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Data X:
100.0 100.0 100.6 95.3 114.2 90.7 91.5 88.4 94.7 86.0 110.6 86.0 71.3 95.3 104.1 95.3 112.3 88.4 110.2 86.0 112.9 81.4 95.1 83.7 103.1 95.3 101.9 88.4 100.4 86.0 106.9 83.7 100.7 76.7 114.3 79.1 73.3 86.0 105.9 86.0 113.9 79.1 112.1 76.7 117.5 69.8 97.5 69.8 112.3 76.7 106.9 69.8 120.9 67.4 92.7 65.1 110.9 58.1 116.5 60.5 77.1 65.1 113.1 62.8 115.9 55.8 123.5 51.2 123.6 48.8 101.5 48.8 121.0 53.5 112.2 48.8 126.0 46.5 101.8 44.2 117.9 39.5 122.2 41.9 82.7 48.8 120.5 46.5 120.3 41.9 134.2 39.5 128.2 37.2 100.5 37.2 126.0 41.9 122.9 39.5 106.1 39.5 130.4 34.9 121.3 34.9 126.1 34.9 88.7 41.9 118.7 41.9 129.3 39.5 136.2 39.5 123.0 41.9 103.5 46.5
Names of X columns:
Productie Werkloosheid
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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