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Data X:
513 96 87 503 86 75 471 82 74 471 92 91 476 99 101 475 101 103 470 102 106 461 100 102 455 101 105 456 100 105 517 99 100 525 97 95 523 97 96 519 97 98 509 96 99 512 92 92 519 91 84 517 87 81 510 82 72 509 89 89 501 91 96 507 90 91 569 87 88 580 89 90 578 95 98 565 85 87 547 94 100 555 94 100 562 97 104 561 99 107 555 97 105 544 96 102 537 94 98 543 100 106 594 96 97 611 98 101 613 98 100 611 94 93 594 93 94 595 94 96 591 94 96 589 97 98 584 98 102 573 95 95 567 89 85 569 89 84 621 89 82 629 90 87 628 86 77 612 92 90 595 91 90 597 95 94 593 99 97 590 98 96 580 95 93 574 96 93 573 94 93 573 98 97 620 98 100 626 98 95 620 98 97 588 102 103 566 101 102 557 92 93 561 99 99 549 101 100 532 99 97 526 102 104 511 102 102 499 101 103 555 99 100 565 98 90 542 98 90
Names of X columns:
Werkl ConsVer Econ
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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