Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
-1.2 81.3 23.6 23.5 -2.4 81.5 25.7 26.9 0.8 83.2 32.5 19.4 -0.1 80.8 33.5 19.3 -1.5 81.3 34.5 25 -4.4 78.8 27.9 14.4 -4.2 82.8 45.3 18.3 3.5 84.9 40.8 26.2 10 93.2 58.5 14.9 8.6 94.9 32.5 20.8 9.5 95 35.5 25.5 9.9 104.1 46.7 37.6 10.4 107.3 53.2 18.7 16 119 36.1 18.6 12.7 112.5 54 18.7 10.2 112.5 58.1 22.7 8.9 94.1 41.8 17.7 12.6 97 43.1 26.4 13.6 109 76 35.8 14.8 112.4 42.8 19 9.5 107.5 41 25 13.7 113.4 61.4 42.1 17 120.3 34.2 47.6 14.7 124.7 53.8 38 17.4 139.9 80.7 44.8 9 146.2 79.5 29.6 9.1 136 96.5 23.3 12.2 135.9 108.3 33.7 15.9 142 100.1 33.6 12.9 141.5 108.5 56.5 10.9 143 127.4 44.4 10.6 148.4 86.5 29.3 13.2 147.6 71.4 26.5 9.6 145.9 88.2 50.6 6.4 149.4 135.6 85.1 5.8 148.5 70.5 42.7 -1 137.7 87.5 46.8 -0.2 130.9 73.3 38.2 2.7 131 92.2 28.5 3.6 129.8 61.1 26.2 -0.9 123.5 45.7 19.9 0.3 125.5 30.5 21.4 -1.1 130.4 34.8 17.6 -2.5 136 29.2 29.9 -3.4 136.8 56.7 39.2 -3.5 140 67.1 52.1 -3.9 142.8 41.8 24.4 -4.6 142.1 46.8 34.9 -0.1 145.6 50.1 19.7 4.3 151.6 81.9 31.4 10.2 165.4 115.8 59.1 8.7 164 102.5 32.5 13.3 163.3 106.6 30 15 164.2 101.4 22.2 20.7 171.5 136.1 23.6 20.7 177.5 143.4 22 26.4 195.2 127.5 19.5 31.2 203.5 113.8 55.8 31.4 208.2 75.3 54.3 26.6 192.3 98.5 67.9 26.6 183.3 113.7 39.6 19.2 166.8 103.7 56.4 6.5 143 73.9 28.5 3.1 115 52.5 39.1 -0.2 114.1 63.9 39.1 -4 117.1 44.9 26.1 -12.6 113.4 31.3 26.7 -13 119.8 24.9 23.7 -17.6 126.1 22.8 21.7 -21.7 137.5 24.8 33.3 -23.2 131.6 22.8 49.3 -16.8 140 20.9 56.3 -19.8 136.1 21.5 49.9
Names of X columns:
Energiedragers Afzet Invoer Uitvoer
Type of Correlation
3. Belgische invoer van energiegrondstoffen
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