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Data X:
6.9 4.8 2.28 6.8 4.8 2.26 6.7 4.7 2.71 6.6 4.7 2.77 6.5 4.7 2.77 6.5 4.6 2.64 7.0 5.0 2.56 7.5 5.4 2.07 7.6 5.5 2.32 7.6 5.6 2.16 7.6 5.6 2.23 7.8 5.8 2.40 8.0 6.0 2.84 8.0 6.1 2.77 8.0 6.1 2.93 7.9 6.0 2.91 7.9 6.0 2.69 8.0 6.1 2.38 8.5 6.5 2.58 9.2 7.1 3.19 9.4 7.4 2.82 9.5 7.4 2.72 9.5 7.5 2.53 9.6 7.6 2.70 9.7 7.8 2.42 9.7 7.8 2.50 9.6 7.7 2.31 9.5 7.6 2.41 9.4 7.5 2.56 9.3 7.3 2.76 9.6 7.6 2.71 10.2 8.0 2.44 10.2 8.8 2.46 10.1 7.9 2.12 9.9 7.8 1.99 9.8 7.7 1.86 9.8 7.8 1.88 9.7 7.7 1.82 9.5 7.5 1.74 9.3 7.3 1.71 9.1 7.1 1.38 9.0 7.0 1.27 9.5 7.3 1.19 10.0 7.8 1.28 10.2 7.9 1.19 10.1 7.9 1.22 10.0 7.8 1.47 9.9 7.8 1.46 10.0 7.9 1.96 9.9 7.8 1.88 9.7 7.6 2.03 9.5 7.4 2.04 9.2 7.2 1.90 9.0 6.9 1.80 9.3 7.1 1.92 9.8 7.5 1.92 9.8 7.6 1.97 9.6 7.4 2.46 9.4 7.3 2.36 9.3 7.2 2.53 9.2 7.3 2.31 9.2 7.2 1.98 9.0 7.1 1.46 8.8 7.0 1.26 8.7 6.9 1.58 8.7 6.8 1.74 9.1 7.2 1.89 9.7 7.6 1.85 9.8 7.7 1.62 9.6 7.6 1.30 9.4 7.5 1.42 9.4 7.5 1.15 9.5 7.6 0.42 9.4 7.6 0.74 9.3 7.6 1.02 9.2 7.5 1.51 9.0 7.3 1.86 8.9 7.2 1.59 9.2 7.4 1.03 9.8 8.0 0.44 9.9 8.2 0.82 9.6 8.0 0.86 9.2 7.7 0.58 9.1 7.7 0.59 9.1 7.8 0.95 9.0 7.8 0.98 8.9 7.7 1.23 8.7 7.5 1.17 8.5 7.3 0.84 8.3 7.1 0.74 8.5 7.1 0.65 8.7 7.2 0.91 8.4 6.8 1.19 8.1 6.6 1.30 7.8 6.4 1.53 7.7 6.4 1.94 7.5 6.5 1.79 7.2 6.3 1.95 6.8 5.9 2.26 6.7 5.5 2.04 6.4 5.2 2.16 6.3 4.9 2.75 6.8 5.4 2.79 7.3 5.8 2.88 7.1 5.7 3.36 7.0 5.6 2.97 6.8 5.5 3.10 6.6 5.4 2.49 6.3 5.4 2.20 6.1 5.4 2.25 6.1 5.5 2.09 6.3 5.8 2.79 6.3 5.7 3.14 6.0 5.4 2.93 6.2 5.6 2.65 6.4 5.8 2.67 6.8 6.2 2.26 7.5 6.8 2.35 7.5 6.7 2.13 7.6 6.7 2.18 7.6 6.4 2.90 7.4 6.3 2.63 7.3 6.3 2.67 7.1 6.4 1.81 6.9 6.3 1.33 6.8 6.0 0.88 7.5 6.3 1.28 7.6 6.3 1.26 7.8 6.6 1.26 8.0 7.5 1.29 8.1 7.8 1.10 8.2 7.9 1.37 8.3 7.8 1.21 8.2 7.6 1.74 8.0 7.5 1.76 7.9 7.6 1.48 7.6 7.5 1.04 7.6 7.3 1.62 8.3 7.6 1.49 8.4 7.5 1.79 8.4 7.6 1.80 8.4 7.9 1.58 8.4 7.9 1.86 8.6 8.1 1.74 8.9 8.2 1.59 8.8 8.0 1.26 8.3 7.5 1.13 7.5 6.8 1.92 7.2 6.5 2.61 7.4 6.6 2.26 8.8 7.6 2.41 9.3 8.0 2.26 9.3 8.1 2.03 8.7 7.7 2.86 8.2 7.5 2.55 8.3 7.6 2.27 8.5 7.8 2.26 8.6 7.8 2.57 8.5 7.8 3.07 8.2 7.5 2.76 8.1 7.5 2.51 7.9 7.1 2.87 8.6 7.5 3.14 8.7 7.5 3.11 8.7 7.6 3.16 8.5 7.7 2.47 8.4 7.7 2.57 8.5 7.9 2.89 8.7 8.1 2.63 8.7 8.2 2.38 8.6 8.2 1.69 8.5 8.2 1.96 8.3 7.9 2.19 8.0 7.3 1.87 8.2 6.9 1.6 8.1 6.6 1.63 8.1 6.7 1.22 8.0 6.9 1.21 7.9 7.0 1.49 7.9 7.1 1.64
Names of X columns:
Totwerkl werklman inflatie
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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