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(296.95,17.20,296.84,17.20,287.54,17.20,287.81,17.20,283.99,20.63,275.79,20.63,269.52,20.63,278.35,20.63,283.43,19.32,289.46,19.32,282.30,19.32,293.55,19.32,304.78,12.99,300.99,12.99,315.29,12.99,316.21,12.99,331.79,18.13,329.38,18.13,317.27,18.13,317.98,18.13,340.28,28.37,339.21,28.37,336.71,28.37,340.11,28.37,347.72,24.35,328.68,24.35,303.05,24.35,299.83,24.35,320.04,24.99,317.94,24.99,303.31,24.99,308.85,24.99,319.19,28.84,314.52,28.84,312.39,28.84,315.77,28.84,320.23,37.88,309.45,37.88,296.54,37.88,297.28,37.88,301.39,54.04,306.68,54.04,305.91,54.04,314.76,54.04,323.34,64.93,341.58,64.93,330.12,64.93,318.16,64.93,317.84,71.81,325.39,71.81,327.56,71.81,329.77,71.81,333.29,99.75,346.10,99.75,358.00,99.75,344.82,99.75,313.30,61.25,301.26,61.25,306.38,61.25,319.31,61.25),dim=c(2,60),dimnames=list(c('GemPrijsTicket_$','GemiddeldeOlieprijs_$'),1:60))
>  y <- array(NA,dim=c(2,60),dimnames=list(c('GemPrijsTicket_$','GemiddeldeOlieprijs_$'),1:60))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par1 = 'kendall'
> main = 'Correlation Matrix'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Dr. Ian E. Holliday
> #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
+ {
+ usr <- par('usr'); on.exit(par(usr))
+ par(usr = c(0, 1, 0, 1))
+ rr <- cor.test(x, y, method=par1)
+ r <- round(rr$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/1xvhb1292587281.ps",horizontal=F,onefile=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")
> 
> n <- length(y[,1])
> n
[1] 2
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,' ',header=TRUE)
> for (i in 1:n) {
+ a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
+ }
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
+ for (j in 1:n) {
+ r <- cor.test(y[i,],y[j,],method=par1)
+ a<-table.element(a,round(r$estimate,3))
+ }
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/20wgh1292587281.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'pair',1,TRUE)
> a<-table.element(a,'Pearson r',1,TRUE)
> a<-table.element(a,'Spearman rho',1,TRUE)
> a<-table.element(a,'Kendall tau',1,TRUE)
> a<-table.row.end(a)
> cor.test(y[1,],y[2,],method=par1)

	Kendall's rank correlation tau

data:  y[1, ] and y[2, ] 
z = 3.8497, p-value = 0.0001183
alternative hypothesis: true tau is not equal to 0 
sample estimates:
      tau 
0.3491043 

> for (i in 1:(n-1))
+ {
+ for (j in (i+1):n)
+ {
+ a<-table.row.start(a)
+ dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
+ a<-table.element(a,dum,header=TRUE)
+ rp <- cor.test(y[i,],y[j,],method='pearson')
+ a<-table.element(a,round(rp$estimate,4))
+ rs <- cor.test(y[i,],y[j,],method='spearman')
+ a<-table.element(a,round(rs$estimate,4))
+ rk <- cor.test(y[i,],y[j,],method='kendall')
+ a<-table.element(a,round(rk$estimate,4))
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-value',header=T)
+ a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
+ a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
+ a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
+ a<-table.row.end(a)
+ }
+ }
Warning message:
In cor.test.default(y[i, ], y[j, ], method = "spearman") :
  Cannot compute exact p-values with ties
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/3wnd81292587281.tab") 
> 
> try(system("convert tmp/1xvhb1292587281.ps tmp/1xvhb1292587281.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.425   0.198   1.062