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Type 'q()' to quit R. > x <- array(list(16198.9,16896.2,16554.2,16698.00,19554.2,19691.6,15903.8,15930.7,18003.8,17444.6,18329.6,17699.4,16260.7,15189.8,14851.9,15672.7,18174.1,17180.8,18406.6,17664.9,18466.5,17862.9,16016.5,16162.3,17428.5,17463.6,17167.2,16772.1,19630.00,19106.9,17183.6,16721.3,18344.7,18161.3,19301.4,18509.9,18147.5,17802.7,16192.9,16409.9,18374.4,17967.7,20515.2,20286.6,18957.2,19537.3,16471.5,18021.9,18746.8,20194.3,19009.5,19049.6,19211.2,20244.7,20547.7,21473.3,19325.8,19673.6,20605.5,21053.2,20056.9,20159.5,16141.4,18203.6,20359.8,21289.5,19711.6,20432.3,15638.6,17180.4,14384.5,15816.8,13855.6,15071.8,14308.3,14521.1,15290.6,15668.8,14423.8,14346.9,13779.7,13881.00,15686.3,15465.9,14733.8,14238.2,12522.5,13557.7,16189.4,16127.6,16059.1,16793.9,16007.1,16014.00,15806.8,16867.9,15160.00,16014.6,15692.1,15878.6,18908.9,18664.9,16969.9,17962.5,16997.5,17332.7,19858.9,19542.1,17681.2,17203.6),dim=c(2,55),dimnames=list(c('Uitvoer','Invoer'),1:55)) > y <- array(NA,dim=c(2,55),dimnames=list(c('Uitvoer','Invoer'),1:55)) > 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/19xdy1292142572.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$estimate,3)) + } + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/2ugt41292142572.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'pair',1,TRUE) > a<-table.element(a,'Pearson r',1,TRUE) > a<-table.element(a,'Spearman rho',1,TRUE) > a<-table.element(a,'Kendall tau',1,TRUE) > a<-table.row.end(a) > cor.test(y[1,],y[2,],method=par1) Pearson's product-moment correlation data: y[1, ] and y[2, ] t = 19.249, df = 53, p-value < 2.2e-16 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: 0.8911823 0.9619382 sample estimates: cor 0.935339 > for (i in 1:(n-1)) + { + for (j in (i+1):n) + { + a<-table.row.start(a) + dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='') + a<-table.element(a,dum,header=TRUE) + rp <- cor.test(y[i,],y[j,],method='pearson') + a<-table.element(a,round(rp$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) + } + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/38q9c1292142572.tab") > > try(system("convert tmp/19xdy1292142572.ps tmp/19xdy1292142572.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.394 0.181 0.810