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Data X:
98.8 100.3 101.9 99.9 100.5 98.5 100.2 98.6 110.4 95.1 98.6 107.2 96.4 93.1 98.1 95.7 101.9 92.2 98.2 93.7 106.2 89.0 99.1 106.7 81.0 86.4 100.0 86.7 94.7 84.5 99.7 95.3 101.0 82.7 99.7 99.3 109.4 80.8 99.3 101.8 102.3 81.8 97.9 96.0 90.7 81.8 97.6 91.7 96.2 82.9 94.7 95.3 96.1 83.8 95.8 96.6 106.0 86.2 97.0 107.2 103.1 86.1 99.0 108.0 102.0 86.2 101.9 98.4 104.7 88.8 103.9 103.1 86.0 89.6 105.1 81.1 92.1 87.8 104.9 96.6 106.9 88.3 105.0 103.7 112.6 88.6 104.6 106.6 101.7 91.0 105.1 97.6 92.0 91.5 105.7 87.6 97.4 95.4 115.6 99.4 97.0 98.7 120.3 98.5 105.4 99.9 121.9 105.2 102.7 98.6 121.7 104.6 98.1 100.3 118.9 97.5 104.5 100.2 113.4 108.9 87.4 100.4 114.0 86.8 89.9 101.4 117.5 88.9 109.8 103.0 120.9 110.3 111.7 109.1 125.1 114.8 98.6 111.4 124.7 94.6 96.9 114.1 128.2 92.0 95.1 121.8 149.7 98.8 97.0 127.6 163.6 93.8 112.7 129.9 173.9 107.6 102.9 128.0 164.5 101.0 97.4 123.5 154.2 95.4 111.4 124.0 147.9 96.5 87.4 127.4 159.3 89.2 96.8 127.6 170.3 87.1 114.1 128.4 170.0 110.5 110.3 131.4 174.2 110.8 103.9 135.1 190.8 104.2 101.6 134.0 179.9 88.9 94.6 144.5 240.8 89.8 95.9 147.3 241.9 90.0 104.7 150.9 241.1 93.9 102.8 148.7 239.6 91.3 98.1 141.4 220.8 87.8 113.9 138.9 209.3 99.7 80.9 139.8 209.9 73.5 95.7 145.6 228.3 79.2 113.2 147.9 242.1 96.9 105.9 148.5 226.4 95.2 108.8 151.1 231.5 95.6 102.3 157.5 229.7 89.7
Names of X columns:
InTotIndProductie PrInGrondstofInd PrInGrondstofYzer InMetalProd
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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