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Data X:
105.9 97.4 103.4 50.7 116.1 106.1 112.2 97.5 109.6 92.4 121.8 106.5 108.8 91.3 111.50 85.2 108.5 77.7 115.4 102.5 119.3 104.8 116.5 107.1 101.9 94 96.6 44.7 116.6 105.9 112.5 99 103.7 88.5 118.5 103.3 105 84 105 76.7 109.1 76.5 112.6 93.6 108.2 96.5 114.4 107.4 95.9 93.6 90.8 44.1 115 108.8 99.8 90.7 103 100.7 108.4 90.1 99.2 82.9 100.6 71.9 107.1 79.8 107 91.1 111.9 103.5 115.6 107.7 97.7 92.9 97.3 49.1 111.8 109.1 99.3 89.2 104.6 96 113.3 109.4 98.7 90.1 98.2 82.7 102.5 74.5 100.8 89.6 111.4 112.5 108.9 113.1 90.4 87.6 94.6 58.5 104.3 105 99 94 103 100.8 105.1 105.9 98.9 88.9 101 82.7 96.5 72.5 102.8 97.4 112.3 113.8 106.5 109.1
Names of X columns:
Excl Bouw
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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Big Analytics Cloud Computing Center
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