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Data X:
-0.1 0 0.4 0.6 0 0 -6.3 1.8 0 0 0.4 2.3 0 0 -1.3 1.4 0 0 0.7 0.4 0 0 -3.5 -0.6 0 0 2 -1 0 0 3.9 0.1 0 0 7.8 0.8 0 0 7 0.7 0 0 -0.9 1.1 0 0 3 1.2 0 38 -0.7 1.1 0.3 43 8.8 0.1 4.1 43 -8.1 -0.5 -1.1 44 2.7 0.4 0 45 2.5 0.3 4.1 35 11.8 -0.6 1.9 36 -1.5 0.4 1.1 36 -7.7 2.2 0 25 -13.5 2.3 0 31 -1.6 2.1 0.8 35 -1.8 1.5 1.5 46 2.3 -0.6 2 47 3.1 -0.9 0 40 -2.5 0.3 4.8 29 7.1 -10.4 -1.4 28 -7.5 -1.1 -4.4 29 -4.8 -0.4 -2.8 29 -7.1 1.1 2.9 30 2.7 2.3 0.7 26 10.5 2.2 0.4 27 7.6 0.3 -2 18 2.8 -1.5 -0.7 15 -5.6 -1.1 0 1 -5 0.6 0 1 -2.9 1 0 2 -5.2 0.4 8.4 2 9.7 0.5 1.4 1 6.9 0.5 0 -4 9.3 -0.2 -1.2 1 -1.4 -0.1 0 6 1.1 -0.5 5.1 4 -11.2 -0.6 -3.7 -1 -0.5 0.7 -4.1 -3 -8.9 1.5 3.5 -8 2.4 0.7 0 -24 1.9 -0.3 1.2 -29 0.5 -0.4 0 -40 -0.1 -0.1 0 -32 -2.8 -0.5 0 -41 -1.8 -0.2 -2.8 -48 -0.9 0.6
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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