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Data X:
13807.9 2236 14101.7 2084.9 16010.3 2409.5 14633.1 2199.3 14478.5 2203.5 15327.3 2254.1 14179.5 1975.8 11398.2 1742.2 16111.5 2520.6 15887.4 2438.1 14529.3 2126.3 13923.1 2267.5 13960.2 2201.1 14807.8 2128.5 17511.5 2596 15845.9 2458.2 14594.2 2210.5 17252.2 2621.2 14832.8 2231.4 13132.1 2103.6 17665.9 2685.8 16913 2539.3 17318.8 2462.4 16224.2 2693.3 15469.6 2307.7 16557.5 2385.9 19414.8 2737.6 17335 2653.9 16525.2 2545.4 18160.4 2848.8 15553.8 2359.5 15262.2 2488.3 18581 2861.1 17564.1 2717.9 18948.6 2844 17187.8 2749 17564.8 2652.9 17668.4 2660.2 20811.7 3187.1 17257.8 2774.1 18984.2 3158.2 20532.6 3244.6 17082.3 2665.5 16894.9 2820.8 20274.9 2983.4 20078.6 3077.4 19900.9 3024.8 17012.2 2731.8 19642.9 3046.2 19024 2834.8 21691 3292.8 18835.9 2946.1 19873.4 3196.9 21468.2 3284.2 19406.8 3003 18385.3 2979 20739.3 3137.4 22268.3 3630.2 21569 3270.7 17514.8 2942.3
Names of X columns:
Total_export_EU Total_export_Netherlands
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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1 seconds
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Big Analytics Cloud Computing Center
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