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Data X:
112.6 105.1 88.8 120.3 113.8 113.3 93.4 133.4 107.8 99.1 92.6 109.4 103.2 100.3 90.7 93.2 103.3 93.5 81.6 91.2 101.2 98.8 84.1 99.2 107.7 106.2 88.1 108.2 110.4 98.3 85.3 101.5 101.9 102.1 82.9 106.9 115.9 117.1 84.8 104.4 89.9 101.5 71.2 77.9 88.6 80.5 68.9 60 117.2 105.9 94.3 99.5 123.9 109.5 97.6 95 100 97.2 85.6 105.6 103.6 114.5 91.9 102.5 94.1 93.5 75.8 93.3 98.7 100.9 79.8 97.3 119.5 121.1 99 127 112.7 116.5 88.5 111.7 104.4 109.3 86.7 96.4 124.7 118.1 97.9 133 89.1 108.3 94.3 72.2 97 105.4 72.9 95.8 121.6 116.2 91.8 124.1 118.8 111.2 93.2 127.6 114 105.8 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 81.4 119 104.9 110.3 85.8 97.4 126.1 132.7 103.6 154 80 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 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 99 121.3 134.2 93.4 126.7 131.5 147.3 106.3 134.1 89 112.4 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 98.5 134.4 121.3 151 99 103.7 120.5 137.4 89.5 119.7 120.4 132.4 83.5 115 137.9 161.3 97.4 132.9 126.1 139.8 87.8 108.5 133.2 146 90.4 113.9 146.6 154.6 97.1 142.9 103.4 142.1 79.4 95.2 117.2 120.5 85 93
Names of X columns:
Prod. Mach. El.Mach. Trans.
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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1 seconds
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Big Analytics Cloud Computing Center
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