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Data X:
1.00 2.05 2756.76 2.00 1.00 2.11 2849.27 2.00 1.00 2.09 2921.44 4.00 1.00 2.05 2981.85 -4.00 1.00 2.08 3080.58 -1.00 1.00 2.06 3106.22 0.00 1.00 2.06 3119.31 10.00 1.00 2.08 3061.26 2.00 1.00 2.07 3097.31 -11.00 1.00 2.06 3161.69 0.00 1.00 2.07 3257.16 8.00 1.00 2.06 3277.01 8.00 1.00 2.09 3295.32 12.00 1.00 2.07 3363.99 2.00 1.00 2.09 3494.17 -10.00 1.25 2.28 3667.03 6.00 1.25 2.33 3813.06 6.00 1.25 2.35 3917.96 -5.00 1.50 2.52 3895.51 11.00 1.50 2.63 3801.06 8.00 1.50 2.58 3570.12 11.00 1.75 2.70 3701.61 0.00 1.75 2.81 3862.27 17.00 2.00 2.97 3970.10 23.00 2.00 3.04 4138.52 16.00 2.25 3.28 4199.75 11.00 2.25 3.33 4290.89 -4.00 2.50 3.50 4443.91 2.00 2.50 3.56 4502.64 7.00 2.50 3.57 4356.98 12.00 2.75 3.69 4591.27 9.00 2.75 3.82 4696.96 5.00 2.75 3.79 4621.40 4.00 3.00 3.96 4562.84 12.00 3.00 4.06 4202.52 11.00 3.00 4.05 4296.49 6.00 3.00 4.03 4435.23 6.00 3.00 3.94 4105.18 1.00 3.00 4.02 4116.68 -2.00 3.00 3.88 3844.49 6.00 3.00 4.02 3720.98 11.00 3.00 4.03 3674.40 -4.00 3.00 4.09 3857.62 -7.00 3.00 3.99 3801.06 -11.00 3.00 4.01 3504.37 -6.00 3.00 4.01 3032.60 -13.00 3.25 4.19 3047.03 -10.00 3.25 4.30 2962.34 -16.00 3.25 4.27 2197.82 -18.00 3.25 3.82 2014.45 -30.00 2.75 3.15 1862.83 -46.00 2.00 2.49 1905.41 -53.00 1.00 1.81 1810.99 -49.00 1.00 1.26 1670.07 -56.00 0.50 1.06 1864.44 -53.00 0.25 0.84 2052.02 -60.00 0.25 0.78 2029.60 -53.00 0.25 0.70 2070.83 -50.00 0.25 0.36 2293.41 -44.00 0.25 0.35 2443.27 -35.00
Names of X columns:
CBI market-I bel20 conjuctuur
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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