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Data X:
130 87.1 122.6 100.0 136.7 110.5 115.4 120.3 138.1 110.8 109 130.5 139.5 104.2 129.1 118.4 140.4 88.9 102.8 114.7 144.6 89.8 96.2 110.2 151.4 90 127.7 111.4 147.9 93.9 128.9 100.9 141.5 91.3 126.5 88.7 143.8 87.8 119.8 118.2 143.6 99.7 113.2 129.5 150.5 73.5 114.1 119.2 150.1 79.2 134.1 109.8 154.9 96.9 130 117.4 162.1 95.2 121.8 143.4 176.7 95.6 132.1 162.2 186.6 89.7 105.3 148.8 194.8 92.8 103 130.5 196.3 88 117.1 166.0 228.8 101.1 126.3 143.3 267.2 92.7 138.1 139.6 237.2 95.8 119.5 171.4 254.7 103.8 138 164.7 258.2 81.8 135.5 166.3 257.9 87.1 178.6 156.2 269.6 105.9 162.2 170.4 266.9 108.1 176.9 161.5 269.6 102.6 204.9 184.3 253.9 93.7 132.2 164.3 258.6 103.5 142.5 175.2 274.2 100.6 164.3 173.1 301.5 113.3 174.9 132.7 304.5 102.4 175.4 136.2 285.1 102.1 143 163.3 287.7 106.9 158.7 160.3 265.5 87.3 155.4 175.5 264.1 93.1 176.6 159.1 276.1 109.1 163.3 164.9 258.9 120.3 178.9 171.7 239.1 104.9 182.7 222.1 250.1 92.6 158.9 195.7 276.8 109.8 115.5 235.2 297.6 111.4 169.4 233.4 295.4 117.9 168 189.1 283 121.6 159.8 230.1 275.8 117.8 129 254.1 279.7 124.2 157.9 260.2 254.6 106.8 169.5 270.3 234.6 102.7 169.1 229.6 176.9 116.8 183.6 277.6 148.1 113.6 168.9 259.0 122.7 96.1 186.2 301.3 124.9 85 227.1 271.5 121.6 83.2 126.4 287.1 128.4 84.9 169.3 295.6 144.5 83 175 273.8 151.8 79.6 133.9 257.9 167.1 83.2 110.1 245.6 173.8 83.8 104.3 278.5 203.7 82.8 108.7 241.5 199.8 71.4 112.6 215.5
Names of X columns:
prijs prod omzet invoer
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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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