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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,69863 + ,318765 + ,1 + ,6341 + ,24 + ,63255 + ,286146 + ,1 + ,1164 + ,17 + ,57320 + ,306844 + ,1 + ,3310 + ,33 + ,75230 + ,307705 + ,0 + ,1366 + ,7 + ,79420 + ,312448 + ,0 + ,965 + ,3 + ,73490 + ,299715 + ,0 + ,3256 + ,66 + ,35250 + ,373399 + ,1 + ,1135 + ,17 + ,62285 + ,299446 + ,0 + ,1270 + ,26 + ,69206 + ,325586 + ,0 + ,661 + ,3 + ,65920 + ,291221 + ,0 + ,1013 + ,2 + ,69770 + ,261173 + ,0 + ,2844 + ,67 + ,72683 + ,255027 + ,1 + ,11528 + ,70 + ,-14545 + ,-78375 + ,0 + ,6526 + ,26 + ,55830 + ,-58143 + ,0 + ,2264 + ,24 + ,55174 + ,227033 + ,1 + ,4461 + ,94 + ,67038 + ,235098 + ,0 + ,3999 + ,30 + ,51252 + ,21267 + ,0 + ,35624 + ,223 + ,157278 + ,238675 + ,0 + ,9252 + ,48 + ,79510 + ,197687 + ,0 + ,15236 + ,90 + ,77440 + ,418341 + ,0 + ,18073 + ,180 + ,27284 + ,-297706) + ,dim=c(5 + ,431) + ,dimnames=list(c('Group' + ,'Costs' + ,'Trades' + ,'Dividends' + ,'Wealth ') + ,1:431)) > y <- array(NA,dim=c(5,431),dimnames=list(c('Group','Costs','Trades','Dividends','Wealth '),1:431)) > 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 = '2' > par2 = 'quantiles' > par1 = '2' > #'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] "Costs" > x[,par1] [1] 162556 29790 87550 84738 54660 42634 40949 42312 37704 16275 [11] 25830 12679 18014 43556 24524 6532 7123 20813 37597 17821 [21] 12988 22330 13326 16189 7146 15824 26088 11326 8568 14416 [31] 3369 11819 6620 4519 2220 18562 10327 5336 2365 4069 [41] 7710 13718 4525 6869 4628 3653 1265 7489 4901 2284 [51] 3160 4150 7285 1134 4658 2384 3748 5371 1285 9327 [61] 5565 1528 3122 7317 2675 13253 880 2053 1424 4036 [71] 3045 5119 1431 554 1975 1286 1012 810 1280 666 [81] 1380 4608 876 814 514 5692 3642 540 2099 567 [91] 2001 2949 2253 6533 1889 3055 272 1414 2564 1383 [101] 1261 975 3366 576 1306 746 3192 2045 5477 1932 [111] 936 3437 5131 2397 1389 1503 402 2239 2234 837 [121] 10579 875 1395 1659 2647 3294 0 94 422 0 [131] 34 1558 0 43 0 316 115 0 0 0 [141] 389 0 1002 36 460 309 0 9 0 14 [151] 520 1766 0 458 20 0 0 98 405 0 [161] 0 0 0 483 454 0 0 757 0 0 [171] 0 36 0 203 0 90 0 71 0 0 [181] 972 531 604 283 23 638 699 149 226 0 [191] 275 0 141 0 28 0 2566 0 0 472 [201] 0 0 0 203 496 10 63 0 1136 0 [211] 0 0 267 474 534 0 15 397 0 1061 [221] 288 0 3 0 20 278 0 0 192 0 [231] 317 0 0 368 0 2 0 53 0 0 [241] 0 94 0 24 2332 0 0 131 0 0 [251] 206 0 167 622 885 0 365 364 0 0 [261] 0 0 226 307 0 0 0 188 0 138 [271] 0 0 0 125 0 282 335 0 813 176 [281] 0 0 249 0 333 0 0 30 0 249 [291] 0 165 453 0 53 382 0 0 0 0 [301] 30 290 0 0 366 2 0 209 384 0 [311] 0 365 0 49 3 133 32 368 1 0 [321] 0 0 0 0 0 22 0 0 0 0 [331] 0 0 0 96 1 0 81 0 26 125 [341] 304 0 0 0 0 0 119 0 0 0 [351] 312 60 587 135 0 0 514 0 0 0 [361] 1 0 0 58 180 0 0 0 0 0 [371] 0 448 227 174 0 0 121 607 0 0 [381] 0 530 571 0 78 2489 131 923 72 572 [391] 397 450 622 694 3425 562 4917 1442 529 2126 [401] 1061 776 611 1526 592 1182 621 989 438 726 [411] 1303 6341 1164 3310 1366 965 3256 1135 1270 661 [421] 1013 2844 11528 6526 2264 4461 3999 35624 9252 15236 [431] 18073 > 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, 333) [333,162556] 216 215 > colnames(x) [1] "Group" "Costs" "Trades" "Dividends" "Wealth." > colnames(x)[par1] [1] "Costs" > x[,par1] [1] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [6] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [11] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [16] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [21] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [26] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [31] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [36] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [41] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [46] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [51] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [56] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [61] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [66] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [71] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [76] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [81] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [86] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [91] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [96] [333,162556] [ 0, 333) [333,162556] [333,162556] [333,162556] [101] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [106] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [111] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [116] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [121] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [126] [333,162556] [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [131] [ 0, 333) [333,162556] [ 0, 333) [ 0, 333) [ 0, 333) [136] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [141] [333,162556] [ 0, 333) [333,162556] [ 0, 333) [333,162556] [146] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [151] [333,162556] [333,162556] [ 0, 333) [333,162556] [ 0, 333) [156] [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [161] [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [333,162556] [166] [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [ 0, 333) [171] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [176] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [181] [333,162556] [333,162556] [333,162556] [ 0, 333) [ 0, 333) [186] [333,162556] [333,162556] [ 0, 333) [ 0, 333) [ 0, 333) [191] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [196] [ 0, 333) [333,162556] [ 0, 333) [ 0, 333) [333,162556] [201] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [206] [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [211] [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [333,162556] [216] [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [333,162556] [221] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [226] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [231] [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [236] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [241] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [246] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [251] [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [333,162556] [256] [ 0, 333) [333,162556] [333,162556] [ 0, 333) [ 0, 333) [261] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [266] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [271] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [276] [ 0, 333) [333,162556] [ 0, 333) [333,162556] [ 0, 333) [281] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [286] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [291] [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [ 0, 333) [296] [333,162556] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [301] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [306] [ 0, 333) [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [311] [ 0, 333) [333,162556] [ 0, 333) [ 0, 333) [ 0, 333) [316] [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [ 0, 333) [321] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [326] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [331] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [336] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [341] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [346] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [351] [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [ 0, 333) [356] [ 0, 333) [333,162556] [ 0, 333) [ 0, 333) [ 0, 333) [361] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [366] [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [ 0, 333) [371] [ 0, 333) [333,162556] [ 0, 333) [ 0, 333) [ 0, 333) [376] [ 0, 333) [ 0, 333) [333,162556] [ 0, 333) [ 0, 333) [381] [ 0, 333) [333,162556] [333,162556] [ 0, 333) [ 0, 333) [386] [333,162556] [ 0, 333) [333,162556] [ 0, 333) [333,162556] [391] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [396] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [401] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [406] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [411] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [416] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [421] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [426] [333,162556] [333,162556] [333,162556] [333,162556] [333,162556] [431] [333,162556] Levels: [ 0, 333) [333,162556] > 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/1ql121293202450.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 1 1584 365 2 16 1919 [1] 0.8127245 [1] 0.9917313 [1] 0.9019053 m.ct.x.pred m.ct.x.actu 1 2 1 176 35 2 4 211 [1] 0.8341232 [1] 0.9813953 [1] 0.9084507 > m Conditional inference tree with 4 terminal nodes Response: as.factor(Costs) Inputs: Group, Trades, Dividends, Wealth. Number of observations: 431 1) Trades <= 6; criterion = 1, statistic = 65.299 2) Dividends <= 65745; criterion = 1, statistic = 124.747 3)* weights = 175 2) Dividends > 65745 4)* weights = 7 1) Trades > 6 5) Trades <= 15; criterion = 0.995, statistic = 10.412 6)* weights = 67 5) Trades > 15 7)* weights = 182 > postscript(file="/var/www/html/rcomp/tmp/2jd051293202450.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/3jd051293202450.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) + } > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } [,1] [,2] [1,] 2 2 [2,] 2 2 [3,] 2 2 [4,] 2 2 [5,] 2 2 [6,] 2 2 [7,] 2 2 [8,] 2 2 [9,] 2 2 [10,] 2 2 [11,] 2 2 [12,] 2 2 [13,] 2 2 [14,] 2 2 [15,] 2 2 [16,] 2 2 [17,] 2 2 [18,] 2 2 [19,] 2 2 [20,] 2 2 [21,] 2 2 [22,] 2 2 [23,] 2 2 [24,] 2 2 [25,] 2 2 [26,] 2 2 [27,] 2 2 [28,] 2 2 [29,] 2 2 [30,] 2 2 [31,] 2 2 [32,] 2 2 [33,] 2 2 [34,] 2 2 [35,] 2 2 [36,] 2 2 [37,] 2 2 [38,] 2 2 [39,] 2 2 [40,] 2 2 [41,] 2 2 [42,] 2 2 [43,] 2 2 [44,] 2 2 [45,] 2 2 [46,] 2 2 [47,] 2 2 [48,] 2 2 [49,] 2 2 [50,] 2 2 [51,] 2 2 [52,] 2 2 [53,] 2 2 [54,] 2 2 [55,] 2 2 [56,] 2 2 [57,] 2 2 [58,] 2 2 [59,] 2 2 [60,] 2 2 [61,] 2 2 [62,] 2 2 [63,] 2 2 [64,] 2 2 [65,] 2 2 [66,] 2 2 [67,] 2 2 [68,] 2 2 [69,] 2 2 [70,] 2 2 [71,] 2 2 [72,] 2 2 [73,] 2 2 [74,] 2 2 [75,] 2 2 [76,] 2 2 [77,] 2 2 [78,] 2 2 [79,] 2 2 [80,] 2 2 [81,] 2 2 [82,] 2 2 [83,] 2 2 [84,] 2 2 [85,] 2 2 [86,] 2 2 [87,] 2 2 [88,] 2 2 [89,] 2 2 [90,] 2 2 [91,] 2 2 [92,] 2 2 [93,] 2 2 [94,] 2 2 [95,] 2 2 [96,] 2 2 [97,] 1 2 [98,] 2 2 [99,] 2 2 [100,] 2 2 [101,] 2 2 [102,] 2 2 [103,] 2 2 [104,] 2 2 [105,] 2 2 [106,] 2 2 [107,] 2 2 [108,] 2 2 [109,] 2 2 [110,] 2 2 [111,] 2 2 [112,] 2 2 [113,] 2 2 [114,] 2 2 [115,] 2 2 [116,] 2 2 [117,] 2 2 [118,] 2 2 [119,] 2 2 [120,] 2 2 [121,] 2 2 [122,] 2 2 [123,] 2 2 [124,] 2 2 [125,] 2 2 [126,] 2 2 [127,] 1 1 [128,] 1 2 [129,] 2 2 [130,] 1 1 [131,] 1 2 [132,] 2 2 [133,] 1 1 [134,] 1 1 [135,] 1 1 [136,] 1 2 [137,] 1 2 [138,] 1 1 [139,] 1 1 [140,] 1 1 [141,] 2 2 [142,] 1 1 [143,] 2 2 [144,] 1 1 [145,] 2 2 [146,] 1 2 [147,] 1 1 [148,] 1 1 [149,] 1 1 [150,] 1 1 [151,] 2 2 [152,] 2 2 [153,] 1 1 [154,] 2 2 [155,] 1 1 [156,] 1 1 [157,] 1 1 [158,] 1 1 [159,] 2 2 [160,] 1 1 [161,] 1 1 [162,] 1 1 [163,] 1 1 [164,] 2 2 [165,] 2 2 [166,] 1 1 [167,] 1 1 [168,] 2 2 [169,] 1 1 [170,] 1 1 [171,] 1 1 [172,] 1 1 [173,] 1 1 [174,] 1 2 [175,] 1 1 [176,] 1 2 [177,] 1 1 [178,] 1 1 [179,] 1 1 [180,] 1 1 [181,] 2 2 [182,] 2 2 [183,] 2 2 [184,] 1 2 [185,] 1 1 [186,] 2 2 [187,] 2 2 [188,] 1 1 [189,] 1 1 [190,] 1 1 [191,] 1 1 [192,] 1 1 [193,] 1 1 [194,] 1 1 [195,] 1 1 [196,] 1 1 [197,] 2 2 [198,] 1 1 [199,] 1 1 [200,] 2 2 [201,] 1 1 [202,] 1 1 [203,] 1 1 [204,] 1 2 [205,] 2 2 [206,] 1 1 [207,] 1 1 [208,] 1 1 [209,] 2 2 [210,] 1 1 [211,] 1 1 [212,] 1 1 [213,] 1 2 [214,] 2 2 [215,] 2 2 [216,] 1 1 [217,] 1 2 [218,] 2 2 [219,] 1 1 [220,] 2 2 [221,] 1 1 [222,] 1 1 [223,] 1 1 [224,] 1 1 [225,] 1 1 [226,] 1 2 [227,] 1 1 [228,] 1 1 [229,] 1 1 [230,] 1 1 [231,] 1 2 [232,] 1 1 [233,] 1 1 [234,] 2 2 [235,] 1 1 [236,] 1 1 [237,] 1 1 [238,] 1 1 [239,] 1 1 [240,] 1 1 [241,] 1 1 [242,] 1 1 [243,] 1 1 [244,] 1 2 [245,] 2 2 [246,] 1 1 [247,] 1 1 [248,] 1 2 [249,] 1 1 [250,] 1 1 [251,] 1 2 [252,] 1 1 [253,] 1 1 [254,] 2 2 [255,] 2 2 [256,] 1 1 [257,] 2 2 [258,] 2 2 [259,] 1 1 [260,] 1 1 [261,] 1 1 [262,] 1 1 [263,] 1 2 [264,] 1 2 [265,] 1 1 [266,] 1 1 [267,] 1 1 [268,] 1 2 [269,] 1 1 [270,] 1 2 [271,] 1 1 [272,] 1 1 [273,] 1 1 [274,] 1 2 [275,] 1 1 [276,] 1 2 [277,] 2 2 [278,] 1 1 [279,] 2 2 [280,] 1 2 [281,] 1 1 [282,] 1 1 [283,] 1 2 [284,] 1 1 [285,] 2 2 [286,] 1 1 [287,] 1 1 [288,] 1 1 [289,] 1 1 [290,] 1 2 [291,] 1 1 [292,] 1 2 [293,] 2 2 [294,] 1 1 [295,] 1 2 [296,] 2 2 [297,] 1 1 [298,] 1 1 [299,] 1 1 [300,] 1 1 [301,] 1 1 [302,] 1 1 [303,] 1 1 [304,] 1 1 [305,] 2 2 [306,] 1 2 [307,] 1 1 [308,] 1 2 [309,] 2 2 [310,] 1 1 [311,] 1 1 [312,] 2 2 [313,] 1 1 [314,] 1 2 [315,] 1 1 [316,] 1 2 [317,] 1 1 [318,] 2 2 [319,] 1 1 [320,] 1 1 [321,] 1 1 [322,] 1 1 [323,] 1 1 [324,] 1 1 [325,] 1 1 [326,] 1 1 [327,] 1 1 [328,] 1 1 [329,] 1 1 [330,] 1 1 [331,] 1 1 [332,] 1 1 [333,] 1 1 [334,] 1 1 [335,] 1 1 [336,] 1 1 [337,] 1 2 [338,] 1 1 [339,] 1 1 [340,] 1 2 [341,] 1 2 [342,] 1 1 [343,] 1 1 [344,] 1 1 [345,] 1 1 [346,] 1 1 [347,] 1 1 [348,] 1 1 [349,] 1 1 [350,] 1 1 [351,] 1 2 [352,] 1 2 [353,] 2 2 [354,] 1 1 [355,] 1 1 [356,] 1 1 [357,] 2 2 [358,] 1 1 [359,] 1 1 [360,] 1 1 [361,] 1 1 [362,] 1 1 [363,] 1 1 [364,] 1 1 [365,] 1 2 [366,] 1 1 [367,] 1 1 [368,] 1 1 [369,] 1 1 [370,] 1 1 [371,] 1 1 [372,] 2 2 [373,] 1 2 [374,] 1 1 [375,] 1 1 [376,] 1 1 [377,] 1 2 [378,] 2 2 [379,] 1 1 [380,] 1 1 [381,] 1 1 [382,] 2 2 [383,] 2 2 [384,] 1 1 [385,] 1 2 [386,] 2 2 [387,] 1 1 [388,] 2 2 [389,] 1 1 [390,] 2 2 [391,] 2 2 [392,] 2 2 [393,] 2 2 [394,] 2 2 [395,] 2 2 [396,] 2 2 [397,] 2 2 [398,] 2 2 [399,] 2 2 [400,] 2 2 [401,] 2 2 [402,] 2 2 [403,] 2 2 [404,] 2 2 [405,] 2 2 [406,] 2 2 [407,] 2 2 [408,] 2 2 [409,] 2 2 [410,] 2 2 [411,] 2 2 [412,] 2 2 [413,] 2 2 [414,] 2 2 [415,] 2 2 [416,] 2 2 [417,] 2 2 [418,] 2 2 [419,] 2 2 [420,] 2 2 [421,] 2 2 [422,] 2 2 [423,] 2 2 [424,] 2 2 [425,] 2 2 [426,] 2 2 [427,] 2 2 [428,] 2 2 [429,] 2 2 [430,] 2 2 [431,] 2 2 [ 0, 333) [333,162556] [ 0, 333) 175 41 [333,162556] 0 215 > postscript(file="/var/www/html/rcomp/tmp/4cmi81293202450.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/5xngw1293202450.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/6jnxk1293202450.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/7been1293202450.tab") + } > > try(system("convert tmp/2jd051293202450.ps tmp/2jd051293202450.png",intern=TRUE)) character(0) > try(system("convert tmp/3jd051293202450.ps tmp/3jd051293202450.png",intern=TRUE)) character(0) > try(system("convert tmp/4cmi81293202450.ps tmp/4cmi81293202450.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.709 0.504 7.814