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Data X:
1.4 1.9 2 1.6 1 1.6 2.1 1.7 -0.8 0 2 1.6 -2.9 -1.3 1.8 1.4 -0.7 -0.4 2.7 2.1 -0.7 -0.3 2.3 1.9 1.5 1.4 1.9 1.7 3 2.6 2 1.8 3.2 2.8 2.3 2 3.1 2.6 2.8 2.5 3.9 3.4 2.4 2.1 1 1.7 2.3 2.1 1.3 1.2 2.7 2.3 0.8 0 2.7 2.4 1.2 0 2.9 2.4 2.9 1.6 3 2.3 3.9 2.5 2.2 1.7 4.5 3.2 2.3 2 4.5 3.4 2.8 2.3 3.3 2.3 2.8 2 2 1.9 2.8 2 1.5 1.7 2.2 1.3 1 1.9 2.6 1.7 2.1 3.3 2.8 1.9 3 3.8 2.5 1.7 4 4.4 2.4 1.6 5.1 4.5 2.3 1.7 4.5 3.5 1.9 1.8 4.2 3 1.7 1.9 3.3 2.8 2 1.9 2.7 2.9 2.1 1.9 1.8 2.6 1.7 2 1.4 2.1 1.8 2.1 0.5 1.5 1.8 1.9 -0.4 1.1 1.8 1.9 0.8 1.5 1.3 1.3 0.7 1.7 1.3 1.3 1.9 2.3 1.3 1.4 2 2.3 1.2 1.2 1.1 1.9 1.4 1.3 0.9 2 2.2 1.8 0.4 1.6 2.9 2.2 0.7 1.2 3.1 2.6 2.1 1.9 3.5 2.8 2.8 2.1 3.6 3.1 3.9 2.4 4.4 3.9 3.5 2.9 4.1 3.7 2 2.5 5.1 4.6 2 2.3 5.8 5.1 1.5 2.5 5.9 5.2 2.5 2.6 5.4 4.9 3.1 2.4 5.5 5.1 2.7 2.5 4.8 4.8 2.8 2.1 3.2 3.9 2.5 2.2 2.7 3.5 3 2.7 2.1 3.3 3.2 3 1.9 2.8 2.8 3.2 0.6 1.6 2.4 3 0.7 1.5 2 2.7 -0.2 0.7 1.8 2.5 -1 -0.1 1.1 1.6 -1.7 -0.7 -1.5 0.1 -0.7 -0.2 -3.7 -1.9 -1 -0.6
Names of X columns:
bbp dnst hicp gzhdsi
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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