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Data X:
467 101.0 460 98.7 448 105.1 443 98.4 436 101.7 431 102.9 484 92.2 510 94.9 513 92.8 503 98.5 471 94.3 471 87.4 476 103.4 475 101.2 470 109.6 461 111.9 455 108.9 456 105.6 517 107.8 525 97.5 523 102.4 519 105.6 509 99.8 512 96.2 519 113.1 517 107.4 510 116.8 509 112.9 501 105.3 507 109.3 569 107.9 580 101.1 578 114.7 565 116.2 547 108.4 555 113.4 562 108.7 561 112.6 555 124.2 544 114.9 537 110.5 543 121.5 594 118.1 611 111.7 613 132.7 611 119.0 594 116.7 595 120.1 591 113.4 589 106.6 584 116.3 573 112.6 567 111.6 569 125.1 621 110.7 629 109.6 628 114.2 612 113.4 595 116.0 597 109.6 593 117.8 590 115.8 580 125.3 574 113.0 573 120.5 573 116.6 620 111.8 626 115.2 620 118.6 588 122.4 566 116.4 557 114.5 561 119.8 549 115.8 532 127.8 526 118.8 511 119.7 499 118.6 555 120.8 565 115.9 542 109.7 527 114.8 510 116.2 514 112.2
Names of X columns:
U productie
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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