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Data X:
91.46 73.74 94.69 90.70 90.24 72.73 92.27 89.53 93.90 77.78 99.52 90.70 96.34 82.83 103.86 90.70 93.90 84.85 102.42 89.53 86.59 83.84 95.65 87.21 75.61 78.79 83.57 82.56 70.73 75.76 80.19 80.23 74.39 79.80 94.20 82.56 84.15 83.84 107.25 84.88 89.02 87.88 114.49 87.21 87.80 82.83 106.76 84.88 74.39 69.70 73.91 80.23 70.73 65.66 64.73 76.74 74.39 68.69 69.08 77.91 78.05 71.72 73.91 77.91 82.93 76.77 81.16 80.23 82.93 79.80 84.06 82.56 79.27 80.81 82.61 83.72 75.61 79.80 82.13 82.56 76.83 79.80 87.44 81.40 78.05 77.78 92.27 79.07 80.49 81.82 99.03 81.40 81.71 84.85 101.93 84.88 78.05 83.84 88.89 88.37 82.93 88.89 92.75 93.02 85.37 92.93 96.14 94.19 84.15 91.92 89.86 91.86 86.59 91.92 88.89 90.70 87.80 91.92 89.86 90.70 86.59 90.91 90.82 91.86 85.37 90.91 96.14 93.02 84.15 93.94 103.38 93.02 81.71 98.99 111.11 93.02 80.49 101.01 112.56 93.02 84.15 98.99 109.18 94.19 89.02 90.91 90.82 97.67 96.34 90.91 90.82 100.00 100.00 90.91 92.75 98.84 100.00 92.93 93.72 98.84 100.00 94.95 97.58 98.84 98.78 94.95 99.03 98.84 96.34 93.94 103.86 98.84 93.90 92.93 105.80 98.84 93.90 96.97 110.63 98.84 92.68 103.03 113.53 98.84 91.46 104.04 113.53 97.67 91.46 102.02 111.59 98.84 86.59 90.91 94.20 98.84 91.46 89.90 95.65 100.00 91.46 91.92 98.55 97.67 95.12 95.96 98.07 98.84 95.12 96.97 98.55 97.67 95.12 95.96 100.00 96.51 92.68 92.93 102.90 96.51 91.46 92.93 106.28 96.51 93.90 101.01 114.49 100.00 98.78 110.10 123.67 103.49 97.56 112.12 123.19 103.49 92.68 105.05 114.98 100.00 80.49 85.86 86.96 93.02 79.27 80.81 82.13 90.70 82.93 83.84 84.06 90.70 91.46 93.94 88.89 96.51 97.56 98.99 95.17 98.84 100.00 100.00 100.00 100.00 98.78 93.94 104.83 98.84 96.34 90.91 107.73 97.67 96.34 91.92 114.98 96.51 92.68 94.95 119.81 95.35 91.46 94.95 120.29 94.19 92.68 91.92 114.98 94.19 89.02 79.80 90.34 94.19 91.46 79.80 89.86 94.19 92.68 82.83 94.69 94.19 91.46 87.88 100.00 95.35 92.68 91.92 102.42 95.35 95.12 90.91 100.00 94.19 96.34 86.87 91.79 91.86 95.12 84.85 86.96 90.70 91.46 87.88 87.92 88.37 80.49 92.93 90.82 88.37 76.83 94.95 92.27 88.37 76.83 92.93 89.86 88.37 73.17 78.79 71.98 86.05 76.83 77.78 74.88 84.88 78.05 79.80 79.71 84.88 76.83 86.87 82.61 86.05 76.83 90.91 85.99 86.05 78.05 91.92 89.86 86.05 81.71 88.89 93.72 86.05 81.71 84.85 94.20 84.88 82.93 84.85 97.10 82.56 75.61 77.78 90.34 76.74 70.73 73.74 86.47 72.09 68.29 70.71 80.68 72.09 65.85 67.68 71.01 75.58 69.51 70.71 75.36 76.74 70.73 71.72 76.33 75.58 67.07 69.70 69.57 72.09 65.85 71.72 67.15 70.93 65.85 75.76 67.63 72.09 65.85 81.82 70.05 74.42 67.07 85.86 75.85 77.91 68.29 89.90 86.47 79.07 69.51 90.91 98.55 79.07 70.73 92.93 104.35 81.40 65.85 87.88 91.30 79.07 59.76 80.81 70.05 80.23 63.41 81.82 69.08 80.23 67.07 83.84 71.50 81.40 71.95 81.82 72.95 80.23 76.83 84.85 75.85 81.40 79.27 89.90 76.81 83.72 78.05 94.95 77.78 87.21 78.05 97.98 82.13 89.53 80.49 102.02 91.79 91.86 82.93 105.05 103.86 94.19 87.80 108.08 110.63 97.67
Names of X columns:
wlhm wlhv wlhj ntwerkz
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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R Server
Big Analytics Cloud Computing Center
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