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Data X:
88.74 88.95 88.92 88.81 88.77 88.90 89.17 90.15 89.61 90.92 89.52 90.78 89.74 90.81 89.40 89.46 89.36 89.22 89.38 88.89 89.36 89.41 89.29 89.59 89.59 90.25 89.79 90.20 89.86 90.27 90.21 90.71 90.37 91.18 90.19 90.66 90.33 89.72 90.22 88.72 90.42 88.91 90.54 89.15 90.73 89.15 91.02 89.08 91.19 89.28 91.53 89.47 91.88 89.53 92.06 90.72 92.32 90.91 92.67 91.38 92.85 91.49 92.82 90.90 93.46 90.93 93.23 90.57 93.54 91.28 93.29 90.83 93.20 91.50 93.60 91.58 93.81 92.49 94.62 94.16 95.22 95.46 95.38 95.80 95.31 95.32 95.30 95.41 95.57 95.35 95.42 95.68 95.53 95.59 95.33 94.96 95.90 96.92 96.06 96.06 96.31 96.59 96.34 96.67 96.49 97.27 96.22 96.38 96.53 96.47 96.50 96.05 96.77 96.76 96.66 96.51 96.58 96.55 96.63 95.97 97.06 97.00 97.73 97.46 98.01 97.90 97.76 98.42 97.49 98.54 97.77 99.00 97.96 98.94 98.23 99.02 98.51 100.07 98.19 98.72 98.37 98.73 98.31 98.04 98.60 99.08 98.97 99.22 99.11 99.57 99.64 100.44 100.03 100.84 99.98 100.75 100.32 100.49 100.44 99.98 100.51 99.96 101.00 99.76 100.88 100.11 100.55 99.79 100.83 100.29 101.51 101.12 102.16 102.65 102.39 102.71 102.54 103.39 102.85 102.80 103.47 102.07 103.57 102.15 103.69 101.21 103.50 101.27 103.47 101.86 103.45 101.65 103.48 101.94 103.93 102.62 103.89 102.71 104.40 103.39 104.79 104.51 104.77 104.09 105.13 104.29 105.26 104.57 104.96 105.39 104.75 105.15 105.01 106.13 105.15 105.46 105.20 106.47 105.77 106.62 105.78 106.52 106.26 108.04 106.13 107.15 106.12 107.32 106.57 107.76 106.44 107.26 106.54 107.89
Names of X columns:
Alg.Index 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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Big Analytics Cloud Computing Center
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