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Data X:
121.6 116.2 91.8 124.1 118.8 111.2 93.2 127.6 114.0 105.8 86.5 110.7 111.5 122.7 98.9 104.6 97.2 99.5 77.2 112.7 102.5 107.9 79.4 115.3 113.4 124.6 90.4 139.4 109.8 115.0 81.4 119.0 104.9 110.3 85.8 97.4 126.1 132.7 103.6 154.0 80.0 99.7 73.6 81.5 96.8 96.5 75.7 88.8 117.2 118.7 99.2 127.7 112.3 112.9 88.7 105.1 117.3 130.5 94.6 114.9 111.1 137.9 98.7 106.4 102.2 115.0 84.2 104.5 104.3 116.8 87.7 121.6 122.9 140.9 103.3 141.4 107.6 120.7 88.2 99.0 121.3 134.2 93.4 126.7 131.5 147.3 106.3 134.1 89.0 112.4 73.1 81.3 104.4 107.1 78.6 88.6 128.9 128.4 101.6 132.7 135.9 137.7 101.4 132.9 133.3 135.0 98.5 134.4 121.3 151.0 99.0 103.7 120.5 137.4 89.5 119.7 120.4 132.4 83.5 115.0 137.9 161.3 97.4 132.9 126.1 139.8 87.8 108.5 133.2 146.0 90.4 113.9 151.1 166.5 101.6 142.0 105.0 143.3 80.0 97.7 119.0 121.0 81.7 92.2 140.4 152.6 96.4 128.8 156.6 154.4 110.2 134.9 137.1 154.6 101.1 128.2 122.7 158.0 89.3 114.8 125.8 142.6 90.0 117.9 139.3 153.4 95.4 119.1 134.9 163.4 100.3 120.7 149.2 167.3 99.5 129.1 132.3 154.8 93.9 117.6 149.0 165.7 100.6 129.2 117.2 144.7 84.7 100.0 119.6 120.9 81.6 87.0 152.0 152.8 109.0 128.0 149.4 160.2 99.0 127.7 127.3 128.3 81.1 93.4 114.1 150.5 81.8 84.1 102.1 117.0 66.5 71.7 107.7 116.0 66.4 83.2 104.4 133.3 86.3 89.1 102.1 116.4 73.6 79.6 96.0 104.0 71.5 62.8 109.3 126.6 87.2 95.1 90.0 92.9 65.3 63.6 83.9 83.6 69.7 61.4
Names of X columns:
X1 X2 X3 X4
Type of Correlation
pearson
spearman
kendall
Chart options
Title:
R Code
panel.tau <- function(x, y, digits=2, prefix='', cex.cor) { usr <- par('usr'); on.exit(par(usr)) par(usr = c(0, 1, 0, 1)) rr <- cor.test(x, y, method='kendall') r <- round(rr$p.value,2) txt <- format(c(r, 0.123456789), digits=digits)[1] txt <- paste(prefix, txt, sep='') if(missing(cex.cor)) cex <- 0.5/strwidth(txt) text(0.5, 0.5, txt, cex = cex) } panel.hist <- function(x, ...) { usr <- par('usr'); on.exit(par(usr)) par(usr = c(usr[1:2], 0, 1.5) ) h <- hist(x, plot = FALSE) breaks <- h$breaks; nB <- length(breaks) y <- h$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Kendall tau rank correlations for all pairs of data series',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'pair',1,TRUE) a<-table.element(a,'tau',1,TRUE) a<-table.element(a,'p-value',1,TRUE) a<-table.row.end(a) n <- length(y[,1]) n cor.test(y[1,],y[2,],method='kendall') for (i in 1:(n-1)) { for (j in (i+1):n) { a<-table.row.start(a) dum <- paste('tau(',dimnames(t(x))[[2]][i]) dum <- paste(dum,',') dum <- paste(dum,dimnames(t(x))[[2]][j]) dum <- paste(dum,')') a<-table.element(a,dum,header=TRUE) r <- cor.test(y[i,],y[j,],method='kendall') a<-table.element(a,r$estimate) a<-table.element(a,r$p.value) a<-table.row.end(a) } } a<-table.end(a) table.save(a,file='mytable.tab')
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Big Analytics Cloud Computing Center
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