# Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # #------------------------------------------------------------------------------ # R source file to validate Pearson's correlation tests in # org.apache.commons.math.stat.correlation.PearsonsCorrelationTest # # To run the test, install R, put this file and testFunctions # into the same directory, launch R from this directory and then enter # source("") # #------------------------------------------------------------------------------ tol <- 1E-15 # error tolerance for tests #------------------------------------------------------------------------------ # Function definitions source("testFunctions") # utility test functions options(digits=16) # override number of digits displayed # Verify Pearson's correlation verifyPearsonsCorrelation <- function(matrix, expectedCorrelation, name) { correlation <- cor(matrix) output <- c("Pearson's Correlation matrix test dataset = ", name) if (assertEquals(expectedCorrelation, correlation,tol,"Pearson's Correlations")) { displayPadded(output, SUCCEEDED, WIDTH) } else { displayPadded(output, FAILED, WIDTH) } } # Verify Spearman's correlation verifySpearmansCorrelation <- function(matrix, expectedCorrelation, name) { correlation <- cor(matrix, method="spearman") output <- c("Spearman's Correlation matrix test dataset = ", name) if (assertEquals(expectedCorrelation, correlation,tol,"Spearman's Correlations")) { displayPadded(output, SUCCEEDED, WIDTH) } else { displayPadded(output, FAILED, WIDTH) } } # function to verify p-values verifyPValues <- function(matrix, pValues, name) { dimension <- dim(matrix)[2] corValues <- matrix(nrow=dimension,ncol=dimension) expectedValues <- matrix(nrow=dimension,ncol=dimension) for (i in 2:dimension) { for (j in 1:(i-1)) { corValues[i,j]<-cor.test(matrix[,i], matrix[,j])$p.value corValues[j,i]<-corValues[i,j] } } for (i in 1:dimension) { corValues[i,i] <- 1 expectedValues[i,i] <- 1 } ptr <- 1 for (i in 2:dimension) { for (j in 1:(i-1)) { expectedValues[i,j] <- pValues[ptr] expectedValues[j,i] <- expectedValues[i,j] ptr <- ptr + 1 } } output <- c("Correlation p-values test dataset = ", name) if (assertEquals(expectedValues, corValues,tol,"p-values")) { displayPadded(output, SUCCEEDED, WIDTH) } else { displayPadded(output, FAILED, WIDTH) } } #-------------------------------------------------------------------------- cat("Correlation test cases\n") # Longley ----------------------------------------------------------------- longley <- matrix(c(60323,83.0,234289,2356,1590,107608,1947, 61122,88.5,259426,2325,1456,108632,1948, 60171,88.2,258054,3682,1616,109773,1949, 61187,89.5,284599,3351,1650,110929,1950, 63221,96.2,328975,2099,3099,112075,1951, 63639,98.1,346999,1932,3594,113270,1952, 64989,99.0,365385,1870,3547,115094,1953, 63761,100.0,363112,3578,3350,116219,1954, 66019,101.2,397469,2904,3048,117388,1955, 67857,104.6,419180,2822,2857,118734,1956, 68169,108.4,442769,2936,2798,120445,1957, 66513,110.8,444546,4681,2637,121950,1958, 68655,112.6,482704,3813,2552,123366,1959, 69564,114.2,502601,3931,2514,125368,1960, 69331,115.7,518173,4806,2572,127852,1961, 70551,116.9,554894,4007,2827,130081,1962), nrow = 16, ncol = 7, byrow = TRUE) # Pearson's expectedCorrelation <- matrix(c( 1.000000000000000, 0.9708985250610560, 0.9835516111796693, 0.5024980838759942, 0.4573073999764817, 0.960390571594376, 0.9713294591921188, 0.970898525061056, 1.0000000000000000, 0.9915891780247822, 0.6206333925590966, 0.4647441876006747, 0.979163432977498, 0.9911491900672053, 0.983551611179669, 0.9915891780247822, 1.0000000000000000, 0.6042609398895580, 0.4464367918926265, 0.991090069458478, 0.9952734837647849, 0.502498083875994, 0.6206333925590966, 0.6042609398895580, 1.0000000000000000, -0.1774206295018783, 0.686551516365312, 0.6682566045621746, 0.457307399976482, 0.4647441876006747, 0.4464367918926265, -0.1774206295018783, 1.0000000000000000, 0.364416267189032, 0.4172451498349454, 0.960390571594376, 0.9791634329774981, 0.9910900694584777, 0.6865515163653120, 0.3644162671890320, 1.000000000000000, 0.9939528462329257, 0.971329459192119, 0.9911491900672053, 0.9952734837647849, 0.6682566045621746, 0.4172451498349454, 0.993952846232926, 1.0000000000000000), nrow = 7, ncol = 7, byrow = TRUE) verifyPearsonsCorrelation(longley, expectedCorrelation, "longley") expectedPValues <- c( 4.38904690369668e-10, 8.36353208910623e-12, 7.8159700933611e-14, 0.0472894097790304, 0.01030636128354301, 0.01316878049026582, 0.0749178049642416, 0.06971758330341182, 0.0830166169296545, 0.510948586323452, 3.693245043123738e-09, 4.327782576751815e-11, 1.167954621905665e-13, 0.00331028281967516, 0.1652293725106684, 3.95834476307755e-10, 1.114663916723657e-13, 1.332267629550188e-15, 0.00466039138541463, 0.1078477071581498, 7.771561172376096e-15) verifyPValues(longley, expectedPValues, "longley") # Spearman's expectedCorrelation <- matrix(c( 1, 0.982352941176471, 0.985294117647059, 0.564705882352941, 0.2264705882352941, 0.976470588235294, 0.976470588235294, 0.982352941176471, 1, 0.997058823529412, 0.664705882352941, 0.2205882352941176, 0.997058823529412, 0.997058823529412, 0.985294117647059, 0.997058823529412, 1, 0.638235294117647, 0.2235294117647059, 0.9941176470588236, 0.9941176470588236, 0.564705882352941, 0.664705882352941, 0.638235294117647, 1, -0.3411764705882353, 0.685294117647059, 0.685294117647059, 0.2264705882352941, 0.2205882352941176, 0.2235294117647059, -0.3411764705882353, 1, 0.2264705882352941, 0.2264705882352941, 0.976470588235294, 0.997058823529412, 0.9941176470588236, 0.685294117647059, 0.2264705882352941, 1, 1, 0.976470588235294, 0.997058823529412, 0.9941176470588236, 0.685294117647059, 0.2264705882352941, 1, 1), nrow = 7, ncol = 7, byrow = TRUE) verifySpearmansCorrelation(longley, expectedCorrelation, "longley") # Swiss Fertility --------------------------------------------------------- fertility <- matrix(c(80.2,17.0,15,12,9.96, 83.1,45.1,6,9,84.84, 92.5,39.7,5,5,93.40, 85.8,36.5,12,7,33.77, 76.9,43.5,17,15,5.16, 76.1,35.3,9,7,90.57, 83.8,70.2,16,7,92.85, 92.4,67.8,14,8,97.16, 82.4,53.3,12,7,97.67, 82.9,45.2,16,13,91.38, 87.1,64.5,14,6,98.61, 64.1,62.0,21,12,8.52, 66.9,67.5,14,7,2.27, 68.9,60.7,19,12,4.43, 61.7,69.3,22,5,2.82, 68.3,72.6,18,2,24.20, 71.7,34.0,17,8,3.30, 55.7,19.4,26,28,12.11, 54.3,15.2,31,20,2.15, 65.1,73.0,19,9,2.84, 65.5,59.8,22,10,5.23, 65.0,55.1,14,3,4.52, 56.6,50.9,22,12,15.14, 57.4,54.1,20,6,4.20, 72.5,71.2,12,1,2.40, 74.2,58.1,14,8,5.23, 72.0,63.5,6,3,2.56, 60.5,60.8,16,10,7.72, 58.3,26.8,25,19,18.46, 65.4,49.5,15,8,6.10, 75.5,85.9,3,2,99.71, 69.3,84.9,7,6,99.68, 77.3,89.7,5,2,100.00, 70.5,78.2,12,6,98.96, 79.4,64.9,7,3,98.22, 65.0,75.9,9,9,99.06, 92.2,84.6,3,3,99.46, 79.3,63.1,13,13,96.83, 70.4,38.4,26,12,5.62, 65.7,7.7,29,11,13.79, 72.7,16.7,22,13,11.22, 64.4,17.6,35,32,16.92, 77.6,37.6,15,7,4.97, 67.6,18.7,25,7,8.65, 35.0,1.2,37,53,42.34, 44.7,46.6,16,29,50.43, 42.8,27.7,22,29,58.33), nrow = 47, ncol = 5, byrow = TRUE) # Pearson's expectedCorrelation <- matrix(c( 1, 0.3530791836199747, -0.6458827064572875, -0.663788857035069, 0.463684700651794, 0.3530791836199747, 1, -0.6865422086171366, -0.63952251894832, 0.4010950530487398, -0.6458827064572875, -0.6865422086171366, 1, 0.698415296288483, -0.572741806064167, -0.663788857035069, -0.63952251894832, 0.698415296288483, 1, -0.1538589170909148, 0.463684700651794, 0.4010950530487398, -0.572741806064167, -0.1538589170909148, 1), nrow = 5, ncol = 5, byrow = TRUE) verifyPearsonsCorrelation(fertility, expectedCorrelation, "swiss fertility") expectedPValues <- c( 0.01491720061472623, 9.45043734069043e-07, 9.95151527133974e-08, 3.658616965962355e-07, 1.304590105694471e-06, 4.811397236181847e-08, 0.001028523190118147, 0.005204433539191644, 2.588307925380906e-05, 0.301807756132683) verifyPValues(fertility, expectedPValues, "swiss fertility") # Spearman's expectedCorrelation <- matrix(c( 1, 0.2426642769364176, -0.660902996352354, -0.443257690360988, 0.4136455623012432, 0.2426642769364176, 1, -0.598859938748963, -0.650463814145816, 0.2886878090882852, -0.660902996352354, -0.598859938748963, 1, 0.674603831406147, -0.4750575257171745, -0.443257690360988, -0.650463814145816, 0.674603831406147, 1, -0.1444163088302244, 0.4136455623012432, 0.2886878090882852, -0.4750575257171745, -0.1444163088302244, 1), nrow = 5, ncol = 5, byrow = TRUE) verifySpearmansCorrelation(fertility, expectedCorrelation, "swiss fertility") displayDashes(WIDTH)