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Data X:
0.0137 -10.94 0.0069 -1.8 -0.0002 2.11 0.0232 -7.09 -0.0642 10.23 0.017 -1.83 0.0754 -1.65 0.0426 -6.9 0.0117 4.21 -0.0188 -3.02 -0.0368 -4.39 -0.0501 3.52 0.0033 -0.27 0.018 -0.78 0.0275 13.19 0.049 -5.37 0.0594 -3.4 0.0293 7.5 -0.0542 -7.85 -0.0076 9.23 0.0055 -0.46 0.0379 -4.38 0.0128 3.67 0.053 -3.23 0.0284 1.69 -0.0024 -2.31 -0.0059 0.57 0.0422 -2.53 -0.0303 6.44 -0.0659 -3.89 -0.0089 -3.78 0.0053 6.38 0.0467 -2.88 -0.0193 -1.37 0.0415 9.87 -0.0112 -8.32 -0.0118 3.71 -0.0418 8.2 -0.0318 -8.03 -0.0712 -7.38 0.005 13.74 0.0419 -11.01 0.0143 9.54 -0.0041 -5.44 -0.0198 -5.45 0.0491 11.75 -0.0167 -4.16 -0.0616 -5.11 -0.0138 -2.03 0.0571 -2.19 0.0014 3.73 -0.0266 3.65 -0.066 -8.23 -0.0256 -2.07 0.0345 6.56 -0.0078 -1.06 -0.0513 -9.14 -0.073 10.64 -0.0347 -1.47
Names of X columns:
wisselkoers 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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Big Analytics Cloud Computing Center
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