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Data X:
100.00 100.00 100.00 100.00 108.16 211.30 99.95 99.97 114.02 333.91 102.07 101.03 102.19 187.83 102.02 101.00 110.37 254.78 102.63 101.30 96.86 121.74 102.88 101.43 94.19 113.91 103.01 101.49 99.52 140.87 104.33 102.14 94.06 142.61 105.21 102.58 97.55 173.91 104.73 102.34 78.15 121.74 104.17 102.07 81.24 113.91 103.69 101.83 92.36 115.65 104.33 102.14 96.06 155.65 105.21 102.58 114.05 256.52 105.31 102.63 110.66 217.39 105.54 102.74 104.92 230.43 106.70 103.32 90.00 171.30 106.60 103.27 95.70 155.65 105.01 102.48 86.03 133.04 104.33 102.14 84.85 140.87 104.17 102.07 100.04 169.57 103.42 101.69 80.92 183.48 102.33 101.15 74.07 173.91 101.82 100.90 77.30 176.52 103.57 101.77 97.23 176.52 103.90 101.93 90.76 306.96 104.58 102.27 100.56 247.83 105.03 102.49 92.01 171.30 105.67 102.80 99.24 140.87 105.69 102.82 105.87 171.30 105.72 102.83 90.99 153.04 105.84 102.89 93.31 184.35 105.79 102.87 91.17 236.52 105.39 102.67 77.33 177.39 105.97 102.96 91.13 164.35 106.50 103.22 85.01 208.70 107.13 103.53 83.90 211.30 109.36 104.63 104.86 403.48 109.36 104.63 110.90 328.70 108.42 104.17 95.44 261.74 107.94 103.93 111.62 254.78 108.10 104.01 108.89 277.39 108.40 104.16 96.18 282.61 110.55 105.22 101.97 357.39 111.81 105.85 99.12 284.35 112.55 106.21 86.78 183.48 111.66 105.77 118.42 186.09 111.38 105.63 118.74 179.13 113.10 106.49 106.53 175.65 115.18 107.51 134.78 317.39 121.07 110.43 104.68 375.65 123.07 111.42 105.30 277.39 123.40 111.58 139.41 313.91 122.92 111.34 103.61 203.48 122.39 111.08 99.78 199.13 123.55 111.66 103.46 240.87 124.97 112.36 120.06 238.26 124.87 112.31 96.71 258.26 123.27 111.52 107.13 335.65 121.96 110.87 105.36 302.61 122.49 111.13 111.69 373.91 125.68 112.71 132.05 570.43 126.76 113.25 126.80 382.61 126.44 113.09 154.48 307.83 125.35 112.55 141.56 435.65 126.01 112.87 109.95 306.09 127.45 113.59 127.90 250.43 130.58 115.14 133.09 350.43 133.09 116.38 120.08 426.09 133.34 116.50 117.56 477.39 132.84 116.25 143.04 437.39 133.80 116.73
Names of X columns:
BV HK BN VI
Type of Correlation
red
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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