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Data X:
0 0 -0.04 0 -0.0325 0 -0.0179 0 -0.0076 0 -0.025 0 -0.0025 0 0.0251 0 -0.0103 0 0.0205 0 -0.0368 0 -0.0228 0 0.0027 0 -0.0303 -4.4 -0.0191 121.4 -0.0173 -209 -0.041 209.5 0.0432 -321.2 -0.0095 150.7 -0.0356 47.4 -0.032 397.5 -0.0169 -356.1 0.0012 65.2 0.0409 -66.8 0.041 -78.2 -0.0166 65 -0.0122 -278.2 -0.0175 132.3 -0.0178 -70 -0.021 226.7 0.0075 -227.5 0.0398 -29.1 0.0106 -448.1 -0.0052 474.9 -0.0176 -13 0.0041 -97 -0.0091 170.1 -0.0133 -113.9 0.0058 39.4 0.01 253.7 0.0312 -156.5 0.0384 -153.8 0.0368 123.6 -0.0144 6.2 0.003 22 0.0003 52.4 0.0203 -129.3 0.0169 112.1 0.0439 -84.2 0.0151 -94.7 0.0034 -45.9 0.0041 54.4 0.0734 19.6 0.0081 7.7 -0.0291 94.6 -0.0233 -15.5 0.0083 59.2 0.047 -188.4 0.001 38 0.0584 112.2
Names of X columns:
dollarkoers export
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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