R version 2.6.1 (2007-11-26)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- array(list(513,6.6,87,503,7.8,75,471,7.4,74,471,7.4,91,476,7.5,101,475,7.4,103,470,7.4,106,461,7,102,455,6.9,105,456,6.9,105,517,7.6,100,525,7.7,95,523,7.6,96,519,8.2,98,509,8,99,512,8.1,92,519,8.3,84,517,8.2,81,510,8.1,72,509,7.7,89,501,7.6,96,507,7.7,91,569,8.2,88,580,8.4,90,578,8.4,98,565,8.6,87,547,8.4,100,555,8.5,100,562,8.7,104,561,8.7,107,555,8.6,105,544,7.4,102,537,7.3,98,543,7.4,106,594,9,97,611,9.2,101,613,9.2,100,611,8.5,93,594,8.3,94,595,8.3,96,591,8.6,96,589,8.6,98,584,8.5,102,573,8.1,95,567,8.1,85,569,8,84,621,8.6,82,629,8.7,87,628,8.7,77,612,8.6,90,595,8.4,90,597,8.4,94,593,8.7,97,590,8.7,96,580,8.5,93,574,8.3,93,573,8.3,93,573,8.3,97,620,8.1,100,626,8.2,95,620,8.1,97,588,8.1,103,566,7.9,102,557,7.7,93,561,8.1,99,549,8,100,532,7.7,97,526,7.8,104,511,7.6,102,499,7.4,103,555,7.7,100,565,7.8,90,542,7.5,90),dim=c(3,73),dimnames=list(c('WLoos','WZoeken','Econ'),1:73))
>  y <- array(NA,dim=c(3,73),dimnames=list(c('WLoos','WZoeken','Econ'),1:73))
>  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/1w4441198167226.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] 3
> cor.test(y[1,],y[2,],method='kendall')

	Kendall's rank correlation tau

data:  y[1, ] and y[2, ] 
z = 7.3538, p-value = 1.925e-13
alternative hypothesis: true tau is not equal to 0 
sample estimates:
      tau 
0.6046687 

> 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/2gwe51198167227.tab") 
> 
> system("convert tmp/1w4441198167226.ps tmp/1w4441198167226.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.115   0.573   2.189