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Data X:
0.8833 18.33 9041.46 0.87 22.6 9476.91 0.8758 24.9 9420.10 0.8858 24.8 9690.65 0.917 23.8 10084.25 0.9554 25.1 10344.12 0.9922 26 10086.71 0.9778 27.4 9959.87 0.9808 27.3 10256.23 0.9811 24.3 10172.04 1.0014 28.4 10258.34 1.0183 24.4 10703.35 1.0622 30.3 11484.51 1.0773 31.5 11568.05 1.0807 29.8 10991.80 1.0848 25.3 10545.34 1.1582 25.6 11462.71 1.1663 26.7 11462.40 1.1372 27.4 11285.57 1.1139 28.6 11552.26 1.1222 26.3 12171.38 1.1692 28.5 12174.88 1.1702 28.4 12531.67 1.2286 29.4 13099.33 1.2613 30.3 13331.94 1.2646 29.6 13021.59 1.2262 32.1 13040.64 1.1985 32.4 13030.09 1.2007 36.3 12362.41 1.2138 34.6 12602.89 1.2266 36.3 12794.66 1.2176 40.3 12874.90 1.2218 40.4 13015.84 1.249 45.4 13495.45 1.2991 39 14123.82 1.3408 35.7 14246.00 1.3119 40.2 13652.94 1.3014 41.7 13616.55 1.3201 49.1 13934.98 1.2938 49.6 13773.79 1.2694 47 13585.12 1.2165 52 13810.92 1.2037 53.1 13657.18 1.2292 57.8 14075.57 1.2256 57.9 14663.08 1.2015 54.6 15107.66 1.1786 51.3 15358.34 1.1856 52.7 16375.51 1.2103 58.5 17602.60 1.1938 56.6 17824.63 1.202 57.9 17892.97 1.2271 64.4 19639.74 1.277 65.1 21790.73 1.265 64.6 19187.52 1.2684 68.9 20357.82 1.2811 68.8 20291.34 1.2727 59.3 19264.86 1.2611 55 18858.49 1.2881 55.4 20156.19 1.3213 58 20222.50 1.2999 50.8 20251.14 1.3074 54.6 21373.38 1.3242 58.6 21091.86 1.3516 63.6 21856.72 1.3511 64.5 21532.48 1.3419 66.9 21085.27 1.3716 71.9 21388.73 1.3622 68.7 21363.38 1.3896 74.2 22842.24 1.4227 75.8 24231.43
Names of X columns:
dollarkoers olieprijs goudprijs
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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