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Data X:
17823.2 16629.6 17872 16670.7 17420.4 16614.8 16704.4 16869.2 15991.2 15663.9 16583.6 16359.9 19123.5 18447.7 17838.7 16889 17209.4 16505 18586.5 18320.9 16258.1 15052.1 15141.6 15699.8 19202.1 18135.3 17746.5 16768.7 19090.1 18883 18040.3 19021 17515.5 18101.9 17751.8 17776.1 21072.4 21489.9 17170 17065.3 19439.5 18690 19795.4 18953.1 17574.9 16398.9 16165.4 16895.6 19464.6 18553 19932.1 19270 19961.2 19422.1 17343.4 17579.4 18924.2 18637.3 18574.1 18076.7 21350.6 20438.6 18594.6 18075.2 19823.1 19563 20844.4 19899.2 19640.2 19227.5 17735.4 17789.6 19813.6 19220.8 22160 21968.9 20664.3 21131.5 17877.4 19484.6 20906.5 22168.7 21164.1 20866.8 21374.4 22176.2 22952.3 23533.8 21343.5 21479.6 23899.3 24347.7 22392.9 22751.6 18274.1 20328.3 22786.7 23650.4 22321.5 23335.7 17842.2 19614.9 16373.5 18042.3 15993.8 17282.5 16446.1 16847.2 17729 18159.5 16643 16540.9 16196.7 15952.7 18252.1 18357.8 17570.4 16685.6 15836.8 15799.5
Names of X columns:
uitvoer invoer
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')
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Big Analytics Cloud Computing Center
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