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Data X:
100.00 100.00 100.00 100.00 98.49 98.86 108.45 127.27 99.15 96.87 115.49 109.09 100.28 103.18 129.58 136.36 103.82 104.66 143.66 100.00 108.16 103.74 147.89 118.18 112.33 103.87 152.11 136.36 110.70 98.10 152.11 100.00 111.04 98.91 156.34 127.27 111.07 109.43 154.93 118.18 113.37 104.89 156.34 136.36 115.28 88.63 143.66 145.45 120.25 97.03 135.21 154.55 121.96 93.79 130.99 100.00 122.35 97.61 125.35 145.45 122.81 98.17 123.94 118.18 131.12 96.31 125.35 154.55 132.04 97.82 126.76 145.45 128.74 87.52 125.35 154.55 126.11 85.71 123.94 172.73 127.05 89.15 126.76 163.64 132.37 90.65 123.94 172.73 132.48 92.74 123.94 145.45 139.09 80.00 136.62 136.36 142.79 84.33 138.03 145.45 143.17 93.26 140.85 145.45 138.82 115.89 142.25 154.55 135.68 105.21 142.25 181.82 135.93 94.23 140.85 181.82 137.42 106.12 126.76 172.73 138.87 94.41 123.94 154.55 137.85 101.30 118.31 163.64 138.32 98.43 112.68 172.73 141.40 107.94 114.08 154.55 147.07 102.82 112.68 181.82 151.79 92.33 109.86 190.91 148.52 97.48 108.45 218.18 147.33 88.37 102.82 227.27 149.45 92.50 101.41 227.27 146.47 81.48 101.41 236.36 143.71 92.55 94.37 200.00 137.72 98.96 94.37 227.27 136.27 77.28 90.14 254.55 139.16 91.01 90.14 254.55 138.75 81.21 88.73 263.64 136.02 88.41 84.51 272.73 133.43 96.02 77.46 281.82 134.22 91.59 66.20 263.64 137.02 86.30 53.52 245.45 135.15 86.37 50.70 200.00 136.08 105.41 35.21 227.27 138.92 76.73 23.94 209.09 144.57 93.26 22.54 236.36 143.21 95.02 30.99 209.09 143.60 84.32 30.99 200.00 145.04 93.24 28.17 163.64 144.08 89.81 26.76 163.64 142.77 111.66 22.54 181.82 145.83 103.23 26.76 145.45 149.59 103.21 36.62 163.64
Names of X columns:
$wssk imp hb infl
Type of Correlation
pearson
spearman
kendall
Chart options
Title:
R Code
panel.tau <- function(x, y, digits=2, prefix='', cex.cor) { usr <- par('usr'); on.exit(par(usr)) par(usr = c(0, 1, 0, 1)) rr <- cor.test(x, y, method='kendall') r <- round(rr$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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