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Data X:
NA NA 38.6 6654.000 5712.000 645 3 5 3 6.3 2 4.5 1.000 6.600 42 3 1 3 NA NA 14 3.385 44.500 60 1 1 1 NA NA NA 0.920 5.700 25 5 2 3 2.1 1.8 39 2547.000 4603.000 624 3 5 4 9.1 0.7 27 10.550 179.500 180 4 4 4 15.8 3.9 19 0.023 0.300 35 1 1 1 5.2 1 30.4 160.000 169.000 392 4 5 4 10.9 3.6 28 3.300 25.600 63 1 2 1 8.3 1.4 50 52.160 440.000 230 1 1 1 11 1.5 7 0.425 6.400 112 5 4 4 3.2 0.7 30 465.000 423.000 271 5 5 5 7.6 2.7 NA 0.550 2.400 NA 2 1 2 NA NA 40 187.100 419.000 365 5 5 5 6.3 2.1 3.5 0.075 1.200 42 1 1 1 8.6 0 50 3.000 25.000 28 2 2 2 6.6 4.1 6 0.785 3.500 42 2 2 2 9.5 1.2 10.4 0.200 5.000 120 2 2 2 4.8 1.3 34 1.410 17.500 NA 1 2 1 12 6.1 7 60.000 91.000 NA 1 1 1 NA 0.3 28 529.000 680.000 400 5 5 5 3.3 0.5 20 27.660 115.000 148 5 5 5 11 3.4 3.9 0.120 1.000 16 3 1 2 NA NA 39.3 207.000 406.000 252 1 4 1 4.7 1.5 41 85.000 325.000 310 1 3 1 NA NA 16.2 36.330 119.500 63 1 1 1 10.4 3.4 9 0.101 4.000 28 5 1 3 7.4 0.8 7.6 1.040 5.500 68 5 3 4 2.1 0.8 46 521.000 655.000 336 5 5 5 NA NA 22.4 100.000 167.000 100 1 1 1 NA NA 16.3 35.000 56.000 33 3 5 4 7.7 1.4 2.6 0.005 0.140 21.5 5 2 4 17.9 2 24 0.010 0.250 50 1 1 1 6.1 1.9 100 62.000 1320.000 267 1 1 1 8.2 2.4 NA 0.122 3.000 30 2 1 1 8.4 2.8 NA 1.350 8.100 45 3 1 3 11.9 1.3 3.2 0.023 0.400 19 4 1 3 10.8 2 2 0.048 0.330 30 4 1 3 13.8 5.6 5 1.700 6.300 12 2 1 1 14.3 3.1 6.5 3.500 10.800 120 2 1 1 NA 1 12.6 250.000 490.000 440 5 5 5 15.2 1.8 12 0.480 15.500 140 2 2 2 10 0.9 20.2 10.000 115.000 170 4 4 4 11.9 1.8 13 1.620 11.400 17 2 1 2 6.5 1.9 27 192.000 180.000 115 4 4 4 7.5 0.9 18 2.500 12.100 31 5 5 5 NA NA 13.7 4.288 39.200 63 2 2 2 10.6 2.6 4.7 0.280 1.900 21 3 1 3 7.4 2.4 9.8 4.235 50.400 52 1 1 1 8.4 1.2 29 6.800 179.000 164 2 3 2 5.7 0.9 7 0.750 12.300 225 2 2 2 4.9 0.5 6 3.600 21.000 225 3 2 3 NA NA 17 14.830 98.200 150 5 5 5 3.2 0.6 20 55.500 175.000 151 5 5 5 NA NA 12.7 1.400 12.500 90 2 2 2 8.1 2.2 3.5 0.060 1.000 NA 3 1 2 11 2.3 4.5 0.900 2.600 60 2 1 2 4.9 0.5 7.5 2.000 12.300 200 3 1 3 13.2 2.6 2.3 0.104 2.500 46 3 2 2 9.7 0.6 24 4.190 58.000 210 4 3 4 12.8 6.6 3 3.500 3.900 14 2 1 1 NA NA 13 4.050 17.000 38 3 1 1
Names of X columns:
1 2 3 4 5 6 7 8 9
Type of Correlation
pearson
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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