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Type 'q()' to quit R. > x <- array(list(194.9,1.79,195.5,1.95,196,2.26,196.2,2.04,196.2,2.16,196.2,2.75,196.2,2.79,197,2.88,197.7,3.36,198,2.97,198.2,3.1,198.5,2.49,198.6,2.2,199.5,2.25,200,2.09,201.3,2.79,202.2,3.14,202.9,2.93,203.5,2.65,203.5,2.67,204,2.26,204.1,2.35,204.3,2.13,204.5,2.18,204.8,2.9,205.1,2.63,205.7,2.67,206.5,1.81,206.9,1.33,207.1,0.88,207.8,1.28,208,1.26,208.5,1.26,208.6,1.29,209,1.1,209.1,1.37,209.7,1.21,209.8,1.74,209.9,1.76,210,1.48,210.8,1.04,211.4,1.62,211.7,1.49,212,1.79,212.2,1.8,212.4,1.58,212.9,1.86,213.4,1.74,213.7,1.59,214,1.26,214.3,1.13,214.8,1.92,215,2.61,215.9,2.26,216.4,2.41,216.9,2.26,217.2,2.03,217.5,2.86,217.9,2.55,218.1,2.27,218.6,2.26,218.9,2.57,219.3,3.07,220.4,2.76,220.9,2.51,221,2.87,221.8,3.14,222,3.11,222.2,3.16,222.5,2.47,222.9,2.57,223.1,2.89),dim=c(2,72),dimnames=list(c('uurloon','inflatie'),1:72)) > y <- array(NA,dim=c(2,72),dimnames=list(c('uurloon','inflatie'),1:72)) > 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' > par1 <- 'pearson' > #'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/14i1q1292314753.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$estimate,3)) + } + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/20azz1292314753.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'pair',1,TRUE) > a<-table.element(a,'Pearson r',1,TRUE) > a<-table.element(a,'Spearman rho',1,TRUE) > a<-table.element(a,'Kendall tau',1,TRUE) > a<-table.row.end(a) > cor.test(y[1,],y[2,],method=par1) Pearson's product-moment correlation data: y[1, ] and y[2, ] t = 0.0923, df = 70, p-value = 0.9267 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: -0.2212012 0.2420826 sample estimates: cor 0.01103275 > for (i in 1:(n-1)) + { + for (j in (i+1):n) + { + a<-table.row.start(a) + dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='') + a<-table.element(a,dum,header=TRUE) + rp <- cor.test(y[i,],y[j,],method='pearson') + a<-table.element(a,round(rp$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/33ax41292314753.tab") > > try(system("convert tmp/14i1q1292314753.ps tmp/14i1q1292314753.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.413 0.183 3.457