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Data X:
2648.9 99.5 2669.6 93.5 3042.3 104.6 2604.2 95.3 2732.1 102.8 2621.7 103.3 2483.7 100.2 2479.3 107.9 2684.6 107.5 2834.7 119.8 2566.1 112 2251.2 102.1 2350 105.3 2299.8 101.3 2542.8 108.4 2530.2 107.4 2508.1 109.1 2616.8 109.5 2534.1 111.4 2181.8 110.1 2578.9 117 2841.9 129.6 2529.9 113.5 2103.2 113.3 2326.2 110.1 2452.6 107.4 2782.1 110.1 2727.3 112.5 2648.2 106 2760.7 117.6 2613 117.8 2225.4 113.5 2713.9 121.2 2923.3 130.4 2707 115.2 2473.9 117.9 2521 110.7 2531.8 107.6 3068.8 124.3 2826.9 115.1 2674.2 112.5 2966.6 127.9 2798.8 117.4 2629.6 119.3 3124.6 130.4 3115.7 126 3083 125.4 2863.9 130.5 2728.7 115.9 2789.4 108.7 3225.7 124 3148.2 119.4 2836.5 118.6 3153.5 131.3 2656.9 111.1 2834.7 124.8 3172.5 132.3 2998.8 126.7 3103.1 131.7 2735.6 130.9 2818.1 122.1 2874.4 113.2 3438.5 133.6 2949.1 119.2 3306.8 129.4 3530 131.4 3003.8 117.1 3206.4 130.5 3514.6 132.3 3522.6 140.8 3525.5 137.5 2996.2 128.6 3231.1 126.7 3030 120.8 3541.7 139.3 3113.2 128.6 3390.8 131.3 3424.2 136.3 3079.8 128.8 3123.4 133.2 3317.1 136.3 3579.9 151.1 3317.9 145 2668.1 134.4
Names of X columns:
Uitvoer Voeding
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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Computing time
1 seconds
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Big Analytics Cloud Computing Center
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