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(-2.9,4.6,0.8,5.5,-7.7,10.1,-3.8,4.2,-5.3,-7.8,-1.9,-7,6,0.4,14.2,1.2,-3.1,-9.2,0,-5.8,-1.8,-2.5,2.1,-4.3,14.4,11.8,14.9,10.9,8.2,2.3,18.2,3.2,0.3,2.5,7.2,3.8,14.2,8.8,1,13.1,6,-0.8,6.8,23.1,18.1,8.4,24.9,4,9.4,4.4,10.3,-2.5,7.1,-5.1,1.7,-4.4,6.9,14,8.6,0.9,6.1,7.9,8.2,7,7.7,3.1,6,1.4,7.2,3.8,7,-0.4,0.2,-6.1,3.5,-8.6,-1,-2.9,-1.5,-7.1,0.5,0.5,1,-0.9,10.7,1.4,14.6,5.7,-7,-9.1,-8.6,-20.7,-3,-0.2,-8.9,2.8,2.6,-4.4,2.5,7.4,-8.9,-6.5,1.7,-4.5,9.3,3.3,24.7,8.1,3.5,-0.4,15.2,-0.2,4.1,5,15.5,7,6.3,1.8,8.9,8.3,9.7,9.5,16.3,12.9,-2.9,-2.2,5.7,6.8,18.9,16.4,23.9,7.6,-0.6,5.4,14.6,2.7,4.5,9,12.7,-0.5,4.9,7.6,10.6,2.9,6.8,11.7,9.7,2.4,22,23.6,24.8,12.7,11.2,16,4.5,3.9,4.5,10.2,13.1,0.3,14.4,18.3,22.4,5.3,3.8,16.1,15.6,-4.2,3.3,15,20.4,-5.9,10.4,18.5,19.1,-0.4,0.6,11.9,11.8,-3,4.7,15.1,7.3,-9.2,14.6,14.4,29.7,6.3,8.6,12.8,13.4,6.4),dim=c(4,48),dimnames=list(c('Totaal','Metaal','Machines','Elektr.Instrumenten'),1:48))
>  y <- array(NA,dim=c(4,48),dimnames=list(c('Totaal','Metaal','Machines','Elektr.Instrumenten'),1:48))
>  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/1hd3z1196107905.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)
Warning messages:
1: In cor.test.default(x, y, method = "kendall") :
  Cannot compute exact p-value with ties
2: In cor.test.default(x, y, method = "kendall") :
  Cannot compute exact p-value with ties
3: In cor.test.default(x, y, method = "kendall") :
  Cannot compute exact p-value with ties
4: In cor.test.default(x, y, method = "kendall") :
  Cannot compute exact p-value with ties
5: In cor.test.default(x, y, method = "kendall") :
  Cannot compute exact p-value with ties
6: In cor.test.default(x, y, method = "kendall") :
  Cannot compute exact p-value with ties
> 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] 4
> cor.test(y[1,],y[2,],method='kendall')

	Kendall's rank correlation tau

data:  y[1, ] and y[2, ] 
z = 4.3558, p-value = 1.326e-05
alternative hypothesis: true tau is not equal to 0 
sample estimates:
      tau 
0.4351694 

Warning message:
In cor.test.default(y[1, ], y[2, ], method = "kendall") :
  Cannot compute exact p-value with ties
> 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)
+ }
+ }
Warning messages:
1: In cor.test.default(y[i, ], y[j, ], method = "kendall") :
  Cannot compute exact p-value with ties
2: In cor.test.default(y[i, ], y[j, ], method = "kendall") :
  Cannot compute exact p-value with ties
3: In cor.test.default(y[i, ], y[j, ], method = "kendall") :
  Cannot compute exact p-value with ties
4: In cor.test.default(y[i, ], y[j, ], method = "kendall") :
  Cannot compute exact p-value with ties
5: In cor.test.default(y[i, ], y[j, ], method = "kendall") :
  Cannot compute exact p-value with ties
6: In cor.test.default(y[i, ], y[j, ], method = "kendall") :
  Cannot compute exact p-value with ties
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/22jnn1196107905.tab") 
> 
> system("convert tmp/1hd3z1196107905.ps tmp/1hd3z1196107905.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.727   0.212   0.799