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Data X:
86.5 98.5 109.2 104.1 99.3 126.3 110.9 98 104 114.5 98.1 96 112.2 98 262 96.4 96.5 89.8 92 96.1 86 102 96.3 92.7 99.7 96.1 126.8 102 95.4 92.8 98.9 95.3 87.8 87.4 93.9 100 94.4 94 72.4 109.3 93.6 104.9 116.4 93.5 52.3 101 93.5 65.3 105.5 93.5 110.2 97.8 93 54.4 95.5 93.1 47.5 113.7 93.3 65.2 103.7 93.2 69.8 100.8 93.1 53.6 113.8 93.1 116.1 84.6 93.2 56.6 95.3 93 47.2 110 93.1 90.6 107.5 93.2 60.4 107.6 93.1 59.3 116 93.1 131.6 96.9 93.1 59.4 97 92.3 65.5 108.1 92.3 70.5 101.9 92.3 81 107.2 92.3 73.3 110.2 92.1 107.5 78.7 92.1 88.9 96.5 92.1 55.8 115.2 92 80.5 104.7 92 86.3 109.1 92.3 112.6 108.4 93.3 148.6 95.5 92.4 47.1 97.8 92.6 57.8 115.1 92.7 81 96.2 92.4 60.1 112 92.2 76.1 111.8 92.7 82.5 82.5 92.7 66.8 100.8 92.8 58.7 116 92.8 54.2 116.3 92.8 103.3 116.6 92.7 77.8 112.9 92.8 118.4 100.9 93.6 64.9 104.1 93.4 40.8 117.4 93.8 77.7 103.3 93.8 66.8 111.6 93.9 69.2 115 94 82.4 92.6 93.9 62.7 105.2 93.9 58.2
Names of X columns:
Indpr Afzpr Inv
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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