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Data X:
0.1 -54.4 0.2 -6.9 -0.1 5.6 -0.1 1.4 -0.4 26.6 -0.1 -12.5 0.1 -12 0.5 24.3 0.2 -47 0 -24.4 0.2 76.1 -0.2 2.7 0.1 -28.2 0.2 11.8 0 -32.8 -0.1 11.5 -1.2 59.8 -0.1 -33.3 0.1 -23.2 1.6 57.9 0.2 -74.2 0 -1.7 -0.7 72.1 -0.2 -12.2 0 -16.1 0.3 4.4 0 -30.6 -0.1 3.9 -0.4 44.1 0 -27.1 -0.1 -12.7 0.6 49.6 0.1 -90.4 0 15.4 -0.1 66.3 -0.2 -30.4 0 12.6 0.3 -12.8 0 -8.6 -0.2 9.7 -0.2 55.8 0 -63.5 0 38 -0.2 18.1 0.1 -88.8 -0.1 15.9 0 63 -0.2 4.1 -0.2 -8.3 0.4 -22.2 -0.1 4.7 -0.3 -2.3 0.1 51.8 -0.2 -47.1 -0.2 12.1 0.3 37 0.1 -73.9 -0.3 -4.9 -0.3 43.4
Names of X columns:
Werkloosheid IndProd
Type of Correlation
pearson
spearman
kendall
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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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