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Data X:
5014 2400 6153 4700 6441 3700 5584 2900 6427 2800 6062 3000 5589 3100 6216 3700 5809 3000 4989 2000 6706 1900 7174 1900 6122 1800 8075 3400 6292 3800 6337 2800 8576 3100 6077 2100 5931 2000 6288 2500 7167 2400 6054 2500 6468 3300 6401 3100 6927 3700 7914 5600 7728 3700 8699 2900 8522 4000 6481 2900 7502 2400 7778 3300 7424 3800 6941 4400 8574 4000 9169 3100 7701 2700 9035 5200 7158 4600 8195 3700 8124 3200 7073 2400 7017 2200 7390 3200 7776 3100 6197 2300 6889 2500 7087 2900 6485 2700 7654 5000 6501 3500 6313 3000 7826 3800 6589 2800 6729 2400 5684 2700 8105 2800 6391 2700 5901 2600 6758 3100
Names of X columns:
bouwaanvragen hypothecairkrediet
Type of Correlation
pearson
spearman
kendall
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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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