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Data X:
100 100 100 100 87.14054095 99.31916948 84.48959366 85.95702149 112.0054296 114.7106298 96.92765114 68.015992 112.312101 114.9941367 98.26560951 91.25437281 109.474134 114.6085397 107.5569871 104.2978511 104.9746116 116.3633855 103.64222 71.11444278 100.4926851 108.0492516 93.45887017 94.35282359 104.2154743 112.8502449 105.2527255 71.91404298 120.1768388 127.2518452 126.1397423 74.8125937 112.1028355 116.4999655 112.4132805 98.4007996 108.1481575 113.8511416 107.9286422 115.6921539 116.802197 126.3771815 100.7928642 109.5452274 102.1699512 103.8290681 106.1199207 110.2948526 95.15358705 108.296889 103.666997 122.0389805 120.6707808 125.0969166 142.888999 91.2043978 111.5234277 115.6701386 120.6144698 114.8425787 119.9669448 130.2545354 104.8067393 118.9905047 113.3697401 131.2064565 121.7294351 103.1984008 110.0717661 124.8665241 121.1100099 124.5877061 111.5567342 122.6191626 129.4846383 90.85457271 132.424212 148.2368766 103.691774 108.9455272 107.900558 117.7160792 116.7740337 123.1384308 122.1626615 128.9232255 105.2031715 107.0964518 124.3992258 130.7380837 122.8444004 121.0894553 110.4450505 113.1192661 121.283449 110.2948526 101.5874013 116.5454922 114.147671 102.1989005 122.3203962 127.9782024 127.4281467 90.30484758 125.2582826 132.9240533 124.6778989 116.4417791 125.4411543 133.9732358 139.147671 118.1909045 108.9902468 121.2623301 154.5094153 119.6401799 118.9243879 128.559702 124.6531219 104.2978511 116.7242723 124.692695 167.1456888 104.4477761 134.1724901 140.9850314 121.6551041 123.5382309 116.8530994 124.6823481 130.4013875 142.0789605 124.5732995 134.9451611 124.2814668 122.8385807 130.9914031 137.2642616 131.0951437 124.4877561 123.4239103 132.6308891 134.2666006 125.6371814 111.4536725 122.7122853 166.3032706 125.5372314 124.5135991 132.5846727 166.8483647 103.5482259 139.2589613 151.5410085 151.2140733 114.0929535 129.8596099 145.764641 154.8562934 127.0864568 112.3460359 134.4043595 139.444995 108.8955522 131.381655 152.9192247 140.8572844 122.1389305 133.0004776 143.9387459 171.308226 116.5417291 134.3220552 152.9709595 133.3994054 106.2468766 144.2379719 162.3356557 131.8384539 119.6901549 134.1278719 148.1658274 147.4231913 167.6661669 150.1891559 167.9499207 158.8453915 124.3378311 140.722563 156.9400566 159.0436075 132.2338831 114.8389975 140.2241843 163.2309217 137.6311844 143.1973003 163.13996 187.9335976 90.30484758 140.2738676 160.969166 195.4410307 127.986007 112.1248303 135.3031662 234.4152626 123.6381809 102.8951536 124.4554046 161.1992071 113.8430785 100.5090242 119.2143202 162.7106046 123.988006 103.3513901 116.21163 192.2943508 76.8115942 111.4134533 125.2638477 151.6352825 112.6936532 104.5887587 114.0987791 134.8116947 137.1314343 101.7840983 110.0413879 112.9088206 200.049975 114.7007441 126.6317169 105.0297324 150.8245877 108.7426474 113.0875354 122.0267592 172.5137431
Names of X columns:
Totuit Totin Invchin Uitvchin
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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