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Data X:
114.08 136.49 129.57 129.41 112.95 142.62 130.02 136.76 135.31 141.71 132.91 136.76 134.31 149.51 138.25 127.94 133.03 147.39 142.68 120.59 140.11 131.96 139.61 122.06 124.69 136.38 138.49 125.00 131.68 127.34 140.48 126.47 150.95 133.85 137.68 125.00 137.26 125.14 135.09 120.59 130.51 141.25 129.46 119.12 143.15 149.32 128.09 116.18 118.01 120.92 128.09 126.47 122.56 134.85 130.81 127.94 147.97 131.93 130.42 127.94 135.74 134.22 127.86 125.00 151.62 143.07 125.42 123.53 154.82 145.37 126.17 125.00 145.59 134.32 128.80 127.94 147.12 126.31 127.04 127.94 175.86 162.21 127.91 126.47 140.66 124.09 130.58 125.00 152.69 153.91 135.89 122.06 154.38 154.34 134.62 117.65 132.45 138.70 134.98 120.59 136.44 150.98 136.33 119.12 153.24 146.39 135.44 119.12 154.11 178.30 134.20 117.65 155.93 168.23 137.08 116.18 142.53 162.52 140.61 116.18 148.73 158.86 138.33 117.65 147.73 152.17 139.13 117.65 166.79 171.01 140.92 116.18 144.30 171.49 143.83 117.65 156.07 189.62 143.78 113.24 161.70 177.46 142.80 105.88 152.10 179.98 145.96 110.29 140.45 156.96 144.96 107.35 155.56 167.89 147.88 102.94 174.53 194.78 151.40 102.94 167.16 192.78 156.26 102.94 159.48 165.06 155.05 105.88 173.22 196.60 156.62 107.35 176.13 151.64 156.94 104.41 180.31 187.02 165.23 100.00 185.84 210.99 167.62 94.12 169.43 219.08 165.55 89.71 195.25 235.68 165.51 95.59 174.99 241.44 167.82 113.24 156.42 187.46 159.36 116.18 182.08 229.57 152.92 110.29 182.00 208.44 141.77 101.47 153.28 215.09 135.49 97.06 136.72 217.00 143.12 101.47 130.19 171.08 140.89 113.24 132.04 178.41 136.05 117.65 143.89 196.34 138.87 117.65 133.38 172.11 140.36 113.24 127.98 154.93 145.26 107.35 150.45 182.26 149.15 108.82 133.55 181.74 149.92 119.12
Names of X columns:
InvoerEU InvoerAM USD Werkloosh
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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