Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
1.8 -8.0 -2.5 -3.7 1.2 -7.5 0.4 -1.2 19.9 18.5 8.6 11.4 2.5 -1.7 0.3 -0.1 -1.4 -1.5 10.4 0.1 22.0 14.6 10.5 12.3 -6.4 3.3 -1.8 -1.3 13.6 4.5 4.8 5.1 11.3 0.9 3.6 3.6 3.0 -11.1 -4.9 -6.4 -1.1 4.6 6.7 6.9 2.1 -6.7 2.2 0.4 7.2 16.9 3.9 6.6 4.6 3.0 1.4 1.9 -1.6 -3.4 -2.9 -3.2 0.9 10.3 1.0 2.9 1.8 -5.8 5.8 4.1 0.7 1.3 -2.0 -1.6 5.1 10.0 -5.5 -3.1 7.4 -10.6 2.6 0.3 1.5 23.0 -0.1 4.2 -9.0 -3.2 -1.0 -1.5 8.1 17.2 0.9 4.1 4.3 11.5 -5.2 -2.4 1.6 12.9 -0.4 1.9 11.6 18.1 1.0 4.2 10.8 3.5 5.6 5.5 -8.5 4.7 -3.9 -2.7 21.5 50.3 5.7 14.2 5.5 15.4 4.2 6.4 2.5 8.9 5.1 6.3 1.5 8.1 4.3 5.5 8.5 -3.3 2.9 1.8 18.7 30.4 10.8 15.3 13.6 13.6 7.8 9.2 1.7 6.1 3.6 4.3 10.7 -14.7 7.6 4.7 -5.3 -7.4 3.8 2.5 -14.8 -13.8 4.3 1.6 5.1 -10.7 7.3 5.1 -5.9 -25.1 3.9 -0.8 6.0 -13.6 3.2 0.5 9.5 7.3 13.2 13.5 2.1 18.1 6.5 9.4 -3.2 -14.1 -0.8 -3.3 6.3 -11.4 8.1 5.6 -2.1 -18.9 4.2 0.7 5.3 -20.3 1.2 -2.2
Names of X columns:
INV DC NDC CON
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
1 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation