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Type 'q()' to quit R. > x <- array(list(13,5,12,3,15,0,12,7,10,4,12,1,15,6,9,3,12,12,11,0,11,5,11,6,15,6,7,6,11,2,11,1,10,5,14,7,10,3,6,3,11,3,15,7,11,8,12,6,14,3,15,5,9,5,13,10,13,2,16,6,13,4,12,6,14,8,11,4,9,5,16,10,12,6,10,7,13,4,16,10,14,4,15,3,5,3,8,3,11,3,16,7,17,15,9,0,9,0,13,4,10,5,6,5,12,2,8,3,14,0,12,9,11,2,16,7,8,7,15,0,7,0,16,10,14,2,16,1,9,8,14,6,11,11,13,3,15,8,5,6,15,9,13,9,11,8,11,8,12,7,12,6,12,5,12,4,14,6,6,3,7,2,14,12,14,8,10,5,13,9,12,6,9,5,12,2,16,4,10,7,14,5,10,6,16,7,15,8,12,6,10,0,8,1,8,5,11,5,13,5,16,7,16,7,14,1,11,3,4,4,14,8,9,6,14,6,8,2,8,2,11,3,12,3,11,0,14,2,15,8,16,8,16,0,11,5,14,9,14,6,12,6,14,3,8,9,13,7,16,8,12,0,16,7,12,0,11,5,4,0,16,14,15,5,10,2,13,8,15,4,12,2,14,6,7,3,19,5,12,9,12,3,13,3,15,0,8,10,12,4,10,2,8,3,10,10,15,7,16,0,13,6,16,8,9,0,14,4,14,10,12,5),dim=c(2,156),dimnames=list(c('IEP','WP'),1:156)) > y <- array(NA,dim=c(2,156),dimnames=list(c('IEP','WP'),1:156)) > 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 = 'Pearson 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/rcomp/tmp/1bzqw1292850354.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/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$estimate,3)) + } + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/2ezo21292850354.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'pair',1,TRUE) > a<-table.element(a,'Pearson r',1,TRUE) > a<-table.element(a,'Spearman rho',1,TRUE) > a<-table.element(a,'Kendall tau',1,TRUE) > a<-table.row.end(a) > cor.test(y[1,],y[2,],method=par1) Pearson's product-moment correlation data: y[1, ] and y[2, ] t = 3.7704, df = 154, p-value = 0.0002318 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: 0.1399607 0.4282837 sample estimates: cor 0.2907078 > for (i in 1:(n-1)) + { + for (j in (i+1):n) + { + a<-table.row.start(a) + dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='') + a<-table.element(a,dum,header=TRUE) + rp <- cor.test(y[i,],y[j,],method='pearson') + a<-table.element(a,round(rp$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/rcomp/tmp/3sr4b1292850354.tab") > > try(system("convert tmp/1bzqw1292850354.ps tmp/1bzqw1292850354.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.410 0.270 0.646