R version 2.8.0 (2008-10-20) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(695 + ,0 + ,641 + ,696 + ,729 + ,839 + ,627 + ,608 + ,638 + ,0 + ,695 + ,641 + ,696 + ,729 + ,696 + ,651 + ,762 + ,0 + ,638 + ,695 + ,641 + ,696 + ,825 + ,691 + ,635 + ,0 + ,762 + ,638 + ,695 + ,641 + ,677 + ,627 + ,721 + ,0 + ,635 + ,762 + ,638 + ,695 + ,656 + ,634 + ,854 + ,0 + ,721 + ,635 + ,762 + ,638 + ,785 + ,731 + ,418 + ,0 + ,854 + ,721 + ,635 + ,762 + ,412 + ,475 + ,367 + ,0 + ,418 + ,854 + ,721 + ,635 + ,352 + ,337 + ,824 + ,0 + ,367 + ,418 + ,854 + ,721 + ,839 + ,803 + ,687 + ,0 + ,824 + ,367 + ,418 + ,854 + ,729 + ,722 + ,601 + ,0 + ,687 + ,824 + ,367 + ,418 + ,696 + ,590 + ,676 + ,0 + ,601 + ,687 + ,824 + ,367 + ,641 + ,724 + ,740 + ,0 + ,676 + ,601 + ,687 + ,824 + ,695 + ,627 + ,691 + ,0 + ,740 + ,676 + ,601 + ,687 + ,638 + ,696 + ,683 + ,0 + ,691 + ,740 + ,676 + ,601 + ,762 + ,825 + ,594 + ,0 + ,683 + ,691 + ,740 + ,676 + ,635 + ,677 + ,729 + ,0 + ,594 + ,683 + ,691 + ,740 + ,721 + ,656 + ,731 + ,0 + ,729 + ,594 + ,683 + ,691 + ,854 + ,785 + ,386 + ,0 + ,731 + ,729 + ,594 + ,683 + ,418 + ,412 + ,331 + ,0 + ,386 + ,731 + ,729 + ,594 + ,367 + ,352 + ,706 + ,0 + ,331 + ,386 + ,731 + ,729 + ,824 + ,839 + ,715 + ,0 + ,706 + ,331 + ,386 + ,731 + ,687 + ,729 + ,657 + ,0 + ,715 + ,706 + ,331 + ,386 + ,601 + ,696 + ,653 + ,0 + ,657 + ,715 + ,706 + ,331 + ,676 + ,641 + ,642 + ,0 + ,653 + ,657 + ,715 + ,706 + ,740 + ,695 + ,643 + ,0 + ,642 + ,653 + ,657 + ,715 + ,691 + ,638 + ,718 + ,0 + ,643 + ,642 + ,653 + ,657 + ,683 + ,762 + ,654 + ,0 + ,718 + ,643 + ,642 + ,653 + ,594 + ,635 + ,632 + ,0 + ,654 + ,718 + ,643 + ,642 + ,729 + ,721 + ,731 + ,0 + ,632 + ,654 + ,718 + ,643 + ,731 + ,854 + ,392 + ,1 + ,731 + ,632 + ,654 + ,718 + ,386 + ,418 + ,344 + ,1 + ,392 + ,731 + ,632 + ,654 + ,331 + ,367 + ,792 + ,1 + ,344 + ,392 + ,731 + ,632 + ,706 + ,824 + ,852 + ,1 + ,792 + ,344 + ,392 + ,731 + ,715 + ,687 + ,649 + ,1 + ,852 + ,792 + ,344 + ,392 + ,657 + ,601 + ,629 + ,1 + ,649 + ,852 + ,792 + ,344 + ,653 + ,676 + ,685 + ,1 + ,629 + ,649 + ,852 + ,792 + ,642 + ,740 + ,617 + ,1 + ,685 + ,629 + ,649 + ,852 + ,643 + ,691 + ,715 + ,1 + ,617 + ,685 + ,629 + ,649 + ,718 + ,683 + ,715 + ,1 + ,715 + ,617 + ,685 + ,629 + ,654 + ,594 + ,629 + ,1 + ,715 + ,715 + ,617 + ,685 + ,632 + ,729 + ,916 + ,1 + ,629 + ,715 + ,715 + ,617 + ,731 + ,731 + ,531 + ,1 + ,916 + ,629 + ,715 + ,715 + ,392 + ,386 + ,357 + ,1 + ,531 + ,916 + ,629 + ,715 + ,344 + ,331 + ,917 + ,1 + ,357 + ,531 + ,916 + ,629 + ,792 + ,706 + ,828 + ,1 + ,917 + ,357 + ,531 + ,916 + ,852 + ,715 + ,708 + ,1 + ,828 + ,917 + ,357 + ,531 + ,649 + ,657 + ,858 + ,1 + ,708 + ,828 + ,917 + ,357 + ,629 + ,653 + ,775 + ,1 + ,858 + ,708 + ,828 + ,917 + ,685 + ,642 + ,785 + ,1 + ,775 + ,858 + ,708 + ,828 + ,617 + ,643 + ,1006 + ,1 + ,785 + ,775 + ,858 + ,708 + ,715 + ,718 + ,789 + ,1 + ,1006 + ,785 + ,775 + ,858 + ,715 + ,654 + ,734 + ,1 + ,789 + ,1006 + ,785 + ,775 + ,629 + ,632 + ,906 + ,1 + ,734 + ,789 + ,1006 + ,785 + ,916 + ,731 + ,532 + ,1 + ,906 + ,734 + ,789 + ,1006 + ,531 + ,392 + ,387 + ,1 + ,532 + ,906 + ,734 + ,789 + ,357 + ,344 + ,991 + ,1 + ,387 + ,532 + ,906 + ,734 + ,917 + ,792 + ,841 + ,1 + ,991 + ,387 + ,532 + ,906 + ,828 + ,852 + ,892 + ,1 + ,841 + ,991 + ,387 + ,532 + ,708 + ,649 + ,782 + ,1 + ,892 + ,841 + ,991 + ,387 + ,858 + ,629) + ,dim=c(8 + ,60) + ,dimnames=list(c('faillissement' + ,'crisis' + ,'t-1' + ,'t-2' + ,'t-3' + ,'t-4' + ,'t-12' + ,'t-24 ') + ,1:60)) > y <- array(NA,dim=c(8,60),dimnames=list(c('faillissement','crisis','t-1','t-2','t-3','t-4','t-12','t-24 '),1:60)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par4 = 'no' > par3 = '2' > par2 = 'quantiles' > par1 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "faillissement" > x[,par1] [1] 695 638 762 635 721 854 418 367 824 687 601 676 740 691 683 [16] 594 729 731 386 331 706 715 657 653 642 643 718 654 632 731 [31] 392 344 792 852 649 629 685 617 715 715 629 916 531 357 917 [46] 828 708 858 775 785 1006 789 734 906 532 387 991 841 892 782 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$centers,1:par3),ncol=2) + clm <- clm[sort.list(clm[,1]),] + for (i in 1:par3) { + cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='') + } + cl$cluster <- as.factor(cl$cluster) + print(cl$cluster) + x[,par1] <- cl$cluster + } > if (par2 == 'quantiles') { + x[,par1] <- cut2(x[,par1],g=par3) + } > if (par2 == 'hclust') { + hc <- hclust(dist(x[,par1])^2, 'cen') + print(hc) + memb <- cutree(hc, k = par3) + dum <- c(mean(x[memb==1,par1])) + for (i in 2:par3) { + dum <- c(dum, mean(x[memb==i,par1])) + } + hcm <- matrix(cbind(dum,1:par3),ncol=2) + hcm <- hcm[sort.list(hcm[,1]),] + for (i in 1:par3) { + memb[memb==hcm[i,2]] <- paste('C',i,sep='') + } + memb <- as.factor(memb) + print(memb) + x[,par1] <- memb + } > if (par2=='equal') { + ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep='')) + x[,par1] <- as.factor(ed) + } > table(x[,par1]) [331, 706) [706,1006] 30 30 > colnames(x) [1] "faillissement" "crisis" "t.1" "t.2" [5] "t.3" "t.4" "t.12" "t.24." > colnames(x)[par1] [1] "faillissement" > x[,par1] [1] [331, 706) [331, 706) [706,1006] [331, 706) [706,1006] [706,1006] [7] [331, 706) [331, 706) [706,1006] [331, 706) [331, 706) [331, 706) [13] [706,1006] [331, 706) [331, 706) [331, 706) [706,1006] [706,1006] [19] [331, 706) [331, 706) [706,1006] [706,1006] [331, 706) [331, 706) [25] [331, 706) [331, 706) [706,1006] [331, 706) [331, 706) [706,1006] [31] [331, 706) [331, 706) [706,1006] [706,1006] [331, 706) [331, 706) [37] [331, 706) [331, 706) [706,1006] [706,1006] [331, 706) [706,1006] [43] [331, 706) [331, 706) [706,1006] [706,1006] [706,1006] [706,1006] [49] [706,1006] [706,1006] [706,1006] [706,1006] [706,1006] [706,1006] [55] [331, 706) [331, 706) [706,1006] [706,1006] [706,1006] [706,1006] Levels: [331, 706) [706,1006] > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > if (par2 != 'none') { + m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x) + if (par4=='yes') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + a<-table.element(a,'Prediction (training)',par3+1,TRUE) + a<-table.element(a,'Prediction (testing)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Actual',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + a<-table.row.end(a) + for (i in 1:10) { + ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1)) + m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,]) + if (i==1) { + m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,]) + m.ct.i.actu <- x[ind==1,par1] + m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,]) + m.ct.x.actu <- x[ind==2,par1] + } else { + m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,])) + m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1]) + m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,])) + m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1]) + } + } + print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,])) + numer <- numer + m.ct.i.tab[i,i] + } + print(m.ct.i.cp <- numer / sum(m.ct.i.tab)) + print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,])) + numer <- numer + m.ct.x.tab[i,i] + } + print(m.ct.x.cp <- numer / sum(m.ct.x.tab)) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj]) + a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4)) + for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj]) + a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4)) + a<-table.row.end(a) + } + a<-table.row.start(a) + a<-table.element(a,'Overall',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.i.cp,4)) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.x.cp,4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/1c98y1292956024.tab") + } + } > m Conditional inference tree with 3 terminal nodes Response: as.factor(faillissement) Inputs: crisis, t.1, t.2, t.3, t.4, t.12, t.24. Number of observations: 60 1) t.12 <= 677; criterion = 1, statistic = 20.556 2)* weights = 29 1) t.12 > 677 3) crisis <= 0; criterion = 0.95, statistic = 7.206 4)* weights = 17 3) crisis > 0 5)* weights = 14 > postscript(file="/var/www/html/freestat/rcomp/tmp/2c98y1292956024.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(m) > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/3n1711292956024.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response') > dev.off() null device 1 > if (par2 == 'none') { + forec <- predict(m) + result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec)) + colnames(result) <- c('Actuals','Forecasts','Residuals') + print(result) + } > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } [,1] [,2] [1,] 1 1 [2,] 1 2 [3,] 2 2 [4,] 1 1 [5,] 2 1 [6,] 2 2 [7,] 1 1 [8,] 1 1 [9,] 2 2 [10,] 1 2 [11,] 1 2 [12,] 1 1 [13,] 2 2 [14,] 1 1 [15,] 1 2 [16,] 1 1 [17,] 2 2 [18,] 2 2 [19,] 1 1 [20,] 1 1 [21,] 2 2 [22,] 2 2 [23,] 1 1 [24,] 1 1 [25,] 1 2 [26,] 1 2 [27,] 2 2 [28,] 1 1 [29,] 1 2 [30,] 2 2 [31,] 1 1 [32,] 1 1 [33,] 2 2 [34,] 2 2 [35,] 1 1 [36,] 1 1 [37,] 1 1 [38,] 1 1 [39,] 2 2 [40,] 2 1 [41,] 1 1 [42,] 2 2 [43,] 1 1 [44,] 1 1 [45,] 2 2 [46,] 2 2 [47,] 2 1 [48,] 2 1 [49,] 2 2 [50,] 2 1 [51,] 2 2 [52,] 2 2 [53,] 2 1 [54,] 2 2 [55,] 1 1 [56,] 1 1 [57,] 2 2 [58,] 2 2 [59,] 2 2 [60,] 2 2 [331, 706) [706,1006] [331, 706) 23 7 [706,1006] 6 24 > postscript(file="/var/www/html/freestat/rcomp/tmp/4ys641292956024.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > if(par2=='none') { + op <- par(mfrow=c(2,2)) + plot(density(result$Actuals),main='Kernel Density Plot of Actuals') + plot(density(result$Residuals),main='Kernel Density Plot of Residuals') + plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals') + plot(density(result$Forecasts),main='Kernel Density Plot of Predictions') + par(op) + } > if(par2!='none') { + plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted') + } > dev.off() null device 1 > if (par2 == 'none') { + detcoef <- cor(result$Forecasts,result$Actuals) + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goodness of Fit',2,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Correlation',1,TRUE) + a<-table.element(a,round(detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'R-squared',1,TRUE) + a<-table.element(a,round(detcoef*detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'RMSE',1,TRUE) + a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/51bna1292956024.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$Actuals)) { + a<-table.row.start(a) + a<-table.element(a,i,header=TRUE) + a<-table.element(a,result$Actuals[i]) + a<-table.element(a,result$Forecasts[i]) + a<-table.element(a,result$Residuals[i]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/6nb4g1292956024.tab") + } > if (par2 != 'none') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + for (i in 1:par3) { + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + } + a<-table.row.end(a) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (j in 1:par3) { + a<-table.element(a,myt[i,j]) + } + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/7xk311292956024.tab") + } > > try(system("convert tmp/2c98y1292956024.ps tmp/2c98y1292956024.png",intern=TRUE)) character(0) > try(system("convert tmp/3n1711292956024.ps tmp/3n1711292956024.png",intern=TRUE)) character(0) > try(system("convert tmp/4ys641292956024.ps tmp/4ys641292956024.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.718 0.671 4.922