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Data X:
269645 308347 1.8 8.4 267037 298427 1.6 8.4 258113 289231 1.9 8.4 262813 291975 1.7 8.6 267413 294912 1.6 8.9 267366 293488 1.3 8.8 264777 290555 1.1 8.3 258863 284736 1.9 7.5 254844 281818 2.6 7.2 254868 287854 2.3 7.4 277267 316263 2.4 8.8 285351 325412 2.2 9.3 286602 326011 2 9.3 283042 328282 2.9 8.7 276687 317480 2.6 8.2 277915 317539 2.3 8.3 277128 313737 2.3 8.5 277103 312276 2.6 8.6 275037 309391 3.1 8.5 270150 302950 2.8 8.2 267140 300316 2.5 8.1 264993 304035 2.9 7.9 287259 333476 3.1 8.6 291186 337698 3.1 8.7 292300 335932 3.2 8.7 288186 323931 2.5 8.5 281477 313927 2.6 8.4 282656 314485 2.9 8.5 280190 313218 2.6 8.7 280408 309664 2.4 8.7 276836 302963 1.7 8.6 275216 298989 2 8.5 274352 298423 2.2 8.3 271311 301631 1.9 8 289802 329765 1.6 8.2 290726 335083 1.6 8.1 292300 327616 1.2 8.1 278506 309119 1.2 8 269826 295916 1.5 7.9 265861 291413 1.6 7.9 269034 291542 1.7 8 264176 284678 1.8 8 255198 276475 1.8 7.9 253353 272566 1.8 8 246057 264981 1.3 7.7 235372 263290 1.3 7.2 258556 296806 1.4 7.5 260993 303598 1.1 7.3 254663 286994 1.5 7 250643 276427 2.2 7 243422 266424 2.9 7 247105 267153 3.1 7.2 248541 268381 3.5 7.3 245039 262522 3.6 7.1 237080 255542 4.4 6.8 237085 253158 4.2 6.4 225554 243803 5.2 6.1 226839 250741 5.8 6.5 247934 280445 5.9 7.7 248333 285257 5.4 7.9 246969 270976 5.5 7.5 245098 261076 4.7 6.9 246263 255603 3.1 6.6 255765 260376 2.6 6.9 264319 263903 2.3 7.7 268347 264291 1.9 8 273046 263276 0.6 8 273963 262572 0.6 7.7 267430 256167 -0.4 7.3 271993 264221 -1.1 7.4 292710 293860 -1.7 8.1 295881 300713 -0.8 8.3
Names of X columns:
man vrouw infl totw
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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Big Analytics Cloud Computing Center
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