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Data X:
0.9383 90.8 15 467.037 0.9217 96.4 3 460.070 0.9095 90 2 447.988 0.892 92.1 -2 442.867 0.8742 97.2 1 436.087 0.8532 95.1 1 431.328 0.8607 88.5 -1 484.015 0.9005 91 -6 509.673 0.9111 90.5 -13 512.927 0.9059 75 -25 502.831 0.8883 66.3 -26 470.984 0.8924 66 -9 471.067 0.8833 68.4 1 476.049 0.87 70.6 3 474.605 0.8758 83.9 6 470.439 0.8858 90.1 2 461.251 0.917 90.6 5 454.724 0.9554 87.1 5 455.626 0.9922 90.8 0 516.847 0.9778 94.1 -5 525.192 0.9808 99.8 -4 522.975 0.9811 96.8 -2 518.585 1.0014 87 -1 509.239 1.0183 96.3 -8 512.238 1.0622 107.1 -16 519.164 1.0773 115.2 -19 517.009 1.0807 106.1 -28 509.933 1.0848 89.5 -11 509.127 1.1582 91.3 -4 500.857 1.1663 97.6 -9 506.971 1.1372 100.7 -12 569.323 1.1139 104.6 -10 579.714 1.1222 94.7 -2 577.992 1.1692 101.8 -13 565.464 1.1702 102.5 0 547.344 1.2286 105.3 0 554.788 1.2613 110.3 4 562.325 1.2646 109.8 7 560.854 1.2262 117.3 5 555.332 1.1985 118.8 2 543.599 1.2007 131.3 -2 536.662 1.2138 125.9 6 542.722 1.2266 133.1 -3 593.530 1.2176 147 1 610.763 1.2218 145.8 0 612.613 1.249 164.4 -7 611.324 1.2991 149.8 -6 594.167 1.3408 137.7 -4 595.454 1.3119 151.7 -4 590.865 1.3014 156.8 -2 589.379 1.3201 180 2 584.428 1.2938 180.4 -5 573.100 1.2694 170.4 -15 567.456 1.2165 191.6 -16 569.028 1.2037 199.5 -18 620.735 1.2292 218.2 -13 628.884 1.2256 217.5 -23 628.232 1.2015 205 -10 612.117 1.1786 194 -10 595.404 1.1856 199.3 -6 597.141 1.2103 219.3 -3 593.408 1.1938 211.1 -4 590.072 1.202 215.2 -7 579.799 1.2271 240.2 -7 574.205 1.277 242.2 -7 572.775 1.265 240.7 -3 572.942 1.2684 255.4 0 619.567 1.2811 253 -5 625.809 1.2727 218.2 -3 619.916 1.2611 203.7 3 587.625 1.2881 205.6 2 565.742 1.3213 215.6 -7 557.274 1.2999 188.5 -1 560.576 1.3074 202.9 0 548.854 1.3242 214 -3 531.673 1.3516 230.3 4 525.919 1.3511 230 2 511.038 1.3419 241 3 498.662 1.3716 259.6 0 555.362 1.3622 247.8 -10 564.591 1.3896 270.3 -10 541.657
Names of X columns:
Dollar Aardolie Consumentenvertrouwen Werkloosheid
Type of Correlation
Default
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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