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(9.3,96.8,4,9.3,114.1,3.8,8.7,110.3,4.7,8.2,103.9,4.3,8.3,101.6,3.9,8.5,94.6,4,8.6,95.9,4.3,8.5,104.7,4.8,8.2,102.8,4.4,8.1,98.1,4.3,7.9,113.9,4.7,8.6,80.9,4.7,8.7,95.7,4.9,8.7,113.2,5,8.5,105.9,4.2,8.4,108.8,4.3,8.5,102.3,4.8,8.7,99,4.8,8.7,100.7,4.8,8.6,115.5,4.2,8.5,100.7,4.6,8.3,109.9,4.8,8,114.6,4.5,8.2,85.4,4.4,8.1,100.5,4.3,8.1,114.8,3.9,8,116.5,3.7,7.9,112.9,4,7.9,102,4.1,8,106,3.7,8,105.3,3.8,7.9,118.8,3.8,8,106.1,3.8,7.7,109.3,3.3,7.2,117.2,3.3,7.5,92.5,3.3,7.3,104.2,3.2,7,112.5,3.4,7,122.4,4.2,7,113.3,4.9,7.2,100,5.1,7.3,110.7,5.5,7.1,112.8,5.6,6.8,109.8,6.4,6.4,117.3,6.1,6.1,109.1,7.1,6.5,115.9,7.8,7.7,96,7.9,7.9,99.8,7.4,7.5,116.8,7.5,6.9,115.7,6.8,6.6,99.4,5.2,6.9,94.3,4.7,7.7,91,4.1,8,93.2,3.9,8,103.1,2.6,7.7,94.1,2.7,7.3,91.8,1.8,7.4,102.7,1,8.1,82.6,0.3),dim=c(3,60),dimnames=list(c('werklh','ecogr','inflatie'),1:60))
>  y <- array(NA,dim=c(3,60),dimnames=list(c('werklh','ecogr','inflatie'),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/1q69x1261053296.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 = -1.9761, p-value = 0.04814
alternative hypothesis: true tau is not equal to 0 
sample estimates:
       tau 
-0.1787110 

> 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/29lft1261053296.tab") 
> 
> try(system("convert tmp/1q69x1261053296.ps tmp/1q69x1261053296.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.437   0.185   0.514