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Data X:
NA -0.32 9.3 NA 2.62 2.94 NA 3.1 0.48 NA 1.59 -1.51 NA -5.79 -7.38 NA -5.35 0.44 NA 0.85 6.2 NA 0.64 -0.21 NA 4.27 3.63 NA 1.66 -2.61 NA -2.09 -3.75 295 0.07 2.16 4034 -0.52 -0.59 -3485 -0.17 0.35 2312 0.53 0.7 6976 2.84 2.31 5929 3.76 0.92 282 6.38 2.62 476 -1.02 -7.4 -3701 1.61 2.63 -552 2.98 1.37 -398 0.62 -2.36 -2534 4.97 4.35 1465 -3.97 -8.94 -1741 -4.75 -0.78 1714 -2.7 2.05 -3792 4.99 7.69 -7342 4.36 -0.63 -5552 7.98 3.62 -274 -1.47 -9.45 2725 4.54 6.01 -34 7.5 2.96 1193 2.28 -5.22 -682 6.04 3.76 -2997 -1.98 -8.02 -690 -9.71 -7.73 -3109 -2.42 7.29 2213 3.71 6.13 3915 -0.14 -3.85 5410 1.05 1.19 683 6.04 4.99 4331 1.84 -4.2 -3353 -0.6 -2.44 187 1.89 2.49 -1402 0.18 -1.71 -1479 -10.44 -10.62 1210 -5.94 4.5 -1097 0.59 6.53 -1331 1.42 0.83
Names of X columns:
Wagens Index Olie
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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