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Data X:
6.3 0.301029996 0.653212514 0 0.819543936 0.21 3 1 3 2.1 0.255272505 1.838849091 3.406028945 3.663040975 0.45 3 5 4 9.1 -0.15490196 1.431363764 1.02325246 2.254064453 0.35 4 4 4 15.8 0.591064607 1.278753601 -1.638272164 -0.522878745 0.19 1 1 1 5.2 0 1.482873584 2.204119983 2.227886705 0.41 4 5 4 10.9 0.556302501 1.447158031 0.51851394 1.408239965 0.26 1 2 1 8.3 0.146128036 1.698970004 1.717337583 2.643452676 0.37 1 1 1 11 0.176091259 0.84509804 -0.37161107 0.806179974 0.31 5 4 4 3.2 -0.15490196 1.477121255 2.667452953 2.626340367 0.39 5 5 5 6.3 0.322219295 0.544068044 -1.124938737 0.079181246 0.21 1 1 1 6.6 0.612783857 0.77815125 -0.105130343 0.544068044 0.21 2 2 2 9.5 0.079181246 1.017033339 -0.698970004 0.698970004 0.32 2 2 2 3.3 -0.301029996 1.301029996 1.441852176 2.06069784 0.34 5 5 5 11 0.531478917 0.591064607 -0.920818754 0 0.08 3 1 2 4.7 0.176091259 1.612783857 1.929418926 2.511883361 0.40 1 3 1 10.4 0.531478917 0.954242509 -0.995678626 0.602059991 0.16 5 1 3 7.4 -0.096910013 0.880813592 0.017033339 0.740362689 0.26 5 3 4 2.1 -0.096910013 1.662757832 2.716837723 2.8162413 0.40 5 5 5 17.9 0.301029996 1.380211242 -2 -0.602059991 0.23 1 1 1 6.1 0.278753601 2 1.792391689 3.120573931 0.38 1 1 1 11.9 0.113943352 0.505149978 -1.638272164 -0.397940009 0.11 4 1 3 13.8 0.748188027 0.698970004 0.230448921 0.799340549 0.03 2 1 1 14.3 0.491361694 0.812913357 0.544068044 1.033423755 0.32 2 1 1 15.2 0.255272505 1.079181246 -0.318758763 1.190331698 0.33 2 2 2 10 -0.045757491 1.305351369 1 2.06069784 0.35 4 4 4 11.9 0.255272505 1.113943352 0.209515015 1.056904851 0.09 2 1 2 6.5 0.278753601 1.431363764 2.283301229 2.255272505 0.31 4 4 4 7.5 -0.045757491 1.255272505 0.397940009 1.08278537 0.17 5 5 5 10.6 0.414973348 0.672097858 -0.552841969 0.278753601 0.12 3 1 3 7.4 0.380211242 0.991226076 0.626853415 1.702430536 0.23 1 1 1 8.4 0.079181246 1.462397998 0.832508913 2.252853031 0.35 2 3 2 5.7 -0.045757491 0.84509804 -0.124938737 1.089905111 0.37 2 2 2 4.9 -0.301029996 0.77815125 0.556302501 1.322219295 0.37 3 2 3 3.2 -0.22184875 1.301029996 1.744292983 2.243038049 0.34 5 5 5 11 0.361727836 0.653212514 -0.045757491 0.414973348 0.25 2 1 2 4.9 -0.301029996 0.875061263 0.301029996 1.089905111 0.36 3 1 3 13.2 0.414973348 0.361727836 -0.982966661 0.397940009 0.22 3 2 2 9.7 -0.22184875 1.380211242 0.622214023 1.763427994 0.37 4 3 4 12.8 0.819543936 0.477121255 0.544068044 0.591064607 0.06 2 1 1
Names of X columns:
SWS logps L logWb Wbr tg P S D
Type of Correlation
pearson
pearson
spearman
kendall
Chart options
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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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