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Data X:
100.00 100.00 100.00 100.00 100.28 99.30 98.49 106.54 100.00 111.19 99.15 127.63 98.62 106.99 100.28 141.72 98.35 108.39 103.82 147.95 98.35 105.59 108.16 142.16 104.68 104.90 112.33 147.95 104.13 84.62 110.70 155.82 103.58 110.49 111.04 164.13 104.68 118.18 111.07 159.16 104.41 105.59 113.37 147.14 105.79 95.80 115.28 159.16 107.99 103.50 120.25 178.85 108.54 102.80 121.96 200.44 107.99 111.89 122.35 189.43 109.09 107.69 122.81 160.16 107.99 104.90 131.12 157.02 109.09 108.39 132.04 168.91 115.43 105.59 128.74 173.19 115.98 81.82 126.11 175.83 115.70 113.99 127.05 158.78 115.15 116.78 132.37 166.96 112.95 104.90 132.48 171.24 115.15 104.20 139.09 179.55 117.36 102.10 142.79 191.00 117.91 106.99 143.17 196.41 118.46 125.17 138.82 206.80 116.80 114.69 135.68 208.94 116.53 107.69 135.93 224.86 117.63 125.17 137.42 217.31 121.49 111.19 138.87 229.96 123.69 97.20 137.85 252.36 124.52 124.48 138.32 255.25 127.27 125.17 141.40 290.37 125.34 121.68 147.07 269.67 127.00 116.78 151.79 240.53 127.00 111.89 148.52 252.86 127.55 116.08 147.33 265.51 127.27 133.57 149.45 299.31 125.62 124.48 146.47 297.42 125.34 120.28 143.71 277.09 125.62 130.07 137.72 313.59 130.03 113.99 136.27 335.75 130.03 105.59 139.16 370.67 129.75 134.27 138.75 375.33 128.10 123.78 136.02 358.65 126.45 133.57 133.43 334.80 128.10 125.87 134.22 335.05 128.93 122.38 137.02 364.07 128.65 124.48 135.15 350.47 127.55 147.55 136.08 350.16 126.72 120.28 138.92 393.46 127.27 135.66 144.57 405.29 127.00 138.46 143.21 406.86 131.13 123.08 143.60 426.12 131.13 113.29 145.04 422.97 129.75 136.36 144.08 373.63 124.79 139.16 142.77 335.18 122.04 139.86 145.83 329.89 121.76 120.98 149.59 346.32 100.00 100.00 100.00 100.00 100.28 99.30 98.49 106.54 100.00 111.19 99.15 127.63 98.62 106.99 100.28 141.72 98.35 108.39 103.82 147.95 98.35 105.59 108.16 142.16 104.68 104.90 112.33 147.95 104.13 84.62 110.70 155.82 103.58 110.49 111.04 164.13 104.68 118.18 111.07 159.16 104.41 105.59 113.37 147.14 105.79 95.80 115.28 159.16 107.99 103.50 120.25 178.85 108.54 102.80 121.96 200.44 107.99 111.89 122.35 189.43 109.09 107.69 122.81 160.16 107.99 104.90 131.12 157.02 109.09 108.39 132.04 168.91 115.43 105.59 128.74 173.19 115.98 81.82 126.11 175.83 115.70 113.99 127.05 158.78 115.15 116.78 132.37 166.96 112.95 104.90 132.48 171.24 115.15 104.20 139.09 179.55 117.36 102.10 142.79 191.00 117.91 106.99 143.17 196.41 118.46 125.17 138.82 206.80 116.80 114.69 135.68 208.94 116.53 107.69 135.93 224.86 117.63 125.17 137.42 217.31 121.49 111.19 138.87 229.96 123.69 97.20 137.85 252.36 124.52 124.48 138.32 255.25 127.27 125.17 141.40 290.37 125.34 121.68 147.07 269.67 127.00 116.78 151.79 240.53 127.00 111.89 148.52 252.86 127.55 116.08 147.33 265.51 127.27 133.57 149.45 299.31 125.62 124.48 146.47 297.42 125.34 120.28 143.71 277.09 125.62 130.07 137.72 313.59 130.03 113.99 136.27 335.75 130.03 105.59 139.16 370.67 129.75 134.27 138.75 375.33 128.10 123.78 136.02 358.65 126.45 133.57 133.43 334.80 128.10 125.87 134.22 335.05 128.93 122.38 137.02 364.07 128.65 124.48 135.15 350.47 127.55 147.55 136.08 350.16 126.72 120.28 138.92 393.46 127.27 135.66 144.57 405.29 127.00 138.46 143.21 406.86 131.13 123.08 143.60 426.12 131.13 113.29 145.04 422.97 129.75 136.36 144.08 373.63 124.79 139.16 142.77 335.18 122.04 139.86 145.83 329.89 121.76 120.98 149.59 346.32
Names of X columns:
WK>25jB ExpBE WsskE-$ RuwOlB/$
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
R Server
Big Analytics Cloud Computing Center
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