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(9487,1169,8700,2154,9627,2249,8947,2687,9283,4359,8829,5382,9947,4459,9628,6398,9318,4596,9605,3024,8640,1887,9214,2070,9567,1351,8547,2218,9185,2461,9470,3028,9123,4784,9278,4975,10170,4607,9434,6249,9655,4809,9429,3157,8739,1910,9552,2228,9784,1594,9089,2467,9763,2222,9330,3607,9144,4685,9895,4962,10404,5770,10195,5480,9987,5000,9789,3228,9437,1993,10096,2288,9776,1580,9106,2111,10258,2192,9766,3601,9826,4665,9957,4876,10036,5813,10508,5589,10146,5331,10166,3075,9365,2002,9968,2306,10123,1507,9144,1992,10447,2487,9699,3490,10451,4647,10192,5594,10404,5611,10597,5788,10633,6204,10727,3013,9784,1931,9667,2549,10297,1504,9426,2090,10274,2702,9598,2939,10400,4500,9985,6208,10761,6415,11081,5657,10297,5964,10751,3163,9760,1997,10133,2422,10806,1376,9734,2202,10083,2683,10691,3303,10446,5202,10517,5231,11353,4880,10436,7998,10721,4977,10701,3531,9793,2025,10142,2205),dim=c(2,84),dimnames=list(c('Geb.','Huw.'),1:84))
>  y <- array(NA,dim=c(2,84),dimnames=list(c('Geb.','Huw.'),1:84))
>  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/1bbip1261143972.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 = 3.5001, p-value = 0.0004652
alternative hypothesis: true tau is not equal to 0 
sample estimates:
      tau 
0.2600460 

> 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/2b27c1261143972.tab") 
> 
> try(system("convert tmp/1bbip1261143972.ps tmp/1bbip1261143972.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.406   0.188   0.523