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Type 'q()' to quit R. > x <- array(list(9.1 + ,4.5 + ,1.0 + ,-1.0 + ,1989.3 + ,9.0 + ,4.3 + ,1.0 + ,3.0 + ,2097.8 + ,9.0 + ,4.3 + ,1.3 + ,2.0 + ,2154.9 + ,8.9 + ,4.2 + ,1.1 + ,3.0 + ,2152.2 + ,8.8 + ,4.0 + ,0.8 + ,5.0 + ,2250.3 + ,8.7 + ,3.8 + ,0.7 + ,5.0 + ,2346.9 + ,8.5 + ,4.1 + ,0.7 + ,3.0 + ,2525.6 + ,8.3 + ,4.2 + ,0.9 + ,2.0 + ,2409.4 + ,8.1 + ,4.0 + ,1.3 + ,1.0 + ,2394.4 + ,7.9 + ,4.3 + ,1.4 + ,-4.0 + ,2401.3 + ,7.8 + ,4.7 + ,1.6 + ,1.0 + ,2354.3 + ,7.6 + ,5.0 + ,2.1 + ,1.0 + ,2450.4 + ,7.4 + ,5.1 + ,0.3 + ,6.0 + ,2504.7 + ,7.2 + ,5.4 + ,2.1 + ,3.0 + ,2661.4 + ,7.0 + ,5.4 + ,2.5 + ,2.0 + ,2880.4 + ,7.0 + ,5.4 + ,2.3 + ,2.0 + ,3064.4 + ,6.8 + ,5.5 + ,2.4 + ,2.0 + ,3141.1 + ,6.8 + ,5.8 + ,3.0 + ,-8.0 + ,3327.7 + ,6.7 + ,5.7 + ,1.7 + ,0.0 + ,3565.0 + ,6.8 + ,5.5 + ,3.5 + ,-2.0 + ,3403.1 + ,6.7 + ,5.6 + ,4.0 + ,3.0 + ,3149.9 + ,6.7 + ,5.6 + ,3.7 + ,5.0 + ,3006.8 + ,6.7 + ,5.5 + ,3.7 + ,8.0 + ,3230.7 + ,6.5 + ,5.5 + ,3.0 + ,8.0 + ,3361.1 + ,6.3 + ,5.7 + ,2.7 + ,9.0 + ,3484.7 + ,6.3 + 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,-6.0 + ,1910.4 + ,8.6 + ,3.5 + ,2.7 + ,0.0 + ,1959.7 + ,8.6 + ,3.7 + ,2.7 + ,-4.0 + ,1969.6 + ,8.6 + ,3.7 + ,2.9 + ,-2.0 + ,2061.4 + ,8.6 + ,3.5 + ,3.0 + ,-2.0 + ,2093.5 + ,8.5 + ,3.3 + ,2.2 + ,-6.0 + ,2120.9 + ,8.4 + ,3.2 + ,2.3 + ,-7.0 + ,2174.6 + ,8.4 + ,3.3 + ,2.8 + ,-6.0 + ,2196.7 + ,8.4 + ,3.1 + ,2.8 + ,-6.0 + ,2350.4 + ,8.5 + ,3.2 + ,2.8 + ,-3.0 + ,2440.3 + ,8.5 + ,3.4 + ,2.2 + ,-2.0 + ,2408.6 + ,8.6 + ,3.5 + ,2.6 + ,-5.0 + ,2472.8 + ,8.6 + ,3.3 + ,2.8 + ,-11.0 + ,2407.6 + ,8.4 + ,3.5 + ,2.5 + ,-11.0 + ,2454.6 + ,8.2 + ,3.5 + ,2.4 + ,-11.0 + ,2448.1 + ,8.0 + ,3.8 + ,2.3 + ,-10.0 + ,2497.8 + ,8.0 + ,4.0 + ,1.9 + ,-14.0 + ,2645.6 + ,8.0 + ,4.0 + ,1.7 + ,-8.0 + ,2756.8 + ,8.0 + ,4.1 + ,2.0 + ,-9.0 + ,2849.3 + ,7.9 + ,4.0 + ,2.1 + ,-5.0 + ,2921.4 + ,7.9 + ,3.8 + ,1.7 + ,-1.0 + ,2981.9 + ,7.8 + ,3.7 + ,1.8 + ,-2.0 + ,3080.6 + ,7.8 + ,3.8 + ,1.8 + ,-5.0 + ,3106.2 + ,8.0 + ,3.7 + ,1.8 + ,-4.0 + ,3119.3 + ,7.8 + ,4.0 + ,1.3 + ,-6.0 + ,3061.3 + ,7.4 + ,4.2 + ,1.3 + ,-2.0 + ,3097.3 + ,7.2 + ,4.0 + ,1.3 + ,-2.0 + ,3161.7 + ,7.0 + ,4.1 + ,1.2 + ,-2.0 + ,3257.2 + ,7.0 + ,4.2 + ,1.4 + ,-2.0 + ,3277.0 + ,7.2 + ,4.5 + ,2.2 + ,2.0 + ,3295.3 + ,7.2 + ,4.6 + ,2.9 + ,1.0 + ,3364.0 + ,7.2 + ,4.5 + ,3.1 + ,-8.0 + ,3494.2 + ,7.0 + ,4.5 + ,3.5 + ,-1.0 + ,3667.0 + ,6.9 + ,4.5 + ,3.6 + ,1.0 + ,3813.1 + ,6.8 + ,4.4 + ,4.4 + ,-1.0 + ,3918.0 + ,6.8 + ,4.3 + ,4.1 + ,2.0 + ,3895.5 + ,6.8 + ,4.5 + ,5.1 + ,2.0 + ,3801.1 + ,6.9 + ,4.1 + ,5.8 + ,1.0 + ,3570.1 + ,7.2 + ,4.1 + ,5.9 + ,-1.0 + ,3701.6 + ,7.2 + ,4.3 + ,5.4 + ,-2.0 + ,3862.3 + ,7.2 + ,4.4 + ,5.5 + ,-2.0 + ,3970.1 + ,7.1 + ,4.7 + ,4.8 + ,-1.0 + ,4138.5 + ,7.2 + ,5.0 + ,3.2 + ,-8.0 + ,4199.8 + ,7.3 + ,4.7 + ,2.7 + ,-4.0 + ,4290.9 + ,7.5 + ,4.5 + ,2.1 + ,-6.0 + ,4443.9 + ,7.6 + ,4.5 + ,1.9 + ,-3.0 + ,4502.6 + ,7.7 + ,4.5 + ,0.6 + ,-3.0 + ,4357.0 + ,7.7 + ,5.5 + ,0.7 + ,-7.0 + ,4591.3 + ,7.7 + ,4.5 + ,-0.2 + ,-9.0 + ,4697.0 + ,7.8 + ,4.4 + ,-1.0 + ,-11.0 + ,4621.4 + ,8.0 + ,4.2 + ,-1.7 + ,-13.0 + ,4562.8 + ,8.1 + ,3.9 + ,-0.7 + ,-11.0 + ,4202.5 + ,8.1 + ,3.9 + ,-1.0 + ,-9.0 + ,4296.5 + ,8.0 + ,4.2 + ,-0.9 + ,-17.0 + ,4435.2 + ,8.1 + ,4.0 + ,0.0 + ,-22.0 + ,4105.2 + ,8.2 + ,3.8 + ,0.3 + ,-25.0 + ,4116.7 + ,8.3 + ,3.7 + ,0.8 + ,-20.0 + ,3844.5 + ,8.4 + ,3.7 + ,0.8 + ,-24.0 + ,3721.0 + ,8.4 + ,3.7 + ,1.9 + ,-24.0 + ,3674.4 + ,8.4 + ,3.7 + ,2.1 + ,-22.0 + ,3857.6 + ,8.5 + ,3.7 + ,2.5 + ,-19.0 + ,3801.1 + ,8.5 + ,3.8 + ,2.7 + ,-18.0 + ,3504.4 + ,8.6 + ,3.7 + ,2.4 + ,-17.0 + ,3032.6 + ,8.6 + ,3.5 + ,2.4 + ,-11.0 + ,3047.0 + ,8.5 + ,3.5 + ,2.9 + ,-11.0 + ,2962.3 + ,8.5 + ,3.1 + ,3.1 + ,-12.0 + ,2197.8) + ,dim=c(5 + ,142) + ,dimnames=list(c('Werkloosheid' + ,'rente' + ,'inflatie' + ,'consumer' + ,'Bel20') + ,1:142)) > y <- array(NA,dim=c(5,142),dimnames=list(c('Werkloosheid','rente','inflatie','consumer','Bel20'),1:142)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par4 = 'yes' > par3 = '4' > par2 = 'none' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Werkloosheid" > x[,par1] [1] 9.1 9.0 9.0 8.9 8.8 8.7 8.5 8.3 8.1 7.9 7.8 7.6 7.4 7.2 7.0 7.0 6.8 6.8 [19] 6.7 6.8 6.7 6.7 6.7 6.5 6.3 6.3 6.3 6.5 6.6 6.5 6.3 6.3 6.5 7.0 7.1 7.3 [37] 7.3 7.4 7.4 7.3 7.4 7.5 7.7 7.7 7.7 7.7 7.7 7.8 8.0 8.1 8.1 8.2 8.2 8.2 [55] 8.1 8.1 8.2 8.3 8.3 8.4 8.5 8.5 8.4 8.0 7.9 8.1 8.5 8.8 8.8 8.6 8.3 8.3 [73] 8.3 8.4 8.4 8.5 8.6 8.6 8.6 8.6 8.6 8.5 8.4 8.4 8.4 8.5 8.5 8.6 8.6 8.4 [91] 8.2 8.0 8.0 8.0 8.0 7.9 7.9 7.8 7.8 8.0 7.8 7.4 7.2 7.0 7.0 7.2 7.2 7.2 [109] 7.0 6.9 6.8 6.8 6.8 6.9 7.2 7.2 7.2 7.1 7.2 7.3 7.5 7.6 7.7 7.7 7.7 7.8 [127] 8.0 8.1 8.1 8.0 8.1 8.2 8.3 8.4 8.4 8.4 8.5 8.5 8.6 8.6 8.5 8.5 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 6.3 6.5 6.6 6.7 6.8 6.9 7 7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8 7.9 8 8.1 8.2 8.3 5 4 1 4 6 2 6 2 9 4 5 2 2 8 6 4 9 9 6 7 8.4 8.5 8.6 8.7 8.8 8.9 9 9.1 11 12 10 1 3 1 2 1 > colnames(x) [1] "Werkloosheid" "rente" "inflatie" "consumer" "Bel20" > colnames(x)[par1] [1] "Werkloosheid" > x[,par1] [1] 9.1 9.0 9.0 8.9 8.8 8.7 8.5 8.3 8.1 7.9 7.8 7.6 7.4 7.2 7.0 7.0 6.8 6.8 [19] 6.7 6.8 6.7 6.7 6.7 6.5 6.3 6.3 6.3 6.5 6.6 6.5 6.3 6.3 6.5 7.0 7.1 7.3 [37] 7.3 7.4 7.4 7.3 7.4 7.5 7.7 7.7 7.7 7.7 7.7 7.8 8.0 8.1 8.1 8.2 8.2 8.2 [55] 8.1 8.1 8.2 8.3 8.3 8.4 8.5 8.5 8.4 8.0 7.9 8.1 8.5 8.8 8.8 8.6 8.3 8.3 [73] 8.3 8.4 8.4 8.5 8.6 8.6 8.6 8.6 8.6 8.5 8.4 8.4 8.4 8.5 8.5 8.6 8.6 8.4 [91] 8.2 8.0 8.0 8.0 8.0 7.9 7.9 7.8 7.8 8.0 7.8 7.4 7.2 7.0 7.0 7.2 7.2 7.2 [109] 7.0 6.9 6.8 6.8 6.8 6.9 7.2 7.2 7.2 7.1 7.2 7.3 7.5 7.6 7.7 7.7 7.7 7.8 [127] 8.0 8.1 8.1 8.0 8.1 8.2 8.3 8.4 8.4 8.4 8.5 8.5 8.6 8.6 8.5 8.5 > 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/144bv1293188500.tab") + } + } > m Conditional inference tree with 10 terminal nodes Response: Werkloosheid Inputs: rente, inflatie, consumer, Bel20 Number of observations: 142 1) rente <= 4.4; criterion = 1, statistic = 79.428 2) Bel20 <= 3047; criterion = 1, statistic = 26.277 3) Bel20 <= 2346.9; criterion = 0.999, statistic = 14.665 4) inflatie <= 1.9; criterion = 0.982, statistic = 8.025 5)* weights = 7 4) inflatie > 1.9 6)* weights = 17 3) Bel20 > 2346.9 7) rente <= 3.7; criterion = 0.995, statistic = 10.42 8)* weights = 11 7) rente > 3.7 9) inflatie <= 1.5; criterion = 0.992, statistic = 9.529 10)* weights = 10 9) inflatie > 1.5 11)* weights = 14 2) Bel20 > 3047 12) consumer <= -4; criterion = 1, statistic = 19.692 13)* weights = 16 12) consumer > -4 14)* weights = 11 1) rente > 4.4 15) inflatie <= 1.7; criterion = 1, statistic = 19.838 16)* weights = 19 15) inflatie > 1.7 17) rente <= 5; criterion = 0.998, statistic = 12.175 18)* weights = 16 17) rente > 5 19)* weights = 21 > postscript(file="/var/www/rcomp/tmp/244bv1293188500.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/344bv1293188500.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 9.1 7.731579 1.368421053 2 9.0 8.785714 0.214285714 3 9.0 8.785714 0.214285714 4 8.9 8.785714 0.114285714 5 8.8 8.785714 0.014285714 6 8.7 8.785714 -0.085714286 7 8.5 8.270000 0.230000000 8 8.3 8.270000 0.030000000 9 8.1 8.270000 -0.170000000 10 7.9 8.270000 -0.370000000 11 7.8 7.731579 0.068421053 12 7.6 7.187500 0.412500000 13 7.4 7.731579 -0.331578947 14 7.2 6.709524 0.490476190 15 7.0 6.709524 0.290476190 16 7.0 6.709524 0.290476190 17 6.8 6.709524 0.090476190 18 6.8 6.709524 0.090476190 19 6.7 7.731579 -1.031578947 20 6.8 6.709524 0.090476190 21 6.7 6.709524 -0.009523810 22 6.7 6.709524 -0.009523810 23 6.7 6.709524 -0.009523810 24 6.5 6.709524 -0.209523810 25 6.3 6.709524 -0.409523810 26 6.3 6.709524 -0.409523810 27 6.3 6.709524 -0.409523810 28 6.5 6.709524 -0.209523810 29 6.6 6.709524 -0.109523810 30 6.5 6.709524 -0.209523810 31 6.3 6.709524 -0.409523810 32 6.3 7.187500 -0.887500000 33 6.5 6.709524 -0.209523810 34 7.0 6.709524 0.290476190 35 7.1 6.709524 0.390476190 36 7.3 6.709524 0.590476190 37 7.3 7.187500 0.112500000 38 7.4 7.187500 0.212500000 39 7.4 7.187500 0.212500000 40 7.3 7.731579 -0.431578947 41 7.4 7.731579 -0.331578947 42 7.5 7.731579 -0.231578947 43 7.7 7.731579 -0.031578947 44 7.7 7.731579 -0.031578947 45 7.7 7.731579 -0.031578947 46 7.7 7.731579 -0.031578947 47 7.7 7.731579 -0.031578947 48 7.8 7.731579 0.068421053 49 8.0 7.731579 0.268421053 50 8.1 8.064286 0.035714286 51 8.1 7.731579 0.368421053 52 8.2 7.731579 0.468421053 53 8.2 8.270000 -0.070000000 54 8.2 8.270000 -0.070000000 55 8.1 8.270000 -0.170000000 56 8.1 8.064286 0.035714286 57 8.2 8.064286 0.135714286 58 8.3 8.472727 -0.172727273 59 8.3 8.064286 0.235714286 60 8.4 8.064286 0.335714286 61 8.5 8.270000 0.230000000 62 8.5 8.270000 0.230000000 63 8.4 8.270000 0.130000000 64 8.0 8.064286 -0.064285714 65 7.9 8.064286 -0.164285714 66 8.1 8.064286 0.035714286 67 8.5 8.505882 -0.005882353 68 8.8 8.505882 0.294117647 69 8.8 8.785714 0.014285714 70 8.6 8.505882 0.094117647 71 8.3 8.505882 -0.205882353 72 8.3 8.785714 -0.485714286 73 8.3 8.505882 -0.205882353 74 8.4 8.505882 -0.105882353 75 8.4 8.505882 -0.105882353 76 8.5 8.505882 -0.005882353 77 8.6 8.505882 0.094117647 78 8.6 8.505882 0.094117647 79 8.6 8.505882 0.094117647 80 8.6 8.505882 0.094117647 81 8.6 8.505882 0.094117647 82 8.5 8.505882 -0.005882353 83 8.4 8.505882 -0.105882353 84 8.4 8.505882 -0.105882353 85 8.4 8.472727 -0.072727273 86 8.5 8.472727 0.027272727 87 8.5 8.472727 0.027272727 88 8.6 8.472727 0.127272727 89 8.6 8.472727 0.127272727 90 8.4 8.472727 -0.072727273 91 8.2 8.472727 -0.272727273 92 8.0 8.064286 -0.064285714 93 8.0 8.064286 -0.064285714 94 8.0 8.064286 -0.064285714 95 8.0 8.064286 -0.064285714 96 7.9 8.064286 -0.164285714 97 7.9 8.064286 -0.164285714 98 7.8 7.136364 0.663636364 99 7.8 8.150000 -0.350000000 100 8.0 8.150000 -0.150000000 101 7.8 8.150000 -0.350000000 102 7.4 7.136364 0.263636364 103 7.2 7.136364 0.063636364 104 7.0 7.136364 -0.136363636 105 7.0 7.136364 -0.136363636 106 7.2 7.187500 0.012500000 107 7.2 7.187500 0.012500000 108 7.2 7.187500 0.012500000 109 7.0 7.187500 -0.187500000 110 6.9 7.187500 -0.287500000 111 6.8 7.136364 -0.336363636 112 6.8 7.136364 -0.336363636 113 6.8 7.187500 -0.387500000 114 6.9 7.136364 -0.236363636 115 7.2 7.136364 0.063636364 116 7.2 7.136364 0.063636364 117 7.2 7.136364 0.063636364 118 7.1 7.187500 -0.087500000 119 7.2 7.187500 0.012500000 120 7.3 7.187500 0.112500000 121 7.5 7.187500 0.312500000 122 7.6 7.187500 0.412500000 123 7.7 7.731579 -0.031578947 124 7.7 7.731579 -0.031578947 125 7.7 7.731579 -0.031578947 126 7.8 8.150000 -0.350000000 127 8.0 8.150000 -0.150000000 128 8.1 8.150000 -0.050000000 129 8.1 8.150000 -0.050000000 130 8.0 8.150000 -0.150000000 131 8.1 8.150000 -0.050000000 132 8.2 8.150000 0.050000000 133 8.3 8.150000 0.150000000 134 8.4 8.150000 0.250000000 135 8.4 8.150000 0.250000000 136 8.4 8.150000 0.250000000 137 8.5 8.150000 0.350000000 138 8.5 8.150000 0.350000000 139 8.6 8.472727 0.127272727 140 8.6 8.472727 0.127272727 141 8.5 8.472727 0.027272727 142 8.5 8.505882 -0.005882353 > 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/4fwtg1293188500.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/5b6861293188500.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/6mxpr1293188500.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/77x6f1293188500.tab") + } > > try(system("convert tmp/244bv1293188500.ps tmp/244bv1293188500.png",intern=TRUE)) character(0) > try(system("convert tmp/344bv1293188500.ps tmp/344bv1293188500.png",intern=TRUE)) character(0) > try(system("convert tmp/4fwtg1293188500.ps tmp/4fwtg1293188500.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.030 0.620 3.616