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Data X:
103.63 107.47 103.34 100.30 103.64 107.99 103.38 98.50 103.66 108.36 103.64 95.10 103.77 108.61 104.04 93.10 103.88 108.80 104.11 92.20 103.91 109.05 104.11 89.00 103.91 109.12 104.11 86.40 103.92 109.28 104.17 84.50 104.05 110.00 105.16 82.70 104.23 110.78 105.86 80.80 104.30 110.84 106.11 81.80 104.31 110.83 106.11 81.80 104.31 111.38 106.11 82.90 104.34 112.78 106.13 83.80 104.55 113.56 106.67 86.20 104.65 113.60 106.85 86.10 104.73 113.72 106.97 86.20 104.75 113.73 107.02 88.80 104.75 113.82 107.02 89.60 104.76 113.85 107.07 87.80 104.94 113.96 107.76 88.30 105.29 114.24 108.10 88.60 105.38 114.36 108.18 91.00 105.43 114.44 108.22 91.50 105.43 114.91 108.22 95.40 105.42 115.76 108.17 98.70 105.52 115.91 108.31 99.90 105.69 116.01 108.31 98.60 105.72 116.01 108.36 100.30 105.74 116.15 108.46 100.20 105.74 116.17 108.46 100.40 105.74 116.20 108.46 101.40 105.95 116.32 109.43 103.00 106.17 116.68 109.55 109.10 106.34 116.74 109.62 111.40 106.37 116.86 109.70 114.10 106.37 117.57 109.70 121.80 106.36 118.07 109.56 127.60 106.44 118.56 109.92 129.90 106.29 118.70 109.81 128.00 106.23 118.76 109.78 123.50 106.23 118.88 109.80 124.00 106.23 118.98 109.80 127.40 106.23 119.30 109.79 127.60 106.34 118.95 110.40 128.40 106.44 119.06 110.95 131.40 106.44 119.34 111.07 135.10 106.48 119.37 111.09 134.00 106.50 119.60 111.10 144.50 106.57 120.14 111.01 147.30 106.40 121.25 111.01 150.90 106.37 121.61 111.35 148.70 106.25 122.01 111.42 141.40 106.21 121.77 111.24 138.90 106.21 122.26 111.24 139.80 106.24 122.13 111.47 145.60 106.19 122.11 111.57 147.90 106.08 122.40 111.96 148.50 106.13 122.59 112.02 151.10 106.09 122.67 112.02 157.50
Names of X columns:
KLA STO SCH TOTPR
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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