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Data X:
2.7 8.4 4.3 1.5 2.2 2.1 2.5 7.5 3.1 1.7 2.3 2.2 2.2 4.0 5.7 1.6 2.1 2.2 2.9 8.5 6.7 1.7 2.8 2.7 3.1 7.6 9.5 1.8 3.1 3.1 3.0 5.5 9.0 1.7 2.9 3.2 2.8 3.3 6.9 2.2 2.6 3.1 2.5 1.4 7.5 2.7 2.7 3.1 1.9 -4.4 7.0 3.0 2.3 2.8 1.9 -6.5 9.3 2.8 2.3 3.0 1.8 -8.5 7.2 2.7 2.1 2.8 2.0 -6.7 6.6 2.7 2.2 2.7 2.6 -3.3 10.4 2.5 2.9 3.2 2.5 -5.1 8.7 2.0 2.6 3.1 2.5 -3.5 7.9 1.8 2.7 3.0 1.6 -3.6 4.1 1.4 1.8 2.0 1.4 -6.3 2.2 1.5 1.3 1.7 0.8 -8.0 -0.5 1.6 0.9 1.2 1.1 -5.3 1.7 1.3 1.3 1.4 1.3 -4.0 0.4 1.1 1.3 1.3 1.2 -4.0 2.6 0.8 1.3 1.3 1.3 0.1 0.7 1.1 1.3 1.1 1.1 -0.9 0.7 1.3 1.1 0.9 1.3 1.1 0.5 1.5 1.4 1.2 1.2 3.1 -2.3 1.8 1.2 0.9 1.6 5.7 0.3 2.7 1.7 1.3 1.7 6.2 -0.2 3.0 1.8 1.4 1.5 -2.2 0.6 3.2 1.5 1.5 0.9 -4.2 -0.6 3.2 1.0 1.1 1.5 -1.6 2.7 3.3 1.6 1.6 1.4 -1.9 2.3 3.2 1.5 1.5 1.6 0.2 4.3 2.9 1.8 1.6 1.7 -1.2 5.4 2.7 1.8 1.7 1.4 -2.4 2.6 2.6 1.6 1.6 1.8 0.8 2.9 2.3 1.9 1.7 1.7 -0.1 2.9 2.2 1.7 1.6 1.4 -1.5 2.9 2.1 1.6 1.6 1.2 -4.4 1.4 2.4 1.3 1.3 1.0 -4.2 1.1 2.5 1.1 1.1 1.7 3.5 1.9 2.4 1.9 1.6 2.4 10.0 2.8 2.3 2.6 1.9 2.0 8.6 1.4 2.1 2.3 1.6 2.1 9.5 0.7 2.3 2.4 1.7 2.0 9.9 -0.8 2.2 2.2 1.6 1.8 10.4 -3.1 2.1 2.0 1.4 2.7 16.0 0.1 2.0 2.9 2.1 2.3 12.7 1.0 2.1 2.6 1.9 1.9 10.2 1.9 2.1 2.3 1.7 2.0 8.9 -0.5 2.5 2.3 1.8 2.3 12.6 1.5 2.2 2.6 2.0 2.8 13.6 3.9 2.3 3.1 2.5 2.4 14.8 1.9 2.3 2.8 2.1 2.3 9.5 2.6 2.2 2.5 2.1 2.7 13.7 1.7 2.2 2.9 2.3 2.7 17.0 1.4 1.6 3.1 2.4 2.9 14.7 2.8 1.8 3.1 2.4 3.0 17.4 0.5 1.7 3.2 2.3 2.2 9.0 1.0 1.9 2.5 1.7 2.3 9.1 1.5 1.8 2.6 2.0 2.8 12.2 1.8 1.9 2.9 2.3 2.8 15.9 2.7 1.5 2.6 2.0 2.8 12.9 3.0 1.0 2.4 2.0 2.2 10.9 -0.3 0.8 1.7 1.3 2.6 10.6 1.1 1.1 2.0 1.7 2.8 13.2 1.7 1.5 2.2 1.9 2.5 9.6 1.6 1.7 1.9 1.7 2.4 6.4 3.0 2.3 1.6 1.6 2.3 5.8 3.3 2.4 1.6 1.7 1.9 -1.0 6.7 3.0 1.2 1.8 1.7 -0.2 5.6 3.0 1.2 1.9 2.0 2.7 6.0 3.2 1.5 1.9 2.1 3.6 4.8 3.2 1.6 1.9 1.7 -0.9 5.9 3.2 1.7 2.0 1.8 0.3 4.3 3.5 1.8 2.1 1.8 -1.1 3.7 4.0 1.8 1.9 1.8 -2.5 5.6 4.3 1.8 1.9 1.3 -3.4 1.7 4.1 1.3 1.3 1.3 -3.5 3.2 4.0 1.3 1.3 1.3 -3.9 3.6 4.1 1.4 1.4 1.2 -4.6 1.7 4.2 1.1 1.2 1.4 -0.1 0.5 4.5 1.5 1.3 2.2 4.3 2.1 5.6 2.2 1.8 2.9 10.2 1.5 6.5 2.9 2.2 3.1 8.7 2.7 7.6 3.1 2.6 3.5 13.3 1.4 8.5 3.5 2.8 3.6 15.0 1.2 8.7 3.6 3.1 4.4 20.7 2.3 8.3 4.4 3.9 4.1 20.7 1.6 8.3 4.2 3.7 5.1 26.4 4.7 8.5 5.2 4.6 5.8 31.2 3.5 8.7 5.8 5.1 5.9 31.4 4.4 8.7 5.9 5.2 5.4 26.6 3.9 8.5 5.4 4.9 5.5 26.6 3.5 7.9 5.5 5.1 4.8 19.2 3.0 7.0 4.7 4.8 3.2 6.5 1.6 5.8 3.1 3.9 2.7 3.1 2.2 4.5 2.6 3.5 2.1 -0.2 4.1 3.7 2.3 3.3 1.9 -4.0 4.3 3.1 1.9 2.8 0.6 -12.6 3.5 2.7 0.6 1.6 0.7 -13.0 1.8 2.3 0.6 1.5 -0.2 -17.6 0.6 1.8 -0.4 0.7 -1.0 -21.7 -0.4 1.5 -1.1 -0.1 -1.7 -23.2 -2.5 1.2 -1.7 -0.7 -0.7 -16.8 -1.6 1.0 -0.8 -0.2 -1.0 -19.8 -1.9 0.9 -1.2 -0.6 -0.9 -17.2 -1.6 0.6 -1.0 -0.6 0.0 -10.4 -0.7 0.6 -0.1 -0.3 0.3 -6.8 -1.1 0.7 0.3 -0.3 0.8 -2.9 0.3 0.5 0.6 -0.1 0.8 -1.9 1.3 0.5 0.7 0.1 1.9 7.0 3.3 0.5 1.7 0.9 2.1 9.8 2.4 0.5 1.8 1.1 2.5 12.5 2.0 0.8 2.3 1.6 2.7 13.7 3.9 0.8 2.5 2.0 2.4 13.7 4.2 1.1 2.6 2.2 2.4 9.7 4.9 1.2 2.3 2.1 2.9 14.0 5.8 1.5 2.9 2.6 3.1 15.3 4.8 1.7 3.0 2.5 3.0 13.4 4.4 1.8 2.9 2.5 3.4 17.1 5.3 1.8 3.1 2.6 3.7 15.7 2.1 2.1 3.2 2.7 3.5 18.3 2.0 2.2 3.4 2.8 3.5 18.1 -0.9 2.5 3.5 2.9 3.3 16.3 0.1 2.7 3.4 2.9 3.1 15.8 -0.5 3.0 3.3 2.9 3.4 17.3 -0.1 3.4 3.7 3.3 4.0 18.0 0.7 3.4 3.8 3.3 3.4 17.6 -0.4 3.5 3.6 3.1 3.4 18.4 -1.5 3.5 3.6 3.0 3.4 17.4 -0.3 3.4 3.6 3.1 3.7 17.9 1.0 3.6 3.8 3.4 3.2 13.5 0.4 3.8 3.5 3.2 3.3 13.7 0.3 3.5 3.6 3.4 3.3 12.6 1.8 3.5 3.7 3.4 3.1 10.4 3.0 3.5 3.4 3.1 2.9 8.8 2.2 3.2 3.2 3.0 2.6 5.4 3.4 2.9 2.8 2.7 2.2 2.1 3.4 2.5 2.3 2.2 2.0 2.8 3.1 2.3 2.3 2.2 2.6 5.6 4.5 2.7 2.9 2.6 2.6 4.8 4.6 3.0 2.8 2.4 2.6 4.5 5.7 3.3 2.8 2.5 2.2 1.5 4.3 3.2 2.3 2.2
Names of X columns:
HICP Energiedragers Niet-bewerkte_levensmiddelen Bewerkte_levensmiddelen Algemene_index Gezondheidsindex
Type of Correlation
kendall
pearson
spearman
kendall
Chart options
Title:
R Code
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$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') n <- length(y[,1]) n a<-table.start() a<-table.row.start(a) a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,' ',header=TRUE) for (i in 1:n) { a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) } a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) for (j in 1:n) { r <- cor.test(y[i,],y[j,],method=par1) a<-table.element(a,round(r$estimate,3)) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.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) 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='mytable1.tab')
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Raw Input
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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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