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Data X:
100.6 115.9 59.7 125 96.1 112.9 58.2 121.7 110 126.3 75.3 134.3 108.2 116.8 69 124.3 106.9 112 66.1 119.1 117.2 129.7 77.5 137.8 105.2 113.6 69.3 120.5 106.3 115.7 70.2 122.7 95.9 119.5 70.2 127.2 107.5 125.8 78.2 133.2 113 129.6 85.4 136.3 111.4 128 82.4 134.9 95.5 112.8 61.2 120.9 90.3 101.6 52.2 109.4 110.8 123.9 85.3 129.6 107.1 118.8 79.9 124.7 101.4 109.1 72.2 114.6 112.9 130.6 85.7 137.4 98.5 112.4 75.5 117.9 100.1 111 69.2 117.4 93.4 116.2 77.6 122 104.4 119.8 85.3 124.8 101.8 117.2 77 123.3 107.9 127.3 89.9 132.8 91.3 107.7 60 115.1 86.6 97.5 54.3 104.2 111.4 120.1 84 125.5 98.4 110.6 69.9 116.8 102.2 111.3 75.1 116.8 103 119.8 81.7 125.5 95.8 105.5 69.9 110.9 96 108.7 68.3 114.9 95.7 128.7 77.3 136.4 106.4 119.5 77.4 125.8 112 121.1 85.3 126.5 116.2 128.4 91 134 93.9 108.8 60.6 116.1 100.5 107.5 57.6 115 112.5 125.6 93.8 130.3 101.2 102.9 78.7 106.5 107.8 107.5 80.3 111.6 114.3 120.4 89.8 125 99.6 104.3 77.5 108.3 98.6 100.6 71.7 105 93.6 121.9 83.2 127.4 99.6 112.7 86.2 116.6 113.1 124.9 100.7 128.6 110.7 123.9 100.8 127.5 88.1 102.2 57.1 108.4 93.1 104.9 62.5 110.8 107.4 109.8 79.7 114.2 99.5 98.9 80.3 101.8 105.6 107.3 92.4 109.8 108.3 112.6 91.8 115.9 99.2 104 85.8 106.9 99.3 110.6 84.2 114.6 107.1 100.8 93.1 105.4 106.9 103.8 101.2 108.1 115.4 117 100.6 118.4 99 108.4 106.7 112.7 100.1 95.5 64 98.4 96.2 96.9 67.5 99.6 96.9 103.9 101 103.9 96.2 101.1 95.5 101.5 91 100.6 97 100.8 99 104.3 103.8 104.5 99 98 95.2 98.2 107.2 99.5 86.7 99.9 110.8 97.4 93.5 97.5 111.1 105.6 102.5 105.7 104.6 117.5 112.3 117.7 94.3 107.4 105.5 107.4 90.7 97.8 75.4 98.4 88.8 91.5 70.4 92 90.9 107.7 108 107.7 90.5 100.1 100 100.2 95.5 96.6 93.3 96.7 103.1 106.8 111.1 106.8 100.6 98 101.1 98 103.1 98.6 98.1 98.6
Names of X columns:
intermediare consumptiegoed duurzaam niet-duurzaam
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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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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