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Data X:
7.6 1.62 -0.8 8.3 1.49 -0.2 8.4 1.79 0.2 8.4 1.8 1 8.4 1.58 0 8.4 1.86 -0.2 8.6 1.74 1 8.9 1.59 0.4 8.8 1.26 1 8.3 1.13 1.7 7.5 1.92 3.1 7.2 2.61 3.3 7.4 2.26 3.1 8.8 2.41 3.5 9.3 2.26 6 9.3 2.03 5.7 8.7 2.86 4.7 8.2 2.55 4.2 8.3 2.27 3.6 8.5 2.26 4.4 8.6 2.57 2.5 8.5 3.07 -0.6 8.2 2.76 -1.9 8.1 2.51 -1.9 7.9 2.87 0.7 8.6 3.14 -0.9 8.7 3.11 -1.7 8.7 3.16 -3.1 8.5 2.47 -2.1 8.4 2.57 0.2 8.5 2.89 1.2 8.7 2.63 3.8 8.7 2.38 4 8.6 1.69 6.6 8.5 1.96 5.3 8.3 2.19 7.6 8 1.87 4.7 8.2 1.6 6.6 8.1 1.63 4.4 8.1 1.22 4.6 8 1.21 6 7.9 1.49 4.8 7.9 1.64 4 8 1.66 2.7 8 1.77 3 7.9 1.82 4.1 8 1.78 4 7.7 1.28 2.7 7.2 1.29 2.6 7.5 1.37 3.1 7.3 1.12 4.4 7 1.51 3 7 2.24 2 7 2.94 1.3 7.2 3.09 1.5 7.3 3.46 1.3 7.1 3.64 3.2 6.8 4.39 1.8 6.4 4.15 3.3 6.1 5.21 1 6.5 5.8 2.4 7.7 5.91 0.4 7.9 5.39 -0.1 7.5 5.46 1.3 6.9 4.72 -1.1 6.6 3.14 -4.4 6.9 2.63 -7.5 7.7 2.32 -12.2 8 1.93 -14.5 8 0.62 -16 7.7 0.6 -16.7 7.3 -0.37 -16.3 7.4 -1.1 -16.9
Names of X columns:
TWG Infl EcGr
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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