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Data X:
0 1 -1.3 16 0 1.1 0.4 38 0 1.2 -6.3 41 0 0.5 0.4 43 0 -1 -1.3 42 0 -0.8 0.7 40 0 -1.1 -3.5 48 0 -0.4 2 46 0 1.2 3.9 51 0 0.6 7.8 52 0 -0.1 7 55 0 0.3 -0.9 55 0 0.2 3 46 0 -0.2 -0.7 38 0.2 -0.8 8.8 43 4.1 -0.8 -8.1 43 -1 1 2.7 44 0 -0.1 2.5 45 4 -0.8 11.8 35 1.9 0.9 -1.5 36 1.1 1.8 -7.7 36 0 0.1 -13.5 25 0 -0.1 -1.6 31 0.7 -0.8 -1.8 35 1.6 -2.1 2.3 46 2 -0.3 3.1 47 0 1.4 -2.5 40 4.8 -10.8 7.1 29 -1.5 9.4 -7.5 28 -4.4 0.5 -4.8 29 -2.7 1.7 -7.1 29 2.8 1.1 2.7 30 0.7 0 10.5 26 0.4 -2.1 7.6 27 -1.9 -1.7 2.8 18 -0.7 0.4 -5.6 15 0 1.6 -5 1 0 0.5 -2.9 1 0 -0.6 -5.2 2 8.3 0.1 9.7 2 1.4 0 6.9 1 0 -0.6 9.3 -4 -1.2 -1.42E-14 -1.4 1 0 -0.4 1.1 6 5.1 -0.1 -11.2 4 -3.7 1.4 -0.5 -1 -4.1 0.7 -8.9 -3 3.5 -0.9 2.4 -8 0 -1 1.9 -24 1.2 -0.1 0.5 -29 0 0.4 -0.1 -40 0 -0.3 -2.8 -32 0.2 0.2 -1.8 -41 -1.1 0.9 -0.9 -48 -3.9 -0.5 -0.9 -48 0.2 -0.5 1.2 -62 -0.4 0.6 6.6 -74 -0.2 0.8 5.1 -65 -0.7 -0.2 5.6 -61 2.2 -1.42E-14 1.3 -78 2.2 0.2 2.1 -61
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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1 seconds
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Big Analytics Cloud Computing Center
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