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Data X:
95.1 117.1 97 118.7 112.7 126.5 102.9 127.5 97.4 134.6 111.4 131.8 87.4 135.9 96.8 142.7 114.1 141.7 110.3 153.4 103.9 145 101.6 137.7 94.6 148.3 95.9 152.2 104.7 169.4 102.8 168.6 98.1 161.1 113.9 174.1 80.9 179 95.7 190.6 113.2 190 105.9 181.6 108.8 174.8 102.3 180.5 99 196.8 100.7 193.8 115.5 197 100.7 216.3 109.9 221.4 114.6 217.9 85.4 229.7 100.5 227.4 114.8 204.2 116.5 196.6 112.9 198.8 102 207.5 106 190.7 105.3 201.6 118.8 210.5 106.1 223.5 109.3 223.8 117.2 231.2 92.5 244 104.2 234.7 112.5 250.2 122.4 265.7 113.3 287.6 100 283.3 110.7 295.4 112.8 312.3 109.8 333.8 117.3 347.7 109.1 383.2 115.9 407.1 96 413.6 99.8 362.7 116.8 321.9 115.7 239.4 99.4 191 94.3 159.7 91 163.4
Names of X columns:
tot.ind.prod.index prijsindex.grondst.incl.energie
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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