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Data X:
100.70 100.80 99.20 97.90 100.80 98.10 96.50 100.80 96.10 96.60 90.10 95.50 96.60 95.70 95.70 95.50 88.60 95.90 91.80 93.30 96.20 89.30 93.30 95.70 87.00 93.30 93.40 85.90 93.30 93.40 88.00 93.30 91.90 87.90 93.30 92.80 89.20 88.60 93.20 90.90 97.40 93.80 91.60 97.40 93.80 90.20 102.90 85.10 89.10 102.90 86.10 87.50 102.90 86.50 86.30 105.10 90.00 86.00 105.10 89.10 84.40 105.10 88.40 86.10 105.10 91.40 91.00 105.10 88.00 92.70 105.10 87.80 88.00 96.90 87.40 84.30 96.90 86.20 82.20 96.90 87.80 80.80 96.90 84.60 79.40 96.90 85.00 80.20 96.90 85.70 82.20 96.50 83.90 82.20 96.50 83.60 81.20 96.50 82.60 82.10 96.00 84.90 88.10 96.00 84.20 88.50 96.00 83.80 92.10 96.00 84.20 98.60 96.00 84.40 100.90 96.00 86.00 100.60 105.80 89.70 101.10 105.80 93.90 102.10 105.80 98.40 103.60 105.80 98.30 102.80 105.80 99.30 108.30 105.80 100.50 104.00 105.80 96.90 106.10 105.80 97.50 106.30 105.80 97.50 109.00 123.60 98.90 111.00 142.20 99.30 113.70 142.20 100.60 112.70 141.20 99.90 110.30 141.20 98.80 114.50 141.20 98.60 119.30 124.70 98.20 121.80 124.70 96.30 125.40 124.70 103.40 129.70 122.70 102.70 129.40 122.70 102.70 134.50 122.70 102.60 141.20 123.30 101.60 141.40 123.30 100.90 152.20 123.30 101.10 167.70 127.20 105.60 173.30 127.20 104.70 168.70 127.20 103.80 172.60 140.00 105.40 169.80 140.00 105.60 172.00 140.00 109.20 179.40 140.00 109.50 174.60 140.00 110.10 172.50 140.00 110.00 172.60 139.00 110.30 176.30 139.00 109.30 178.90 139.00 110.20 179.60 147.00 113.00 179.90 147.00 113.60 180.30 147.00 111.20 180.90 147.10 111.30 177.70 147.10 115.00
Names of X columns:
TM Buizen Niet-EGKS
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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