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Data X:
6.3000 0.3010 1.5041 0.0000 0.8195 1.6232 3.0000 1.0000 3.0000 2.1000 0.2553 4.2341 3.4060 3.6630 2.7952 3.0000 5.0000 4.0000 9.1000 -0.1549 3.2958 1.0233 2.2541 2.2553 4.0000 4.0000 4.0000 15.8000 0.5911 2.9444 -1.6383 -0.5229 1.5441 1.0000 1.0000 1.0000 5.2000 0.0000 3.4144 2.2041 2.2279 2.5933 4.0000 5.0000 4.0000 10.9000 0.5563 3.3322 0.5185 1.4082 1.7993 1.0000 2.0000 1.0000 8.3000 0.1461 3.9120 1.7173 2.6435 2.3617 1.0000 1.0000 1.0000 11.0000 0.1761 1.9459 -0.3716 0.8062 2.0492 5.0000 4.0000 4.0000 3.2000 -0.1549 3.4012 2.6675 2.6263 2.4487 5.0000 5.0000 5.0000 6.3000 0.3222 1.2528 -1.1249 0.0792 1.6232 1.0000 1.0000 1.0000 6.6000 0.6128 1.7918 -0.1051 0.5441 1.6232 2.0000 2.0000 2.0000 9.5000 0.0792 2.3418 -0.6990 0.6990 2.0792 2.0000 2.0000 2.0000 3.3000 -0.3010 2.9957 1.4419 2.0607 2.1703 5.0000 5.0000 5.0000 11.0000 0.5315 1.3610 -0.9208 0.0000 1.2041 3.0000 1.0000 2.0000 4.7000 0.1761 3.7136 1.9294 2.5119 2.4914 1.0000 3.0000 1.0000 10.4000 0.5315 2.1972 -0.9957 0.6021 1.4472 5.0000 1.0000 3.0000 7.4000 -0.0969 2.0281 0.0170 0.7404 1.8325 5.0000 3.0000 4.0000 2.1000 -0.0969 3.8286 2.7168 2.8162 2.5263 5.0000 5.0000 5.0000 17.9000 0.3010 3.1781 -2.0000 -0.6021 1.6990 1.0000 1.0000 1.0000 6.1000 0.2788 4.6052 1.7924 3.1206 2.4265 1.0000 1.0000 1.0000 11.9000 0.1139 1.1632 -1.6383 -0.3979 1.2788 4.0000 1.0000 3.0000 13.8000 0.7482 1.6094 0.2304 0.7993 1.0792 2.0000 1.0000 1.0000 14.3000 0.4914 1.8718 0.5441 1.0334 2.0792 2.0000 1.0000 1.0000 15.2000 0.2553 2.4849 -0.3188 1.1903 2.1461 2.0000 2.0000 2.0000 10.0000 -0.0458 3.0057 1.0000 2.0607 2.2304 4.0000 4.0000 4.0000 11.9000 0.2553 2.5649 0.2095 1.0569 1.2304 2.0000 1.0000 2.0000 6.5000 0.2788 3.2958 2.2833 2.2553 2.0607 4.0000 4.0000 4.0000 7.5000 -0.0458 2.8904 0.3979 1.0828 1.4914 5.0000 5.0000 5.0000 10.6000 0.4150 1.5476 -0.5528 0.2788 1.3222 3.0000 1.0000 3.0000 7.4000 0.3802 2.2824 0.6269 1.7024 1.7160 1.0000 1.0000 1.0000 8.4000 0.0792 3.3673 0.8325 2.2529 2.2148 2.0000 3.0000 2.0000 5.7000 -0.0458 1.9459 -0.1249 1.0899 2.3522 2.0000 2.0000 2.0000 4.9000 -0.3010 1.7918 0.5563 1.3222 2.3522 3.0000 2.0000 3.0000 3.2000 -0.2218 2.9957 1.7443 2.2430 2.1790 5.0000 5.0000 5.0000 11.0000 0.3617 1.5041 -0.0458 0.4150 1.7782 2.0000 1.0000 2.0000 4.9000 -0.3010 2.0149 0.3010 1.0899 2.3010 3.0000 1.0000 3.0000 13.2000 0.4150 0.8329 -0.9830 0.3979 1.6628 3.0000 2.0000 2.0000 9.7000 -0.2218 3.1781 0.6222 1.7634 2.3222 4.0000 3.0000 4.0000 12.8000 0.8195 1.0986 0.5441 0.5911 1.1461 2.0000 1.0000 1.0000
Names of X columns:
SWS logPS LnL logWb logWbr logGt P S D
Type of Correlation
50
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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