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Data X:
-10 0.2 111.3 1181.7 3 -0.1 19.4 -1872.7 7 0.4 -30.8 -1410.7 -2 0.1 -18.6 1109.3 -7 -0.2 5.5 -43.8 -1 -0.6 -109.6 1273 -8 0.6 62.3 -627.5 6 -0.1 28.1 -413.7 62 0.2 31.7 512.8 11 0.1 -24.6 -367.9 -2 -0.3 8.9 -3398.1 -13 0.4 -71.7 4579.9 -18 -0.1 187.1 442.9 8 -0.3 124.4 -1757.6 7 -0.2 -177.1 -107.9 -1 -0.2 209.6 -277.7 -6 0.7 -186.5 722.5 -11 0.7 -56.9 2598.1 -7 -0.4 113 -1524.5 6 0.1 -7.1 -959.1 51 -0.1 140.5 2450.2 17 -0.2 96.4 -1957.7 2 0.9 -192.2 -2046.3 -2 -0.4 37.6 3956.7 -17 -0.4 -136.1 48.8 1 0.1 213.4 -451.6 -4 0.3 -211.1 -716 -2 0.5 148.7 -713.2 -5 -0.4 -38.3 592.4 -11 -0.1 -135 2539.9 -6 0.4 -26 -1284.8 2 0 -136.5 -629.3 52 0.2 205.2 1377.1 8 0.1 -6.1 -2328.4 -1 -0.8 -145.5 -1116.5 -16 0.1 135.2 4060.5 -17 0.5 -10.3 -1455.6 2 0 -17.9 1343.6 -4 0 56.9 -1049.8 -3 -0.6 13.3 -524.8 -10 0.4 -8.3 236.3 -6 0.2 1.2 3320.6 -1 -0.3 -52 -3902.4 0 -0.1 7.3 2269.5 47 -0.1 94.9 355.9 6 -0.4 -41 -2220.5 -6 -0.2 -146.7 -1409.5 -32 0.3 75.8 3299.2 -22 0.1 -29.2 467.5 -9 -0.4 34.4 29.1 4 0.1 5.1 -2617.8 -12 0 -16.8 1580.8 -17 0 13.6 -350.1 -6 -0.5 -92.9 2776.5 -15 0 -16.3 -2510.5 -12 0 31 1464.7 56 -0.1 13.5 827.6 10 0.2 18.9 -1378.5 -23 0.8 -114.9 -1744
Names of X columns:
Werkloosheid Inflatie Import Uitvoer
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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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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