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Data X:
581 103.5 597 104.6 587 118.6 536 106.3 524 110.7 537 121.6 536 107 533 107.6 528 125.6 516 113.5 502 129.2 506 130.9 518 104.7 534 115.2 528 124.5 478 112.3 469 127.5 490 120.6 493 117.5 508 117.7 517 120.4 514 125 510 131.6 527 121.1 542 114.2 565 112.1 555 127 499 116.8 511 112 526 129.7 532 113.6 549 115.7 561 119.5 557 125.8 566 129.6 588 128 620 112.8 626 101.6 620 123.9 573 118.8 573 109.1 574 130.6 580 112.4 590 111 593 116.2 597 119.8 595 117.2 612 127.3 628 107.7 629 97.5 621 120.1 569 110.6 567 111.3 573 119.8 584 105.5 589 108.7 591 128.7 595 119.5 594 121.1 611 128.4
Names of X columns:
Prod Werkl
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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1 seconds
R Server
Big Analytics Cloud Computing Center
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