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Data X:
105.3 1.0137 85.6 85.21 103 0.9834 95.85 96.95 103.8 0.9643 109.51 108.8 103.4 0.947 91.72 89.38 105.8 0.906 107.95 106.63 101.4 0.9492 98.11 97.76 97 0.9397 94.22 89.05 94.3 0.9041 84.4 93.78 96.6 0.8721 109.89 103.71 97.1 0.8552 114.16 108.24 95.7 0.8564 109.05 114.7 96.9 0.8973 99.54 105.82 97.4 0.9383 103.87 107.63 95.3 0.9217 103.17 105.43 93.6 0.9095 115.68 114.78 91.5 0.892 98.41 101.86 93.1 0.8742 106.7 108.64 91.7 0.8532 108.01 106.31 94.3 0.8607 100.58 93.22 93.9 0.9005 86.44 89.95 90.9 0.9111 102.2 97.27 88.3 0.9059 109.59 102.92 91.3 0.8883 101.87 99.76 91.7 0.8924 88.89 92.26 92.4 0.8833 98.67 95.84 92 0.87 98.08 96.13 95.6 0.8758 109.49 105.52 95.8 0.8858 105.35 102 96.4 0.917 107 102.12 99 0.9554 104.3 100 107 0.9922 103.72 94.49 109.7 0.9778 83.42 86.73 116.2 0.9808 108.82 101.99 115.9 0.9811 116.98 111.83 113.8 1.0014 104.05 101.12 112.6 1.0183 94.31 103.98 113.7 1.0622 101.96 103.26 115.9 1.0773 101.66 101.81 110.3 1.0807 110.45 109.34 111.3 1.0848 106.12 103.01 113.4 1.1582 103.26 97.71 108.2 1.1663 106.8 101.3 104.8 1.1372 104.26 96.48 106 1.1139 80.81 84.62 110.9 1.1222 112.42 104.31 115 1.1692 115.47 111.64 118.4 1.1702 103.34 100.47 121.4 1.2286 102.6 106.24 128.8 1.2613 100.69 101.05 131.7 1.2646 105.67 104.49 141.7 1.2262 123.61 122.69 142.9 1.1985 113.08 109.8 139.4 1.2007 106.46 101.95 134.7 1.2138 123.38 125.07 125 1.2266 109.87 103.46 113.6 1.2176 95.74 102.75 111.5 1.2218 123.06 118.68 108.5 1.249 123.39 118.96 112.3 1.2991 120.28 118.57 116.6 1.3408 115.33 120.39
Names of X columns:
LM D/E EX IM
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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Big Analytics Cloud Computing Center
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