R version 2.9.0 (2009-04-17) Copyright (C) 2009 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. 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. 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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 = '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 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] "Group" > x[,par1] [1] 1 1 1 0 1 1 0 1 1 1 0 0 1 0 1 0 0 1 1 0 1 1 0 0 0 0 1 0 0 0 1 1 1 1 0 0 0 [38] 1 1 0 0 0 0 0 0 1 1 1 0 0 1 1 1 1 1 0 0 0 0 1 1 0 1 1 0 0 0 1 0 1 1 0 0 0 [75] 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 1 0 1 0 1 0 1 0 1 1 0 0 0 0 0 1 1 0 1 0 [112] 1 0 1 1 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [149] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 1 [186] 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 [223] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 1 0 0 0 0 0 0 1 [260] 0 1 1 0 0 1 0 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 1 [297] 0 1 0 0 1 0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 [334] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 [371] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 1 0 0 0 [408] 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 > 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 1 311 120 > colnames(x) [1] "Group" "Costs" "Trades" "Dividends" "Wealth." > colnames(x)[par1] [1] "Group" > x[,par1] [1] 1 1 1 0 1 1 0 1 1 1 0 0 1 0 1 0 0 1 1 0 1 1 0 0 0 0 1 0 0 0 1 1 1 1 0 0 0 [38] 1 1 0 0 0 0 0 0 1 1 1 0 0 1 1 1 1 1 0 0 0 0 1 1 0 1 1 0 0 0 1 0 1 1 0 0 0 [75] 0 1 0 0 0 1 0 1 0 0 0 1 0 0 0 0 0 1 0 1 0 1 0 1 0 1 1 0 0 0 0 0 1 1 0 1 0 [112] 1 0 1 1 0 0 0 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [149] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 1 [186] 1 1 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 [223] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 1 0 0 0 0 0 0 1 [260] 0 1 1 0 0 1 0 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 1 [297] 0 1 0 0 1 0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 0 [334] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 [371] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 1 0 0 0 [408] 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/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/rcomp/tmp/1zila1293202536.tab") + } + } > m Conditional inference tree with 2 terminal nodes Response: Group Inputs: Costs, Trades, Dividends, Wealth. Number of observations: 431 1) Wealth. <= 469107; criterion = 1, statistic = 20.438 2)* weights = 388 1) Wealth. > 469107 3)* weights = 43 > postscript(file="/var/www/html/rcomp/tmp/2zila1293202536.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/rcomp/tmp/3zila1293202536.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 0.7209302 0.2790698 2 1 0.7209302 0.2790698 3 1 0.7209302 0.2790698 4 0 0.2293814 -0.2293814 5 1 0.7209302 0.2790698 6 1 0.7209302 0.2790698 7 0 0.7209302 -0.7209302 8 1 0.7209302 0.2790698 9 1 0.7209302 0.2790698 10 1 0.7209302 0.2790698 11 0 0.7209302 -0.7209302 12 0 0.7209302 -0.7209302 13 1 0.7209302 0.2790698 14 0 0.2293814 -0.2293814 15 1 0.7209302 0.2790698 16 0 0.7209302 -0.7209302 17 0 0.7209302 -0.7209302 18 1 0.7209302 0.2790698 19 1 0.7209302 0.2790698 20 0 0.2293814 -0.2293814 21 1 0.7209302 0.2790698 22 1 0.7209302 0.2790698 23 0 0.7209302 -0.7209302 24 0 0.2293814 -0.2293814 25 0 0.2293814 -0.2293814 26 0 0.7209302 -0.7209302 27 1 0.7209302 0.2790698 28 0 0.2293814 -0.2293814 29 0 0.7209302 -0.7209302 30 0 0.2293814 -0.2293814 31 1 0.7209302 0.2790698 32 1 0.7209302 0.2790698 33 1 0.7209302 0.2790698 34 1 0.7209302 0.2790698 35 0 0.7209302 -0.7209302 36 0 0.2293814 -0.2293814 37 0 0.7209302 -0.7209302 38 1 0.7209302 0.2790698 39 1 0.7209302 0.2790698 40 0 0.2293814 -0.2293814 41 0 0.2293814 -0.2293814 42 0 0.2293814 -0.2293814 43 0 0.7209302 -0.7209302 44 0 0.2293814 -0.2293814 45 0 0.2293814 -0.2293814 46 1 0.2293814 0.7706186 47 1 0.7209302 0.2790698 48 1 0.7209302 0.2790698 49 0 0.2293814 -0.2293814 50 0 0.2293814 -0.2293814 51 1 0.7209302 0.2790698 52 1 0.7209302 0.2790698 53 1 0.7209302 0.2790698 54 1 0.7209302 0.2790698 55 1 0.2293814 0.7706186 56 0 0.2293814 -0.2293814 57 0 0.7209302 -0.7209302 58 0 0.2293814 -0.2293814 59 0 0.2293814 -0.2293814 60 1 0.2293814 0.7706186 61 1 0.7209302 0.2790698 62 0 0.2293814 -0.2293814 63 1 0.2293814 0.7706186 64 1 0.2293814 0.7706186 65 0 0.2293814 -0.2293814 66 0 0.2293814 -0.2293814 67 0 0.2293814 -0.2293814 68 1 0.2293814 0.7706186 69 0 0.2293814 -0.2293814 70 1 0.2293814 0.7706186 71 1 0.2293814 0.7706186 72 0 0.2293814 -0.2293814 73 0 0.2293814 -0.2293814 74 0 0.2293814 -0.2293814 75 0 0.2293814 -0.2293814 76 1 0.2293814 0.7706186 77 0 0.2293814 -0.2293814 78 0 0.2293814 -0.2293814 79 0 0.2293814 -0.2293814 80 1 0.2293814 0.7706186 81 0 0.2293814 -0.2293814 82 1 0.2293814 0.7706186 83 0 0.2293814 -0.2293814 84 0 0.2293814 -0.2293814 85 0 0.2293814 -0.2293814 86 1 0.2293814 0.7706186 87 0 0.2293814 -0.2293814 88 0 0.2293814 -0.2293814 89 0 0.2293814 -0.2293814 90 0 0.2293814 -0.2293814 91 0 0.2293814 -0.2293814 92 1 0.2293814 0.7706186 93 0 0.2293814 -0.2293814 94 1 0.2293814 0.7706186 95 0 0.2293814 -0.2293814 96 1 0.2293814 0.7706186 97 0 0.2293814 -0.2293814 98 1 0.2293814 0.7706186 99 0 0.2293814 -0.2293814 100 1 0.2293814 0.7706186 101 1 0.2293814 0.7706186 102 0 0.2293814 -0.2293814 103 0 0.2293814 -0.2293814 104 0 0.2293814 -0.2293814 105 0 0.2293814 -0.2293814 106 0 0.2293814 -0.2293814 107 1 0.2293814 0.7706186 108 1 0.7209302 0.2790698 109 0 0.2293814 -0.2293814 110 1 0.2293814 0.7706186 111 0 0.2293814 -0.2293814 112 1 0.2293814 0.7706186 113 0 0.2293814 -0.2293814 114 1 0.2293814 0.7706186 115 1 0.2293814 0.7706186 116 0 0.2293814 -0.2293814 117 0 0.2293814 -0.2293814 118 0 0.2293814 -0.2293814 119 1 0.2293814 0.7706186 120 0 0.2293814 -0.2293814 121 0 0.2293814 -0.2293814 122 0 0.2293814 -0.2293814 123 0 0.2293814 -0.2293814 124 1 0.7209302 0.2790698 125 1 0.2293814 0.7706186 126 1 0.2293814 0.7706186 127 0 0.2293814 -0.2293814 128 0 0.2293814 -0.2293814 129 0 0.2293814 -0.2293814 130 0 0.2293814 -0.2293814 131 0 0.2293814 -0.2293814 132 0 0.2293814 -0.2293814 133 0 0.2293814 -0.2293814 134 0 0.2293814 -0.2293814 135 0 0.2293814 -0.2293814 136 0 0.2293814 -0.2293814 137 0 0.2293814 -0.2293814 138 0 0.2293814 -0.2293814 139 0 0.2293814 -0.2293814 140 0 0.2293814 -0.2293814 141 0 0.2293814 -0.2293814 142 0 0.2293814 -0.2293814 143 0 0.2293814 -0.2293814 144 0 0.2293814 -0.2293814 145 0 0.2293814 -0.2293814 146 0 0.2293814 -0.2293814 147 0 0.2293814 -0.2293814 148 0 0.2293814 -0.2293814 149 0 0.2293814 -0.2293814 150 0 0.2293814 -0.2293814 151 0 0.2293814 -0.2293814 152 0 0.2293814 -0.2293814 153 0 0.2293814 -0.2293814 154 0 0.2293814 -0.2293814 155 0 0.2293814 -0.2293814 156 0 0.2293814 -0.2293814 157 0 0.2293814 -0.2293814 158 0 0.2293814 -0.2293814 159 0 0.2293814 -0.2293814 160 0 0.2293814 -0.2293814 161 0 0.2293814 -0.2293814 162 0 0.2293814 -0.2293814 163 0 0.2293814 -0.2293814 164 0 0.2293814 -0.2293814 165 0 0.2293814 -0.2293814 166 0 0.2293814 -0.2293814 167 0 0.2293814 -0.2293814 168 0 0.2293814 -0.2293814 169 0 0.2293814 -0.2293814 170 0 0.2293814 -0.2293814 171 0 0.2293814 -0.2293814 172 0 0.2293814 -0.2293814 173 0 0.2293814 -0.2293814 174 0 0.2293814 -0.2293814 175 0 0.2293814 -0.2293814 176 0 0.2293814 -0.2293814 177 0 0.2293814 -0.2293814 178 1 0.2293814 0.7706186 179 0 0.2293814 -0.2293814 180 0 0.2293814 -0.2293814 181 0 0.2293814 -0.2293814 182 1 0.2293814 0.7706186 183 0 0.2293814 -0.2293814 184 1 0.2293814 0.7706186 185 1 0.2293814 0.7706186 186 1 0.2293814 0.7706186 187 1 0.2293814 0.7706186 188 0 0.2293814 -0.2293814 189 0 0.2293814 -0.2293814 190 0 0.2293814 -0.2293814 191 0 0.2293814 -0.2293814 192 0 0.2293814 -0.2293814 193 0 0.2293814 -0.2293814 194 0 0.2293814 -0.2293814 195 0 0.2293814 -0.2293814 196 1 0.2293814 0.7706186 197 1 0.2293814 0.7706186 198 1 0.2293814 0.7706186 199 1 0.2293814 0.7706186 200 1 0.2293814 0.7706186 201 1 0.2293814 0.7706186 202 1 0.2293814 0.7706186 203 1 0.2293814 0.7706186 204 1 0.2293814 0.7706186 205 1 0.2293814 0.7706186 206 1 0.2293814 0.7706186 207 1 0.2293814 0.7706186 208 1 0.2293814 0.7706186 209 1 0.2293814 0.7706186 210 1 0.2293814 0.7706186 211 0 0.2293814 -0.2293814 212 0 0.2293814 -0.2293814 213 0 0.2293814 -0.2293814 214 0 0.2293814 -0.2293814 215 0 0.2293814 -0.2293814 216 0 0.2293814 -0.2293814 217 0 0.2293814 -0.2293814 218 0 0.2293814 -0.2293814 219 0 0.2293814 -0.2293814 220 0 0.2293814 -0.2293814 221 0 0.2293814 -0.2293814 222 0 0.2293814 -0.2293814 223 0 0.2293814 -0.2293814 224 0 0.2293814 -0.2293814 225 0 0.2293814 -0.2293814 226 0 0.2293814 -0.2293814 227 0 0.2293814 -0.2293814 228 0 0.2293814 -0.2293814 229 0 0.2293814 -0.2293814 230 0 0.2293814 -0.2293814 231 0 0.2293814 -0.2293814 232 0 0.2293814 -0.2293814 233 0 0.2293814 -0.2293814 234 0 0.2293814 -0.2293814 235 0 0.2293814 -0.2293814 236 0 0.2293814 -0.2293814 237 0 0.2293814 -0.2293814 238 0 0.2293814 -0.2293814 239 0 0.2293814 -0.2293814 240 0 0.2293814 -0.2293814 241 0 0.2293814 -0.2293814 242 0 0.2293814 -0.2293814 243 0 0.2293814 -0.2293814 244 0 0.2293814 -0.2293814 245 0 0.2293814 -0.2293814 246 1 0.2293814 0.7706186 247 1 0.2293814 0.7706186 248 0 0.2293814 -0.2293814 249 1 0.2293814 0.7706186 250 1 0.2293814 0.7706186 251 0 0.2293814 -0.2293814 252 1 0.2293814 0.7706186 253 0 0.2293814 -0.2293814 254 0 0.2293814 -0.2293814 255 0 0.2293814 -0.2293814 256 0 0.2293814 -0.2293814 257 0 0.2293814 -0.2293814 258 0 0.2293814 -0.2293814 259 1 0.2293814 0.7706186 260 0 0.2293814 -0.2293814 261 1 0.2293814 0.7706186 262 1 0.2293814 0.7706186 263 0 0.2293814 -0.2293814 264 0 0.2293814 -0.2293814 265 1 0.2293814 0.7706186 266 0 0.2293814 -0.2293814 267 1 0.2293814 0.7706186 268 0 0.2293814 -0.2293814 269 1 0.2293814 0.7706186 270 0 0.2293814 -0.2293814 271 1 0.2293814 0.7706186 272 1 0.2293814 0.7706186 273 1 0.2293814 0.7706186 274 0 0.2293814 -0.2293814 275 0 0.2293814 -0.2293814 276 0 0.2293814 -0.2293814 277 0 0.2293814 -0.2293814 278 0 0.2293814 -0.2293814 279 1 0.2293814 0.7706186 280 0 0.2293814 -0.2293814 281 1 0.2293814 0.7706186 282 0 0.2293814 -0.2293814 283 0 0.2293814 -0.2293814 284 0 0.2293814 -0.2293814 285 0 0.2293814 -0.2293814 286 0 0.2293814 -0.2293814 287 1 0.2293814 0.7706186 288 0 0.2293814 -0.2293814 289 1 0.2293814 0.7706186 290 0 0.2293814 -0.2293814 291 1 0.2293814 0.7706186 292 0 0.2293814 -0.2293814 293 0 0.2293814 -0.2293814 294 0 0.2293814 -0.2293814 295 0 0.2293814 -0.2293814 296 1 0.2293814 0.7706186 297 0 0.2293814 -0.2293814 298 1 0.2293814 0.7706186 299 0 0.2293814 -0.2293814 300 0 0.2293814 -0.2293814 301 1 0.2293814 0.7706186 302 0 0.2293814 -0.2293814 303 0 0.2293814 -0.2293814 304 1 0.2293814 0.7706186 305 0 0.2293814 -0.2293814 306 0 0.2293814 -0.2293814 307 1 0.2293814 0.7706186 308 1 0.2293814 0.7706186 309 0 0.2293814 -0.2293814 310 1 0.2293814 0.7706186 311 1 0.2293814 0.7706186 312 0 0.2293814 -0.2293814 313 1 0.2293814 0.7706186 314 1 0.2293814 0.7706186 315 0 0.2293814 -0.2293814 316 0 0.2293814 -0.2293814 317 0 0.2293814 -0.2293814 318 0 0.2293814 -0.2293814 319 0 0.2293814 -0.2293814 320 0 0.2293814 -0.2293814 321 0 0.2293814 -0.2293814 322 0 0.2293814 -0.2293814 323 0 0.2293814 -0.2293814 324 1 0.2293814 0.7706186 325 0 0.2293814 -0.2293814 326 0 0.2293814 -0.2293814 327 1 0.2293814 0.7706186 328 1 0.2293814 0.7706186 329 0 0.2293814 -0.2293814 330 0 0.2293814 -0.2293814 331 0 0.2293814 -0.2293814 332 0 0.2293814 -0.2293814 333 0 0.2293814 -0.2293814 334 0 0.2293814 -0.2293814 335 0 0.2293814 -0.2293814 336 0 0.2293814 -0.2293814 337 0 0.2293814 -0.2293814 338 0 0.2293814 -0.2293814 339 0 0.2293814 -0.2293814 340 0 0.2293814 -0.2293814 341 0 0.2293814 -0.2293814 342 0 0.2293814 -0.2293814 343 0 0.2293814 -0.2293814 344 0 0.2293814 -0.2293814 345 0 0.2293814 -0.2293814 346 0 0.2293814 -0.2293814 347 0 0.2293814 -0.2293814 348 0 0.2293814 -0.2293814 349 0 0.2293814 -0.2293814 350 0 0.2293814 -0.2293814 351 0 0.2293814 -0.2293814 352 0 0.2293814 -0.2293814 353 0 0.2293814 -0.2293814 354 0 0.2293814 -0.2293814 355 0 0.2293814 -0.2293814 356 0 0.2293814 -0.2293814 357 0 0.2293814 -0.2293814 358 0 0.2293814 -0.2293814 359 0 0.2293814 -0.2293814 360 0 0.2293814 -0.2293814 361 0 0.2293814 -0.2293814 362 0 0.2293814 -0.2293814 363 0 0.2293814 -0.2293814 364 1 0.2293814 0.7706186 365 0 0.2293814 -0.2293814 366 0 0.2293814 -0.2293814 367 0 0.2293814 -0.2293814 368 0 0.2293814 -0.2293814 369 0 0.2293814 -0.2293814 370 0 0.2293814 -0.2293814 371 0 0.2293814 -0.2293814 372 0 0.2293814 -0.2293814 373 0 0.2293814 -0.2293814 374 0 0.2293814 -0.2293814 375 0 0.2293814 -0.2293814 376 0 0.2293814 -0.2293814 377 0 0.2293814 -0.2293814 378 0 0.2293814 -0.2293814 379 0 0.2293814 -0.2293814 380 0 0.2293814 -0.2293814 381 0 0.2293814 -0.2293814 382 0 0.2293814 -0.2293814 383 0 0.2293814 -0.2293814 384 0 0.2293814 -0.2293814 385 0 0.2293814 -0.2293814 386 0 0.2293814 -0.2293814 387 0 0.2293814 -0.2293814 388 0 0.2293814 -0.2293814 389 0 0.2293814 -0.2293814 390 0 0.2293814 -0.2293814 391 0 0.2293814 -0.2293814 392 0 0.2293814 -0.2293814 393 0 0.2293814 -0.2293814 394 0 0.2293814 -0.2293814 395 1 0.2293814 0.7706186 396 0 0.2293814 -0.2293814 397 0 0.2293814 -0.2293814 398 1 0.7209302 0.2790698 399 0 0.2293814 -0.2293814 400 1 0.2293814 0.7706186 401 0 0.2293814 -0.2293814 402 0 0.2293814 -0.2293814 403 0 0.2293814 -0.2293814 404 1 0.2293814 0.7706186 405 0 0.2293814 -0.2293814 406 0 0.2293814 -0.2293814 407 0 0.2293814 -0.2293814 408 0 0.2293814 -0.2293814 409 0 0.2293814 -0.2293814 410 0 0.2293814 -0.2293814 411 0 0.2293814 -0.2293814 412 1 0.2293814 0.7706186 413 1 0.2293814 0.7706186 414 1 0.2293814 0.7706186 415 0 0.2293814 -0.2293814 416 0 0.2293814 -0.2293814 417 0 0.2293814 -0.2293814 418 1 0.2293814 0.7706186 419 0 0.2293814 -0.2293814 420 0 0.2293814 -0.2293814 421 0 0.2293814 -0.2293814 422 0 0.2293814 -0.2293814 423 1 0.2293814 0.7706186 424 0 0.2293814 -0.2293814 425 0 0.2293814 -0.2293814 426 1 0.2293814 0.7706186 427 0 0.2293814 -0.2293814 428 0 0.2293814 -0.2293814 429 0 0.2293814 -0.2293814 430 0 0.2293814 -0.2293814 431 0 0.2293814 -0.2293814 > 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/html/rcomp/tmp/4ar3d1293202536.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/rcomp/tmp/5o1i41293202536.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/rcomp/tmp/6hai71293202536.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/rcomp/tmp/7kbgc1293202536.tab") + } > > try(system("convert tmp/2zila1293202536.ps tmp/2zila1293202536.png",intern=TRUE)) character(0) > try(system("convert tmp/3zila1293202536.ps tmp/3zila1293202536.png",intern=TRUE)) character(0) > try(system("convert tmp/4ar3d1293202536.ps tmp/4ar3d1293202536.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 8.028 0.685 20.268