Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
36 29 114.1 4.3 24 31 110.3 3.9 10 31 103.9 4 17 33 101.6 4.3 14 37 94.6 4.8 61 30 95.9 4.4 57 20 104.7 4.3 34 19 102.8 4.7 53 17 98.1 4.7 11 22 113.9 4.9 56 12 80.9 5 51 25 95.7 4.2 36 25 113.2 4.3 33 29 105.9 4.8 16 32 108.8 4.8 12 31 102.3 4.8 21 28 99 4.2 63 28 100.7 4.6 55 28 115.5 4.8 47 32 100.7 4.5 48 35 109.9 4.4 12 30 114.6 4.3 48 32 85.4 3.9 59 38 100.5 3.7 41 37 114.8 4 39 28 116.5 4.1 20 34 112.9 3.7 38 35 102 3.8 49 32 106 3.8 59 39 105.3 3.8 36 37 118.8 3.3 42 38 106.1 3.3 46 35 109.3 3.3 8 25 117.2 3.2 53 25 92.5 3.4 50 26 104.2 4.2 47 13 112.5 4.9 24 19 122.4 5.1 17 17 113.3 5.5 45 21 100 5.6 47 23 110.7 6.4 27 18 112.8 6.1 45 12 109.8 7.1 31 7 117.3 7.8 45 4 109.1 7.9 13 14 115.9 7.4 39 16 96 7.5 47 13 99.8 6.8 30 13 116.8 5.2 14 10 115.7 4.7 3 19 99.4 4.1 5 13 94.3 3.9 43 14 91 2.6 53 25 93.2 2.7 35 28 103.1 1.8 21 30 94.1 1 34 31 91.8 0.3 1 42 102.7 1.3 44 41 82.6 1 46 38 89.1 1.1
Names of X columns:
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')
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation