toString() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedMultivariateSummaryStatistics: Generates a text report displaying summary statistics from values that have been added.
toString() - Method in class org.apache.commons.math4.legacy.stat.descriptive.SynchronizedSummaryStatistics: Generates a text report displaying summary statistics from values that have been added.
toString() - Method in class org.apache.commons.math4.legacy.stat.Frequency: Return a string representation of this frequency distribution.
toString() - Method in class org.apache.commons.math4.legacy.stat.interval.ConfidenceInterval
TournamentSelection - Class in org.apache.commons.math4.legacy.genetics: Tournament selection scheme.
TournamentSelection(int) - Constructor for class org.apache.commons.math4.legacy.genetics.TournamentSelection: Creates a new TournamentSelection instance.
transpose() - Method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Transposes this matrix.
transpose() - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Returns the transpose of this matrix.
transpose() - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Returns the transpose of this matrix.
transpose() - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Returns the transpose of this matrix.
transpose() - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Returns the transpose of this matrix.
transpose() - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Returns the transpose of this matrix.
transpose() - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Returns the transpose of this matrix.
TrapezoidIntegrator - Class in org.apache.commons.math4.legacy.analysis.integration: Implements the Trapezoid Rule for integration of real univariate functions.
TrapezoidIntegrator() - Constructor for class org.apache.commons.math4.legacy.analysis.integration.TrapezoidIntegrator: Construct a trapezoid integrator with default settings.
TrapezoidIntegrator(double, double, int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.TrapezoidIntegrator: Build a trapezoid integrator with given accuracies and iterations counts.
TrapezoidIntegrator(int, int) - Constructor for class org.apache.commons.math4.legacy.analysis.integration.TrapezoidIntegrator: Build a trapezoid integrator with given iteration counts.
TricubicInterpolatingFunction - Class in org.apache.commons.math4.legacy.analysis.interpolation: Function that implements the tricubic spline interpolation, as proposed in Tricubic interpolation in three dimensions
F.
TricubicInterpolatingFunction(double[], double[], double[], double[][][], double[][][], double[][][], double[][][], double[][][], double[][][], double[][][], double[][][]) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.TricubicInterpolatingFunction
TricubicInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Generates a tricubic interpolating function.
TricubicInterpolator() - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.TricubicInterpolator
TRIGGER_ONLY_DECREASING_EVENTS - org.apache.commons.math4.legacy.ode.events.FilterType: Constant for triggering only decreasing events.
TRIGGER_ONLY_INCREASING_EVENTS - org.apache.commons.math4.legacy.ode.events.FilterType: Constant for triggering only increasing events.
TrivariateFunction - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a trivariate real function.
TrivariateGridInterpolator - Interface in org.apache.commons.math4.legacy.analysis.interpolation: Interface representing a trivariate real interpolating function where the sample points must be specified on a regular grid.
tTest(double[], double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
tTest(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.
tTest(double[], double[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
tTest(double[], double[], double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Performs a two-sided t-test evaluating the null hypothesis that sample1 and sample2 are drawn from populations with the same mean, with significance level alpha.
tTest(double, double[]) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
tTest(double, double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant mu.
tTest(double, double[], double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
tTest(double, double[], double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which sample is drawn equals mu.
tTest(double, double, double, double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes p-value for 2-sided, 1-sample t-test.
tTest(double, double, double, double, double, double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Computes p-value for 2-sided, 2-sample t-test.
tTest(double, StatisticalSummary) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
tTest(double, StatisticalSummary) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by sampleStats with the constant mu.
tTest(double, StatisticalSummary, double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
tTest(double, StatisticalSummary, double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by stats is drawn equals mu.
tTest(StatisticalSummary, StatisticalSummary) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
tTest(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
tTest(StatisticalSummary, StatisticalSummary, double) - Static method in class org.apache.commons.math4.legacy.stat.inference.InferenceTestUtils
tTest(StatisticalSummary, StatisticalSummary, double) - Method in class org.apache.commons.math4.legacy.stat.inference.TTest: Performs a two-sided t-test evaluating the null hypothesis that sampleStats1 and sampleStats2 describe datasets drawn from populations with the same mean, with significance level alpha.
TTest - Class in org.apache.commons.math4.legacy.stat.inference: An implementation for Student's t-tests.
TTest() - Constructor for class org.apache.commons.math4.legacy.stat.inference.TTest
TWO_SIDED - org.apache.commons.math4.legacy.stat.inference.AlternativeHypothesis: Represents a two-sided test.

U

Ulp - Class in org.apache.commons.math4.legacy.analysis.function: ulp function.
Ulp() - Constructor for class org.apache.commons.math4.legacy.analysis.function.Ulp
unbounded(int) - Static method in class org.apache.commons.math4.legacy.optim.SimpleBounds: Factory method that creates instance of this class that represents unbounded ranges.
UnboundedSolutionException - Exception in org.apache.commons.math4.legacy.optim.linear: This class represents exceptions thrown by optimizers when a solution escapes to infinity.
UnboundedSolutionException() - Constructor for exception org.apache.commons.math4.legacy.optim.linear.UnboundedSolutionException: Simple constructor using a default message.
unboundedToBounded(double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateFunctionMappingAdapter: Maps an array from unbounded to bounded.
uniform(UniformRandomProvider) - Method in class org.apache.commons.math4.legacy.random.CorrelatedVectorFactory
UniformCrossover<T> - Class in org.apache.commons.math4.legacy.genetics: Perform Uniform Crossover [UX] on the specified chromosomes.
UniformCrossover(double) - Constructor for class org.apache.commons.math4.legacy.genetics.UniformCrossover: Creates a new UniformCrossover policy using the given mixing ratio.
unitize() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Converts this vector into a unit vector.
unitize() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Converts this vector into a unit vector.
unitVector() - Method in class org.apache.commons.math4.legacy.linear.OpenMapRealVector: Creates a unit vector pointing in the direction of this vector.
unitVector() - Method in class org.apache.commons.math4.legacy.linear.RealVector: Creates a unit vector pointing in the direction of this vector.
UnivariateDifferentiableFunction - Interface in org.apache.commons.math4.legacy.analysis.differentiation: Interface for univariate functions derivatives.
UnivariateDifferentiableMatrixFunction - Interface in org.apache.commons.math4.legacy.analysis.differentiation: Extension of UnivariateMatrixFunction representing a univariate differentiable matrix function.
UnivariateDifferentiableSolver - Interface in org.apache.commons.math4.legacy.analysis.solvers: Interface for (univariate real) rootfinding algorithms.
UnivariateDifferentiableVectorFunction - Interface in org.apache.commons.math4.legacy.analysis.differentiation: Extension of UnivariateVectorFunction representing a univariate differentiable vectorial function.
UnivariateFunction - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a univariate real function.
UnivariateFunctionDifferentiator - Interface in org.apache.commons.math4.legacy.analysis.differentiation: Interface defining the function differentiation operation.
UnivariateIntegrator - Interface in org.apache.commons.math4.legacy.analysis.integration: Interface for univariate real integration algorithms.
UnivariateInterpolator - Interface in org.apache.commons.math4.legacy.analysis.interpolation: Interface representing a univariate real interpolating function.
UnivariateMatrixFunction - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a univariate matrix function.
UnivariateMatrixFunctionDifferentiator - Interface in org.apache.commons.math4.legacy.analysis.differentiation: Interface defining the function differentiation operation.
UnivariateObjectiveFunction - Class in org.apache.commons.math4.legacy.optim.univariate: Scalar function to be optimized.
UnivariateObjectiveFunction(UnivariateFunction) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.UnivariateObjectiveFunction
UnivariateOptimizer - Class in org.apache.commons.math4.legacy.optim.univariate: Base class for a univariate scalar function optimizer.
UnivariateOptimizer(ConvergenceChecker<UnivariatePointValuePair>) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.UnivariateOptimizer
UnivariatePeriodicInterpolator - Class in org.apache.commons.math4.legacy.analysis.interpolation: Adapter for classes implementing the UnivariateInterpolator interface.
UnivariatePeriodicInterpolator(UnivariateInterpolator, double) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.UnivariatePeriodicInterpolator: Builds an interpolator.
UnivariatePeriodicInterpolator(UnivariateInterpolator, double, int) - Constructor for class org.apache.commons.math4.legacy.analysis.interpolation.UnivariatePeriodicInterpolator: Builds an interpolator.
UnivariatePointValuePair - Class in org.apache.commons.math4.legacy.optim.univariate: This class holds a point and the value of an objective function at this point.
UnivariatePointValuePair(double, double) - Constructor for class org.apache.commons.math4.legacy.optim.univariate.UnivariatePointValuePair: Build a point/objective function value pair.
UnivariateSolver - Interface in org.apache.commons.math4.legacy.analysis.solvers: Interface for (univariate real) root-finding algorithms.
UnivariateSolverUtils - Class in org.apache.commons.math4.legacy.analysis.solvers: Utility routines for UnivariateSolver objects.
UnivariateStatistic - Interface in org.apache.commons.math4.legacy.stat.descriptive: Base interface implemented by all statistics.
UnivariateVectorFunction - Interface in org.apache.commons.math4.legacy.analysis: An interface representing a univariate vectorial function.
UnivariateVectorFunctionDifferentiator - Interface in org.apache.commons.math4.legacy.analysis.differentiation: Interface defining the function differentiation operation.
UnknownParameterException - Exception in org.apache.commons.math4.legacy.ode: Exception to be thrown when a parameter is unknown.
UnknownParameterException(String) - Constructor for exception org.apache.commons.math4.legacy.ode.UnknownParameterException: Construct an exception from the unknown parameter.
unlimited() - Static method in class org.apache.commons.math4.legacy.optim.MaxEval: Factory method that creates instance of this class that represents a virtually unlimited number of evaluations.
unlimited() - Static method in class org.apache.commons.math4.legacy.optim.MaxIter: Factory method that creates instance of this class that represents a virtually unlimited number of iterations.
unmodifiableRealVector(RealVector) - Static method in class org.apache.commons.math4.legacy.linear.RealVector: Returns an unmodifiable view of the specified vector.
update(Simplex, boolean, int) - Method in interface org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv.SimplexOptimizer.Observer: Method called after each modification of the simplex.
updateHighOrderDerivativesPhase1(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsFieldIntegrator: Update the high order scaled derivatives for Adams integrators (phase 1).
updateHighOrderDerivativesPhase1(Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsNordsieckFieldTransformer: Update the high order scaled derivatives for Adams integrators (phase 1).
updateHighOrderDerivativesPhase1(Array2DRowRealMatrix) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsIntegrator: Update the high order scaled derivatives for Adams integrators (phase 1).
updateHighOrderDerivativesPhase1(Array2DRowRealMatrix) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsNordsieckTransformer: Update the high order scaled derivatives for Adams integrators (phase 1).
updateHighOrderDerivativesPhase2(double[], double[], Array2DRowRealMatrix) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsIntegrator: Update the high order scaled derivatives Adams integrators (phase 2).
updateHighOrderDerivativesPhase2(double[], double[], Array2DRowRealMatrix) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsNordsieckTransformer: Update the high order scaled derivatives Adams integrators (phase 2).
updateHighOrderDerivativesPhase2(T[], T[], Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsFieldIntegrator: Update the high order scaled derivatives Adams integrators (phase 2).
updateHighOrderDerivativesPhase2(T[], T[], Array2DRowFieldMatrix<T>) - Method in class org.apache.commons.math4.legacy.ode.nonstiff.AdamsNordsieckFieldTransformer: Update the high order scaled derivatives Adams integrators (phase 2).
UpdatingMultipleLinearRegression - Interface in org.apache.commons.math4.legacy.stat.regression: An interface for regression models allowing for dynamic updating of the data.
UPSIDE - org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance.Direction: The UPSIDE Direction is used to specify that the observations above the.
UPSIDE_VARIANCE - Static variable in class org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance: The UPSIDE Direction is used to specify that the observations above the cutoff point will be used to calculate SemiVariance.

V

validate(RealVector) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.ParameterValidator: Validates the set of parameters.
validateCovarianceData(double[][], double[][]) - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Validates that the x data and covariance matrix have the same number of rows and that the covariance matrix is square.
validateSampleData(double[][], double[]) - Method in class org.apache.commons.math4.legacy.stat.regression.AbstractMultipleLinearRegression: Validates sample data.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Abs: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Acos: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Acosh: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Asin: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Asinh: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Atan: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Atanh: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Cbrt: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Ceil: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Constant: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Cos: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Cosh: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Exp: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Expm1: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Floor: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Gaussian: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.HarmonicOscillator: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Identity: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Inverse: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Log: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Log10: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Log1p: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Logistic: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Logit: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Minus: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Power: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Rint: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Sigmoid: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Signum: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Sin: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Sinc: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Sinh: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Sqrt: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.StepFunction: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Tan: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Tanh: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.function.Ulp: Compute the value of the function.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.HermiteInterpolator: Interpolate value at a specified abscissa.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Compute the value of the function for the given argument.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Calculate the function value at the given point.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Calculate the function value at the given point.
value(double) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialSplineFunction: Compute the value for the function.
value(double) - Method in interface org.apache.commons.math4.legacy.analysis.UnivariateFunction: Compute the value of the function.
value(double) - Method in interface org.apache.commons.math4.legacy.analysis.UnivariateMatrixFunction: Compute the value for the function.
value(double) - Method in interface org.apache.commons.math4.legacy.analysis.UnivariateVectorFunction: Compute the value for the function.
value(double) - Method in class org.apache.commons.math4.legacy.special.BesselJ: Returns the value of the constructed Bessel function of the first kind, for the passed argument.
value(double[]) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.GradientFunction: Compute the value for the function at the given point.
value(double[]) - Method in class org.apache.commons.math4.legacy.analysis.differentiation.JacobianFunction: Compute the value for the function at the given point.
value(double[]) - Method in interface org.apache.commons.math4.legacy.analysis.MultivariateFunction: Compute the value for the function at the given point.
value(double[]) - Method in interface org.apache.commons.math4.legacy.analysis.MultivariateMatrixFunction: Compute the value for the function at the given point.
value(double[]) - Method in interface org.apache.commons.math4.legacy.analysis.MultivariateVectorFunction: Compute the value for the function at the given point.
value(double[]) - Method in class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction: Computes the value of the linear equation at the current point.
value(double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.LeastSquaresConverter: Compute the value for the function at the given point.
value(double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateFunctionMappingAdapter: Compute the underlying function value from an unbounded point.
value(double[]) - Method in class org.apache.commons.math4.legacy.optim.nonlinear.scalar.MultivariateFunctionPenaltyAdapter: Computes the underlying function value from an unbounded point.
value(double[], double[][], double[], double, double) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.InterpolatingMicrosphere: Estimate the value at the requested location.
value(double, double) - Method in interface org.apache.commons.math4.legacy.analysis.BivariateFunction: Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math4.legacy.analysis.function.Add: Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math4.legacy.analysis.function.Atan2: Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math4.legacy.analysis.function.Divide: Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math4.legacy.analysis.function.Max: Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math4.legacy.analysis.function.Min: Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math4.legacy.analysis.function.Multiply: Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math4.legacy.analysis.function.Pow: Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math4.legacy.analysis.function.Subtract: Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.BicubicInterpolatingFunction: Compute the value for the function.
value(double, double) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.PiecewiseBicubicSplineInterpolatingFunction: Compute the value for the function.
value(double, double) - Static method in class org.apache.commons.math4.legacy.special.BesselJ: Returns the first Bessel function, \(J_{order}(x)\).
value(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.function.Gaussian.Parametric: Computes the value of the Gaussian at x.
value(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.function.HarmonicOscillator.Parametric: Computes the value of the harmonic oscillator at x.
value(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.function.Logistic.Parametric: Computes the value of the sigmoid at x.
value(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.function.Logit.Parametric: Computes the value of the logit at x.
value(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.function.Sigmoid.Parametric: Computes the value of the sigmoid at x.
value(double, double...) - Method in interface org.apache.commons.math4.legacy.analysis.ParametricUnivariateFunction: Compute the value of the function.
value(double, double...) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction.Parametric: Compute the value of the function.
value(double, double, double) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.TricubicInterpolatingFunction: Compute the value for the function.
value(double, double, double) - Method in interface org.apache.commons.math4.legacy.analysis.TrivariateFunction: Compute the value for the function.
value(DerivativeStructure) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.UnivariateDifferentiableFunction: Simple mathematical function.
value(DerivativeStructure) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.UnivariateDifferentiableMatrixFunction: Compute the value for the function.
value(DerivativeStructure) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.UnivariateDifferentiableVectorFunction: Compute the value for the function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Acos: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Acosh: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Asin: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Asinh: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Atan: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Atanh: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Cbrt: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Constant: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Cos: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Cosh: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Exp: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Expm1: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Gaussian: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.HarmonicOscillator: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Identity: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Inverse: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Log: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Log10: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Log1p: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Logistic: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Logit: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Minus: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Power: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Sigmoid: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Sin: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Sinc: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Sinh: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Sqrt: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Tan: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.function.Tanh: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.HermiteInterpolator: Interpolate value at a specified abscissa.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunction: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Simple mathematical function.
value(DerivativeStructure) - Method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialSplineFunction: Simple mathematical function.
value(DerivativeStructure[]) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.MultivariateDifferentiableFunction: Compute the value for the function at the given point.
value(DerivativeStructure[]) - Method in interface org.apache.commons.math4.legacy.analysis.differentiation.MultivariateDifferentiableVectorFunction: Compute the value for the function at the given point.
value(RealVector) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.DifferentiatorVectorMultivariateJacobianFunction: Compute the function value and its Jacobian.
value(RealVector) - Method in interface org.apache.commons.math4.legacy.fitting.leastsquares.MultivariateJacobianFunction: Compute the function value and its Jacobian.
value(RealVector) - Method in class org.apache.commons.math4.legacy.optim.linear.LinearObjectiveFunction: Computes the value of the linear equation at the current point.
value(T) - Method in class org.apache.commons.math4.legacy.analysis.interpolation.FieldHermiteInterpolator: Interpolate value at a specified abscissa.
value(T) - Method in interface org.apache.commons.math4.legacy.analysis.RealFieldUnivariateFunction: Compute the value of the function.
ValueAndJacobianFunction - Interface in org.apache.commons.math4.legacy.fitting.leastsquares: A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.analysis.solvers.AllowedSolution: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver.Method: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer.Decomposition: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer.EmptyClusterStrategy: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.ode.events.Action: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.ode.events.EventHandler.Action: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.ode.events.FilterType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.ode.sampling.StepNormalizerMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.optim.linear.PivotSelectionRule: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.optim.linear.Relationship: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.optim.nonlinear.scalar.GoalType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer.Formula: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance.Direction: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.stat.inference.AlternativeHypothesis: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.stat.ranking.NaNStrategy: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.apache.commons.math4.legacy.stat.ranking.TiesStrategy: Returns the enum constant of this type with the specified name.
values() - Static method in enum org.apache.commons.math4.legacy.analysis.solvers.AllowedSolution: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.analysis.solvers.BaseSecantSolver.Method: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer.Decomposition: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.ml.clustering.KMeansPlusPlusClusterer.EmptyClusterStrategy: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.ode.events.Action: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.ode.events.EventHandler.Action: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.ode.events.FilterType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.ode.sampling.StepNormalizerBounds: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.ode.sampling.StepNormalizerMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.optim.linear.PivotSelectionRule: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.optim.linear.Relationship: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.optim.nonlinear.scalar.GoalType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer.Formula: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.stat.descriptive.moment.SemiVariance.Direction: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile.EstimationType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.stat.inference.AlternativeHypothesis: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.stat.ranking.NaNStrategy: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.apache.commons.math4.legacy.stat.ranking.TiesStrategy: Returns an array containing the constants of this enum type, in the order they are declared.
valuesIterator() - Method in class org.apache.commons.math4.legacy.stat.Frequency: Returns an Iterator over the set of values that have been added.
variance(double[]) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the variance of the entries in the input array, or Double.NaN if the array is empty.
variance(double[], double) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the variance of the entries in the input array, using the precomputed mean value.
variance(double[], double, int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the variance of the entries in the specified portion of the input array, using the precomputed mean value.
variance(double[], int, int) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the variance of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
Variance - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Computes the variance of the available values.
Variance() - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Constructs a Variance with default (true) isBiasCorrected property.
Variance(boolean) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Constructs a Variance with the specified isBiasCorrected property.
Variance(boolean, SecondMoment) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Constructs a Variance with the specified isBiasCorrected property and the supplied external second moment.
Variance(SecondMoment) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Constructs a Variance based on an external second moment.
Variance(Variance) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.Variance: Copy constructor, creates a new Variance identical to the original.
varianceDifference(double[], double[], double) - Static method in class org.apache.commons.math4.legacy.stat.StatUtils: Returns the variance of the (signed) differences between corresponding elements of the input arrays -- i.e., var(sample1[i] - sample2[i]).
vecAbsoluteTolerance - Variable in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Allowed absolute vectorial error.
vecAbsoluteTolerance - Variable in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Allowed absolute vectorial error.
vecRelativeTolerance - Variable in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeFieldIntegrator: Allowed relative vectorial error.
vecRelativeTolerance - Variable in class org.apache.commons.math4.legacy.ode.nonstiff.AdaptiveStepsizeIntegrator: Allowed relative vectorial error.
VECTOR - Static variable in class org.apache.commons.math4.legacy.linear.ConjugateGradient: Key for the exception context.
VectorialCovariance - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Returns the covariance matrix of the available vectors.
VectorialCovariance(int, boolean) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialCovariance: Constructs a VectorialCovariance.
VectorialMean - Class in org.apache.commons.math4.legacy.stat.descriptive.moment: Returns the arithmetic mean of the available vectors.
VectorialMean(int) - Constructor for class org.apache.commons.math4.legacy.stat.descriptive.moment.VectorialMean: Constructs a VectorialMean.
verifyBracketing(double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Check that the endpoints specify an interval and the function takes opposite signs at the endpoints.
verifyBracketing(UnivariateFunction, double, double) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: Check that the endpoints specify an interval and the end points bracket a root.
verifyInputArray(double[], double[]) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionNewtonForm: Verifies that the input arrays are valid.
verifyInterpolationArray(double[], double[], boolean) - Static method in class org.apache.commons.math4.legacy.analysis.polynomials.PolynomialFunctionLagrangeForm: Check that the interpolation arrays are valid.
verifyInterval(double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Check that the endpoints specify an interval.
verifyInterval(double, double) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: Check that the endpoints specify an interval.
verifySequence(double, double, double) - Method in class org.apache.commons.math4.legacy.analysis.solvers.BaseAbstractUnivariateSolver: Check that lower < initial < upper.
verifySequence(double, double, double) - Static method in class org.apache.commons.math4.legacy.analysis.solvers.UnivariateSolverUtils: Check that lower < initial < upper.
visit(int, double) - Method in interface org.apache.commons.math4.legacy.linear.RealVectorChangingVisitor: Visit one entry of the vector.
visit(int, double) - Method in interface org.apache.commons.math4.legacy.linear.RealVectorPreservingVisitor: Visit one entry of the vector.
visit(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.DefaultRealMatrixChangingVisitor: Visit one matrix entry.
visit(int, int, double) - Method in class org.apache.commons.math4.legacy.linear.DefaultRealMatrixPreservingVisitor: Visit one matrix entry.
visit(int, int, double) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrixChangingVisitor: Visit one matrix entry.
visit(int, int, double) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrixPreservingVisitor: Visit one matrix entry.
visit(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixChangingVisitor: Visit one matrix entry.
visit(int, int, T) - Method in class org.apache.commons.math4.legacy.linear.DefaultFieldMatrixPreservingVisitor: Visit one matrix entry.
visit(int, int, T) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrixChangingVisitor: Visit one matrix entry.
visit(int, int, T) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrixPreservingVisitor: Visit one matrix entry.
visit(int, T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVectorChangingVisitor: Visit one entry of the vector.
visit(int, T) - Method in interface org.apache.commons.math4.legacy.linear.FieldVectorPreservingVisitor: Visit one entry of the vector.

W

walkInColumnOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixChangingVisitor<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (and possibly change) all matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (and possibly change) some matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (but don't change) all matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Visit (but don't change) some matrix entries in column order.
walkInColumnOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (but don't change) some matrix entries in column order.
walkInDefaultOrder(FieldVectorChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Visits (and possibly alters) all entries of this vector in default order (increasing index).
walkInDefaultOrder(FieldVectorChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Visits (and possibly alters) all entries of this vector in default order (increasing index).
walkInDefaultOrder(FieldVectorChangingVisitor<T>, int, int) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Visits (and possibly alters) some entries of this vector in default order (increasing index).
walkInDefaultOrder(FieldVectorChangingVisitor<T>, int, int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Visits (and possibly alters) some entries of this vector in default order (increasing index).
walkInDefaultOrder(FieldVectorPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Visits (but does not alter) all entries of this vector in default order (increasing index).
walkInDefaultOrder(FieldVectorPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Visits (but does not alter) all entries of this vector in default order (increasing index).
walkInDefaultOrder(FieldVectorPreservingVisitor<T>, int, int) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Visits (but does not alter) some entries of this vector in default order (increasing index).
walkInDefaultOrder(FieldVectorPreservingVisitor<T>, int, int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Visits (but does not alter) some entries of this vector in default order (increasing index).
walkInDefaultOrder(RealVectorChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Visits (and possibly alters) all entries of this vector in default order (increasing index).
walkInDefaultOrder(RealVectorChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Visits (and possibly alters) all entries of this vector in default order (increasing index).
walkInDefaultOrder(RealVectorChangingVisitor, int, int) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Visits (and possibly alters) some entries of this vector in default order (increasing index).
walkInDefaultOrder(RealVectorChangingVisitor, int, int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Visits (and possibly alters) some entries of this vector in default order (increasing index).
walkInDefaultOrder(RealVectorPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Visits (but does not alter) all entries of this vector in default order (increasing index).
walkInDefaultOrder(RealVectorPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Visits (but does not alter) all entries of this vector in default order (increasing index).
walkInDefaultOrder(RealVectorPreservingVisitor, int, int) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Visits (but does not alter) some entries of this vector in default order (increasing index).
walkInDefaultOrder(RealVectorPreservingVisitor, int, int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Visits (but does not alter) some entries of this vector in default order (increasing index).
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(FieldVectorChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Visits (and possibly alters) all entries of this vector in optimized order.
walkInOptimizedOrder(FieldVectorChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Visits (and possibly alters) all entries of this vector in optimized order.
walkInOptimizedOrder(FieldVectorChangingVisitor<T>, int, int) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Visits (and possibly change) some entries of this vector in optimized order.
walkInOptimizedOrder(FieldVectorChangingVisitor<T>, int, int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Visits (and possibly change) some entries of this vector in optimized order.
walkInOptimizedOrder(FieldVectorPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Visits (but does not alter) all entries of this vector in optimized order.
walkInOptimizedOrder(FieldVectorPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Visits (but does not alter) all entries of this vector in optimized order.
walkInOptimizedOrder(FieldVectorPreservingVisitor<T>, int, int) - Method in class org.apache.commons.math4.legacy.linear.ArrayFieldVector: Visits (but does not alter) some entries of this vector in optimized order.
walkInOptimizedOrder(FieldVectorPreservingVisitor<T>, int, int) - Method in class org.apache.commons.math4.legacy.linear.SparseFieldVector: Visits (but does not alter) some entries of this vector in optimized order.
walkInOptimizedOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (and possibly change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (and possibly change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (but don't change) all matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (but don't change) some matrix entries using the fastest possible order.
walkInOptimizedOrder(RealVectorChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Visits (and possibly alters) all entries of this vector in optimized order.
walkInOptimizedOrder(RealVectorChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Visits (and possibly alters) all entries of this vector in optimized order.
walkInOptimizedOrder(RealVectorChangingVisitor, int, int) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Visits (and possibly change) some entries of this vector in optimized order.
walkInOptimizedOrder(RealVectorChangingVisitor, int, int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Visits (and possibly change) some entries of this vector in optimized order.
walkInOptimizedOrder(RealVectorPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Visits (but does not alter) all entries of this vector in optimized order.
walkInOptimizedOrder(RealVectorPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Visits (but does not alter) all entries of this vector in optimized order.
walkInOptimizedOrder(RealVectorPreservingVisitor, int, int) - Method in class org.apache.commons.math4.legacy.linear.ArrayRealVector: Visits (but does not alter) some entries of this vector in optimized order.
walkInOptimizedOrder(RealVectorPreservingVisitor, int, int) - Method in class org.apache.commons.math4.legacy.linear.RealVector: Visits (but does not alter) some entries of this vector in optimized order.
walkInRowOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(FieldMatrixChangingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (but don't change) all matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Visit (but don't change) all matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Visit (but don't change) all matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (but don't change) all matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractFieldMatrix: Visit (but don't change) some matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowFieldMatrix: Visit (but don't change) some matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockFieldMatrix: Visit (but don't change) some matrix entries in row order.
walkInRowOrder(FieldMatrixPreservingVisitor<T>, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.FieldMatrix: Visit (but don't change) some matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (and possibly change) all matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(RealMatrixChangingVisitor, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (and possibly change) some matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (but don't change) all matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Visit (but don't change) all matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Visit (but don't change) all matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (but don't change) all matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.AbstractRealMatrix: Visit (but don't change) some matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.Array2DRowRealMatrix: Visit (but don't change) some matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in class org.apache.commons.math4.legacy.linear.BlockRealMatrix: Visit (but don't change) some matrix entries in row order.
walkInRowOrder(RealMatrixPreservingVisitor, int, int, int, int) - Method in interface org.apache.commons.math4.legacy.linear.RealMatrix: Visit (but don't change) some matrix entries in row order.
weight(RealMatrix) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresBuilder: Configure the weight matrix.
weightDiagonal(LeastSquaresProblem, RealVector) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Apply a diagonal weight matrix to the LeastSquaresProblem.
WeightedEvaluation - Interface in org.apache.commons.math4.legacy.stat.descriptive: Weighted evaluation for statistics.
WeightedObservedPoint - Class in org.apache.commons.math4.legacy.fitting: This class is a simple container for weighted observed point in curve fitting.
WeightedObservedPoint(double, double, double) - Constructor for class org.apache.commons.math4.legacy.fitting.WeightedObservedPoint: Simple constructor.
WeightedObservedPoints - Class in org.apache.commons.math4.legacy.fitting: Simple container for weighted observed points used in curve fitting algorithms.
WeightedObservedPoints() - Constructor for class org.apache.commons.math4.legacy.fitting.WeightedObservedPoints
weightMatrix(LeastSquaresProblem, RealMatrix) - Static method in class org.apache.commons.math4.legacy.fitting.leastsquares.LeastSquaresFactory: Apply a dense weight matrix to the LeastSquaresProblem.
wilcoxonSignedRank(double[], double[]) - Method in class org.apache.commons.math4.legacy.stat.inference.WilcoxonSignedRankTest: Computes the Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample.
wilcoxonSignedRankTest(double[], double[], boolean) - Method in class org.apache.commons.math4.legacy.stat.inference.WilcoxonSignedRankTest: Returns the observed significance level, or p-value, associated with a Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample.
WilcoxonSignedRankTest - Class in org.apache.commons.math4.legacy.stat.inference: An implementation of the Wilcoxon signed-rank test.
WilcoxonSignedRankTest() - Constructor for class org.apache.commons.math4.legacy.stat.inference.WilcoxonSignedRankTest: Create a test instance where NaN's are left in place and ties get the average of applicable ranks.
WilcoxonSignedRankTest(NaNStrategy, TiesStrategy) - Constructor for class org.apache.commons.math4.legacy.stat.inference.WilcoxonSignedRankTest: Create a test instance using the given strategies for NaN's and ties.
WilsonScoreInterval - Class in org.apache.commons.math4.legacy.stat.interval: Implements the Wilson score method for creating a binomial proportion confidence interval.
WilsonScoreInterval() - Constructor for class org.apache.commons.math4.legacy.stat.interval.WilsonScoreInterval
withCostRelativeTolerance(double) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer
withDecomposition(GaussNewtonOptimizer.Decomposition) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.GaussNewtonOptimizer: Configure the decomposition algorithm.
withEstimationType(Percentile.EstimationType) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Median: Build a new instance similar to the current one except for the estimation type.
withEstimationType(Percentile.EstimationType) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Build a new instance similar to the current one except for the estimation type.
withInitialStepBoundFactor(double) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer
withKthSelector(KthSelector) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Median: Build a new instance similar to the current one except for the kthSelector instance specifically set.
withKthSelector(KthSelector) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Build a new instance similar to the current one except for the kthSelector instance specifically set.
withMaxIterations(int) - Method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter: Configure the maximum number of iterations.
withNaNStrategy(NaNStrategy) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Median: Build a new instance similar to the current one except for the NaN handling strategy.
withNaNStrategy(NaNStrategy) - Method in class org.apache.commons.math4.legacy.stat.descriptive.rank.Percentile: Build a new instance similar to the current one except for the NaN handling strategy.
withOrthoTolerance(double) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer: Modifies the given parameter.
withParameterRelativeTolerance(double) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer
withRankingThreshold(double) - Method in class org.apache.commons.math4.legacy.fitting.leastsquares.LevenbergMarquardtOptimizer
withStartPoint(double[]) - Method in class org.apache.commons.math4.legacy.fitting.SimpleCurveFitter: Configure the start point (initial guess).
writeBaseExternal(ObjectOutput) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator: Save the base state of the instance.
writeExternal(ObjectOutput) - Method in class org.apache.commons.math4.legacy.ode.sampling.AbstractStepInterpolator
writeExternal(ObjectOutput) - Method in class org.apache.commons.math4.legacy.ode.sampling.NordsieckStepInterpolator

Z

zero(Field<T>, int, int) - Static method in class org.apache.commons.math4.legacy.field.linalg.FieldDenseMatrix: Factory method.
ZERO - Static variable in class org.apache.commons.math4.legacy.linear.BigReal: A big real representing 0.

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