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Data X:
109 99.2 109 99.5 109.2 99.3 113.3 99.9 112.3 100 112.3 100.3 116.3 100.5 118.3 100.7 119.4 100.9 119.4 100.8 119.4 100.9 120.1 101 121.7 100.3 123.7 100.1 123.7 99.8 128.5 99.9 127.1 99.9 122.6 100.2 119.8 99.7 122.7 100.4 123.4 100.9 123.8 101.3 121.8 101.4 121.2 101.3 121.2 100.9 121.2 100.9 121.2 100.9 129.6 101.1 131 101.1 131 101.3 129.8 101.8 129.8 102.9 134.9 103.2 131.2 103.3 127.1 104.5 130.5 105 130.5 104.9 131.7 104.9 131.7 105.4 131.7 106 131.7 105.7 128.7 105.9 125 106.2 124.5 106.4 123 106.9 122.8 107.3 123.1 107.9 124.8 109.2 126.9 110.2 131.7 110.2 136.8 110.5 143.7 110.6 150.1 110.8 152.7 111.3 152.6 111.1 150.5 111.2 154.9 111.2 158 111.1 158.1 111.5 160.6 112.1 160.6 111.4
Names of X columns:
Energie Voeding
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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