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Data X:
89.1 19 96.96 98.13 83.3 22 93.11 98.29 97.7 19 95.62 99.1 100.9 13 98.30 99.26 108.3 12 96.38 98.85 113.2 8 100.82 98.05 105 16 99.06 98.53 104 19 94.03 99.34 109.8 19 102.07 100.14 98.6 24 99.31 100.3 93.5 20 98.64 100.22 98.2 14 101.82 99.9 88 18 99.14 99.58 85.3 14 97.63 99.9 96.8 13 100.06 100.78 98.8 15 101.32 100.78 110.3 19 101.49 100.46 111.6 22 105.43 100.06 111.2 28 105.09 100.28 106.9 28 99.48 100.78 117.6 32 108.53 101.58 97 34 104.34 102.06 97.3 38 106.10 102.02 98.4 44 107.35 101.68 87.6 43 103.00 101.32 87.4 45 104.50 101.81 94.7 48 105.17 102.3 101.5 45 104.84 102.12 110.4 43 106.18 102.1 108.4 46 108.86 101.75 109.7 55 107.77 101.5 105.2 52 102.74 102.16 111.1 51 112.63 103.47 96.2 52 106.26 104.05 97.3 54 108.86 104.09 98.9 58 111.38 103.55 91.7 55 106.85 102.77 90.9 56 107.86 102.89 98.8 39 107.94 103.6 111.5 35 111.38 103.76 119 34 111.29 103.92 115.3 35 113.72 103.35 116.3 38 111.88 103.32 113.6 31 109.87 104.2 115.1 31 113.72 105.44 109.7 28 111.71 105.81 97.6 24 114.81 106.25 100.8 21 112.05 105.94 94 10 111.54 105.82 87.2 14 110.87 105.96 102.9 18 110.87 106.49 111.3 9 115.48 106.32 106.6 7 111.63 105.88 108.9 9 116.24 105.07 108.3 13 113.56 105.12 100.5 11 106.01 106.15 104 7 110.45 107.38 89.9 13 107.77 107.75 86.8 18 108.61 107.87 91.2 17 108.19 107.39
Names of X columns:
Ind Consve Best HICP
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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