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Data X:
16.4 18.0 94.3 6.9 17.8 19.6 99.4 6.6 22.3 23.3 115.7 6.9 22.8 23.7 116.8 7.5 18.3 20.3 99.8 7.9 22.4 22.8 96.0 7.7 23.9 24.3 115.9 6.5 21.3 21.5 109.1 6.1 23.0 23.5 117.3 6.4 21.4 22.2 109.8 6.8 21.2 20.9 112.8 7.1 20.9 22.2 110.7 7.3 17.9 19.5 100.0 7.2 20.7 21.1 113.3 7.0 22.2 22.0 122.4 7.0 19.8 19.2 112.5 7.0 17.7 17.8 104.2 7.3 19.6 19.2 92.5 7.5 20.8 19.9 117.2 7.2 19.8 19.6 109.3 7.7 18.6 18.1 106.1 8.0 21. 20.4 118.8 7.9 18.6 18.1 105.3 8.0 18.9 18.6 106.0 8.0 17.3 17.6 102.0 7.9 20.0 19.4 112.9 7.9 19.9 19.3 116.5 8.8 19.5 18.6 114.8 8.1 16.2 16.9 100.5 8.1 17.6 16.4 85.4 8.2 19.8 19.0 86.6 8.0 19.4 18.7 109.9 8.3 17.2 17.1 100.7 8.5 21.1 21.5 115.5 8.6 17.8 17.8 100.7 8.7 17.5 18.1 99.0 8.7 18.0 19.0 102.3 8.5 19.1 18.9 108.8 8.4 17.7 16.8 105.9 8.5 19.2 18.1 113.2 8.7 15.1 15.7 95.7 8.7 16.3 15.1 80.9 8.6 18.6 18.3 113.9 7.9 17.2 16.5 98.1 8.1 17.8 16.9 102.8 8.2 19.1 18.4 104.7 8.5 16.6 16.4 95.9 8.6 16.0 15.7 94.6 8.5 16.7 16.9 101.6 8.3 17.4 16.6 103.9 8.2 17.9 16.7 110.3 8.7 17.8 16.6 114.1 9.3 13.9 14.4 96.8 9.3 15.9 14.5 87.4 8.8 17.9 17.5 111.4 7.4 15.4 14.3 97.4 7.2 16.4 15.4 102.9 7.5 17.9 17.2 112.7 8.3 15.3 14.6 97.0 8.8 14.6 14.2 95.1 8.9 14.9 14.9 96.9 8.6 15.0 14.1 98.6 8.4 16.7 15.6 111.7 8.4 16.3 14.6 109.8 8.4 11.7 11.9 89.9 8.4 15.1 13.5 87.4 8.3 15.5 14.2 104.5 7.6 15.0 13.7 98.1 7.6 15.4 14.4 102.7 7.9 16.0 15.3 105.4 8.0 14.7 14.3 97.0 8.2 14.8 14.5 97.4 8.3
Names of X columns:
Import Export Industriele_productie Werkloosheid
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
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Big Analytics Cloud Computing Center
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