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Data X:
3926 106.70 3517 110.20 4142 125.90 4353 100.10 5029 106.40 4755 114.80 3862 81.30 4406 87.00 4567 104.20 4863 108.00 4121 105.00 3626 94.50 3804 92.00 3491 95.90 4151 108.80 4254 103.40 4717 102.10 4866 110.10 4001 83.20 3758 82.70 4780 106.80 5016 113.70 4296 102.50 4467 96.60 3891 92.10 3872 95.60 3867 102.30 3973 98.60 4640 98.20 4538 104.50 3836 84.00 3770 73.80 4374 103.90 4497 106.00 3945 97.20 3862 102.60 3608 89.00 3301 93.80 3882 116.70 3605 106.80 4305 98.50 4216 118.70 3971 90.00 3988 91.90 4317 113.30 4484 113.10 4247 104.10 3520 108.70 3687 96.70 3405 101.00 3990 116.90 4047 105.80 4549 99.00 4559 129.40 3926 83.00 4206 88.90 4517 115.90 4387 104.20 3219 113.40 3129 112.20
Names of X columns:
Verkeersongevallen Ind.Nijverheid
Type of Correlation
pearson
spearman
kendall
Chart options
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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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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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