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Data X:
-0.055 -22.4 -14 9012 -0.0517 -25.8 0 14535 -0.0337 -6.1 4 22451 -0.0062 -2 4 18384 0.0428 -6.6 4 18637 0.1022 -8 4 24298 0.1315 2.3 1 32832 0.0773 3.1 1 15519 0.0697 9.3 9 10048 0.0752 21.8 23 15754 0.1131 20.7 25 38255 0.1259 30.3 1 41171 0.1789 38.7 -17 43115 0.2073 44.6 -22 42404 0.2049 22.2 -34 39494 0.199 -0.6 -13 47876 0.2412 0.7 -9 46133 0.2109 10.5 -14 51345 0.145 9.9 -12 52476 0.1361 10.5 -5 54522 0.1414 -5.1 2 55017 0.1881 5 -11 46879 0.1688 15.5 1 38105 0.2103 9 8 42550 0.1991 3.2 20 43161 0.1873 -5.4 26 43845 0.1455 11.2 33 45399 0.1137 29.3 13 34472 0.0425 40 2 35805 0.0475 28.3 15 35751 0.0894 32.4 9 24207 0.1037 42.4 11 31049 0.0996 51.1 2 34621 0.0798 62.6 6 45860 0.1289 47.3 -6 46823 0.1122 32.4 -4 40666 0.0506 41.4 -8 28540 0.0368 47 -9 28525 0.0939 62.7 -3 29096 0.0953 61.6 -7 29501 0.0687 39.1 -13 30794 0.0027 65.7 -22 26306 -0.0229 66.4 -15 27205 0.0116 71.2 -14 18121 0.0038 71.7 -23 15619 -0.0475 40.6 -3 793 -0.1205 44.2 -4 1237 -0.1552 61.6 -2 1687 -0.1016 67.6 1 2543 -0.1076 54.3 -2 693 -0.1181 35.2 -9 -4629 -0.0667 59.8 -2 1105 0.0076 71.8 8 5319 0.0485 49.1 13 3914 0.0647 55.9 18 -1168 0.0519 34.8 8 -3075 0.0471 0.7 20 -8316 0.0596 -1.3 13 -24492 0.1095 11.6 12 -29662 0.1357 16.3 -1 -39867 0.0896 -30.8 2 -32832 0.1136 -8.2 4 -41218 0.1222 -1.2 4 -48126 0.1245 -9.9 11 -48286 0.0741 -12.2 9 -61737 0.0769 0.3 6 -74280 0.1032 4.2 0 -64205 0.0811 -5.2 -5 -61218 0.1169 52.1 -7 -78259
Names of X columns:
Dollar Olie Vertrouwen Werk
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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