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Data X:
-7.7 13.5 -4.6 4.2 -5.3 -1.9 1.9 -7 6 -12.3 16.1 1.2 -3.1 4.2 -14.2 -5.8 -1.8 10.1 2.1 -4.3 14.4 2.3 12.8 10.9 8.2 -11.2 3.3 3.2 0.3 4.4 -11 3.8 14.2 21.1 -6.2 13.1 6 -5 5.8 23.1 18.1 -1.7 18.1 4 9.4 2.1 -14.6 -2.5 7.1 6.1 -8.6 -4.4 6.9 9.6 6.9 0.9 6.1 -13.2 -0.4 7 7.7 8.1 -2.2 1.4 7.2 5.5 1 -0.4 0.2 -8.2 -3.5 -8.6 -1 -9 -5 -7.1 0.5 -9.1 2.5 -0.9 10.7 14.6 13.6 5.7 -7 -17.2 -23.2 -20.7 -3 -5.7 -0.3 2.8 2.6 3.8 11.4 7.4 -8.9 2.5 -0.8 -4.5 9.3 12.4 23 8.1 3.5 -15 -9.5 -0.2 4.1 22.2 0.3 7 6.3 7.5 -6.6 8.3 9.7 5.7 7.4 12.9 -2.9 -4.7 -10.6 6.8 18.9 4 18.2 7.6 -0.6 20.4 -9.3 2.7 4.5 -13.2 -1.9 -0.5 4.9 0.1 -2.1 2.9 6.8 6 -0.9 2.4 22 28.3 15.1 12.7 11.2 12 -20.3 3.9 4.5 -10.2 8.6 0.3 14.4 31.5 9.3 5.3 3.8 16 -6.8 -4.2 3.3 9 4.8 -5.9 10.4 -9.8 -1.3 -0.4 0.6 -0.1 -7.3 -3 4.7 25.3 -4.5 -9.2 14.6 -17.1 22.4 6.3 8.6 -3.2 -16.3 6.4
Names of X columns:
totaal metaal machines elektr.app
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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