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(493.000,58.972,481.000,59.249,462.000,63.955,457.000,53.785,442.000,52.760,439.000,44.795,488.000,37.348,521.000,32.370,501.000,32.717,485.000,40.974,464.000,33.591,460.000,21.124,467.000,58.608,460.000,46.865,448.000,51.378,443.000,46.235,436.000,47.206,431.000,45.382,484.000,41.227,510.000,33.795,513.000,31.295,503.000,42.625,471.000,33.625,471.000,21.538,476.000,56.421,475.000,53.152,470.000,53.536,461.000,52.408,455.000,41.454,456.000,38.271,517.000,35.306,525.000,26.414,523.000,31.917,519.000,38.030,509.000,27.534,512.000,18.387,519.000,50.556,517.000,43.901,510.000,48.572,509.000,43.899,501.000,37.532,507.000,40.357,569.000,35.489,580.000,29.027,578.000,34.485,565.000,42.598,547.000,30.306,555.000,26.451,562.000,47.460,561.000,50.104,555.000,61.465,544.000,53.726,537.000,39.477,543.000,43.895,594.000,31.481,611.000,29.896,613.000,33.842,611.000,39.120,594.000,33.702,595.000,25.094),dim=c(2,60),dimnames=list(c('werkloosheid','nieuwewagens'),1:60))
>  y <- array(NA,dim=c(2,60),dimnames=list(c('werkloosheid','nieuwewagens'),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: 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/1aez21228473258.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 = -3.011, p-value = 0.002604
alternative hypothesis: true tau is not equal to 0 
sample estimates:
       tau 
-0.2674232 

> 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/24i811228473258.tab") 
> 
> system("convert tmp/1aez21228473258.ps tmp/1aez21228473258.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.412   0.187   0.492