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Data X:
8 359 8.798 8.1 304.6 8.841 8.3 297.7 8.896 8.2 303.3 8.951 8.1 304.7 9.027 7.7 331.3 9.079 7.6 318.8 9.129 7.7 306.8 9.178 8.2 331.1 9.190 8.4 284.1 9.251 8.4 259.7 9.328 8.6 335.8 9.428 8.4 338.5 9.499 8.5 310.3 9.556 8.7 322.1 9.606 8.7 289.3 9.632 8.6 300.8 9.660 7.4 360.6 9.651 7.3 327.3 9.695 7.4 304.1 9.727 9 362 9.757 9.2 287.8 9.788 9.2 286.1 9.813 8.5 358.2 9.823 8.3 346 9.837 8.3 329.9 9.842 8.6 334.3 9.855 8.6 303.7 9.863 8.5 307.6 9.855 8.1 351.7 9.858 8.1 324.6 9.853 8 311.9 9.858 8.6 361.5 9.859 8.7 271.1 9.865 8.7 286.5 9.876 8.6 352.8 9.928 8.4 322.4 9.948 8.4 335 9.987 8.7 322.2 10.022 8.7 313.6 10.068 8.5 323.3 10.101 8.3 379.1 10.131 8.3 315.6 10.143 8.3 353.6 10.170 8.1 371.7 10.192 8.2 282.9 10.214 8.1 298.8 10.239 8.1 361.8 10.263 7.9 365.9 10.310 7.7 357.6 10.355 8.1 335.4 10.396 8 340.1 10.446 7.7 337.8 10.511 7.8 389.6 10.585
Names of X columns:
Werkloos Prod Tot.Bevolking
Type of Correlation
Default
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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