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Data X:
2.67 1.74 3.2 2.72 1.75 1.9 2.84 1.83 0 3 2.09 0.6 3.08 2.12 0.2 3.21 2.29 0.9 3.44 2.4 2.4 3.74 2.82 4.7 4.08 3.18 9.4 4.79 4 12.5 5.44 4.8 15.8 6.02 5.28 18.2 6.01 5.37 16.8 5.85 5.27 17.3 5.93 5.33 19.3 5.85 5.23 17.9 5.74 5.08 20.2 5.75 5.11 18.7 5.78 5.1 20.1 5.62 4.97 18.2 5.67 5 18.4 5.89 5.2 18.2 5.67 4.9 18.9 5.64 4.82 19.9 5.64 5.04 21.3 5.64 4.82 20 5.54 4.77 19.5 5.52 4.79 19.6 5.28 4.58 20.9 5.25 4.59 21 5.23 4.57 19.9 5.09 4.35 19.6 5 4.27 20.9 5.02 4.39 21.7 4.8 3.97 22.9 4.71 3.84 21.5 4.51 3.73 21.3 4.51 3.58 23.5 4.42 3.45 21.6 4.4 3.44 24.5 4.25 3.25 22.2 4.18 3.25 23.5 4.09 3.02 20.9 3.97 2.87 20.7 3.89 2.92 18.1 4.02 2.95 17.1 3.81 2.75 14.8 3.67 2.7 13.8 3.68 2.75 15.2 3.66 2.72 16 3.66 2.71 17.6 3.65 2.76 15 3.67 2.68 15 3.66 2.78 16.3 3.7 2.86 19.4 3.77 2.75 21.3 3.74 2.87 20.5 3.8 2.91 21.1 3.79 2.79 21.6 3.75 2.77 22.6
Names of X columns:
venn< venn> ip
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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