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Data X:
21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4 10.4 14.7 32.4 30.4 33.9 21.5 15.5 15.2 13.3 19.2 27.3 26 30.4 15.8 19.7 15 21.4 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4 160 160 108 258 360 225 360 146.7 140.8 167.6 167.6 275.8 275.8 275.8 472 460 440 78.7 75.7 71.1 120.1 318 304 350 400 79 120.3 95.1 351 145 301 121 110 110 93 110 175 105 245 62 95 123 123 180 180 180 205 215 230 66 52 65 97 150 150 245 175 66 91 113 264 175 335 109 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 3.92 3.07 3.07 3.07 2.93 3 3.23 4.08 4.93 4.22 3.7 2.76 3.15 3.73 3.08 4.08 4.43 3.77 4.22 3.62 3.54 4.11 2.62 2.875 2.32 3.215 3.44 3.46 3.57 3.19 3.15 3.44 3.44 4.07 3.73 3.78 5.25 5.424 5.345 2.2 1.615 1.835 2.465 3.52 3.435 3.84 3.845 1.935 2.14 1.513 3.17 2.77 3.57 2.78 16.46 17.02 18.61 19.44 17.02 20.22 15.84 20 22.9 18.3 18.9 17.4 17.6 18 17.98 17.82 17.42 19.47 18.52 19.9 20.01 16.87 17.3 15.41 17.05 18.9 16.7 16.9 14.5 15.5 14.6 18.6
Names of X columns:
MazdaRX4 MazdaRX4Wag Datsun710 Hornet4Drive HornetSport Valiant Duster360 Merc240D Merc230 Merc280 Merc280C Merc450SE Merc450SL Merc450SLC CadillacFl LincolnCont ChryslerImp Fiat128 HondaCivic ToyotaCorolla ToyotaCoron DodgeChall AMCJavel CamaroZ28 PontiacFireb FiatX1-9 Porsche914-2 LotusEuropa FordPantL FerrariDino MaseratiBora Volvo142E
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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