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Data X:
1.4 2 0.4 1.2 2 1 1 2 1.7 1.7 2 3.1 2.4 2 3.3 2 2 3.1 2.1 2 3.5 2 2 6 1.8 2 5.7 2.7 2 4.7 2.3 2 4.2 1.9 2 3.6 2 2 4.4 2.3 2 2.5 2.8 2 -0.6 2.4 2 -1.9 2.3 2 -1.9 2.7 2 0.7 2.7 2 -0.9 2.9 2 -1.7 3 2 -3.1 2.2 2 -2.1 2.3 2 0.2 2.8 2.21 1.2 2.8 2.25 3.8 2.8 2.25 4 2.2 2.45 6.6 2.6 2.5 5.3 2.8 2.5 7.6 2.5 2.64 4.7 2.4 2.75 6.6 2.3 2.93 4.4 1.9 3 4.6 1.7 3.17 6 2 3.25 4.8 2.1 3.39 4 1.7 3.5 2.7 1.8 3.5 3 1.8 3.65 4.1 1.8 3.75 4 1.3 3.75 2.7 1.3 3.9 2.6 1.3 4 3.1 1.2 4 4.4 1.4 4 3 2.2 4 2 2.9 4 1.3 3.1 4 1.5 3.5 4 1.3 3.6 4 3.2 4.4 4 1.8 4.1 4 3.3 5.1 4 1 5.8 4 2.4 5.9 4.18 0.4 5.4 4.25 -0.1 5.5 4.25 1.3 4.8 3.97 -1.1 3.2 3.42 -4.4 2.7 2.75 -7.5 2.1 2.31 -12.2 1.9 2 -14.5 0.6 1.66 -16 0.7 1.31 -16.7 -0.2 1.09 -16.3 -1 1 -16.9 -1.7 1 -15 -0.7 1 -14.6 -1 1 -14.3
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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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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