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(12008,4.0,9169,5.9,8788,7.1,8417,10.5,8247,15.1,8197,16.8,8236,15.3,8253,18.4,7733,16.1,8366,11.3,8626,7.9,8863,5.6,10102,3.4,8463,4.8,9114,6.5,8563,8.5,8872,15.1,8301,15.7,8301,18.7,8278,19.2,7736,12.9,7973,14.4,8268,6.2,9476,3.3,11100,4.6,8962,7.1,9173,7.8,8738,9.9,8459,13.6,8078,17.1,8411,17.8,8291,18.6,7810,14.7,8616,10.5,8312,8.6,9692,4.4,9911,2.3,8915,2.8,9452,8.8,9112,10.7,8472,13.9,8230,19.3,8384,19.5,8625,20.4,8221,15.3,8649,7.9,8625,8.3,10443,4.5,10357,3.2,8586,5.0,8892,6.6,8329,11.1,8101,12.8,7922,16.3,8120,17.4,7838,18.9,7735,15.8,8406,11.7,8209,6.4,9451,2.9,10041,4.7,9411,2.4,10405,7.2,8467,10.7,8464,13.4,8102,18.3,7627,18.4,7513,16.8,7510,16.6,8291,14.1,8064,6.1,9383,3.5,9706,1.7,8579,2.3,9474,4.5,8318,9.3,8213,14.2,8059,17.3,9111,23.0,7708,16.3,7680,18.4,8014,14.2,8007,9.1,8718,5.9,9486,7.2,9113,6.8,9025,8.0,8476,14.3,7952,14.6,7759,17.5,7835,17.2,7600,17.2,7651,14.1,8319,10.4,8812,6.8,8630,4.1),dim=c(2,96),dimnames=list(c('Sterfte','Temp'),1:96))
>  y <- array(NA,dim=c(2,96),dimnames=list(c('Sterfte','Temp'),1:96))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par1 = 'pearson'
> main = 'Correlation Matrix'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Patrick Wessa
> #To cite this work: Patrick Wessa, (2010), Multivariate Correlation Matrix (v1.0.4) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/Patrick.Wessa/rwasp_pairs.wasp#output/
> #Source of accompanying publication: 
> #Technical description: 
> panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
+ {
+ usr <- par('usr'); on.exit(par(usr))
+ par(usr = c(0, 1, 0, 1))
+ rr <- cor.test(x, y, method=par1)
+ r <- round(rr$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/11nyy1291985820.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")
> 
> 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/2ffvo1291985820.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)

	Pearson's product-moment correlation

data:  y[1, ] and y[2, ] 
t = -8.7792, df = 94, p-value = 7.232e-14
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.7683118 -0.5439275 
sample estimates:
       cor 
-0.6712173 

> 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/31xuc1291985820.tab") 
> 
> try(system("convert tmp/11nyy1291985820.ps tmp/11nyy1291985820.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.424   0.193   0.835