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Data X:
21 6 160 110 3.9 2.62 16.46 21 6 160 110 3.9 2.875 17.02 22.8 4 108 93 3.85 2.32 18.61 21.4 6 258 110 3.08 3.215 19.44 18.7 8 360 175 3.15 3.44 17.02 18.1 6 225 105 2.76 3.46 20.22 14.3 8 360 245 3.21 3.57 15.84 24.4 4 146.7 62 3.69 3.19 20 22.8 4 140.8 95 3.92 3.15 22.9 19.2 6 167.6 123 3.92 3.44 18.3 17.8 6 167.6 123 3.92 3.44 18.9 16.4 8 275.8 180 3.07 4.07 17.4 17.3 8 275.8 180 3.07 3.73 17.6 15.2 8 275.8 180 3.07 3.78 18 10.4 8 472 205 2.93 5.25 17.98 10.4 8 460 215 3 5.424 17.82 14.7 8 440 230 3.23 5.345 17.42 32.4 4 78.7 66 4.08 2.2 19.47 30.4 4 75.7 52 4.93 1.615 18.52 33.9 4 71.1 65 4.22 1.835 19.9 21.5 4 120.1 97 3.7 2.465 20.01 15.5 8 318 150 2.76 3.52 16.87 15.2 8 304 150 3.15 3.435 17.3 13.3 8 350 245 3.73 3.84 15.41 19.2 8 400 175 3.08 3.845 17.05 27.3 4 79 66 4.08 1.935 18.9 26 4 120.3 91 4.43 2.14 16.7 30.4 4 95.1 113 3.77 1.513 16.9 15.8 8 351 264 4.22 3.17 14.5 19.7 6 145 175 3.62 2.77 15.5 15 8 301 335 3.54 3.57 14.6 21.4 4 121 109 4.11 2.78 18.6
Names of X columns:
X1 X2 X3 X4 X5 X6 X7
Type of Correlation
pearson
spearman
kendall
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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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