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Data X:
35.323 26 21 21 35.478 20 16 15 4.39 19 19 18 41.667 19 18 11 22.173 20 16 8 28.021 25 23 19 18.109 25 17 4 13.962 22 12 20 40.174 26 19 16 16.065 22 16 14 18.145 17 19 10 18.439 22 20 13 10.603 19 13 14 34.811 24 20 8 69.064 26 27 23 51.202 21 17 11 14.786 13 8 9 33.01 26 25 24 81.101 20 26 5 89.232 22 13 15 21.223 14 19 5 15.173 21 15 19 241.66 7 5 6 26.848 23 16 13 8.752 17 14 11 60.535 25 24 17 60.535 25 24 17 26.052 19 9 5 49.218 20 19 9 30.669 23 19 15 18.673 22 25 17 86 22 19 17 10.632 21 18 20 35.802 15 15 12 33.974 20 12 7 36.972 22 21 16 4.928 18 12 7 53.976 20 15 14 15.467 28 28 24 35.723 22 25 15 40.424 18 19 15 9.706 23 20 10 26.532 20 24 14 23.843 25 26 18 18.062 26 25 12 35.681 15 12 9 68.125 17 12 9 23.937 23 15 8 31.479 21 17 18 66.659 13 14 10 250.234 18 16 17 49.469 19 11 14 42.951 22 20 16 43.402 16 11 10 24.112 24 22 19 56.95 18 20 10 17.313 20 19 14 25.658 24 17 10 48.172 14 21 4 13.891 22 23 19 32.048 24 18 9 19.797 18 17 12 31.317 21 27 16 20.966 23 25 11 22.708 17 19 18 26.81 22 22 11 52.004 24 24 24 32.354 21 20 17 27.128 22 19 18 26.529 16 11 9 28.392 21 22 19 57.393 23 22 18 194.731 22 16 12 9.415 24 20 23 91.076 24 24 22 57.751 16 16 14 8.236 16 16 14 20.407 21 22 16 13.681 26 24 23 79.659 15 16 7 53.48 25 27 10 6.906 18 11 12 50.202 23 21 12 37.877 20 20 12 85.903 17 20 17 35.351 25 27 21 283.801 24 20 16 5.974 17 12 11 3.441 19 8 14 51.987 20 21 13 13.22 15 18 9 1.455 27 24 19 18.187 22 16 13 21.29 23 18 19 5.686 16 20 13 4.944 19 20 13 32.789 25 19 13 50.494 19 17 14 35.162 19 16 12 38.095 26 26 22 19.172 21 15 11 24.5 20 22 5 20.573 24 17 18 42.042 22 23 19 302.912 20 21 14 25.027 18 19 15 16.488 18 14 12 32.36 24 17 19 6.193 24 12 15 37.7 22 24 17 6.343 23 18 8 23.025 22 20 10 48.578 20 16 12 21.564 18 20 12 33.697 25 22 20 10.831 18 12 12 19.172 16 16 12 21.075 20 17 14 33.189 19 22 6 60.5 15 12 10 33.686 19 14 18 40.838 19 23 18 13.491 16 15 7 106.637 17 17 18 35.897 28 28 9 7.314 23 20 17 49.094 25 23 22 14.667 20 13 11 54.179 17 18 15 145.846 23 23 17 18.56 16 19 15 23.525 23 23 22 21.804 11 12 9 26.301 18 16 13 41.33 24 23 20 10.5 23 13 14 13.338 21 22 14 60.31 16 18 12 34.256 24 23 20 48.267 23 20 20 41.559 18 10 8 32.45 20 17 17 10.951 9 18 9 22.561 24 15 18 57.095 25 23 22 19.105 20 17 10 13.151 21 17 13 27.426 25 22 15 15.355 22 20 18 13.82 21 20 18 47.21 21 19 12 110.349 22 18 12 34.985 27 22 20 27.257 24 20 12 23.556 24 22 16 50.108 21 18 16 18.158 18 16 18 87.357 16 16 16 18.187 22 16 13 28.33 20 16 17 13.474 18 17 13 26.244 20 18 17
Names of X columns:
First_Click I1 I2 I3
Type of Correlation
kendall
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')
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