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Data X:
1.21 512238 99.29 1946.81 1.74 519164 98.69 1765.9 1.76 517009 107.92 1635.25 1.48 509933 101.03 1833.42 1.04 509127 97.55 1910.43 1.62 500857 103.02 1959.67 1.49 506971 94.08 1969.6 1.79 569323 94.12 2061.41 1.8 579714 115.08 2093.48 1.58 577992 116.48 2120.88 1.86 565464 103.42 2174.56 1.74 547344 112.51 2196.72 1.59 554788 95.55 2350.44 1.26 562325 97.53 2440.25 1.13 560854 119.26 2408.64 1.92 555332 100.94 2472.81 2.61 543599 97.73 2407.6 2.26 536662 115.25 2454.62 2.41 542722 92.8 2448.05 2.26 593530 99.2 2497.84 2.03 610763 118.69 2645.64 2.86 612613 110.12 2756.76 2.55 611324 110.26 2849.27 2.27 594167 112.9 2921.44 2.26 590865 102.17 3080.58 2.57 589379 99.38 3106.22 3.07 584428 116.1 3119.31 2.76 573100 103.77 3061.26 2.51 567456 101.81 3097.31 2.87 569028 113.74 3161.69 3.14 620735 89.67 3257.16 3.11 628884 99.5 3277.01 3.16 628232 122.89 3295.32 2.47 612117 108.61 3363.99 2.57 595404 114.37 3494.17 2.89 597141 110.5 3667.03 2.63 593408 104.08 3813.06 2.38 590072 103.64 3917.96 1.69 579799 121.61 3895.51 1.96 574205 101.14 3733.22 2.19 572775 115.97 3801.06 1.87 572942 120.12 3570.12 1.6 619567 95.97 3701.61 1.63 625809 105.01 3862.27 1.22 619916 124.68 3970.1 1.21 587625 123.89 4138.52 1.49 565742 123.61 4199.75 1.64 557274 114.76 4290.89 1.66 560576 108.75 4443.91 1.77 548854 106.09 4502.64 1.82 531673 123.17 4356.98 1.78 525919 106.16 4591.27 1.28 511038 115.18 4696.96 1.29 498662 120.6 4621.4 1.37 555362 109.48 4562.84 1.12 564591 114.44 4202.52 1.51 541657 121.44 4296.49 2.24 527070 129.48 4435.23 2.94 509846 124.32 4105.18 3.09 514258 112.59 4116.68
Names of X columns:
X1 X2 X3 X4
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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Raw Output
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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