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Data X:
NA NA 0.52 6.82 6.76 2.81 3.00 5.00 3.00 6.30 0.30 0.92 3.00 3.82 1.62 3.00 1.00 3.00 NA NA 1.10 3.53 4.65 1.78 1.00 1.00 1.00 NA NA 1.22 -0.04 3.76 1.40 5.00 2.00 3.00 2.10 0.26 0.59 6.41 6.66 2.80 3.00 5.00 4.00 9.10 -0.15 0.99 4.02 5.25 2.26 4.00 4.00 4.00 15.80 0.59 1.29 -1.64 -0.52 1.54 1.00 1.00 1.00 5.20 0.00 0.79 5.20 5.23 2.59 4.00 5.00 4.00 10.90 0.56 1.16 3.52 4.41 1.80 1.00 2.00 1.00 8.30 0.15 0.99 4.72 5.64 2.36 1.00 1.00 1.00 11.00 0.18 1.10 -0.37 3.81 2.05 5.00 4.00 4.00 3.20 -0.15 0.59 5.67 5.63 2.45 5.00 5.00 5.00 7.60 0.43 1.01 -0.26 3.38 NA 2.00 1.00 2.00 NA NA 0.49 5.27 5.62 2.56 5.00 5.00 5.00 6.30 0.32 0.92 -1.12 3.08 1.62 1.00 1.00 1.00 8.60 NA 0.93 3.48 4.40 1.45 2.00 2.00 2.00 6.60 0.61 1.03 -0.11 3.54 1.62 2.00 2.00 2.00 9.50 0.08 1.03 -0.70 3.70 2.08 2.00 2.00 2.00 4.80 0.11 0.79 3.15 4.24 NA 1.00 2.00 1.00 12.00 0.79 1.26 4.78 4.91 NA 1.00 1.00 1.00 NA -0.52 NA 5.72 5.83 2.60 5.00 5.00 5.00 3.30 -0.30 0.58 4.44 5.06 2.17 5.00 5.00 5.00 11.00 0.53 1.16 -0.92 3.00 1.20 3.00 1.00 2.00 NA NA 1.08 5.32 5.61 2.40 1.00 4.00 1.00 4.70 0.18 0.79 4.93 5.51 2.49 1.00 3.00 1.00 NA NA 1.11 4.56 5.08 1.80 1.00 1.00 1.00 10.40 0.53 1.14 -1.00 3.60 1.45 5.00 1.00 3.00 7.40 -0.10 0.91 3.02 3.74 1.83 5.00 3.00 4.00 2.10 -0.10 0.46 5.72 5.82 2.53 5.00 5.00 5.00 NA NA 1.03 5.00 5.20 2.00 1.00 1.00 1.00 NA NA NA 4.54 4.75 1.52 3.00 5.00 4.00 7.70 0.15 0.96 -2.30 -0.85 1.33 5.00 2.00 4.00 17.90 0.30 1.30 -2.00 -0.60 1.70 1.00 1.00 1.00 6.10 0.28 0.90 4.79 6.12 2.43 1.00 1.00 1.00 8.20 0.38 1.03 -0.91 3.48 1.48 2.00 1.00 1.00 8.40 0.45 1.05 3.13 3.91 1.65 3.00 1.00 3.00 11.90 0.11 1.12 -1.64 -0.40 1.28 4.00 1.00 3.00 10.80 0.30 1.11 -1.32 -0.48 1.48 4.00 1.00 3.00 13.80 0.75 1.29 3.23 3.80 1.08 2.00 1.00 1.00 14.30 0.49 1.24 3.54 4.03 2.08 2.00 1.00 1.00 NA 0.00 NA 5.40 5.69 2.64 5.00 5.00 5.00 15.20 0.26 1.23 -0.32 4.19 2.15 2.00 2.00 2.00 10.00 -0.05 1.04 4.00 5.06 2.23 4.00 4.00 4.00 11.90 0.26 1.14 3.21 4.06 1.23 2.00 1.00 2.00 6.50 0.28 0.92 5.28 5.26 2.06 4.00 4.00 4.00 7.50 -0.05 0.92 3.40 4.08 1.49 5.00 5.00 5.00 NA NA 1.10 3.63 4.59 1.80 2.00 2.00 2.00 10.60 0.41 1.12 -0.55 3.28 1.32 3.00 1.00 3.00 7.40 0.38 0.99 3.63 4.70 1.72 1.00 1.00 1.00 8.40 0.08 0.98 3.83 5.25 2.21 2.00 3.00 2.00 5.70 -0.05 0.82 -0.12 4.09 2.35 2.00 2.00 2.00 4.90 -0.30 0.73 3.56 4.32 2.35 3.00 2.00 3.00 NA NA 0.41 4.17 4.99 2.18 5.00 5.00 5.00 3.20 -0.22 0.58 4.74 5.24 2.18 5.00 5.00 5.00 NA NA 1.04 3.15 4.10 1.95 2.00 2.00 2.00 8.10 0.34 1.01 -1.22 3.00 NA 3.00 1.00 2.00 11.00 0.36 1.12 -0.05 3.41 1.78 2.00 1.00 2.00 4.90 -0.30 0.73 3.30 4.09 2.30 3.00 1.00 3.00 13.20 0.41 1.20 -0.98 3.40 1.66 3.00 2.00 2.00 9.70 -0.22 1.01 3.62 4.76 2.32 4.00 3.00 4.00 12.80 0.82 1.29 3.54 3.59 1.15 2.00 1.00 1.00 NA NA NA 3.61 4.23 1.58 3.00 1.00 1.00
Names of X columns:
SWS Pslog Llog wblog wbrlog tglog P S D
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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