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Data X:
95.1 93.8 124 121.8 97 93.8 128.8 127.6 112.7 107.6 133.5 129.9 102.9 101 132.6 128 97.4 95.4 128.4 123.5 111.4 96.5 127.3 124 87.4 89.2 126.7 127.4 96.8 87.1 123.3 127.6 114.1 110.5 123.2 128.4 110.3 110.8 124.4 131.4 103.9 104.2 128.2 135.1 101.6 88.9 128.7 134 94.6 89.8 135.7 144.5 95.9 90 139 147.3 104.7 93.9 145.4 150.9 102.8 91.3 142.4 148.7 98.1 87.8 137.7 141.4 113.9 99.7 137 138.9 80.9 73.5 137.1 139.8 95.7 79.2 139.3 145.6 113.2 96.9 139.6 147.9 105.9 95.2 140.4 148.5 108.8 95.6 142.3 151.1 102.3 89.7 148.3 157.5 99 92.8 157.7 167.5 100.7 88 161.6 172.3 115.5 101.1 161.7 173.5 100.7 92.7 171.8 187.5 109.9 95.8 185.1 205.5 114.6 103.8 176.7 195.1 85.4 81.8 184.4 204.5 100.5 87.1 183 204.5 114.8 105.9 180.9 201.7 116.5 108.1 187 207 112.9 102.6 189.9 206.6 102 93.7 193.8 210.6 106 103.5 194.5 211.1 105.3 100.6 198.7 215 118.8 113.3 204.7 223.9 106.1 102.4 213.2 238.2 109.3 102.1 214.7 238.9 117.2 106.9 211 229.6 92.5 87.3 213.2 232.2 104.2 93.1 206.2 222.1 112.5 109.1 210.8 221.6 122.4 120.3 216.2 227.3 113.3 104.9 213.3 221 100 92.6 213.1 213.6 110.7 109.8 238.5 243.4 112.8 111.4 253 253.8 109.8 117.9 262.7 265.3 117.3 121.6 263.2 268.2 109.1 117.8 263.2 268.5 115.9 124.2 267.9 266.9 96 106.8 268 268.4 99.8 102.7 248.4 250.8 116.8 116.8 230.8 231.2 115.7 113.6 190.6 192 99.4 96.1 173.5 171.4 94.3 85 164.7 160
Names of X columns:
TIA IAidM APiGEE PiIG
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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