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Data X:
120.9 611 119.6 594 125.9 595 116.1 591 107.5 589 116.7 584 112.5 573 113 567 126.4 569 114.1 621 112.5 629 112.4 628 113.1 612 116.3 595 111.7 597 118.8 593 116.5 590 125.1 580 113.1 574 119.6 573 114.4 573 114 620 117.8 626 117 620 120.9 588 115 566 117.3 557 119.4 561 114.9 549 125.8 532 117.6 526 117.6 511 114.9 499 121.9 555 117 565 106.4 542 110.5 527 113.6 510 114.2 514 125.4 517 124.6 508 120.2 493 120.8 490 111.4 469 124.1 478 120.2 528 125.5 534 116 518 117 506 105.7 502 102 516 106.4 528 96.9 533 107.6 536 98.8 537 101.1 524 105.7 536 104.6 587 103.2 597 101.6 581
Names of X columns:
ChemischeNijverheid Werkloosheid
Type of Correlation
kendall
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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