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Data X:
627 216234 1.59 696 213586 1.26 825 209465 1.13 677 204045 1.92 656 200237 2.61 785 203666 2.26 412 241476 2.41 352 260307 2.26 839 243324 2.03 729 244460 2.86 696 233575 2.55 641 237217 2.27 695 235243 2.26 638 230354 2.57 762 227184 3.07 635 221678 2.76 721 217142 2.51 854 219452 2.87 418 256446 3.14 367 265845 3.11 824 248624 3.16 687 241114 2.47 601 229245 2.57 676 231805 2.89 740 219277 2.63 691 219313 2.38 683 212610 1.69 594 214771 1.96 729 211142 2.19 731 211457 1.87 386 240048 1.6 331 240636 1.63 707 230580 1.22 715 208795 1.21 657 197922 1.49 653 194596 1.64 642 194581 1.66 643 185686 1.77 718 178106 1.82 654 172608 1.78 632 167302 1.28 731 168053 1.29 392 202300 1.37 344 202388 1.12 792 182516 1.51 852 173476 2.24 649 166444 2.94 629 171297 3.09 685 169701 3.46 617 164182 3.64 715 161914 4.39 715 159612 4.15 629 151001 5.21 916 158114 5.8 531 186530 5.91 357 187069 5.39 917 174330 5.46 828 169362 4.72 708 166827 3.14 858 178037 2.63 775 186413 2.32 785 189226 1.93 1006 191563 0.62 789 188906 0.6 734 186005 -0.37 906 195309 -1.1 532 223532 -1.68 387 226899 -0.78 991 214126 -1.19 841 206903 -0.97 892 204442 -0.12 782 220375 0.26
Names of X columns:
Faillissementen Werklozen Inflatie
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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1 seconds
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Big Analytics Cloud Computing Center
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