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Data X:
109.87 103.5 104.9 115.7 95.74 102.8 105.2 115.2 123.06 118.72 105.5 115.1 123.39 119.01 105.7 115.4 120.28 118.61 105.9 115.5 115.33 120.43 106.2 115.1 110.4 111.83 106.5 114.6 114.49 116.79 106.8 114.5 132.03 131.71 107 114.4 123.16 120.57 107.2 113.9 118.82 117.83 107.6 113.1 128.32 130.8 107.9 112.6 112.24 107.46 108.2 112.6 104.53 112.09 108.4 112.7 132.57 129.47 108.8 112.5 122.52 119.72 109.3 112.2 131.8 134.81 110.1 112 124.55 135.8 110.9 119.4 120.96 129.27 111.7 119.3 122.6 126.94 112.5 119.3 145.52 153.45 113.4 119.2 118.57 121.86 114.2 118.7 134.25 133.47 114.9 118 136.7 135.34 115.5 117.5 121.37 117.1 116.3 117.7 111.63 120.65 117.3 118.4 134.42 132.49 118.4 119 137.65 137.6 119.5 119.3 137.86 138.69 120.5 119.5 119.77 125.53 121.4 119.8 130.69 133.09 122.1 120 128.28 129.08 123 120 147.45 145.94 123.9 120.1 128.42 129.07 124.7 120.6 136.9 139.69 125.4 121.2 143.95 142.09 125.9 121.6 135.64 137.29 126.2 121.6 122.48 127.03 126.6 121.3 136.83 137.25 127.1 121 153.04 156.87 127.5 120.8 142.71 150.89 127.7 121 123.46 139.14 127.7 121.5 144.37 158.3 127.5 121.8 146.15 149 127 121.7 147.61 158.36 126.3 121.3 158.51 168.06 125.7 120.7 147.4 153.38 125.1 120 165.05 173.86 124.4 119.3 154.64 162.47 123.5 118.5 126.2 145.17 122.4 117.7 157.36 168.89 121 117.1 154.15 166.64 119.6 116.6 123.21 140.07 118.2 116 113.07 128.84 117.1 115.2 110.45 123.41 116.3 114.4 113.57 120.3 115.4 113.9 122.44 129.67 114.7 113.5 114.93 118.1 114 113.1 111.85 113.91 113.4 112.8 126.04 131.09 112.7 112.6 121.34 119.15 112.1 112.3
Names of X columns:
Uitvoer Invoer Invgdn Consgdn
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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