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Data X:
104.3 97.5 0.2 513 103.9 97.1 0.8 503 103.9 97.5 1.2 471 103.9 98.5 4.5 471 108.0 100.5 0.4 476 108.0 102.8 5.9 475 108.0 105.2 6.5 470 108.0 107.4 12.8 461 108.0 108.0 4.2 455 108.0 107.6 -3.3 456 108.0 107.0 -12.5 517 108.0 105.8 -16.3 525 108.0 104.3 -10.5 523 108.0 103.8 -11.8 519 108.0 104.4 -11.4 509 108.0 106.2 -17.7 512 108.0 108.5 -17.3 519 108.0 109.8 -18.6 517 108.0 110.3 -17.9 510 108.0 109.7 -21.4 509 108.0 108.7 -19.4 501 108.0 108.9 -15.5 507 108.0 109.7 -7.7 569 108.0 110.4 -0.7 580 108.0 111.4 -1.6 578 108.0 112.6 1.4 565 108.0 113.6 0.7 547 108.2 113.8 9.5 555 112.3 113.2 1.4 562 111.3 113.6 4.1 561 111.3 113.9 6.6 555 115.3 113.4 18.4 544 117.2 113.8 16.9 537 118.3 116.0 9.2 543 118.3 118.3 -4.3 594 118.3 120.5 -5.9 611 119.0 121.9 -7.7 613 120.6 121.2 -5.4 611 122.6 120.2 -2.3 594 122.6 120.6 -4.8 595 127.4 110.2 2.3 591 125.9 109.2 -5.2 589 121.5 108.7 -10 584 118.8 109.9 -17.1 573 121.6 112.2 -14.4 567 122.3 114.5 -3.9 569 122.7 114.7 3.7 621 120.8 113.2 6.5 629 120.1 112.1 0.9 628 120.1 112.6 -4.1 612 120.1 113.6 -7 595 120.1 114.0 -12.2 597 128.4 114.5 -2.5 593 129.8 115.0 4.4 590 129.8 114.9 13.7 580 128.6 114.8 12.3 574 128.6 114.3 13.4 573 133.7 113.7 2.2 573 130.0 114.5 1.7 620 125.9 116.0 -7.2 626 129.4 116.6 -4.8 620 129.4 116.2 -2.9 588 130.6 115.7 -2.4 566 130.6 115.6 -2.5 557 130.6 115.2 -5.3 561 130.8 115.0 -7.1 549 129.7 115.7 -8 532 125.8 115.9 -8.9 526 126.0 115.6 -7.7 511 125.6 115.9 -1.1 499 125.4 117.0 4 555 124.7 117.9 9.6 565 126.9 118.8 10.9 542 129.1 119.9 13 527
Names of X columns:
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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