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Data X:
110.40 109.20 99.90 72.50 96.40 88.60 99.80 59.40 101.90 94.30 99.80 85.70 106.20 98.30 100.30 88.20 81.00 86.40 99.90 62.80 94.70 80.60 99.90 87.00 101.00 104.10 100.00 79.20 109.40 108.20 100.10 112.00 102.30 93.40 100.10 79.20 90.70 71.90 100.20 132.10 96.20 94.10 100.30 40.10 96.10 94.90 100.60 69.00 106.00 96.40 100.00 59.40 103.10 91.10 100.10 73.80 102.00 84.40 100.20 57.40 104.70 86.40 100.00 81.10 86.00 88.00 100.10 46.60 92.10 75.10 100.10 41.40 106.90 109.70 100.10 71.20 112.60 103.00 100.50 67.90 101.70 82.10 100.50 72.00 92.00 68.00 100.50 145.50 97.40 96.40 96.30 39.70 97.00 94.30 96.30 51.90 105.40 90.00 96.80 73.70 102.70 88.00 96.80 70.90 98.10 76.10 96.90 60.80 104.50 82.50 96.80 61.00 87.40 81.40 96.80 54.50 89.90 66.50 96.80 39.10 109.80 97.20 96.80 66.60 111.70 94.10 97.00 58.50 98.60 80.70 97.00 59.80 96.90 70.50 97.00 80.90 95.10 87.80 96.80 37.30 97.00 89.50 96.90 44.60 112.70 99.60 97.20 48.70 102.90 84.20 97.30 54.00 97.40 75.10 97.30 49.50 111.40 92.00 97.20 61.60 87.40 80.80 97.30 35.00 96.80 73.10 97.30 35.70 114.10 99.80 97.30 51.30 110.30 90.00 97.30 49.00 103.90 83.10 97.30 41.50 101.60 72.40 97.30 72.50 94.60 78.80 98.10 42.10 95.90 87.30 96.80 44.10 104.70 91.00 96.80 45.10 102.80 80.10 96.80 50.30 98.10 73.60 96.80 40.90 113.90 86.40 96.80 47.20 80.90 74.50 96.80 36.90 95.70 71.20 96.80 40.90 113.20 92.40 96.80 38.30 105.90 81.50 96.80 46.30 108.80 85.30 96.80 28.40 102.30 69.90 96.80 78.40 99.00 84.20 96.90 36.80 100.70 90.70 97.10 50.70 115.50 100.30 97.10 42.80
Names of X columns:
iptot ipkl pkl invkl
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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