Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
12 25 6 15 16 10 3 1 3 1 20 38 39 39 39 3 5 4 21 6 29 29 32 28 4 4 4 38 36 23 2 2 9 1 1 1 9 13 34 35 29 38 4 5 4 27 35 31 21 24 17 1 2 1 19 17 37 31 36 33 1 1 1 28 18 13 10 15 19 5 4 4 3 6 33 37 35 35 5 5 5 12 27 4 4 5 10 1 1 1 15 37 10 13 9 10 2 2 2 22 14 19 8 12 21 2 2 2 5 1 24 30 27 24 5 5 5 28 33 5 7 4 3 3 1 2 6 18 35 34 34 36 1 3 1 25 33 17 5 11 7 5 1 3 16 8 16 16 13 18 5 3 4 1 8 36 38 37 37 5 5 5 39 25 27 1 1 14 1 1 1 11 23 39 33 38 34 1 1 1 31 16 3 2 3 5 4 1 3 35 38 9 18 14 1 2 1 1 36 32 12 22 17 21 2 1 1 37 20 20 11 22 23 2 2 2 24 10 26 28 27 27 4 4 4 31 20 21 17 18 4 2 1 2 14 23 29 36 33 20 4 4 4 18 10 22 20 19 8 5 5 5 26 30 8 9 6 6 3 1 3 16 29 18 26 25 15 1 1 1 20 14 32 27 31 26 2 3 2 10 10 13 12 20 31 2 2 2 7 1 10 24 23 31 3 2 3 3 4 24 32 30 25 5 5 5 28 28 6 14 8 16 2 1 2 7 1 15 19 20 29 3 1 3 34 30 1 6 7 13 3 2 2 23 4 27 25 26 30 4 3 4 33 39 2 22 10 2 2 1 1
Names of X columns:
Sloww Psleep Lifespan Weight Wbrain Gdracht Predation Splaats Danger
Type of Correlation
pearson
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=par1) 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$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...) } bitmap(file='test1.png') pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main) dev.off() load(file='createtable') n <- length(y[,1]) n a<-table.start() a<-table.row.start(a) a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,' ',header=TRUE) for (i in 1:n) { a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) } a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE) for (j in 1:n) { r <- cor.test(y[i,],y[j,],method=par1) a<-table.element(a,round(r$estimate,3)) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'pair',1,TRUE) a<-table.element(a,'Pearson r',1,TRUE) a<-table.element(a,'Spearman rho',1,TRUE) a<-table.element(a,'Kendall tau',1,TRUE) a<-table.row.end(a) cor.test(y[1,],y[2,],method=par1) for (i in 1:(n-1)) { for (j in (i+1):n) { a<-table.row.start(a) dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='') a<-table.element(a,dum,header=TRUE) rp <- cor.test(y[i,],y[j,],method='pearson') a<-table.element(a,round(rp$estimate,4)) rs <- cor.test(y[i,],y[j,],method='spearman') a<-table.element(a,round(rs$estimate,4)) rk <- cor.test(y[i,],y[j,],method='kendall') a<-table.element(a,round(rk$estimate,4)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-value',header=T) a<-table.element(a,paste('(',round(rp$p.value,4),')',sep='')) a<-table.element(a,paste('(',round(rs$p.value,4),')',sep='')) a<-table.element(a,paste('(',round(rk$p.value,4),')',sep='')) a<-table.row.end(a) } } a<-table.end(a) table.save(a,file='mytable1.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