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(2.02,2.64,2.03,2.75,2.01,2.7,2.08,2.87,2.02,3.03,2.03,3.14,2.07,3.02,2.04,2.86,2.05,3.07,2.11,2.93,2.09,2.83,2.05,2.72,2.08,2.73,2.06,2.72,2.06,2.77,2.08,2.61,2.07,2.47,2.06,2.3,2.07,2.38,2.06,2.43,2.09,2.39,2.07,2.6,2.09,2.84,2.28,2.87,2.33,2.92,2.35,3.08,2.52,3.33,2.63,3.48,2.58,3.57,2.70,3.66,2.81,3.77,2.97,3.75,3.04,3.75,3.28,3.81,3.33,3.82,3.50,3.89,3.56,4.05,3.57,4.1,3.69,4.07,3.82,4.26,3.79,4.4,3.96,4.61,4.06,4.63,4.05,4.48,4.03,4.46,3.94,4.45,4.02,4.32,3.88,4.52,4.02,4.21,4.03,3.97,4.09,4.12,3.99,4.5,4.01,4.73,4.01,5.26,4.19,5.2,4.30,4.94,4.27,4.95,3.82,4.52,3.15,3.85,2.49,3.41,1.81,2.95,1.26,2.68,1.06,2.53,0.84,2.44,0.78,2.16,0.70,2.2,0.36,2.1,0.35,2.29,0.36,2.03,0.36,2.05,0.36,1.94),dim=c(2,71),dimnames=list(c('Intb','Eobm'),1:71))
>  y <- array(NA,dim=c(2,71),dimnames=list(c('Intb','Eobm'),1:71))
>  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/1nzzr1260622899.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 = 9.6148, p-value < 2.2e-16
alternative hypothesis: true tau is not equal to 0 
sample estimates:
      tau 
0.7846115 

> 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/2zgm81260622899.tab") 
> 
> system("convert tmp/1nzzr1260622899.ps tmp/1nzzr1260622899.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.403   0.177   0.482