R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- array(list(14.3,15.89,113,14.2,16.93,110,15.9,20.28,107,15.3,22.52,103,15.5,23.51,98,15.1,22.59,98,15,23.51,137,12.1,24.76,148,15.8,26.08,147,16.9,25.29,139,15.1,23.38,130,13.7,25.29,128,14.8,28.42,127,14.7,31.85,123,16,30.1,118,15.4,25.45,114,15,24.95,108,15.5,26.84,111,15.1,27.52,151,11.7,27.94,159,16.3,25.23,158,16.7,26.53,148,15,27.21,138,14.9,28.53,137,14.6,30.35,136,15.3,31.21,133,17.9,32.86,126,16.4,33.2,120,15.4,35.73,114,17.9,34.53,116,15.9,36.54,153,13.9,40.1,162,17.8,40.56,161,17.9,46.14,149,17.4,42.85,139,16.7,38.22,135,16,40.18,130,16.6,42.19,127,19.1,47.56,122,17.8,47.26,117,17.2,44.03,112,18.6,49.83,113,16.3,53.35,149,15.1,58.9,157,19.2,59.64,157,17.7,56.99,147,19.1,53.2,137,18,53.24,132,17.5,57.85,125,17.8,55.69,123,21.1,55.64,117,17.2,62.52,114,19.4,64.4,111,19.8,64.65,112,17.6,67.71,144,16.2,67.21,150,19.5,59.37,149,19.9,53.26,134,20,52.42,123,17.3,55.03,116),dim=c(3,60),dimnames=list(c('BuitlH','POil','WK<25j'),1:60))
>  y <- array(NA,dim=c(3,60),dimnames=list(c('BuitlH','POil','WK<25j'),1:60))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> main = 'Kendall tau Correlation Plot'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
+ {
+ usr <- par('usr'); on.exit(par(usr))
+ par(usr = c(0, 1, 0, 1))
+ rr <- cor.test(x, y, method='kendall')
+ r <- round(rr$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', ...)
+ }
> postscript(file="/var/www/html/rcomp/tmp/1jfne1261149716.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/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
[1] 3
> cor.test(y[1,],y[2,],method='kendall')

	Kendall's rank correlation tau

data:  y[1, ] and y[2, ] 
z = 5.5905, p-value = 2.264e-08
alternative hypothesis: true tau is not equal to 0 
sample estimates:
      tau 
0.4985869 

> 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="/var/www/html/rcomp/tmp/2tbm61261149716.tab") 
> 
> try(system("convert tmp/1jfne1261149716.ps tmp/1jfne1261149716.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.458   0.211   1.027