R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- array(list(4.8,19.2,3,5.5,26.6,3.5,5.4,26.6,3.9,5.9,31.4,4.4,5.8,31.2,3.5,5.1,26.4,4.7,4.1,20.7,1.6,4.4,20.7,2.3,3.6,15,1.2,3.5,13.3,1.4,3.1,8.7,2.7,2.9,10.2,1.5,2.2,4.3,2.1,1.4,-0.1,0.5,1.2,-4.6,1.7,1.3,-3.9,3.6,1.3,-3.5,3.2,1.3,-3.4,1.7,1.8,-2.5,5.6,1.8,-1.1,3.7,1.8,0.3,4.3,1.7,-0.9,5.9,2.1,3.6,4.8,2,2.7,6,1.7,-0.2,5.6,1.9,-1,6.7,2.3,5.8,3.3,2.4,6.4,3,2.5,9.6,1.6,2.8,13.2,1.7,2.6,10.6,1.1,2.2,10.9,-0.3,2.8,12.9,3,2.8,15.9,2.7,2.8,12.2,1.8,2.3,9.1,1.5,2.2,9,1,3,17.4,0.5,2.9,14.7,2.8,2.7,17,1.4,2.7,13.7,1.7,2.3,9.5,2.6,2.4,14.8,1.9,2.8,13.6,3.9,2.3,12.6,1.5,2,8.9,-0.5,1.9,10.2,1.9,2.3,12.7,1,2.7,16,0.1,1.8,10.4,-3.1,2,9.9,-0.8,2.1,9.5,0.7,2,8.6,1.4,2.4,10,2.8,1.7,3.5,1.9,1,-4.2,1.1,1.2,-4.4,1.4,1.4,-1.5,2.9,1.7,-0.1,2.9,1.8,0.8,2.9),dim=c(3,60),dimnames=list(c('Totaal','Energiedragers','onbewerktebewerkte_levensmiddelen'),1:60))
>  y <- array(NA,dim=c(3,60),dimnames=list(c('Totaal','Energiedragers','onbewerktebewerkte_levensmiddelen'),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/1ex6s1229000748.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 = 8.6263, p-value < 2.2e-16
alternative hypothesis: true tau is not equal to 0 
sample estimates:
      tau 
0.7768486 

> 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/2a3mg1229000748.tab") 
> 
> system("convert tmp/1ex6s1229000748.ps tmp/1ex6s1229000748.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.441   0.208   0.505