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Data X:
14.3 15.89 113 14.2 16.93 110 15.9 20.28 107 15.3 22.52 103 15.5 23.51 98 15.1 22.59 98 15 23.51 137 12.1 24.76 148 15.8 26.08 147 16.9 25.29 139 15.1 23.38 130 13.7 25.29 128 14.8 28.42 127 14.7 31.85 123 16 30.1 118 15.4 25.45 114 15 24.95 108 15.5 26.84 111 15.1 27.52 151 11.7 27.94 159 16.3 25.23 158 16.7 26.53 148 15 27.21 138 14.9 28.53 137 14.6 30.35 136 15.3 31.21 133 17.9 32.86 126 16.4 33.2 120 15.4 35.73 114 17.9 34.53 116 15.9 36.54 153 13.9 40.1 162 17.8 40.56 161 17.9 46.14 149 17.4 42.85 139 16.7 38.22 135 16 40.18 130 16.6 42.19 127 19.1 47.56 122 17.8 47.26 117 17.2 44.03 112 18.6 49.83 113 16.3 53.35 149 15.1 58.9 157 19.2 59.64 157 17.7 56.99 147 19.1 53.2 137 18 53.24 132 17.5 57.85 125 17.8 55.69 123 21.1 55.64 117 17.2 62.52 114 19.4 64.4 111 19.8 64.65 112 17.6 67.71 144 16.2 67.21 150 19.5 59.37 149 19.9 53.26 134 20 52.42 123 17.3 55.03 116
Names of X columns:
BuitlH POil WK<25j
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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