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Data X:
4.8 19.2 3 5.5 26.6 3.5 5.4 26.6 3.9 5.9 31.4 4.4 5.8 31.2 3.5 5.1 26.4 4.7 4.1 20.7 1.6 4.4 20.7 2.3 3.6 15 1.2 3.5 13.3 1.4 3.1 8.7 2.7 2.9 10.2 1.5 2.2 4.3 2.1 1.4 -0.1 0.5 1.2 -4.6 1.7 1.3 -3.9 3.6 1.3 -3.5 3.2 1.3 -3.4 1.7 1.8 -2.5 5.6 1.8 -1.1 3.7 1.8 0.3 4.3 1.7 -0.9 5.9 2.1 3.6 4.8 2 2.7 6 1.7 -0.2 5.6 1.9 -1 6.7 2.3 5.8 3.3 2.4 6.4 3 2.5 9.6 1.6 2.8 13.2 1.7 2.6 10.6 1.1 2.2 10.9 -0.3 2.8 12.9 3 2.8 15.9 2.7 2.8 12.2 1.8 2.3 9.1 1.5 2.2 9 1 3 17.4 0.5 2.9 14.7 2.8 2.7 17 1.4 2.7 13.7 1.7 2.3 9.5 2.6 2.4 14.8 1.9 2.8 13.6 3.9 2.3 12.6 1.5 2 8.9 -0.5 1.9 10.2 1.9 2.3 12.7 1 2.7 16 0.1 1.8 10.4 -3.1 2 9.9 -0.8 2.1 9.5 0.7 2 8.6 1.4 2.4 10 2.8 1.7 3.5 1.9 1 -4.2 1.1 1.2 -4.4 1.4 1.4 -1.5 2.9 1.7 -0.1 2.9 1.8 0.8 2.9
Names of X columns:
Totaal Energiedragers onbewerktebewerkte_levensmiddelen
Type of Correlation
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='kendall') 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$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Kendall tau rank correlations for all pairs of data series',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'pair',1,TRUE) a<-table.element(a,'tau',1,TRUE) a<-table.element(a,'p-value',1,TRUE) a<-table.row.end(a) n <- length(y[,1]) n cor.test(y[1,],y[2,],method='kendall') for (i in 1:(n-1)) { for (j in (i+1):n) { a<-table.row.start(a) dum <- paste('tau(',dimnames(t(x))[[2]][i]) dum <- paste(dum,',') dum <- paste(dum,dimnames(t(x))[[2]][j]) dum <- paste(dum,')') a<-table.element(a,dum,header=TRUE) r <- cor.test(y[i,],y[j,],method='kendall') a<-table.element(a,r$estimate) a<-table.element(a,r$p.value) a<-table.row.end(a) } } a<-table.end(a) table.save(a,file='mytable.tab')
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