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Data X:
85.6 92.81 88 75.6 89 59.04 88.4 48.7 97.5 72.81 95 111.7 104 91.81 101.8 119.5 99.4 68.07 107.6 103.4 103.2 49.16 118.9 96.3 103 124.61 126.9 96.6 91.2 109.89 106.3 110.4 85.9 110.51 109.2 104.4 80.7 114.77 104.6 110.7 86.7 92.37 100.8 93.6 80.7 103.63 92.1 114.8 81.5 90.43 86.4 74.9 83.4 65.86 96 69.8 83.5 83.33 98.5 104.2 89.5 94.49 112 109.3 85.8 68.98 113.9 92.7 77.4 55.46 120 91.7 67.5 132.89 126.7 84.4 63.7 121.71 112.8 94.5 59.4 127.01 116.2 103.6 62 134.04 110.6 105.9 62.4 106.48 105 108 58.1 117.55 101.2 119.9 58 101.61 99.3 84.5 56.3 82.66 101.9 76.7 61.4 89.28 106.4 120.5 59.8 109.24 118.9 119.6 54.3 88.16 121.9 102.3 47 59.23 132 101.7 50.5 164.21 121.4 86.9 48.1 125.13 117 93.6 58.8 152.68 122.7 113.6 70.4 132.96 113 106.7 71.9 112.42 104 96.1 73.3 136.43 101.2 124.6 83.5 107.32 100.8 72.5 90.1 87.61 98.9 89 101.3 97.86 103 115.3 98.3 106.60 117.8 119.1 106.7 92.17 126.6 104.4 109.9 65.31 127.6 104.9 111.1 161.49 115.8 76.9 119 162.25 114.8 95.3 120.7 175.13 119.2 114.9 104.5 147.28 109.9 98.9 121.6 144.48 98.9 102.9 129.6 122.67 98.6 90 124.5 102.27 96.6 81 130.1 88.64 96.7 66.2 142.3 89.59 103.5 86.7 140 112.20 115.3 86.7 143.3 91.98 122.5 103.4 113.4 57.85 125.3 89.5 113.8 160.49 111.2 113.7 120.7 128.33 110.7 120.2 112.9 140.69 114.2 137.8 115.5 126.61 105.6 99.1 121.9 129.27 95.5 110.4 119.3 124.27 97.3 112.3 111 112.90 95.5 82.2 114.2 92.54 96.3 72.2 113.5 85.70 100.2 106.7 94 116.72 113.4 106.4 83.2 92.08 121.4 110 82.8 58.98 122.1 87.5 85.8 154.50 119.3 79.7 88.7 145.55 110.8 83.3 105.3 146.60 110.1 91.8 113.1 143.51 99.7 89.2 113.8 113.52 104.8 90.6 109.4 104.80 105.4 92.6
Names of X columns:
olie wagens electric vervoersm
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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