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 + ,29121.29 + ,0.367 + ,0.452 + ,0.38 + ,19176.77204 + ,0 + ,2986.95 + ,0.721 + ,0.898 + ,0.624 + ,12959.5639 + ,5 + ,34586.18 + ,0.652 + ,0.838 + ,0.621 + ,188681.0992 + ,0 + ,13068.16 + ,0.422 + ,0.49 + ,0.557 + ,104331.6133 + ,0 + ,86.75 + ,0.744 + ,0.83 + ,0.723 + ,1118.317379 + ,9 + ,41343.2 + ,0.806 + ,0.882 + ,0.713 + ,446044.1436 + ,4 + ,2966.8 + ,0.76 + ,0.856 + ,0.566 + ,10247.78888 + ,79 + ,21515.75 + ,0.981 + ,0.976 + ,0.837 + ,1379382.222 + ,0 + ,8214.16 + ,0.858 + ,0.96 + ,0.842 + ,417656.1625 + ,20 + ,8303.51 + ,0.671 + ,0.8 + ,0.639 + ,63403.65075 + ,5 + ,310.43 + ,0.671 + ,0.877 + ,0.779 + ,7787.514 + ,1 + ,1180.08 + ,0.747 + ,0.868 + ,0.808 + ,NA + ,0 + ,156118.46 + ,0.415 + ,0.772 + ,0.391 + ,111879.1217 + ,0 + ,285.65 + ,0.747 + ,0.896 + ,0.743 + ,3685 + ,25 + ,9612.63 + ,0.776 + ,0.794 + ,0.702 + ,55132.0804 + ,4 + ,10423.49 + ,0.882 + ,0.947 + ,0.832 + ,513661.1111 + ,0 + ,314.52 + ,0.663 + ,0.884 + ,0.582 + ,1447.5 + ,0 + 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,0.923 + ,0.869 + ,14991300 + ,0 + ,3301.08 + ,0.763 + ,0.899 + ,0.7 + ,46709.79768 + ,8 + ,27865.74 + ,0.711 + ,0.762 + ,0.486 + ,45359.43236 + ,0 + ,221.55 + ,0.554 + ,0.805 + ,0.527 + ,760.0397903 + ,5 + ,27223.23 + ,0.692 + ,0.858 + ,0.669 + ,316482.1908 + ,0 + ,89571.13 + ,0.503 + ,0.87 + ,0.478 + ,123600.1414 + ,0 + ,23495.36 + ,0.31 + ,0.718 + ,0.444 + ,33757.50332 + ,0 + ,13460.31 + ,0.48 + ,0.458 + ,0.362 + ,19206.04493 + ,0 + ,11651.86 + ,0.566 + ,0.495 + ,0.19 + ,9656.199514) + ,dim=c(6 + ,182) + ,dimnames=list(c('TotalPoints' + ,'POP' + ,'Education2011' + ,'LifeExpectancy2011' + ,'GNI/cap2011' + ,'GDP') + ,1:182)) > y <- array(NA,dim=c(6,182),dimnames=list(c('TotalPoints','POP','Education2011','LifeExpectancy2011','GNI/cap2011','GDP'),1:182)) > 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 = '3' > par2 = 'none' > par1 = '1' > par4 <- 'no' > par3 <- '3' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_regression_trees.wasp/ > #Source of accompanying publication: > # > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from 'package:base': as.Date, as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Hmisc library by Frank E Harrell Jr Type library(help='Hmisc'), ?Overview, or ?Hmisc.Overview') to see overall documentation. NOTE:Hmisc no longer redefines [.factor to drop unused levels when subsetting. To get the old behavior of Hmisc type dropUnusedLevels(). Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "TotalPoints" > x[,par1] [1] 1 0 5 0 0 9 4 79 0 20 5 1 0 0 25 4 0 0 [19] 0 0 0 2 34 0 3 0 0 0 0 27 0 0 0 0 267 15 [37] 0 0 0 0 19 37 2 29 21 0 0 7 0 0 4 0 0 0 [55] 3 20 0 4 89 2 0 14 107 0 198 2 5 2 0 0 0 0 [73] 0 1 53 0 8 3 33 0 10 0 69 32 80 0 42 23 0 1 [91] 0 0 6 0 0 0 0 14 0 0 0 3 0 0 0 0 0 14 [109] 0 7 2 1 0 0 0 50 39 0 0 0 13 0 0 0 0 0 [127] 0 0 0 20 2 2 2 88 22 204 0 0 0 0 1 0 9 0 [145] 0 2 5 9 0 20 39 0 0 0 0 0 0 16 14 0 1 0 [163] 5 0 0 0 8 8 15 0 0 5 49 317 0 8 0 5 0 0 [181] 0 0 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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 2 3 4 5 6 7 8 9 10 13 14 15 16 19 20 21 22 23 100 7 10 4 4 7 1 2 4 3 1 1 4 2 1 1 4 1 1 1 25 27 29 32 33 34 37 39 42 49 50 53 69 79 80 88 89 107 198 204 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 267 317 1 1 > colnames(x) [1] "TotalPoints" "POP" "Education2011" [4] "LifeExpectancy2011" "GNI.cap2011" "GDP" > colnames(x)[par1] [1] "TotalPoints" > x[,par1] [1] 1 0 5 0 0 9 4 79 0 20 5 1 0 0 25 4 0 0 [19] 0 0 0 2 34 0 3 0 0 0 0 27 0 0 0 0 267 15 [37] 0 0 0 0 19 37 2 29 21 0 0 7 0 0 4 0 0 0 [55] 3 20 0 4 89 2 0 14 107 0 198 2 5 2 0 0 0 0 [73] 0 1 53 0 8 3 33 0 10 0 69 32 80 0 42 23 0 1 [91] 0 0 6 0 0 0 0 14 0 0 0 3 0 0 0 0 0 14 [109] 0 7 2 1 0 0 0 50 39 0 0 0 13 0 0 0 0 0 [127] 0 0 0 20 2 2 2 88 22 204 0 0 0 0 1 0 9 0 [145] 0 2 5 9 0 20 39 0 0 0 0 0 0 16 14 0 1 0 [163] 5 0 0 0 8 8 15 0 0 5 49 317 0 8 0 5 0 0 [181] 0 0 > 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/13dre1357242226.tab") + } + } > m Conditional inference tree with 7 terminal nodes Response: TotalPoints Inputs: POP, Education2011, LifeExpectancy2011, GNI.cap2011, GDP Number of observations: 182 1) GDP <= 1847977; criterion = 1, statistic = 126.128 2) GDP <= 774983.4; criterion = 1, statistic = 49.252 3) Education2011 <= 0.806; criterion = 1, statistic = 26.538 4) GDP <= 28840.2; criterion = 0.993, statistic = 10.175 5) POP <= 22417.45; criterion = 0.992, statistic = 9.866 6)* weights = 85 5) POP > 22417.45 7)* weights = 7 4) GDP > 28840.2 8)* weights = 46 3) Education2011 > 0.806 9) POP <= 9074.06; criterion = 0.953, statistic = 6.705 10)* weights = 18 9) POP > 9074.06 11)* weights = 9 2) GDP > 774983.4 12)* weights = 8 1) GDP > 1847977 13)* weights = 9 > postscript(file="/var/fisher/rcomp/tmp/29vgd1357242226.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/3alx61357242226.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 5.5714286 -4.57142857 2 0 0.8588235 -0.85882353 3 5 5.0869565 -0.08695652 4 0 5.0869565 -5.08695652 5 0 0.8588235 -0.85882353 6 9 5.0869565 3.91304348 7 4 0.8588235 3.14117647 8 79 38.5000000 40.50000000 9 0 9.3888889 -9.38888889 10 20 5.0869565 14.91304348 11 5 0.8588235 4.14117647 12 1 0.8588235 0.14117647 13 0 5.0869565 -5.08695652 14 0 0.8588235 -0.85882353 15 25 5.0869565 19.91304348 16 4 28.6666667 -24.66666667 17 0 0.8588235 -0.85882353 18 0 0.8588235 -0.85882353 19 0 0.8588235 -0.85882353 20 0 0.8588235 -0.85882353 21 0 0.8588235 -0.85882353 22 2 0.8588235 1.14117647 23 34 151.6666667 -117.66666667 24 0 0.8588235 -0.85882353 25 3 5.0869565 -2.08695652 26 0 0.8588235 -0.85882353 27 0 0.8588235 -0.85882353 28 0 0.8588235 -0.85882353 29 0 0.8588235 -0.85882353 30 27 38.5000000 -11.50000000 31 0 0.8588235 -0.85882353 32 0 0.8588235 -0.85882353 33 0 0.8588235 -0.85882353 34 0 5.0869565 -5.08695652 35 267 151.6666667 115.33333333 36 15 5.0869565 9.91304348 37 0 0.8588235 -0.85882353 38 0 0.8588235 -0.85882353 39 0 5.0869565 -5.08695652 40 0 0.8588235 -0.85882353 41 19 5.0869565 13.91304348 42 37 28.6666667 8.33333333 43 2 0.8588235 1.14117647 44 29 28.6666667 0.33333333 45 21 9.3888889 11.61111111 46 0 0.8588235 -0.85882353 47 0 0.8588235 -0.85882353 48 7 5.0869565 1.91304348 49 0 5.5714286 -5.57142857 50 0 5.0869565 -5.08695652 51 4 5.0869565 -1.08695652 52 0 0.8588235 -0.85882353 53 0 0.8588235 -0.85882353 54 0 0.8588235 -0.85882353 55 3 9.3888889 -6.38888889 56 20 5.0869565 14.91304348 57 0 0.8588235 -0.85882353 58 4 9.3888889 -5.38888889 59 89 151.6666667 -62.66666667 60 2 0.8588235 1.14117647 61 0 0.8588235 -0.85882353 62 14 9.3888889 4.61111111 63 107 151.6666667 -44.66666667 64 0 5.0869565 -5.08695652 65 198 151.6666667 46.33333333 66 2 28.6666667 -26.66666667 67 5 0.8588235 4.14117647 68 2 5.0869565 -3.08695652 69 0 0.8588235 -0.85882353 70 0 0.8588235 -0.85882353 71 0 0.8588235 -0.85882353 72 0 0.8588235 -0.85882353 73 0 0.8588235 -0.85882353 74 1 9.3888889 -8.38888889 75 53 28.6666667 24.33333333 76 0 9.3888889 -9.38888889 77 8 38.5000000 -30.50000000 78 3 38.5000000 -35.50000000 79 33 5.5714286 27.42857143 80 0 5.0869565 -5.08695652 81 10 9.3888889 0.61111111 82 0 9.3888889 -9.38888889 83 69 151.6666667 -82.66666667 84 32 0.8588235 31.14117647 85 80 151.6666667 -71.66666667 86 0 0.8588235 -0.85882353 87 42 28.6666667 13.33333333 88 23 5.0869565 17.91304348 89 0 0.8588235 -0.85882353 90 1 5.0869565 -4.08695652 91 0 0.8588235 -0.85882353 92 0 0.8588235 -0.85882353 93 6 9.3888889 -3.38888889 94 0 5.0869565 -5.08695652 95 0 0.8588235 -0.85882353 96 0 0.8588235 -0.85882353 97 0 5.0869565 -5.08695652 98 14 9.3888889 4.61111111 99 0 5.0869565 -5.08695652 100 0 0.8588235 -0.85882353 101 0 0.8588235 -0.85882353 102 3 5.0869565 -2.08695652 103 0 0.8588235 -0.85882353 104 0 0.8588235 -0.85882353 105 0 0.8588235 -0.85882353 106 0 0.8588235 -0.85882353 107 0 0.8588235 -0.85882353 108 14 38.5000000 -24.50000000 109 0 0.8588235 -0.85882353 110 7 0.8588235 6.14117647 111 2 0.8588235 1.14117647 112 1 5.0869565 -4.08695652 113 0 0.8588235 -0.85882353 114 0 0.8588235 -0.85882353 115 0 5.5714286 -5.57142857 116 50 38.5000000 11.50000000 117 39 9.3888889 29.61111111 118 0 0.8588235 -0.85882353 119 0 0.8588235 -0.85882353 120 0 5.0869565 -5.08695652 121 13 9.3888889 3.61111111 122 0 5.0869565 -5.08695652 123 0 5.0869565 -5.08695652 124 0 9.3888889 -9.38888889 125 0 0.8588235 -0.85882353 126 0 0.8588235 -0.85882353 127 0 0.8588235 -0.85882353 128 0 5.0869565 -5.08695652 129 0 5.0869565 -5.08695652 130 20 28.6666667 -8.66666667 131 2 5.0869565 -3.08695652 132 2 5.0869565 -3.08695652 133 2 0.8588235 1.14117647 134 88 38.5000000 49.50000000 135 22 28.6666667 -6.66666667 136 204 151.6666667 52.33333333 137 0 0.8588235 -0.85882353 138 0 0.8588235 -0.85882353 139 0 0.8588235 -0.85882353 140 0 0.8588235 -0.85882353 141 1 5.0869565 -4.08695652 142 0 0.8588235 -0.85882353 143 9 5.0869565 3.91304348 144 0 0.8588235 -0.85882353 145 0 0.8588235 -0.85882353 146 2 5.0869565 -3.08695652 147 5 9.3888889 -4.38888889 148 9 9.3888889 -0.38888889 149 0 0.8588235 -0.85882353 150 20 5.0869565 14.91304348 151 39 38.5000000 0.50000000 152 0 5.0869565 -5.08695652 153 0 0.8588235 -0.85882353 154 0 0.8588235 -0.85882353 155 0 5.5714286 -5.57142857 156 0 0.8588235 -0.85882353 157 0 0.8588235 -0.85882353 158 16 9.3888889 6.61111111 159 14 9.3888889 4.61111111 160 0 0.8588235 -0.85882353 161 1 0.8588235 0.14117647 162 0 5.5714286 -5.57142857 163 5 5.0869565 -0.08695652 164 0 0.8588235 -0.85882353 165 0 0.8588235 -0.85882353 166 0 0.8588235 -0.85882353 167 8 0.8588235 7.14117647 168 8 5.0869565 2.91304348 169 15 5.0869565 9.91304348 170 0 0.8588235 -0.85882353 171 0 5.0869565 -5.08695652 172 5 5.5714286 -0.57142857 173 49 28.6666667 20.33333333 174 317 151.6666667 165.33333333 175 0 5.0869565 -5.08695652 176 8 5.0869565 2.91304348 177 0 0.8588235 -0.85882353 178 5 5.0869565 -0.08695652 179 0 5.0869565 -5.08695652 180 0 5.0869565 -5.08695652 181 0 0.8588235 -0.85882353 182 0 0.8588235 -0.85882353 > 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/49x0u1357242226.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/5zol21357242226.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/6i93w1357242227.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/7qztk1357242227.tab") + } > > try(system("convert tmp/29vgd1357242226.ps tmp/29vgd1357242226.png",intern=TRUE)) character(0) > try(system("convert tmp/3alx61357242226.ps tmp/3alx61357242226.png",intern=TRUE)) character(0) > try(system("convert tmp/49x0u1357242226.ps tmp/49x0u1357242226.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.412 0.606 6.295