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Data X:
25.5 7.5 2 25.6 7.4 1.8 23.7 7.1 2.7 22 6.8 2.3 21.3 6.9 1.9 20.7 7.2 2 20.4 7.4 2.3 20.3 7.3 2.8 20.4 6.9 2.4 19.8 6.9 2.3 19.5 6.8 2.7 23.1 7.1 2.7 23.5 7.2 2.9 23.5 7.1 3 22.9 7 2.2 21.9 6.9 2.3 21.5 7.1 2.8 20.5 7.3 2.8 20.2 7.5 2.8 19.4 7.5 2.2 19.2 7.5 2.6 18.8 7.3 2.8 18.8 7 2.5 22.6 6.7 2.4 23.3 6.5 2.3 23 6.5 1.9 21.4 6.5 1.7 19.9 6.6 2 18.8 6.8 2.1 18.6 6.9 1.7 18.4 6.9 1.8 18.6 6.8 1.8 19.9 6.8 1.8 19.2 6.5 1.3 18.4 6.1 1.3 21.1 6.1 1.3 20.5 5.9 1.2 19.1 5.7 1.4 18.1 5.9 2.2 17 5.9 2.9 17.1 6.1 3.1 17.4 6.3 3.5 16.8 6.2 3.6 15.3 5.9 4.4 14.3 5.7 4.1 13.4 5.4 5.1 15.3 5.6 5.8 22.1 6.2 5.9 23.7 6.3 5.4 22.2 6 5.5 19.5 5.6 4.8 16.6 5.5 3.2 17.3 5.9 2.7 19.8 6.5 2.1 21.2 6.8 1.9 21.5 6.8 0.6 20.6 6.5 0.7 19.1 6.2 -0.2 19.6 6.2 -1 23.5 6.5 -1.7 24 6.7 -0.7
Names of X columns:
W<25 W>25 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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