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(5560,36.68,3922,36.7,3759,36.71,4138,36.72,4634,36.73,3996,36.73,4308,36.87,4429,37.31,5219,37.39,4929,37.42,5755,37.51,5592,37.67,4163,37.67,4962,37.71,5208,37.78,4755,37.79,4491,37.84,5732,37.88,5731,38.34,5040,38.58,6102,38.72,4904,38.83,5369,38.9,5578,38.92,4619,38.94,4731,39.1,5011,39.14,5299,39.16,4146,39.32,4625,39.34,4736,39.44,4219,39.92,5116,40.19,4205,40.2,4121,40.27,5103,40.28,4300,40.3,4578,40.34,3809,40.4,5526,40.43,4247,40.48,3830,40.48,4394,40.63,4826,40.74,4409,40.77,4569,40.91,4106,40.92,4794,41.03,3914,41,3793,41.04,4405,41.33,4022,41.44,4100,41.46,4788,41.55,3163,41.55,3585,41.81,3903,41.78,4178,41.84,3863,41.84,4187,41.86),dim=c(2,60),dimnames=list(c('Bouwvergunningen_woningen','Uurtarief_loodgieter'),1:60))
>  y <- array(NA,dim=c(2,60),dimnames=list(c('Bouwvergunningen_woningen','Uurtarief_loodgieter'),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/1xuqg1260730312.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 = -3.3232, p-value = 0.0008898
alternative hypothesis: true tau is not equal to 0 
sample estimates:
       tau 
-0.2947669 

> 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/2pl1o1260730312.tab") 
> 
> try(system("convert tmp/1xuqg1260730312.ps tmp/1xuqg1260730312.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.408   0.180   1.149