R version 2.12.0 (2010-10-15) Copyright (C) 2010 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) 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. 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(-25 + ,37 + ,-16 + ,-33 + ,-28 + ,-23 + ,33 + ,-15 + ,-32 + ,-26 + ,-24 + ,36 + ,-16 + ,-32 + ,-27 + ,-24 + ,37 + ,-14 + ,-31 + ,-26 + ,-25 + ,39 + ,-14 + ,-31 + ,-27 + ,-25 + ,39 + ,-14 + ,-32 + ,-27 + ,-24 + ,37 + ,-16 + ,-32 + ,-27 + ,-24 + ,37 + ,-17 + ,-33 + ,-28 + ,-22 + ,36 + ,-15 + ,-31 + ,-26 + ,1 + ,23 + ,-9 + ,-21 + ,-13 + ,-5 + ,21 + ,-9 + ,-17 + ,-13 + ,-10 + ,24 + ,-7 + ,-14 + ,-14 + ,-10 + ,25 + ,-4 + ,-10 + ,-12 + ,-15 + ,29 + ,-9 + ,-13 + ,-16 + ,-13 + ,24 + ,-8 + ,-19 + ,-16 + ,-11 + ,22 + ,-6 + ,-10 + ,-12 + ,-15 + ,28 + ,-5 + ,-13 + ,-15 + ,-15 + ,39 + ,-7 + ,-11 + ,-18 + ,-16 + ,36 + ,-6 + ,-9 + ,-17 + ,-4 + ,32 + ,-1 + ,-1 + ,-10 + ,-5 + ,27 + ,-2 + ,-3 + ,-9 + ,-9 + ,33 + ,-1 + ,-7 + ,-13 + ,-14 + ,36 + ,-3 + ,-6 + ,-15 + ,-11 + ,34 + ,-2 + ,-1 + ,-12 + ,-7 + ,34 + ,-2 + ,-11 + ,-13 + ,-7 + ,31 + ,-1 + ,-3 + ,-10 + ,-9 + ,37 + ,-2 + ,-1 + ,-13 + ,-5 + ,36 + ,-1 + ,-2 + ,-11 + ,-10 + ,35 + ,0 + ,-2 + ,-12 + ,-9 + ,32 + ,1 + 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,-1 + ,3 + ,-13 + ,-4 + ,40 + ,1 + ,6 + ,-9 + ,4 + ,31 + ,0 + ,0 + ,-7 + ,7 + ,27 + ,1 + ,3 + ,-4 + ,3 + ,24 + ,1 + ,4 + ,-4 + ,3 + ,23 + ,3 + ,7 + ,-2 + ,8 + ,17 + ,2 + ,6 + ,0 + ,3 + ,16 + ,0 + ,6 + ,-2 + ,-3 + ,15 + ,0 + ,6 + ,-3 + ,4 + ,8 + ,3 + ,6 + ,1 + ,-5 + ,5 + ,-2 + ,2 + ,-2 + ,-1 + ,6 + ,0 + ,2 + ,-1 + ,5 + ,5 + ,1 + ,2 + ,1 + ,0 + ,12 + ,-1 + ,3 + ,-3 + ,-6 + ,8 + ,-2 + ,-1 + ,-4 + ,-13 + ,17 + ,-1 + ,-4 + ,-9 + ,-15 + ,22 + ,-1 + ,4 + ,-9 + ,-8 + ,24 + ,1 + ,5 + ,-7 + ,-20 + ,36 + ,-2 + ,3 + ,-14) + ,dim=c(5 + ,323) + ,dimnames=list(c('VooruitzichtenEconomischeSituatie' + ,'VooruitzichtenWerkloosheid' + ,'VooruitzichtenFinanciëleSituatieGezinnen' + ,'VooruitzichtenSpaarvermogenGezinnen' + ,'IndicatorConsumentenvertrouwen') + ,1:323)) > y <- array(NA,dim=c(5,323),dimnames=list(c('VooruitzichtenEconomischeSituatie','VooruitzichtenWerkloosheid','VooruitzichtenFinanciëleSituatieGezinnen','VooruitzichtenSpaarvermogenGezinnen','IndicatorConsumentenvertrouwen'),1:323)) > 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 = '1' > par2 = 'none' > par1 = '5' > #'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 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] "IndicatorConsumentenvertrouwen" > x[,par1] [1] -28 -26 -27 -26 -27 -27 -27 -28 -26 -13 -13 -14 -12 -16 -16 -12 -15 -18 [19] -17 -10 -9 -13 -15 -12 -13 -10 -13 -11 -12 -10 -13 -12 -11 -11 -11 -8 [37] -7 -10 -8 -8 -7 -7 -6 -8 -6 -3 1 0 -3 0 0 -1 -1 0 [55] 1 0 2 3 2 4 3 4 3 1 2 4 3 2 -4 -5 -5 -7 [73] -13 -11 -3 -3 -5 -4 -4 -4 -5 -4 -5 -6 -9 -10 -11 -13 -13 -13 [91] -11 -12 -14 -20 -17 -16 -24 -24 -22 -25 -24 -25 -24 -25 -24 -26 -25 -24 [109] -22 -20 -14 -13 -10 -10 -11 -6 -2 -3 -2 -4 -7 -8 -7 -4 -7 -5 [127] -6 -12 -12 -16 -20 -16 -16 -18 -15 -12 -13 -13 -12 -11 -9 -9 -8 -8 [145] -15 -16 -21 -21 -16 -13 -12 -8 -9 -1 -5 -9 -1 3 2 3 5 5 [163] 3 2 1 -4 1 1 6 3 2 2 2 -8 0 -2 3 5 8 8 [181] 9 11 13 12 13 15 13 16 10 14 14 15 13 8 7 3 3 4 [199] 4 0 -4 -14 -18 -8 -1 1 2 0 1 0 -1 -3 -3 -3 -4 -8 [217] -9 -13 -18 -11 -9 -10 -13 -11 -5 -15 -6 -6 -3 -1 -3 -4 -6 0 [235] -4 -2 -2 -6 -7 -6 -6 -3 -2 -5 -11 -11 -11 -10 -14 -8 -9 -5 [253] -1 -2 -5 -4 -6 -2 -2 -2 -2 2 1 -8 -1 1 -1 2 2 1 [271] -1 -2 -2 -1 -8 -4 -6 -3 -3 -7 -9 -11 -13 -11 -9 -17 -22 -25 [289] -20 -24 -24 -22 -19 -18 -17 -11 -11 -12 -10 -15 -15 -15 -13 -8 -13 -9 [307] -7 -4 -4 -2 0 -2 -3 1 -2 -1 1 -3 -4 -9 -9 -7 -14 > 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]) -28 -27 -26 -25 -24 -22 -21 -20 -19 -18 -17 -16 -15 -14 -13 -12 -11 -10 -9 -8 2 4 4 5 8 4 2 4 1 5 4 8 8 6 19 12 18 10 14 15 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 11 13 11 17 15 16 13 11 13 13 11 5 3 1 1 3 1 1 1 1 13 14 15 16 4 2 2 1 > colnames(x) [1] "VooruitzichtenEconomischeSituatie" [2] "VooruitzichtenWerkloosheid" [3] "VooruitzichtenFinanci..leSituatieGezinnen" [4] "VooruitzichtenSpaarvermogenGezinnen" [5] "IndicatorConsumentenvertrouwen" > colnames(x)[par1] [1] "IndicatorConsumentenvertrouwen" > x[,par1] [1] -28 -26 -27 -26 -27 -27 -27 -28 -26 -13 -13 -14 -12 -16 -16 -12 -15 -18 [19] -17 -10 -9 -13 -15 -12 -13 -10 -13 -11 -12 -10 -13 -12 -11 -11 -11 -8 [37] -7 -10 -8 -8 -7 -7 -6 -8 -6 -3 1 0 -3 0 0 -1 -1 0 [55] 1 0 2 3 2 4 3 4 3 1 2 4 3 2 -4 -5 -5 -7 [73] -13 -11 -3 -3 -5 -4 -4 -4 -5 -4 -5 -6 -9 -10 -11 -13 -13 -13 [91] -11 -12 -14 -20 -17 -16 -24 -24 -22 -25 -24 -25 -24 -25 -24 -26 -25 -24 [109] -22 -20 -14 -13 -10 -10 -11 -6 -2 -3 -2 -4 -7 -8 -7 -4 -7 -5 [127] -6 -12 -12 -16 -20 -16 -16 -18 -15 -12 -13 -13 -12 -11 -9 -9 -8 -8 [145] -15 -16 -21 -21 -16 -13 -12 -8 -9 -1 -5 -9 -1 3 2 3 5 5 [163] 3 2 1 -4 1 1 6 3 2 2 2 -8 0 -2 3 5 8 8 [181] 9 11 13 12 13 15 13 16 10 14 14 15 13 8 7 3 3 4 [199] 4 0 -4 -14 -18 -8 -1 1 2 0 1 0 -1 -3 -3 -3 -4 -8 [217] -9 -13 -18 -11 -9 -10 -13 -11 -5 -15 -6 -6 -3 -1 -3 -4 -6 0 [235] -4 -2 -2 -6 -7 -6 -6 -3 -2 -5 -11 -11 -11 -10 -14 -8 -9 -5 [253] -1 -2 -5 -4 -6 -2 -2 -2 -2 2 1 -8 -1 1 -1 2 2 1 [271] -1 -2 -2 -1 -8 -4 -6 -3 -3 -7 -9 -11 -13 -11 -9 -17 -22 -25 [289] -20 -24 -24 -22 -19 -18 -17 -11 -11 -12 -10 -15 -15 -15 -13 -8 -13 -9 [307] -7 -4 -4 -2 0 -2 -3 1 -2 -1 1 -3 -4 -9 -9 -7 -14 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/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/rcomp/tmp/1xc5l1323871568.tab") + } + } > m Conditional inference tree with 25 terminal nodes Response: IndicatorConsumentenvertrouwen Inputs: VooruitzichtenEconomischeSituatie, VooruitzichtenWerkloosheid, VooruitzichtenFinanci..leSituatieGezinnen, VooruitzichtenSpaarvermogenGezinnen Number of observations: 323 1) VooruitzichtenWerkloosheid <= 32; criterion = 1, statistic = 230.02 2) VooruitzichtenFinanci..leSituatieGezinnen <= 2; criterion = 1, statistic = 125.069 3) VooruitzichtenSpaarvermogenGezinnen <= 1; criterion = 1, statistic = 42.863 4) VooruitzichtenFinanci..leSituatieGezinnen <= -4; criterion = 1, statistic = 15.111 5)* weights = 10 4) VooruitzichtenFinanci..leSituatieGezinnen > -4 6) VooruitzichtenWerkloosheid <= 12; criterion = 0.998, statistic = 11.818 7)* weights = 8 6) VooruitzichtenWerkloosheid > 12 8)* weights = 14 3) VooruitzichtenSpaarvermogenGezinnen > 1 9) VooruitzichtenWerkloosheid <= 17; criterion = 1, statistic = 29.6 10) VooruitzichtenSpaarvermogenGezinnen <= 11; criterion = 0.987, statistic = 8.653 11)* weights = 14 10) VooruitzichtenSpaarvermogenGezinnen > 11 12)* weights = 7 9) VooruitzichtenWerkloosheid > 17 13) VooruitzichtenEconomischeSituatie <= -9; criterion = 1, statistic = 17.932 14)* weights = 19 13) VooruitzichtenEconomischeSituatie > -9 15)* weights = 16 2) VooruitzichtenFinanci..leSituatieGezinnen > 2 16) VooruitzichtenWerkloosheid <= 1; criterion = 1, statistic = 82.543 17)* weights = 16 16) VooruitzichtenWerkloosheid > 1 18) VooruitzichtenWerkloosheid <= 14; criterion = 1, statistic = 49.975 19) VooruitzichtenSpaarvermogenGezinnen <= 9; criterion = 1, statistic = 18.512 20) VooruitzichtenEconomischeSituatie <= 2; criterion = 0.997, statistic = 11.231 21)* weights = 12 20) VooruitzichtenEconomischeSituatie > 2 22)* weights = 8 19) VooruitzichtenSpaarvermogenGezinnen > 9 23) VooruitzichtenWerkloosheid <= 7; criterion = 0.989, statistic = 8.986 24)* weights = 9 23) VooruitzichtenWerkloosheid > 7 25)* weights = 16 18) VooruitzichtenWerkloosheid > 14 26) VooruitzichtenEconomischeSituatie <= -5; criterion = 1, statistic = 19.598 27)* weights = 16 26) VooruitzichtenEconomischeSituatie > -5 28) VooruitzichtenEconomischeSituatie <= 1; criterion = 0.995, statistic = 10.591 29)* weights = 16 28) VooruitzichtenEconomischeSituatie > 1 30)* weights = 10 1) VooruitzichtenWerkloosheid > 32 31) VooruitzichtenFinanci..leSituatieGezinnen <= -4; criterion = 1, statistic = 89.78 32) VooruitzichtenSpaarvermogenGezinnen <= 7; criterion = 1, statistic = 17.995 33) VooruitzichtenFinanci..leSituatieGezinnen <= -14; criterion = 0.994, statistic = 10.04 34)* weights = 9 33) VooruitzichtenFinanci..leSituatieGezinnen > -14 35)* weights = 17 32) VooruitzichtenSpaarvermogenGezinnen > 7 36)* weights = 12 31) VooruitzichtenFinanci..leSituatieGezinnen > -4 37) VooruitzichtenFinanci..leSituatieGezinnen <= 3; criterion = 1, statistic = 44.008 38) VooruitzichtenWerkloosheid <= 47; criterion = 1, statistic = 33.418 39) VooruitzichtenEconomischeSituatie <= -19; criterion = 0.999, statistic = 12.899 40)* weights = 19 39) VooruitzichtenEconomischeSituatie > -19 41) VooruitzichtenSpaarvermogenGezinnen <= -1; criterion = 0.999, statistic = 13.598 42)* weights = 9 41) VooruitzichtenSpaarvermogenGezinnen > -1 43)* weights = 21 38) VooruitzichtenWerkloosheid > 47 44) VooruitzichtenEconomischeSituatie <= -4; criterion = 0.999, statistic = 14.434 45)* weights = 17 44) VooruitzichtenEconomischeSituatie > -4 46)* weights = 8 37) VooruitzichtenFinanci..leSituatieGezinnen > 3 47) VooruitzichtenEconomischeSituatie <= -4; criterion = 0.996, statistic = 10.802 48)* weights = 12 47) VooruitzichtenEconomischeSituatie > -4 49)* weights = 8 > postscript(file="/var/www/rcomp/tmp/2gm191323871568.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/rcomp/tmp/31zmf1323871568.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) + } Actuals Forecasts Residuals 1 -28 -26.8888889 -1.11111111 2 -26 -26.8888889 0.88888889 3 -27 -26.8888889 -0.11111111 4 -26 -26.8888889 0.88888889 5 -27 -26.8888889 -0.11111111 6 -27 -26.8888889 -0.11111111 7 -27 -26.8888889 -0.11111111 8 -28 -26.8888889 -1.11111111 9 -26 -26.8888889 0.88888889 10 -13 -13.5000000 0.50000000 11 -13 -13.5000000 0.50000000 12 -14 -13.5000000 -0.50000000 13 -12 -13.5000000 1.50000000 14 -16 -13.5000000 -2.50000000 15 -16 -13.5000000 -2.50000000 16 -12 -13.5000000 1.50000000 17 -15 -13.5000000 -1.50000000 18 -18 -22.7058824 4.70588235 19 -17 -22.7058824 5.70588235 20 -10 -9.1428571 -0.85714286 21 -9 -9.1428571 0.14285714 22 -13 -12.6666667 -0.33333333 23 -15 -12.6666667 -2.33333333 24 -12 -12.6666667 0.66666667 25 -13 -12.6666667 -0.33333333 26 -10 -9.1428571 -0.85714286 27 -13 -12.6666667 -0.33333333 28 -11 -12.6666667 1.66666667 29 -12 -12.6666667 0.66666667 30 -10 -9.1428571 -0.85714286 31 -13 -12.6666667 -0.33333333 32 -12 -12.6666667 0.66666667 33 -11 -10.0476190 -0.95238095 34 -11 -9.1428571 -1.85714286 35 -11 -9.1428571 -1.85714286 36 -8 -9.1428571 1.14285714 37 -7 -9.1428571 2.14285714 38 -10 -9.1428571 -0.85714286 39 -8 -7.8947368 -0.10526316 40 -8 -7.8947368 -0.10526316 41 -7 -7.8947368 0.89473684 42 -7 -9.1428571 2.14285714 43 -6 -4.4375000 -1.56250000 44 -8 -9.1428571 1.14285714 45 -6 -4.4375000 -1.56250000 46 -3 -0.5833333 -2.41666667 47 1 -1.5714286 2.57142857 48 0 -0.5833333 0.58333333 49 -3 -5.3750000 2.37500000 50 0 -0.5833333 0.58333333 51 0 -1.5714286 1.57142857 52 -1 -0.5833333 -0.41666667 53 -1 -1.5714286 0.57142857 54 0 -0.5833333 0.58333333 55 1 2.2500000 -1.25000000 56 0 -0.5833333 0.58333333 57 2 2.2500000 -0.25000000 58 3 2.2500000 0.75000000 59 2 2.2500000 -0.25000000 60 4 4.5555556 -0.55555556 61 3 2.5000000 0.50000000 62 4 2.2500000 1.75000000 63 3 2.2500000 0.75000000 64 1 -0.5833333 1.58333333 65 2 -0.5833333 2.58333333 66 4 4.5555556 -0.55555556 67 3 2.5000000 0.50000000 68 2 2.5000000 -0.50000000 69 -4 -0.5833333 -3.41666667 70 -5 -1.5714286 -3.42857143 71 -5 -7.8947368 2.89473684 72 -7 -7.8947368 0.89473684 73 -13 -7.8947368 -5.10526316 74 -11 -7.8947368 -3.10526316 75 -3 -4.4375000 1.43750000 76 -3 -3.8125000 0.81250000 77 -5 -4.4375000 -0.56250000 78 -4 -4.4375000 0.43750000 79 -4 -3.8125000 -0.18750000 80 -4 -3.8125000 -0.18750000 81 -5 -3.8125000 -1.18750000 82 -4 -4.4375000 0.43750000 83 -5 -3.8125000 -1.18750000 84 -6 -7.2500000 1.25000000 85 -9 -10.0476190 1.04761905 86 -10 -10.0476190 0.04761905 87 -11 -10.0476190 -0.95238095 88 -13 -13.0000000 0.00000000 89 -13 -13.0000000 0.00000000 90 -13 -13.0000000 0.00000000 91 -11 -13.0000000 2.00000000 92 -12 -13.0000000 1.00000000 93 -14 -13.0000000 -1.00000000 94 -20 -19.1176471 -0.88235294 95 -17 -19.1176471 2.11764706 96 -16 -19.1176471 3.11764706 97 -24 -22.7058824 -1.29411765 98 -24 -22.7058824 -1.29411765 99 -22 -19.1176471 -2.88235294 100 -25 -16.1666667 -8.83333333 101 -24 -22.7058824 -1.29411765 102 -25 -22.7058824 -2.29411765 103 -24 -19.1176471 -4.88235294 104 -25 -22.7058824 -2.29411765 105 -24 -22.7058824 -1.29411765 106 -26 -22.7058824 -3.29411765 107 -25 -22.7058824 -2.29411765 108 -24 -22.7058824 -1.29411765 109 -22 -22.7058824 0.70588235 110 -20 -22.7058824 2.70588235 111 -14 -13.0000000 -1.00000000 112 -13 -13.0000000 0.00000000 113 -10 -10.0476190 0.04761905 114 -10 -10.0476190 0.04761905 115 -11 -10.0476190 -0.95238095 116 -6 -4.4375000 -1.56250000 117 -2 -0.3000000 -1.70000000 118 -3 -4.4375000 1.43750000 119 -2 -2.0625000 0.06250000 120 -4 -3.8125000 -0.18750000 121 -7 -4.4375000 -2.56250000 122 -8 -7.8947368 -0.10526316 123 -7 -7.8947368 0.89473684 124 -4 -4.4375000 0.43750000 125 -7 -7.8947368 0.89473684 126 -5 -3.8125000 -1.18750000 127 -6 -4.4375000 -1.56250000 128 -12 -13.0000000 1.00000000 129 -12 -13.0000000 1.00000000 130 -16 -16.1666667 0.16666667 131 -20 -16.1666667 -3.83333333 132 -16 -16.1666667 0.16666667 133 -16 -16.1666667 0.16666667 134 -18 -16.1666667 -1.83333333 135 -15 -16.1666667 1.16666667 136 -12 -13.0000000 1.00000000 137 -13 -13.0000000 0.00000000 138 -13 -16.1666667 3.16666667 139 -12 -16.1666667 4.16666667 140 -11 -16.1666667 5.16666667 141 -9 -10.0476190 1.04761905 142 -9 -7.8947368 -1.10526316 143 -8 -7.8947368 -0.10526316 144 -8 -7.8947368 -0.10526316 145 -15 -13.0000000 -2.00000000 146 -16 -16.1666667 0.16666667 147 -21 -19.1176471 -1.88235294 148 -21 -19.1176471 -1.88235294 149 -16 -16.1666667 0.16666667 150 -13 -13.0000000 0.00000000 151 -12 -13.0000000 1.00000000 152 -8 -10.0476190 2.04761905 153 -9 -10.0476190 1.04761905 154 -1 -4.4375000 3.43750000 155 -5 -7.8947368 2.89473684 156 -9 -7.8947368 -1.10526316 157 -1 -4.4375000 3.43750000 158 3 2.5000000 0.50000000 159 2 2.5000000 -0.50000000 160 3 2.5000000 0.50000000 161 5 2.5000000 2.50000000 162 5 1.7142857 3.28571429 163 3 2.5000000 0.50000000 164 2 1.7142857 0.28571429 165 1 1.7142857 -0.71428571 166 -4 -7.8947368 3.89473684 167 1 1.7142857 -0.71428571 168 1 1.7142857 -0.71428571 169 6 4.5555556 1.44444444 170 3 2.5000000 0.50000000 171 2 2.5000000 -0.50000000 172 2 2.5000000 -0.50000000 173 2 1.7142857 0.28571429 174 -8 -7.8947368 -0.10526316 175 0 1.7142857 -1.71428571 176 -2 -3.8125000 1.81250000 177 3 4.5555556 -1.55555556 178 5 4.5555556 0.44444444 179 8 11.9375000 -3.93750000 180 8 4.5555556 3.44444444 181 9 11.9375000 -2.93750000 182 11 11.9375000 -0.93750000 183 13 11.9375000 1.06250000 184 12 11.9375000 0.06250000 185 13 11.9375000 1.06250000 186 15 11.9375000 3.06250000 187 13 11.9375000 1.06250000 188 16 11.9375000 4.06250000 189 10 11.9375000 -1.93750000 190 14 11.9375000 2.06250000 191 14 11.9375000 2.06250000 192 15 11.9375000 3.06250000 193 13 11.9375000 1.06250000 194 8 11.9375000 -3.93750000 195 7 11.9375000 -4.93750000 196 3 4.5555556 -1.55555556 197 3 2.5000000 0.50000000 198 4 4.5555556 -0.55555556 199 4 4.5555556 -0.55555556 200 0 -3.8125000 3.81250000 201 -4 -3.8125000 -0.18750000 202 -14 -13.0000000 -1.00000000 203 -18 -19.1176471 1.11764706 204 -8 -10.0476190 2.04761905 205 -1 -2.0625000 1.06250000 206 1 -0.3000000 1.30000000 207 2 -0.3000000 2.30000000 208 0 -0.3000000 0.30000000 209 1 -0.3000000 1.30000000 210 0 -0.3000000 0.30000000 211 -1 -2.0625000 1.06250000 212 -3 -3.8125000 0.81250000 213 -3 -2.0625000 -0.93750000 214 -3 -2.0625000 -0.93750000 215 -4 -2.0625000 -1.93750000 216 -8 -7.2500000 -0.75000000 217 -9 -7.2500000 -1.75000000 218 -13 -13.0000000 0.00000000 219 -18 -19.1176471 1.11764706 220 -11 -10.0476190 -0.95238095 221 -9 -7.2500000 -1.75000000 222 -10 -10.0476190 0.04761905 223 -13 -19.1176471 6.11764706 224 -11 -10.0476190 -0.95238095 225 -5 -4.5000000 -0.50000000 226 -15 -19.1176471 4.11764706 227 -6 -4.5000000 -1.50000000 228 -6 -4.5000000 -1.50000000 229 -3 -4.5000000 1.50000000 230 -1 -0.3000000 -0.70000000 231 -3 -4.5000000 1.50000000 232 -4 -4.5000000 0.50000000 233 -6 -4.5000000 -1.50000000 234 0 -0.3000000 0.30000000 235 -4 -2.0625000 -1.93750000 236 -2 -2.0625000 0.06250000 237 -2 -2.0625000 0.06250000 238 -6 -7.2500000 1.25000000 239 -7 -7.2500000 0.25000000 240 -6 -7.2500000 1.25000000 241 -6 -7.2500000 1.25000000 242 -3 -4.5000000 1.50000000 243 -2 -0.3000000 -1.70000000 244 -5 -3.8125000 -1.18750000 245 -11 -10.0476190 -0.95238095 246 -11 -10.0476190 -0.95238095 247 -11 -10.0476190 -0.95238095 248 -10 -10.0476190 0.04761905 249 -14 -13.0000000 -1.00000000 250 -8 -7.2500000 -0.75000000 251 -9 -7.2500000 -1.75000000 252 -5 -7.2500000 2.25000000 253 -1 -2.0625000 1.06250000 254 -2 -2.0625000 0.06250000 255 -5 -3.8125000 -1.18750000 256 -4 -3.8125000 -0.18750000 257 -6 -3.8125000 -2.18750000 258 -2 -2.0625000 0.06250000 259 -2 -2.0625000 0.06250000 260 -2 -3.8125000 1.81250000 261 -2 -2.0625000 0.06250000 262 2 2.5000000 -0.50000000 263 1 -0.5833333 1.58333333 264 -8 -7.2500000 -0.75000000 265 -1 -2.0625000 1.06250000 266 1 2.5000000 -1.50000000 267 -1 -2.0625000 1.06250000 268 2 2.2500000 -0.25000000 269 2 2.5000000 -0.50000000 270 1 2.5000000 -1.50000000 271 -1 -0.5833333 -0.41666667 272 -2 -1.5714286 -0.42857143 273 -2 -0.5833333 -1.41666667 274 -1 -1.5714286 0.57142857 275 -8 -5.3750000 -2.62500000 276 -4 -1.5714286 -2.42857143 277 -6 -5.3750000 -0.62500000 278 -3 -5.3750000 2.37500000 279 -3 -5.3750000 2.37500000 280 -7 -5.3750000 -1.62500000 281 -9 -5.3750000 -3.62500000 282 -11 -13.5000000 2.50000000 283 -13 -13.5000000 0.50000000 284 -11 -9.1428571 -1.85714286 285 -9 -7.8947368 -1.10526316 286 -17 -22.7058824 5.70588235 287 -22 -22.7058824 0.70588235 288 -25 -22.7058824 -2.29411765 289 -20 -19.1176471 -0.88235294 290 -24 -19.1176471 -4.88235294 291 -24 -22.7058824 -1.29411765 292 -22 -19.1176471 -2.88235294 293 -19 -19.1176471 0.11764706 294 -18 -19.1176471 1.11764706 295 -17 -19.1176471 2.11764706 296 -11 -12.7500000 1.75000000 297 -11 -12.7500000 1.75000000 298 -12 -12.7500000 0.75000000 299 -10 -12.7500000 2.75000000 300 -15 -12.7500000 -2.25000000 301 -15 -12.7500000 -2.25000000 302 -15 -12.7500000 -2.25000000 303 -13 -12.7500000 -0.25000000 304 -8 -10.0476190 2.04761905 305 -13 -10.0476190 -2.95238095 306 -9 -10.0476190 1.04761905 307 -7 -9.1428571 2.14285714 308 -4 -4.4375000 0.43750000 309 -4 -4.4375000 0.43750000 310 -2 -0.3000000 -1.70000000 311 0 -1.5714286 1.57142857 312 -2 -1.5714286 -0.42857143 313 -3 -1.5714286 -1.42857143 314 1 2.2500000 -1.25000000 315 -2 -1.5714286 -0.42857143 316 -1 -1.5714286 0.57142857 317 1 -1.5714286 2.57142857 318 -3 -1.5714286 -1.42857143 319 -4 -5.3750000 1.37500000 320 -9 -9.1428571 0.14285714 321 -9 -7.8947368 -1.10526316 322 -7 -4.4375000 -2.56250000 323 -14 -13.0000000 -1.00000000 > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } > postscript(file="/var/www/rcomp/tmp/4bok81323871568.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/rcomp/tmp/5h4ee1323871568.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/rcomp/tmp/6a9741323871568.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/rcomp/tmp/76aoa1323871568.tab") + } > > try(system("convert tmp/2gm191323871568.ps tmp/2gm191323871568.png",intern=TRUE)) character(0) > try(system("convert tmp/31zmf1323871568.ps tmp/31zmf1323871568.png",intern=TRUE)) character(0) > try(system("convert tmp/4bok81323871568.ps tmp/4bok81323871568.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.310 0.170 5.467