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Data X:
1 1.6 105.4 168802 -0.8 1.7 104.4 173276 -2.9 1.6 104.9 172957 -0.7 1.4 106.9 173558 -0.7 2.1 107.6 173820 1.5 1.9 106.5 171663 3 1.7 106 174110 3.2 1.8 106.5 174338 3.1 2 105.9 175440 3.9 2.5 104.3 174922 1 2.1 103.8 172188 1.3 2.1 102.7 171330 0.8 2.3 103.2 169560 1.2 2.4 103.5 174579 2.9 2.4 104.5 173740 3.9 2.3 103.5 173427 4.5 1.7 103.8 172952 4.5 2 102.6 170305 3.3 2.3 102.1 172717 2 2 105.1 173019 1.5 2 106.2 173690 1 1.3 106.5 172439 2.1 1.7 106.3 171914 3 1.9 107.6 171968 4 1.7 107.4 169500 5.1 1.6 109.2 173898 4.5 1.7 108.5 172308 4.2 1.8 107 171568 3.3 1.9 107.8 164939 2.7 1.9 109.7 161275 1.8 1.9 110.6 160770 1.4 2 110.9 162466 0.5 2.1 111.7 160185 -0.4 1.9 111.2 154836 0.8 1.9 110.2 154103 0.7 1.3 112.5 150495 1.9 1.3 111.6 142707 2 1.4 111.2 149962 1.1 1.2 112.6 149967 0.9 1.3 113.1 144572 0.4 1.8 111.8 143819 0.7 2.2 106.3 141070 2.1 2.6 115 144119 2.8 2.8 114 145330 3.9 3.1 113.1 143279 3.5 3.9 114.9 139063 2 3.7 115.5 139202 2 4.6 113.8 133632 1.5 5.1 114.7 134476 2.5 5.2 114.2 141859 3.1 4.9 112.9 140693 2.7 5.1 112.1 138047 2.8 4.8 111.1 138346 2.5 3.9 109.2 140167 3 3.5 106.6 146796 3.2 3.3 104.1 152228 2.8 2.8 103.2 155410 2.4 1.6 91.2 159032 2 1.5 93.6 160312 1.8 0.7 93.9 157687 1.1 -0.1 93.8 160141 -1.5 -0.7 93.8 167421 -3.7 -0.2 93.8 167628 -4.2 -0.6 94.3 164403 -3.5 -0.6 94.5 163405
Names of X columns:
bbp cpi productie werkzoekenden
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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