R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-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(1 + ,26 + ,21 + ,21 + ,23 + ,17 + ,23 + ,4 + ,1 + ,20 + ,16 + ,15 + ,24 + ,17 + ,20 + ,4 + ,1 + ,19 + ,19 + ,18 + ,22 + ,18 + ,20 + ,6 + ,2 + ,19 + ,18 + ,11 + ,20 + ,21 + ,21 + ,8 + ,1 + ,20 + ,16 + ,8 + ,24 + ,20 + ,24 + ,8 + ,1 + ,25 + ,23 + ,19 + ,27 + ,28 + ,22 + ,4 + ,2 + ,25 + ,17 + ,4 + ,28 + ,19 + ,23 + ,4 + ,1 + ,22 + ,12 + ,20 + ,27 + ,22 + ,20 + ,8 + ,1 + ,26 + ,19 + ,16 + ,24 + ,16 + ,25 + ,5 + ,1 + ,22 + ,16 + ,14 + ,23 + ,18 + ,23 + ,4 + ,2 + ,17 + ,19 + ,10 + ,24 + ,25 + ,27 + ,4 + ,2 + ,22 + ,20 + ,13 + ,27 + ,17 + ,27 + ,4 + ,1 + ,19 + ,13 + ,14 + ,27 + ,14 + ,22 + ,4 + ,1 + ,24 + ,20 + ,8 + ,28 + ,11 + ,24 + ,4 + ,1 + ,26 + ,27 + ,23 + ,27 + ,27 + ,25 + ,4 + ,2 + ,21 + ,17 + ,11 + ,23 + ,20 + ,22 + ,8 + ,1 + ,13 + ,8 + ,9 + ,24 + ,22 + ,28 + ,4 + ,2 + ,26 + ,25 + ,24 + ,28 + ,22 + ,28 + ,4 + ,2 + ,20 + ,26 + ,5 + ,27 + ,21 + ,27 + ,4 + ,1 + ,22 + ,13 + ,15 + ,25 + ,23 + ,25 + ,8 + ,2 + ,14 + ,19 + ,5 + ,19 + ,17 + ,16 + ,4 + ,1 + ,21 + ,15 + ,19 + ,24 + ,24 + ,28 + ,7 + ,1 + ,7 + ,5 + ,6 + ,20 + ,14 + ,21 + ,4 + ,2 + ,23 + ,16 + ,13 + ,28 + ,17 + ,24 + ,4 + ,1 + ,17 + ,14 + ,11 + ,26 + ,23 + ,27 + ,5 + ,1 + ,25 + ,24 + ,17 + ,23 + ,24 + ,14 + ,4 + ,1 + ,25 + ,24 + ,17 + ,23 + ,24 + ,14 + ,4 + ,1 + ,19 + ,9 + ,5 + ,20 + ,8 + ,27 + ,4 + ,2 + ,20 + ,19 + ,9 + ,11 + ,22 + ,20 + ,4 + ,1 + ,23 + ,19 + ,15 + ,24 + ,23 + ,21 + ,4 + ,2 + ,22 + ,25 + ,17 + ,25 + ,25 + ,22 + ,4 + ,1 + ,22 + ,19 + ,17 + ,23 + ,21 + ,21 + ,4 + ,1 + ,21 + ,18 + ,20 + ,18 + ,24 + ,12 + ,15 + ,2 + ,15 + ,15 + ,12 + ,20 + ,15 + ,20 + ,10 + ,2 + ,20 + ,12 + ,7 + ,20 + ,22 + ,24 + ,4 + ,2 + ,22 + ,21 + ,16 + ,24 + ,21 + ,19 + ,8 + ,1 + ,18 + ,12 + ,7 + ,23 + ,25 + ,28 + ,4 + ,2 + ,20 + ,15 + ,14 + ,25 + ,16 + ,23 + ,4 + ,2 + ,28 + ,28 + ,24 + ,28 + ,28 + ,27 + ,4 + ,1 + ,22 + ,25 + ,15 + ,26 + ,23 + ,22 + ,4 + ,1 + ,18 + ,19 + ,15 + ,26 + ,21 + ,27 + ,7 + ,1 + ,23 + ,20 + ,10 + ,23 + ,21 + ,26 + ,4 + ,1 + ,20 + ,24 + ,14 + ,22 + ,26 + ,22 + ,6 + ,2 + ,25 + ,26 + ,18 + ,24 + ,22 + ,21 + ,5 + ,2 + ,26 + ,25 + ,12 + ,21 + ,21 + ,19 + ,4 + ,1 + ,15 + ,12 + ,9 + ,20 + ,18 + ,24 + ,16 + ,2 + ,17 + ,12 + ,9 + ,22 + ,12 + ,19 + ,5 + ,2 + ,23 + ,15 + ,8 + ,20 + ,25 + ,26 + ,12 + ,1 + ,21 + ,17 + ,18 + ,25 + ,17 + ,22 + ,6 + ,2 + ,13 + ,14 + ,10 + ,20 + ,24 + ,28 + ,9 + ,1 + ,18 + ,16 + ,17 + ,22 + ,15 + ,21 + ,9 + ,1 + ,19 + ,11 + ,14 + ,23 + ,13 + ,23 + ,4 + ,1 + ,22 + ,20 + ,16 + ,25 + ,26 + ,28 + ,5 + ,1 + ,16 + ,11 + ,10 + ,23 + ,16 + ,10 + ,4 + ,2 + ,24 + ,22 + ,19 + ,23 + ,24 + ,24 + ,4 + ,1 + ,18 + ,20 + ,10 + ,22 + ,21 + ,21 + ,5 + ,1 + ,20 + ,19 + ,14 + ,24 + ,20 + ,21 + ,4 + ,1 + ,24 + ,17 + ,10 + ,25 + ,14 + ,24 + ,4 + ,2 + ,14 + ,21 + ,4 + ,21 + ,25 + ,24 + ,4 + ,2 + ,22 + ,23 + ,19 + ,12 + ,25 + ,25 + ,5 + ,1 + ,24 + ,18 + ,9 + ,17 + ,20 + ,25 + ,4 + ,1 + ,18 + ,17 + ,12 + ,20 + ,22 + ,23 + ,6 + ,1 + ,21 + ,27 + ,16 + ,23 + ,20 + ,21 + ,4 + ,2 + ,23 + ,25 + ,11 + ,23 + ,26 + ,16 + ,4 + ,1 + ,17 + ,19 + ,18 + ,20 + ,18 + ,17 + ,18 + ,2 + ,22 + ,22 + ,11 + ,28 + ,22 + ,25 + ,4 + ,2 + ,24 + ,24 + ,24 + ,24 + ,24 + ,24 + ,6 + ,2 + ,21 + ,20 + ,17 + ,24 + ,17 + ,23 + ,4 + ,1 + ,22 + ,19 + ,18 + ,24 + ,24 + ,25 + ,4 + ,1 + ,16 + ,11 + ,9 + ,24 + ,20 + ,23 + ,5 + ,1 + ,21 + ,22 + ,19 + ,28 + ,19 + ,28 + ,4 + ,2 + ,23 + ,22 + ,18 + ,25 + ,20 + ,26 + ,4 + ,2 + ,22 + ,16 + ,12 + ,21 + ,15 + ,22 + ,5 + ,1 + ,24 + ,20 + ,23 + ,25 + ,23 + ,19 + ,10 + ,1 + ,24 + ,24 + ,22 + ,25 + ,26 + ,26 + ,5 + ,1 + ,16 + ,16 + ,14 + ,18 + ,22 + ,18 + ,8 + ,1 + ,16 + ,16 + ,14 + ,17 + ,20 + ,18 + ,8 + ,2 + ,21 + ,22 + ,16 + ,26 + ,24 + ,25 + ,5 + ,2 + ,26 + ,24 + ,23 + ,28 + ,26 + ,27 + ,4 + ,2 + ,15 + ,16 + ,7 + ,21 + ,21 + ,12 + ,4 + ,2 + ,25 + ,27 + ,10 + ,27 + ,25 + ,15 + ,4 + ,1 + ,18 + ,11 + ,12 + ,22 + ,13 + ,21 + ,5 + ,0 + ,23 + ,21 + ,12 + ,21 + ,20 + ,23 + ,4 + ,1 + ,20 + ,20 + ,12 + ,25 + ,22 + ,22 + ,4 + ,2 + ,17 + ,20 + ,17 + ,22 + ,23 + ,21 + ,8 + ,2 + ,25 + ,27 + ,21 + ,23 + ,28 + ,24 + ,4 + ,1 + ,24 + ,20 + ,16 + ,26 + ,22 + ,27 + ,5 + ,1 + ,17 + ,12 + ,11 + ,19 + ,20 + ,22 + ,14 + ,1 + ,19 + ,8 + ,14 + ,25 + ,6 + ,28 + ,8 + ,1 + ,20 + ,21 + ,13 + ,21 + ,21 + ,26 + ,8 + ,1 + ,15 + ,18 + ,9 + ,13 + ,20 + ,10 + ,4 + ,2 + ,27 + ,24 + ,19 + ,24 + ,18 + ,19 + ,4 + ,1 + ,22 + ,16 + ,13 + ,25 + ,23 + ,22 + ,6 + ,1 + ,23 + ,18 + ,19 + ,26 + ,20 + ,21 + ,4 + ,1 + ,16 + ,20 + ,13 + ,25 + ,24 + ,24 + ,7 + ,1 + ,19 + ,20 + ,13 + ,25 + ,22 + ,25 + ,7 + ,2 + ,25 + ,19 + ,13 + ,22 + ,21 + ,21 + ,4 + ,1 + ,19 + ,17 + ,14 + ,21 + ,18 + ,20 + ,6 + ,2 + ,19 + ,16 + ,12 + ,23 + ,21 + ,21 + ,4 + ,2 + ,26 + ,26 + ,22 + ,25 + ,23 + ,24 + ,7 + ,1 + ,21 + ,15 + ,11 + ,24 + ,23 + ,23 + ,4 + ,2 + ,20 + ,22 + ,5 + ,21 + ,15 + ,18 + ,4 + ,1 + ,24 + ,17 + ,18 + ,21 + ,21 + ,24 + ,8 + ,1 + ,22 + ,23 + ,19 + ,25 + ,24 + ,24 + ,4 + ,2 + ,20 + ,21 + ,14 + ,22 + ,23 + ,19 + ,4 + ,1 + ,18 + ,19 + ,15 + ,20 + ,21 + ,20 + ,10 + ,2 + ,18 + ,14 + ,12 + ,20 + ,21 + ,18 + ,8 + ,1 + ,24 + ,17 + ,19 + ,23 + ,20 + ,20 + ,6 + ,1 + ,24 + ,12 + ,15 + ,28 + ,11 + ,27 + ,4 + ,1 + ,22 + ,24 + ,17 + ,23 + ,22 + ,23 + ,4 + ,1 + ,23 + ,18 + ,8 + ,28 + ,27 + ,26 + ,4 + ,1 + ,22 + ,20 + ,10 + ,24 + ,25 + ,23 + ,5 + ,1 + ,20 + ,16 + ,12 + ,18 + ,18 + ,17 + ,4 + ,1 + ,18 + ,20 + ,12 + ,20 + ,20 + ,21 + ,6 + ,1 + ,25 + ,22 + ,20 + ,28 + ,24 + ,25 + ,4 + ,2 + ,18 + ,12 + ,12 + ,21 + ,10 + ,23 + ,5 + ,1 + ,16 + ,16 + ,12 + ,21 + ,27 + ,27 + ,7 + ,1 + ,20 + ,17 + ,14 + ,25 + ,21 + ,24 + ,8 + ,2 + ,19 + ,22 + ,6 + ,19 + ,21 + ,20 + ,5 + ,1 + ,15 + ,12 + ,10 + ,18 + ,18 + ,27 + ,8 + ,1 + ,19 + ,14 + ,18 + ,21 + ,15 + ,21 + ,10 + ,1 + ,19 + ,23 + ,18 + ,22 + ,24 + ,24 + ,8 + ,1 + ,16 + ,15 + ,7 + ,24 + ,22 + ,21 + ,5 + ,1 + ,17 + ,17 + ,18 + ,15 + ,14 + ,15 + ,12 + ,1 + ,28 + ,28 + ,9 + ,28 + ,28 + ,25 + ,4 + ,2 + ,23 + ,20 + ,17 + ,26 + ,18 + ,25 + ,5 + ,1 + ,25 + ,23 + ,22 + ,23 + ,26 + ,22 + ,4 + ,1 + ,20 + ,13 + ,11 + ,26 + ,17 + ,24 + ,6 + ,2 + ,17 + ,18 + ,15 + ,20 + ,19 + ,21 + ,4 + ,2 + ,23 + ,23 + ,17 + ,22 + ,22 + ,22 + ,4 + ,1 + ,16 + ,19 + ,15 + ,20 + ,18 + ,23 + ,7 + ,2 + ,23 + ,23 + ,22 + ,23 + ,24 + ,22 + ,7 + ,2 + ,11 + ,12 + ,9 + ,22 + ,15 + ,20 + ,10 + ,2 + ,18 + ,16 + ,13 + ,24 + ,18 + ,23 + ,4 + ,2 + ,24 + ,23 + ,20 + ,23 + ,26 + ,25 + ,5 + ,1 + ,23 + ,13 + ,14 + ,22 + ,11 + ,23 + ,8 + ,1 + ,21 + ,22 + ,14 + ,26 + ,26 + ,22 + ,11 + ,2 + ,16 + ,18 + ,12 + ,23 + ,21 + ,25 + ,7 + ,2 + ,24 + ,23 + ,20 + ,27 + ,23 + ,26 + ,4 + ,1 + ,23 + ,20 + ,20 + ,23 + ,23 + ,22 + ,8 + ,1 + ,18 + ,10 + ,8 + ,21 + ,15 + ,24 + ,6 + ,1 + ,20 + ,17 + ,17 + ,26 + ,22 + ,24 + ,7 + ,1 + ,9 + ,18 + ,9 + ,23 + ,26 + ,25 + ,5 + ,2 + ,24 + ,15 + ,18 + ,21 + ,16 + ,20 + ,4 + ,1 + ,25 + ,23 + ,22 + ,27 + ,20 + ,26 + ,8 + ,1 + ,20 + ,17 + ,10 + ,19 + ,18 + ,21 + ,4 + ,2 + ,21 + ,17 + ,13 + ,23 + ,22 + ,26 + ,8 + ,2 + ,25 + ,22 + ,15 + ,25 + ,16 + ,21 + ,6 + ,2 + ,22 + ,20 + ,18 + ,23 + ,19 + ,22 + ,4 + ,2 + ,21 + ,20 + ,18 + ,22 + ,20 + ,16 + ,9 + ,1 + ,21 + ,19 + ,12 + ,22 + ,19 + ,26 + ,5 + ,1 + ,22 + ,18 + ,12 + ,25 + ,23 + ,28 + ,6 + ,1 + ,27 + ,22 + ,20 + ,25 + ,24 + ,18 + ,4 + ,2 + ,24 + ,20 + ,12 + ,28 + ,25 + ,25 + ,4 + ,2 + ,24 + ,22 + ,16 + ,28 + ,21 + ,23 + ,4 + ,2 + ,21 + ,18 + ,16 + ,20 + ,21 + ,21 + ,5 + ,1 + ,18 + ,16 + ,18 + ,25 + ,23 + ,20 + ,6 + ,1 + ,16 + ,16 + ,16 + ,19 + ,27 + ,25 + ,16 + ,1 + ,22 + ,16 + ,13 + ,25 + ,23 + ,22 + ,6 + ,1 + ,20 + ,16 + ,17 + ,22 + ,18 + ,21 + ,6 + ,2 + ,18 + ,17 + ,13 + ,18 + ,16 + ,16 + ,4 + ,1 + ,20 + ,18 + ,17 + ,20 + ,16 + ,18 + ,4) + ,dim=c(8 + ,162) + ,dimnames=list(c('G' + ,'I1' + ,'I2' + ,'I3' + ,'E1' + ,'E2' + ,'E3' + ,'A') + ,1:162)) > y <- array(NA,dim=c(8,162),dimnames=list(c('G','I1','I2','I3','E1','E2','E3','A'),1:162)) > 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 = '' > par2 = 'none' > par1 = '1' > par4 <- 'no' > par3 <- '' > par2 <- 'none' > par1 <- '1' > #'GNU S' R Code compiled by R2WASP v. 1.2.291 () > #Author: root > #To cite this work: Wessa P., 2012, Recursive Partitioning (Regression Trees) (v1.0.3) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_regression_trees.wasp/ > #Source of accompanying publication: > # > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from 'package:base': as.Date, as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Hmisc library by Frank E Harrell Jr Type library(help='Hmisc'), ?Overview, or ?Hmisc.Overview') to see overall documentation. NOTE:Hmisc no longer redefines [.factor to drop unused levels when subsetting. To get the old behavior of Hmisc type dropUnusedLevels(). Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "G" > x[,par1] [1] 1 1 1 2 1 1 2 1 1 1 2 2 1 1 1 2 1 2 2 1 2 1 1 2 1 1 1 1 2 1 2 1 1 2 2 2 1 [38] 2 2 1 1 1 1 2 2 1 2 2 1 2 1 1 1 1 2 1 1 1 2 2 1 1 1 2 1 2 2 2 1 1 1 2 2 1 [75] 1 1 1 2 2 2 2 1 0 1 2 2 1 1 1 1 1 2 1 1 1 1 2 1 2 2 1 2 1 1 2 1 2 1 1 1 1 [112] 1 1 1 1 2 1 1 2 1 1 1 1 1 1 2 1 1 2 2 1 2 2 2 2 1 1 2 2 1 1 1 1 2 1 1 2 2 [149] 2 2 1 1 1 2 2 2 1 1 1 1 2 1 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 0 1 2 1 98 63 > colnames(x) [1] "G" "I1" "I2" "I3" "E1" "E2" "E3" "A" > colnames(x)[par1] [1] "G" > x[,par1] [1] 1 1 1 2 1 1 2 1 1 1 2 2 1 1 1 2 1 2 2 1 2 1 1 2 1 1 1 1 2 1 2 1 1 2 2 2 1 [38] 2 2 1 1 1 1 2 2 1 2 2 1 2 1 1 1 1 2 1 1 1 2 2 1 1 1 2 1 2 2 2 1 1 1 2 2 1 [75] 1 1 1 2 2 2 2 1 0 1 2 2 1 1 1 1 1 2 1 1 1 1 2 1 2 2 1 2 1 1 2 1 2 1 1 1 1 [112] 1 1 1 1 2 1 1 2 1 1 1 1 1 1 2 1 1 2 2 1 2 2 2 2 1 1 2 2 1 1 1 1 2 1 1 2 2 [149] 2 2 1 1 1 2 2 2 1 1 1 1 2 1 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/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/fisher/rcomp/tmp/13m341354891606.tab") + } + } > m Conditional inference tree with 2 terminal nodes Response: G Inputs: I1, I2, I3, E1, E2, E3, A Number of observations: 162 1) I2 <= 21; criterion = 0.987, statistic = 9.694 2)* weights = 118 1) I2 > 21 3)* weights = 44 > postscript(file="/var/fisher/rcomp/tmp/2b14f1354891606.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/fisher/rcomp/tmp/3hzio1354891606.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 1 1.305085 -0.3050847 2 1 1.305085 -0.3050847 3 1 1.305085 -0.3050847 4 2 1.305085 0.6949153 5 1 1.305085 -0.3050847 6 1 1.590909 -0.5909091 7 2 1.305085 0.6949153 8 1 1.305085 -0.3050847 9 1 1.305085 -0.3050847 10 1 1.305085 -0.3050847 11 2 1.305085 0.6949153 12 2 1.305085 0.6949153 13 1 1.305085 -0.3050847 14 1 1.305085 -0.3050847 15 1 1.590909 -0.5909091 16 2 1.305085 0.6949153 17 1 1.305085 -0.3050847 18 2 1.590909 0.4090909 19 2 1.590909 0.4090909 20 1 1.305085 -0.3050847 21 2 1.305085 0.6949153 22 1 1.305085 -0.3050847 23 1 1.305085 -0.3050847 24 2 1.305085 0.6949153 25 1 1.305085 -0.3050847 26 1 1.590909 -0.5909091 27 1 1.590909 -0.5909091 28 1 1.305085 -0.3050847 29 2 1.305085 0.6949153 30 1 1.305085 -0.3050847 31 2 1.590909 0.4090909 32 1 1.305085 -0.3050847 33 1 1.305085 -0.3050847 34 2 1.305085 0.6949153 35 2 1.305085 0.6949153 36 2 1.305085 0.6949153 37 1 1.305085 -0.3050847 38 2 1.305085 0.6949153 39 2 1.590909 0.4090909 40 1 1.590909 -0.5909091 41 1 1.305085 -0.3050847 42 1 1.305085 -0.3050847 43 1 1.590909 -0.5909091 44 2 1.590909 0.4090909 45 2 1.590909 0.4090909 46 1 1.305085 -0.3050847 47 2 1.305085 0.6949153 48 2 1.305085 0.6949153 49 1 1.305085 -0.3050847 50 2 1.305085 0.6949153 51 1 1.305085 -0.3050847 52 1 1.305085 -0.3050847 53 1 1.305085 -0.3050847 54 1 1.305085 -0.3050847 55 2 1.590909 0.4090909 56 1 1.305085 -0.3050847 57 1 1.305085 -0.3050847 58 1 1.305085 -0.3050847 59 2 1.305085 0.6949153 60 2 1.590909 0.4090909 61 1 1.305085 -0.3050847 62 1 1.305085 -0.3050847 63 1 1.590909 -0.5909091 64 2 1.590909 0.4090909 65 1 1.305085 -0.3050847 66 2 1.590909 0.4090909 67 2 1.590909 0.4090909 68 2 1.305085 0.6949153 69 1 1.305085 -0.3050847 70 1 1.305085 -0.3050847 71 1 1.590909 -0.5909091 72 2 1.590909 0.4090909 73 2 1.305085 0.6949153 74 1 1.305085 -0.3050847 75 1 1.590909 -0.5909091 76 1 1.305085 -0.3050847 77 1 1.305085 -0.3050847 78 2 1.590909 0.4090909 79 2 1.590909 0.4090909 80 2 1.305085 0.6949153 81 2 1.590909 0.4090909 82 1 1.305085 -0.3050847 83 0 1.305085 -1.3050847 84 1 1.305085 -0.3050847 85 2 1.305085 0.6949153 86 2 1.590909 0.4090909 87 1 1.305085 -0.3050847 88 1 1.305085 -0.3050847 89 1 1.305085 -0.3050847 90 1 1.305085 -0.3050847 91 1 1.305085 -0.3050847 92 2 1.590909 0.4090909 93 1 1.305085 -0.3050847 94 1 1.305085 -0.3050847 95 1 1.305085 -0.3050847 96 1 1.305085 -0.3050847 97 2 1.305085 0.6949153 98 1 1.305085 -0.3050847 99 2 1.305085 0.6949153 100 2 1.590909 0.4090909 101 1 1.305085 -0.3050847 102 2 1.590909 0.4090909 103 1 1.305085 -0.3050847 104 1 1.590909 -0.5909091 105 2 1.305085 0.6949153 106 1 1.305085 -0.3050847 107 2 1.305085 0.6949153 108 1 1.305085 -0.3050847 109 1 1.305085 -0.3050847 110 1 1.590909 -0.5909091 111 1 1.305085 -0.3050847 112 1 1.305085 -0.3050847 113 1 1.305085 -0.3050847 114 1 1.305085 -0.3050847 115 1 1.590909 -0.5909091 116 2 1.305085 0.6949153 117 1 1.305085 -0.3050847 118 1 1.305085 -0.3050847 119 2 1.590909 0.4090909 120 1 1.305085 -0.3050847 121 1 1.305085 -0.3050847 122 1 1.590909 -0.5909091 123 1 1.305085 -0.3050847 124 1 1.305085 -0.3050847 125 1 1.590909 -0.5909091 126 2 1.305085 0.6949153 127 1 1.590909 -0.5909091 128 1 1.305085 -0.3050847 129 2 1.305085 0.6949153 130 2 1.590909 0.4090909 131 1 1.305085 -0.3050847 132 2 1.590909 0.4090909 133 2 1.305085 0.6949153 134 2 1.305085 0.6949153 135 2 1.590909 0.4090909 136 1 1.305085 -0.3050847 137 1 1.590909 -0.5909091 138 2 1.305085 0.6949153 139 2 1.590909 0.4090909 140 1 1.305085 -0.3050847 141 1 1.305085 -0.3050847 142 1 1.305085 -0.3050847 143 1 1.305085 -0.3050847 144 2 1.305085 0.6949153 145 1 1.590909 -0.5909091 146 1 1.305085 -0.3050847 147 2 1.305085 0.6949153 148 2 1.590909 0.4090909 149 2 1.305085 0.6949153 150 2 1.305085 0.6949153 151 1 1.305085 -0.3050847 152 1 1.305085 -0.3050847 153 1 1.590909 -0.5909091 154 2 1.305085 0.6949153 155 2 1.590909 0.4090909 156 2 1.305085 0.6949153 157 1 1.305085 -0.3050847 158 1 1.305085 -0.3050847 159 1 1.305085 -0.3050847 160 1 1.305085 -0.3050847 161 2 1.305085 0.6949153 162 1 1.305085 -0.3050847 > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } > postscript(file="/var/fisher/rcomp/tmp/4bj051354891606.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/fisher/rcomp/tmp/5457y1354891606.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/fisher/rcomp/tmp/6pu2j1354891606.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/fisher/rcomp/tmp/7bjfy1354891606.tab") + } > > try(system("convert tmp/2b14f1354891606.ps tmp/2b14f1354891606.png",intern=TRUE)) character(0) > try(system("convert tmp/3hzio1354891606.ps tmp/3hzio1354891606.png",intern=TRUE)) character(0) > try(system("convert tmp/4bj051354891606.ps tmp/4bj051354891606.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.036 0.579 5.598