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(86.5,98.5,109.2,104.1,99.3,126.3,110.9,98,104,114.5,98.1,96,112.2,98,262,96.4,96.5,89.8,92,96.1,86,102,96.3,92.7,99.7,96.1,126.8,102,95.4,92.8,98.9,95.3,87.8,87.4,93.9,100,94.4,94,72.4,109.3,93.6,104.9,116.4,93.5,52.3,101,93.5,65.3,105.5,93.5,110.2,97.8,93,54.4,95.5,93.1,47.5,113.7,93.3,65.2,103.7,93.2,69.8,100.8,93.1,53.6,113.8,93.1,116.1,84.6,93.2,56.6,95.3,93,47.2,110,93.1,90.6,107.5,93.2,60.4,107.6,93.1,59.3,116,93.1,131.6,96.9,93.1,59.4,97,92.3,65.5,108.1,92.3,70.5,101.9,92.3,81,107.2,92.3,73.3,110.2,92.1,107.5,78.7,92.1,88.9,96.5,92.1,55.8,115.2,92,80.5,104.7,92,86.3,109.1,92.3,112.6,108.4,93.3,148.6,95.5,92.4,47.1,97.8,92.6,57.8,115.1,92.7,81,96.2,92.4,60.1,112,92.2,76.1,111.8,92.7,82.5,82.5,92.7,66.8,100.8,92.8,58.7,116,92.8,54.2,116.3,92.8,103.3,116.6,92.7,77.8,112.9,92.8,118.4,100.9,93.6,64.9,104.1,93.4,40.8,117.4,93.8,77.7,103.3,93.8,66.8,111.6,93.9,69.2,115,94,82.4,92.6,93.9,62.7,105.2,93.9,58.2),dim=c(3,61),dimnames=list(c('Indpr','Afzpr','Inv'),1:61))
>  y <- array(NA,dim=c(3,61),dimnames=list(c('Indpr','Afzpr','Inv'),1:61))
>  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/1twlp1198234766.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 = -0.5176, p-value = 0.6047
alternative hypothesis: true tau is not equal to 0 
sample estimates:
        tau 
-0.04628492 

> 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/2mld51198234766.tab") 
> 
> system("convert tmp/1twlp1198234766.ps tmp/1twlp1198234766.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.659   0.206   0.721