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Data X:
5 6 445 369 7 5 301 380 6 7 350 474 2 10 305 413 7 10 450 537 9 5 360 439 11 8 287 355 7 2 417 473 7 11 361 435 14 7 478 478 3 11 302 450 4 9 294 365 4 2 300 315 5 3 364 340 4 12 356 326 7 9 340 483 6 7 377 406 10 4 507 409 7 6 321 423 7 9 354 404 5 10 549 551 9 2 444 467 2 6 400 332 1 2 401 442 3 6 259 305 7 6 288 368 7 9 346 411 4 2 287 318 7 10 381 398 8 16 474 586 4 4 329 367 4 4 423 383 5 11 407 533 7 3 412 527 5 5 566 418 7 3 372 576 3 5 290 359 4 11 354 342 6 8 370 456 4 3 377 406 7 1 467 374 5 7 409 568 5 5 310 335 5 6 434 458 0 9 339 456 3 7 385 386 7 8 469 457 6 4 313 396 4 6 373 366 3 4 310 499 6 5 320 354 2 5 340 365 5 13 489 594 3 4 419 456 6 8 460 366 4 4 324 398 5 5 352 468 7 9 473 609 6 4 340 418 4 8 282 352
Names of X columns:
aantdoddon aantdodvrij aantongdon aantongvrij
Type of Correlation
pearson
spearman
kendall
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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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