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Data X:
130.3 485 130.9 464 104.7 460 115.2 467 124.5 460 112.3 448 127.5 443 120.6 436 117.5 431 117.7 484 120.4 510 125 513 131.6 503 121.1 471 114.2 471 112.1 476 127 475 116.8 470 112 461 129.7 455 113.6 456 115.7 517 119.5 525 125.8 523 129.6 519 128 509 112.8 512 101.6 519 123.9 517 118.8 510 109.1 509 130.6 501 112.4 507 111 569 116.2 580 119.8 578 117.2 565 127.3 547 107.7 555 97.5 562 120.1 561 110.6 555 111.3 544 119.8 537 105.5 543 108.7 594 128.7 611 119.5 613 121.1 611 128.4 594 108.8 595 107.5 591 125.6 589 102.9 584 107.5 573 120.4 567 104.3 569 100.6 621 121.9 629 112.7 628 124.9 612 123.9 595 102.2 597 104.9 593 109.8 590 98.9 580 107.3 574 112.6 573 104 573 110.6 620 100.8 626 103.8 620 117 588 108.4 566 95.5 557 96.9 561 103.9 549 101.1 532 100.6 526 104.3 511 98 499 99.5 555 97.4 565 105.6 542 117.5 527 107.4 510 97.8 514 91.5 517 107.7 508 100.1 493 96.6 490 106.8 469 98 478 98.6 528
Names of X columns:
PROD WLH
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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