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(308347,1.8,298427,1.6,289231,1.9,291975,1.7,294912,1.6,293488,1.3,290555,1.1,284736,1.9,281818,2.6,287854,2.3,316263,2.4,325412,2.2,326011,2,328282,2.9,317480,2.6,317539,2.3,313737,2.3,312276,2.6,309391,3.1,302950,2.8,300316,2.5,304035,2.9,333476,3.1,337698,3.1,335932,3.2,323931,2.5,313927,2.6,314485,2.9,313218,2.6,309664,2.4,302963,1.7,298989,2,298423,2.2,301631,1.9,329765,1.6,335083,1.6,327616,1.2,309119,1.2,295916,1.5,291413,1.6,291542,1.7,284678,1.8,276475,1.8,272566,1.8,264981,1.3,263290,1.3,296806,1.4,303598,1.1,286994,1.5,276427,2.2,266424,2.9,267153,3.1,268381,3.5,262522,3.6,255542,4.4,253158,4.2,243803,5.2,250741,5.8,280445,5.9,285257,5.4,270976,5.5,261076,4.7,255603,3.1,260376,2.6,263903,2.3,264291,1.9,263276,0.6,262572,0.6,256167,-0.4,264221,-1.1,293860,-1.7,300713,-0.8),dim=c(2,72),dimnames=list(c('werkloosheidvrouwen','inflatie'),1:72))
>  y <- array(NA,dim=c(2,72),dimnames=list(c('werkloosheidvrouwen','inflatie'),1:72))
>  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/1ith41261625944.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] 2
> cor.test(y[1,],y[2,],method='kendall')

	Kendall's rank correlation tau

data:  y[1, ] and y[2, ] 
z = -0.2872, p-value = 0.774
alternative hypothesis: true tau is not equal to 0 
sample estimates:
        tau 
-0.02342924 

> 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/20izz1261625944.tab") 
> 
> try(system("convert tmp/1ith41261625944.ps tmp/1ith41261625944.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.383   0.194   0.492