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Data X:
5560 36.68 3922 36.7 3759 36.71 4138 36.72 4634 36.73 3996 36.73 4308 36.87 4429 37.31 5219 37.39 4929 37.42 5755 37.51 5592 37.67 4163 37.67 4962 37.71 5208 37.78 4755 37.79 4491 37.84 5732 37.88 5731 38.34 5040 38.58 6102 38.72 4904 38.83 5369 38.9 5578 38.92 4619 38.94 4731 39.1 5011 39.14 5299 39.16 4146 39.32 4625 39.34 4736 39.44 4219 39.92 5116 40.19 4205 40.2 4121 40.27 5103 40.28 4300 40.3 4578 40.34 3809 40.4 5526 40.43 4247 40.48 3830 40.48 4394 40.63 4826 40.74 4409 40.77 4569 40.91 4106 40.92 4794 41.03 3914 41 3793 41.04 4405 41.33 4022 41.44 4100 41.46 4788 41.55 3163 41.55 3585 41.81 3903 41.78 4178 41.84 3863 41.84 4187 41.86
Names of X columns:
Bouwvergunningen_woningen Uurtarief_loodgieter
Type of Correlation
pearson
spearman
kendall
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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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