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Data X:
0 3441000000 0.1 -0.0169 -1.77636E-15 -4114000000 -0.4 -0.0439 0.1 -2429000000 -0.1 -0.0151 0 7771000000 0.2 -0.0034 -0.8 -5635000000 0.6 -0.0041 0 -2170000000 -0.6 -0.0734 0 12078000000 0.1 -0.0081 1.1 -6869000000 -0.2 0.0291 -1.77636E-15 -2367000000 -0.1 0.0233 0 -689000000 0.3 -0.0083 -0.9 10531000000 -0.4 -0.047 0 -10956000000 0.1 -0.001 -0.1 1974000000 0.3 -0.0584 0.1 2597000000 0.2 -0.0327 0 -4439000000 0.2 -0.0033 0 1399000000 -0.7 0.0384 0.8 7394000000 -0.7 0.0277 0.1 -13410000000 0.4 -0.0022 -0.2 3412000000 -0.1 -0.0131 -1 48000000 0.1 -0.0128 -0.1 10090000000 0.2 0.009 0 -9025000000 -0.9 -0.0042 0.6 -2988000000 0.4 -0.0272 0 9828000000 0.4 -0.0501 0 -6896000000 -0.1 -0.0417 0 -11000000 -0.3 0.0289 0 5331000000 -0.5 0.0105 -0.1 -1954000000 0.4 -0.0187 0.2 713000000 0.1 0.0263 0 6322000000 -0.4 0.0244 0.1 -2806000000 0 0.0529 -0.8 -10643000000 -0.2 0.0128 0 2092000000 -0.1 -0.0255 -0.1 13973000000 0.8 0.0036
Names of X columns:
werkloosheid brutoschuld inflatie wisselkoers
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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