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(2849.27,10872,2921.44,10625,2981.85,10407,3080.58,10463,3106.22,10556,3119.31,10646,3061.26,10702,3097.31,11353,3161.69,11346,3257.16,11451,3277.01,11964,3295.32,12574,3363.99,13031,3494.17,13812,3667.03,14544,3813.06,14931,3917.96,14886,3895.51,16005,3801.06,17064,3570.12,15168,3701.61,16050,3862.27,15839,3970.1,15137,4138.52,14954,4199.75,15648,4290.89,15305,4443.91,15579,4502.64,16348,4356.98,15928,4591.27,16171,4696.96,15937,4621.4,15713,4562.84,15594,4202.52,15683,4296.49,16438,4435.23,17032,4105.18,17696,4116.68,17745,3844.49,19394,3720.98,20148,3674.4,20108,3857.62,18584,3801.06,18441,3504.37,18391,3032.6,19178,3047.03,18079,2962.34,18483,2197.82,19644,2014.45,19195,1862.83,19650,1905.41,20830,1810.99,23595,1670.07,22937,1864.44,21814,2052.02,21928,2029.6,21777,2070.83,21383,2293.41,21467,2443.27,22052,2513.17,22680),dim=c(2,60),dimnames=list(c('X','Y'),1:60))
>  y <- array(NA,dim=c(2,60),dimnames=list(c('X','Y'),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: 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/14vvl1259437084.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 = -1.6774, p-value = 0.09346
alternative hypothesis: true tau is not equal to 0 
sample estimates:
       tau 
-0.1486296 

> 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/24zcm1259437084.tab") 
> 
> system("convert tmp/14vvl1259437084.ps tmp/14vvl1259437084.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.407   0.186   0.536