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Data X:
100.00 100.00 100.00 100.00 101.25 98.20 117.87 95.00 96.25 90.09 113.95 117.50 93.75 82.88 107.33 107.50 95.00 82.88 104.96 97.50 97.50 85.59 97.73 100.00 97.50 86.49 99.07 107.50 97.50 85.59 108.16 120.00 93.75 81.98 106.20 110.00 93.75 80.18 101.34 107.50 88.75 81.08 117.67 117.50 93.75 90.99 83.57 117.50 93.75 92.79 98.86 122.50 95.00 91.89 116.94 125.00 96.25 86.49 109.40 105.00 96.25 82.88 112.40 107.50 98.75 83.78 105.68 120.00 101.25 84.68 102.27 120.00 102.50 84.68 104.03 120.00 102.50 82.88 119.32 105.00 102.50 81.08 104.03 115.00 98.75 81.08 113.53 120.00 91.25 81.08 118.39 112.50 86.25 88.29 88.22 110.00 82.50 90.09 103.82 107.50 83.75 88.29 118.60 97.50 86.25 83.78 120.35 92.50 87.50 81.08 116.63 100.00 88.75 81.08 105.37 102.50 90.00 81.98 109.50 92.50 88.75 81.98 108.78 95.00 86.25 81.98 122.73 95.00 87.50 82.88 109.61 95.00 85.00 79.28 112.91 82.50 80.00 74.77 121.07 82.50 83.75 75.68 95.56 82.50 82.50 72.97 107.64 80.00 80.00 69.37 116.22 85.00 78.75 71.17 126.45 105.00 77.50 71.17 117.05 122.50 81.25 72.07 103.31 127.50 85.00 71.17 114.36 137.50 85.00 68.47 116.53 140.00 80.00 63.96 113.43 160.00 76.25 61.26 121.18 152.50 72.50 58.56 112.71 177.50 76.25 62.16 119.73 195.00 90.00 73.87 99.17 197.50 91.25 78.38 103.10 185.00 86.25 74.77 120.66 187.50 76.25 71.17 119.52 170.00 72.50 67.57 102.69 130.00 77.50 70.27 97.42 117.50 88.75 74.77 94.01 102.50 96.25 75.68 96.28 97.50 98.75 73.87 106.51 65.00 96.25 69.37 97.21 67.50 92.50 64.86 94.83 45.00 93.75 65.77 106.10 25.00 100.00 72.97 85.33 7.50
Names of X columns:
werklhmannen werklhvrouwen ecogroei inflatie
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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