Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
100.70 101.30 99.80 97.90 97.60 103.50 96.50 96.40 103.10 96.60 97.00 105.60 96.60 96.40 105.70 95.50 94.70 106.60 91.80 89.30 107.00 89.30 85.90 105.20 87.00 83.30 105.70 85.90 81.50 105.00 88.00 85.00 105.10 87.90 84.80 105.90 89.20 87.50 105.30 90.90 89.00 104.90 91.60 90.00 103.20 90.20 89.60 103.40 89.10 87.40 104.40 87.50 84.80 104.50 86.30 81.90 105.90 86.00 81.10 110.60 84.40 79.10 112.40 86.10 80.50 111.80 91.00 88.50 111.00 92.70 90.90 111.00 88.00 84.90 109.10 84.30 80.00 107.80 82.20 76.50 107.20 80.80 75.40 108.40 79.40 73.50 107.50 80.20 74.30 106.40 82.20 77.70 106.20 82.20 77.90 104.90 81.20 76.70 106.20 82.10 77.20 107.60 88.10 86.00 107.00 88.50 86.90 104.50 92.10 92.00 105.10 98.60 101.70 104.70 100.90 104.50 103.70 100.60 101.70 104.90 101.10 100.60 105.90 102.10 100.30 106.10 103.60 102.50 106.10 102.80 101.00 106.80 108.30 108.60 106.40 104.00 103.40 107.80 106.10 106.40 107.60 106.30 106.60 107.60 109.00 108.90 108.40 111.00 110.50 109.50 113.70 114.00 109.20 112.70 112.80 109.10 110.30 109.60 110.00 114.50 116.00 109.00 119.30 124.60 109.00 121.80 129.00 111.90 125.40 131.50 109.30 129.70 138.60 112.10 129.40 138.10 112.10 134.50 146.30 112.50 141.20 157.60 113.60 141.40 158.40 112.90 152.20 176.30 114.00 167.70 199.90 116.10 173.30 210.40 116.50 168.70 202.60 117.10 172.60 207.10 117.10 169.80 202.00 117.10 172.00 203.40 116.50 179.40 216.30 116.50 174.60 207.30 116.30 172.50 203.50 116.50 172.60 204.40 119.20 176.30 203.70 118.60 178.90 205.70 117.50 179.60 208.00 117.10 179.90 209.30 117.60 180.30 208.70 118.30 180.90 206.50 118.60 177.70 204.50 116.70
Names of X columns:
TM NF GM
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