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Data X:
NA NA 38.60 6654.00 5712.00 645.00 3.00 5.00 3.00 6.30 2.00 4.50 1.00 6600.00 42.00 3.00 1.00 3.00 NA NA 14.00 3.39 44.50 60.00 1.00 1.00 1.00 NA NA NA 0.92 5.70 25.00 5.00 2.00 3.00 2.10 1.80 69.00 2547.00 4603.00 624.00 3.00 5.00 4.00 9.10 0.70 27.00 10.55 179.50 180.00 4.00 4.00 4.00 15.80 3.90 19.00 0.02 0.30 35.00 1.00 1.00 1.00 5.20 1.00 30.40 160.00 169.00 392.00 4.00 5.00 4.00 10.90 3.60 28.00 3.30 25.60 63.00 1.00 2.00 1.00 8.30 1.40 50.00 52.16 440.00 230.00 1.00 1.00 1.00 11.00 1.50 7.00 0.43 6.40 112.00 5.00 4.00 4.00 3.20 0.70 30.00 465.00 423.00 281.00 5.00 5.00 5.00 7.60 2.70 NA 0.55 2.40 NA 2.00 1.00 2.00 NA NA 40.00 187.10 419.00 365.00 5.00 5.00 5.00 6.30 2.10 3.50 0.08 1.20 42.00 1.00 1.00 1.00 8.60 0.00 50.00 3.00 25.00 28.00 2.00 2.00 2.00 6.60 4.10 6.00 0.79 3500.00 42.00 2.00 2.00 2.00 9.50 1.20 10.40 0.20 5.00 120.00 2.00 2.00 2.00 4.80 1.30 34.00 1.41 17.50 NA 1.00 2.00 1.00 12.00 6.10 7.00 60.00 81.00 NA 1.00 1.00 1.00 NA 0.30 28.00 529.00 680.00 400.00 5.00 5.00 5.00 3.30 0.50 20.00 27.66 115.00 148.00 5.00 5.00 5.00 11.00 3.40 3.90 0.12 1.00 16.00 3.00 1.00 2.00 NA NA 39.30 207.00 406.00 252.00 1.00 4.00 1.00 4.70 1.50 41.00 85.00 325.00 310.00 1.00 3.00 1.00 NA NA 16.20 36.33 119.50 63.00 1.00 1.00 1.00 10.40 3.40 9.00 0.10 4.00 28.00 5.00 1.00 3.00 7.40 0.80 7.60 1.04 5.50 68.00 5.00 3.00 4.00 2.10 0.80 46.00 521.00 655.00 336.00 5.00 5.00 5.00 NA NA 22.40 100.00 157.00 100.00 1.00 1.00 1.00 NA NA 16.30 35.00 56.00 33.00 3.00 5.00 4.00 7.70 1.40 2.60 0.01 0.14 21.50 5.00 2.00 4.00 17.90 2.00 24.00 0.01 0.25 50.00 1.00 1.00 1.00 6.10 1.90 100.00 62.00 1320.00 267.00 1.00 1.00 1.00 8.20 2.40 NA 0.12 3.00 30.00 2.00 1.00 1.00 8.40 2.80 NA 1.35 8.10 45.00 3.00 1.00 3.00 11.90 1.30 3.20 0.02 0.40 19.00 4.00 1.00 3.00 10.80 2.00 2.00 0.05 0.33 30.00 4.00 1.00 3.00 13.80 5.60 5.00 1.70 6.30 12.00 2.00 1.00 1.00 14.30 3.10 6.50 3.50 10.80 120.00 2.00 1.00 1.00 NA 1.00 23.60 250.00 490.00 440.00 5.00 5.00 5.00 15.20 1.80 12.00 0.48 15.50 140.00 2.00 2.00 2.00 10.00 0.90 20.20 10.00 115.00 170.00 4.00 4.00 4.00 11.90 1.80 13.00 1.62 11.40 17.00 2.00 1.00 2.00 6.50 1.90 27.00 192.00 180.00 115.00 4.00 4.00 4.00 7.50 0.90 18.00 2.50 12.10 31.00 5.00 5.00 5.00 NA NA 13.70 4.29 39.20 63.00 2.00 2.00 2.00 10.60 2.60 4.70 0.28 1.90 21.00 3.00 1.00 3.00 7.40 2.40 9.80 4.24 50.40 52.00 1.00 1.00 1.00 8.40 1.20 29.00 6.80 179.00 164.00 2.00 3.00 2.00 5.70 0.90 7.00 0.75 12.30 225.00 2.00 2.00 2.00 4.90 0.50 6.00 3.60 21.00 225.00 3.00 2.00 3.00 NA NA 17.00 14.83 98.20 150.00 5.00 5.00 5.00 3.20 0.60 20.00 55.50 175.00 151.00 5.00 5.00 5.00 NA NA 12.70 1.40 12.50 90.00 2.00 2.00 2.00 8.10 2.20 3.50 0.06 1.00 NA 3.00 1.00 2.00 11.00 2.30 4.50 0.90 2.60 60.00 2.00 1.00 2.00 4.90 0.50 7.50 2.00 12.30 200.00 3.00 1.00 3.00 13.20 2.60 2.30 0.10 2.50 46.00 3.00 2.00 2.00 9.70 0.60 24.00 4.19 58.00 210.00 4.00 3.00 4.00 12.80 6.60 3.00 3.50 3.90 14.00 2.00 1.00 1.00 NA NA 13.00 4.05 17.00 38.00 3.00 1.00 1.00
Names of X columns:
SWS PS L Wb Wbr Tg P S D
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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