R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- array(list(15.4,19.5,10.8,19.5,27.2,24.5,12.8,17.3,12,15.8,22.3,28.2,15.5,18.1,24.1,26.9,18.1,11.6,23,16.4,22.5,22.6,25.4,30.3,22.4,15.3,16.9,13.1,19.8,24,14.4,14.6,18.8,25,16.4,19.7,15,18.7,16.1,7.4,14.7,30.7,10.1,28.3,22,14.8,12.7,17.5,16.7,23.4,32.6,24.6,17.6,16.9,22.4,22.9,34.3,20,21.1,23.5,27.9,18.3,26,19.7,17.5,21.4,23.6,14.6,24.6,20.3,12.4,11.7,18.2,25.8,9.8,17.5,17.6,22.1,16.2,22.2,13.6,16.7,11.9,23.2,16,16.6,13.9,19.5,10.6,16.3,24.1,29.7,18.5,22.6,24.2,22.5,22.6,18.3,31.4,24.8,17.6,17.5,34.3,19.6,29.3,25,28.8,13.3,27.3,21.7,25.9,23.3,35.6,16.3,27.4,16.6,21.1,23.2,30.2,21.2,27.6,20.2,24.6,17.1,26.9,15,21.1,20.6,19.9,17.6,25.5,18.2,23.7,24.5,14.6,14.5),dim=c(2,68),dimnames=list(c('textiel','vervaardiging'),1:68))
>  y <- array(NA,dim=c(2,68),dimnames=list(c('textiel','vervaardiging'),1:68))
>  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: Wessa P., (2007), Multivariate Correlation Matrix (v1.0.3) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_pairs.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description
> panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
+ {
+ usr <- par('usr'); on.exit(par(usr))
+ par(usr = c(0, 1, 0, 1))
+ rr <- cor.test(x, y, method='kendall')
+ r <- round(rr$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/18n381197985011.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 
> 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] 2
> cor.test(y[1,],y[2,],method='kendall')

	Kendall's rank correlation tau

data:  y[1, ] and y[2, ] 
z = 1.7104, p-value = 0.08719
alternative hypothesis: true tau is not equal to 0 
sample estimates:
      tau 
0.1425735 

> 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/273m11197985011.tab") 
> 
> system("convert tmp/18n381197985011.ps tmp/18n381197985011.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.652   0.184   0.702