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Data X:
0.00 16.00 0.00 38.00 0.00 41.00 0.00 43.00 0.00 42.00 0.00 40.00 0.00 48.00 0.00 46.00 0.00 51.00 0.00 52.00 0.00 55.00 0.00 55.00 0.00 46.00 0.00 38.00 0.20 43.00 4.10 43.00 -1.00 44.00 0.00 45.00 4.00 35.00 1.90 36.00 1.10 36.00 0.00 25.00 0.00 31.00 0.70 35.00 1.60 46.00 2.00 47.00 0.00 40.00 4.80 29.00 -1.50 28.00 -4.40 29.00 -2.70 29.00 2.80 30.00 0.70 26.00 0.40 27.00 -1.90 18.00 -0.70 15.00 0.00 1.00 0.00 1.00 0.00 2.00 8.30 2.00 1.40 1.00 0.00 -4.00 -1.20 1.00 0.00 6.00 5.10 4.00 -3.70 -1.00 -4.10 -3.00 3.50 -8.00 0.00 -24.00 1.20 -29.00 0.00 -40.00 0.00 -32.00 0.20 -41.00 -1.10 -48.00 -3.90 -48.00 0.20 -62.00 -0.40 -74.00 -0.20 -65.00 -0.70 -61.00 2.20 -78.00 2.20 -61.00
Names of X columns:
EP WLH
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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