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(153.4
+ ,174.1
+ ,145.3
+ ,145.9
+ ,159.5
+ ,180.4
+ ,143.6
+ ,158.5
+ ,157.4
+ ,182.6
+ ,142.8
+ ,152.2
+ ,169.1
+ ,207.1
+ ,155.9
+ ,153.7
+ ,172.6
+ ,213.7
+ ,156.2
+ ,157.9
+ ,161.7
+ ,186.5
+ ,149.8
+ ,154.4
+ ,159.2
+ ,179.1
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+ ,150.7
+ ,157.4
+ ,168.3
+ ,155.5
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+ ,153.9
+ ,156.5
+ ,159.3
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+ ,144.3
+ ,143
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+ ,142.2
+ ,138.9
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+ ,145.2
+ ,140.1
+ ,137.8
+ ,142.8
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+ ,136.3
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+ ,153.3
+ ,140.3
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+ ,149.1
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+ ,107.6
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+ ,114.7
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+ ,99.3
+ ,119.6
+ ,108
+ ,103.7
+ ,97.5
+ ,120.2
+ ,107.7
+ ,103
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+ ,99.9
+ ,96.9
+ ,88
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+ ,104.7
+ ,94.7
+ ,111
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+ ,102.2
+ ,99.4
+ ,107.8
+ ,103.4
+ ,99
+ ,98.9
+ ,110.5
+ ,104.7
+ ,95.8
+ ,96.4
+ ,118.3
+ ,105.8
+ ,94.5
+ ,95.3
+ ,123
+ ,105.3
+ ,102.7
+ ,99.5
+ ,112.1
+ ,103
+ ,103.2
+ ,101.6
+ ,104.2
+ ,103.8
+ ,105.6
+ ,103.9
+ ,102.4
+ ,103.4
+ ,103.9
+ ,106.6
+ ,100.3
+ ,105.8
+ ,107.2
+ ,108.3
+ ,102.6
+ ,101.4
+ ,100.7
+ ,102
+ ,101.5
+ ,97
+ ,92.1
+ ,93.8
+ ,103.4
+ ,94.3
+ ,90.3
+ ,91.6
+ ,99.4
+ ,96.6
+ ,93.4
+ ,97.7
+ ,97.9
+ ,97.1
+ ,98.5
+ ,94.8
+ ,98
+ ,95.7
+ ,100.8
+ ,98
+ ,90.2
+ ,96.9
+ ,102.3
+ ,103.8
+ ,87.1
+ ,97.4
+ ,104.7
+ ,97.8
+ ,91.8
+ ,95.3
+ ,101.1
+ ,91.2
+ ,94.8
+ ,93.6
+ ,101.4
+ ,89.3
+ ,91.8
+ ,91.5
+ ,99.5
+ ,87.5
+ ,89.3
+ ,93.1
+ ,98.4
+ ,90.4
+ ,91.7
+ ,91.7
+ ,96.3
+ ,94.2
+ ,86.2
+ ,94.3
+ ,100.7
+ ,102.2
+ ,82.8
+ ,93.9
+ ,101.2
+ ,101.3
+ ,82.3
+ ,90.9
+ ,100.3
+ ,96
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+ ,88.3
+ ,97.8
+ ,90.8
+ ,79.4
+ ,91.3
+ ,97.4
+ ,93.2
+ ,85.3
+ ,91.7
+ ,98.6
+ ,90.9
+ ,87.5
+ ,92.4
+ ,99.7
+ ,91.1
+ ,88.3
+ ,92
+ ,99
+ ,90.2
+ ,88.6
+ ,95.6
+ ,98.1
+ ,94.3
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+ ,95.8
+ ,97
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+ ,110.8
+ ,115.3
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+ ,119.2
+ ,110.3
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+ ,111.5
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+ ,111.4
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+ ,113.4
+ ,115.3
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+ ,113.9
+ ,97.5
+ ,106
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+ ,98.3
+ ,110.9
+ ,113
+ ,120.8
+ ,100.6
+ ,115
+ ,111.2
+ ,141.1
+ ,94.9
+ ,118.4
+ ,117.6
+ ,147.4
+ ,93.6
+ ,121.4
+ ,121.7
+ ,148
+ ,98
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+ ,104.3
+ ,131.7
+ ,129.8
+ ,165
+ ,103.9
+ ,141.7
+ ,137.1
+ ,187
+ ,105.3
+ ,142.9
+ ,141.4
+ ,190.3
+ ,102.6
+ ,139.4
+ ,137.4
+ ,182.4
+ ,103.3
+ ,134.7
+ ,130.7
+ ,168.8
+ ,107.9
+ ,125
+ ,117.2
+ ,151.2
+ ,107.8
+ ,113.6
+ ,110.8
+ ,120.1
+ ,109.8
+ ,111.5
+ ,111.4
+ ,112.5
+ ,110.6
+ ,108.5
+ ,108.2
+ ,106.2
+ ,110.8
+ ,112.3
+ ,108.8
+ ,107.1
+ ,119.3
+ ,116.6
+ ,110.2
+ ,108.5
+ ,128.1
+ ,115.5
+ ,109.5
+ ,106.5
+ ,127.6
+ ,120.1
+ ,109.5
+ ,108.3
+ ,137.9
+ ,132.9
+ ,116
+ ,125.6
+ ,151.4
+ ,128.1
+ ,111.2
+ ,124
+ ,143.6
+ ,129.3
+ ,112.1
+ ,127.2
+ ,143.4
+ ,132.5
+ ,114
+ ,136.9
+ ,141.9
+ ,131
+ ,119.1
+ ,135.8
+ ,135.2
+ ,124.9
+ ,114.1
+ ,124.3
+ ,133.1
+ ,120.8
+ ,115.1
+ ,115.4
+ ,129.6
+ ,122
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+ ,113.6
+ ,134.1
+ ,122.1
+ ,110.8
+ ,114.4
+ ,136.8
+ ,127.4
+ ,116
+ ,118.4
+ ,143.5
+ ,135.2
+ ,119.2
+ ,117
+ ,162.5
+ ,137.3
+ ,126.5
+ ,116.5
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+ ,137.3
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+ ,143
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+ ,133.9
+ ,134.5
+ ,111.1
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+ ,147.9
+ ,151.8
+ ,170.4
+ ,131.8
+ ,156
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+ ,175
+ ,130.6
+ ,163
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+ ,175.8
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+ ,180.9
+ ,148.4
+ ,159.5
+ ,160.7
+ ,180.3
+ ,148.7
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+ ,156
+ ,169.6
+ ,144.3
+ ,156.4
+ ,159.5
+ ,172.3
+ ,152.5
+ ,156.6
+ ,168.7
+ ,184.8
+ ,162.9
+ ,162.4
+ ,169.9
+ ,177.7
+ ,167.2
+ ,166.8
+ ,169.9
+ ,184.6
+ ,166.5
+ ,162.6
+ ,185.9
+ ,211.4
+ ,185.6
+ ,168.1)
+ ,dim=c(4
+ ,141)
+ ,dimnames=list(c('Totaal'
+ ,'Graan'
+ ,'Olie'
+ ,'Suiker')
+ ,1:141))
>  y <- array(NA,dim=c(4,141),dimnames=list(c('Totaal','Graan','Olie','Suiker'),1:141))
>  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/11mhi1196418241.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] 4
> cor.test(y[1,],y[2,],method='kendall')

	Kendall's rank correlation tau

data:  y[1, ] and y[2, ] 
z = 13.4654, p-value < 2.2e-16
alternative hypothesis: true tau is not equal to 0 
sample estimates:
      tau 
0.7665145 

> 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/2ag531196418241.tab") 
> 
> system("convert tmp/11mhi1196418241.ps tmp/11mhi1196418241.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.684   0.419   1.746