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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,3.638 + ,1.000 + ,0.903 + ,2.657 + ,2.342 + ,3.639 + ,0.954 + ,0.903 + ,2.544 + ,2.190 + ,3.639 + ,1.176 + ,0.903 + ,2.545 + ,2.199 + ,3.640 + ,1.114 + ,0.903 + ,2.487 + ,2.301 + ,3.641 + ,1.176 + ,0.903 + ,2.544 + ,2.255 + ,3.641 + ,1.079 + ,0.903 + ,2.502 + ,2.322 + ,3.642 + ,1.146 + ,0.903 + ,2.602 + ,2.243 + ,3.642 + ,1.079 + ,0.903 + ,2.602 + ,2.279 + ,3.646 + ,1.114 + ,0.903 + ,2.658 + ,2.352 + ,3.646 + ,1.000 + ,0.903 + ,2.544 + ,2.161 + ,3.647 + ,1.146 + ,0.903 + ,2.544 + ,2.204 + ,3.649 + ,1.146 + ,0.903 + ,2.502 + ,2.176 + ,3.649 + ,1.146 + ,0.903 + ,2.602 + ,2.243 + ,3.650 + ,1.079 + ,0.903 + ,2.602 + ,2.176 + ,3.650 + ,1.079 + ,0.903 + ,2.502 + ,2.176 + ,3.653 + ,1.176 + ,0.903 + ,2.544 + ,2.255 + ,3.653 + ,1.114 + ,0.903 + ,2.544 + ,2.190 + ,3.653 + ,1.146 + ,0.903 + ,2.556 + ,2.332 + ,3.664 + ,1.146 + ,0.903 + ,2.632 + ,2.318 + ,3.666 + ,1.041 + ,0.903 + ,2.480 + ,2.146 + ,3.666 + ,1.204 + ,0.903 + ,2.556 + ,2.230 + ,3.668 + ,1.114 + ,0.903 + ,2.545 + ,2.170 + ,3.668 + ,1.146 + ,0.903 + ,2.602 + ,2.230 + ,3.669 + ,1.079 + ,0.903 + ,2.544 + ,2.176 + ,3.672 + ,1.176 + ,0.903 + ,2.483 + ,2.286 + ,3.675 + ,1.279 + ,0.903 + ,2.643 + ,2.332 + ,3.675 + ,1.041 + ,0.903 + ,2.602 + ,2.230 + ,3.676 + ,1.079 + ,0.903 + ,2.602 + ,2.223 + ,3.691 + ,1.114 + ,0.903 + ,2.658 + ,2.352 + ,3.695 + ,1.041 + ,0.903 + ,2.632 + ,2.297 + ,3.695 + ,1.079 + ,0.903 + ,2.583 + ,2.255 + ,3.695 + ,1.079 + ,0.903 + ,2.602 + ,2.176 + ,3.699 + ,1.146 + ,0.903 + ,2.602 + ,2.243 + ,3.711 + ,1.079) + ,dim=c(5 + ,632) + ,dimnames=list(c('cylinders' + ,'engine.displacement' + ,'horsepower' + ,'weight' + ,'acceleration ') + ,1:632)) > y <- array(NA,dim=c(5,632),dimnames=list(c('cylinders','engine.displacement','horsepower','weight','acceleration '),1:632)) > 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 = '5' > #'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] "acceleration..." > x[,par1] [1] 1.061 1.041 1.021 1.000 0.929 1.000 1.000 0.903 1.000 1.176 1.190 1.312 [13] 1.243 1.243 1.097 1.146 1.176 1.267 1.161 1.146 1.190 1.190 1.079 1.114 [25] 1.079 1.079 1.279 1.176 1.146 1.146 1.161 1.279 1.279 1.312 1.230 1.217 [37] 1.079 1.130 1.114 1.041 1.130 1.097 1.130 1.146 1.204 1.161 1.255 1.204 [49] 1.161 1.176 1.114 1.061 1.161 1.097 1.079 1.114 1.041 1.041 1.217 1.255 [61] 1.217 1.204 1.146 1.097 1.176 1.290 1.217 1.267 1.146 1.114 0.978 1.190 [73] 1.146 1.041 1.146 1.041 1.217 1.204 1.217 1.322 1.230 1.255 1.146 1.161 [85] 1.204 1.190 1.190 1.161 1.279 1.161 1.146 1.176 1.204 1.204 1.290 1.061 [97] 1.146 1.130 1.322 1.279 1.279 1.130 1.079 1.230 1.204 1.130 1.217 1.161 [109] 1.176 1.230 1.130 1.243 1.228 1.173 1.185 1.114 1.143 1.107 1.161 1.246 [121] 1.346 1.344 1.248 1.210 1.250 1.230 1.215 1.196 1.121 1.223 1.083 1.176 [133] 1.146 1.170 1.270 1.225 1.097 1.137 1.228 1.248 1.045 1.057 1.161 1.161 [145] 1.260 1.199 1.201 1.215 1.161 1.107 1.332 1.158 1.270 1.121 1.107 1.260 [157] 1.199 1.236 1.236 1.223 1.272 1.121 1.127 1.137 1.217 1.167 1.161 1.246 [169] 1.201 1.134 1.199 1.173 1.220 1.260 1.238 1.220 1.188 1.121 1.182 1.155 [181] 1.176 1.146 1.182 1.176 1.394 1.346 1.173 1.283 1.204 1.053 1.121 1.167 [193] 1.190 1.215 1.258 1.303 1.199 1.190 1.176 1.182 1.158 1.283 1.299 1.140 [205] 1.185 1.179 1.196 1.215 1.100 1.111 1.215 1.207 1.288 1.238 1.173 1.210 [217] 1.152 1.170 1.310 1.140 1.199 1.233 1.220 1.270 1.255 1.204 1.255 1.185 [229] 1.246 1.167 1.161 1.161 1.196 1.215 1.230 1.143 1.238 1.193 1.064 1.270 [241] 1.255 1.230 1.230 1.204 1.279 1.255 1.230 1.146 1.204 1.079 1.279 1.279 [253] 1.322 1.322 1.176 1.146 1.301 1.204 1.146 1.146 1.146 1.146 1.176 1.230 [265] 1.322 1.279 1.322 1.204 1.176 1.204 1.279 1.255 1.176 1.279 1.176 1.342 [277] 1.204 1.279 1.204 1.176 1.230 1.204 1.204 1.279 1.204 1.279 1.255 1.342 [289] 1.204 1.279 1.230 1.230 1.176 1.255 1.279 1.301 1.204 1.342 1.230 1.204 [301] 1.255 1.279 1.204 1.146 1.146 1.176 1.176 1.230 1.230 1.176 1.398 1.176 [313] 1.176 1.230 1.176 1.255 1.176 1.176 1.230 1.204 1.204 1.176 1.176 1.342 [325] 1.204 1.204 1.255 1.146 1.146 1.114 1.176 1.176 1.146 1.176 1.230 1.146 [337] 1.230 1.230 1.230 1.146 1.176 1.114 1.230 1.146 1.380 1.255 1.204 1.204 [349] 1.255 1.176 1.204 1.279 1.230 1.230 1.079 1.204 1.176 1.176 1.279 1.146 [361] 1.380 1.230 1.114 1.176 1.255 1.230 1.322 1.114 1.204 1.204 1.255 1.301 [373] 1.176 1.279 1.301 1.114 1.176 1.176 1.230 1.204 1.146 1.176 1.204 1.176 [385] 1.176 1.255 1.176 1.204 1.230 1.255 1.230 1.114 1.146 1.146 1.176 1.204 [397] 1.146 1.176 1.204 1.279 1.041 1.114 1.301 1.176 1.146 1.279 1.114 1.204 [409] 1.255 1.230 1.279 1.176 1.146 1.146 1.176 1.204 1.146 1.255 1.230 1.176 [421] 1.114 1.146 1.204 1.176 1.279 1.146 1.114 1.255 1.204 1.230 1.204 1.204 [433] 1.176 1.204 1.204 1.146 1.146 1.176 1.204 1.204 1.176 1.255 1.204 1.204 [445] 1.255 1.230 1.114 1.204 1.204 1.041 1.204 1.204 1.146 1.176 1.204 1.204 [457] 1.176 1.230 1.301 1.230 1.146 1.204 1.301 1.176 1.255 1.301 1.255 1.230 [469] 1.230 1.176 1.230 1.230 1.255 1.000 1.230 1.230 1.176 1.146 1.204 1.255 [481] 1.301 1.301 1.079 1.398 1.255 1.041 1.230 1.230 1.146 1.301 1.176 1.176 [493] 1.342 1.204 1.255 1.342 1.255 1.176 1.204 1.204 1.204 1.230 1.176 1.230 [505] 1.204 1.204 1.279 1.041 1.176 1.204 1.204 1.342 1.230 1.114 1.230 1.322 [517] 1.079 1.041 1.204 1.114 1.041 1.204 1.230 1.079 1.204 1.279 1.301 1.279 [529] 1.000 1.114 1.322 1.176 0.903 1.230 1.279 1.255 1.255 1.204 1.255 1.041 [541] 1.079 1.079 1.079 1.114 1.279 1.279 1.114 1.146 1.000 1.114 1.230 1.279 [553] 1.230 1.041 1.176 1.176 0.954 1.176 1.114 1.114 1.279 1.230 1.322 1.114 [565] 1.114 1.114 1.146 1.114 1.176 1.146 1.079 1.279 1.146 1.146 1.114 1.114 [577] 1.146 1.114 1.114 1.146 1.146 1.146 1.146 1.041 1.114 1.079 1.114 1.114 [589] 1.041 1.176 1.204 1.079 1.000 1.204 1.176 0.954 1.079 1.176 1.000 0.954 [601] 1.176 1.114 1.176 1.079 1.146 1.079 1.114 1.000 1.146 1.146 1.146 1.079 [613] 1.079 1.176 1.114 1.146 1.146 1.041 1.204 1.114 1.146 1.079 1.176 1.279 [625] 1.041 1.079 1.114 1.041 1.079 1.079 1.146 1.079 > 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]) [0.903,1.19) [1.188,1.40] 317 315 > colnames(x) [1] "cylinders" "engine.displacement" "horsepower" [4] "weight" "acceleration..." > colnames(x)[par1] [1] "acceleration..." > x[,par1] [1] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [6] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [11] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [16] [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [0.903,1.19) [21] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [26] [0.903,1.19) [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [31] [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [36] [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [41] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [46] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [51] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [56] [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [61] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [66] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [71] [0.903,1.19) [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [76] [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [81] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [86] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [0.903,1.19) [91] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [96] [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [101] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [106] [0.903,1.19) [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [111] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [116] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [121] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [126] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [131] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [136] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [141] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [146] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [151] [1.188,1.40] [0.903,1.19) [1.188,1.40] [0.903,1.19) [0.903,1.19) [156] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [161] [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [166] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [171] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [176] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [181] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [186] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [191] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [196] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [201] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [206] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [211] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [216] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [221] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [226] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [0.903,1.19) [231] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [236] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [241] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [246] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [0.903,1.19) [251] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [256] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [261] [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [266] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [271] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [0.903,1.19) [276] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [281] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [286] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [291] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [296] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [301] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [306] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [311] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [316] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [321] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [326] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [331] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [336] [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [341] [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [1.188,1.40] [346] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [351] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [356] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [361] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [366] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [371] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [376] [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [381] [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [0.903,1.19) [386] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [391] [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [396] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [401] [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [0.903,1.19) [406] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [411] [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [416] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [421] [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [1.188,1.40] [426] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [431] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [436] [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [441] [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [446] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [451] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [456] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [461] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [466] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [471] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [476] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [481] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [486] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [491] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [1.188,1.40] [496] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [501] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [1.188,1.40] [506] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [511] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [516] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [521] [0.903,1.19) [1.188,1.40] [1.188,1.40] [0.903,1.19) [1.188,1.40] [526] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [531] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [1.188,1.40] [536] [1.188,1.40] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [541] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [546] [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [551] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [556] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [561] [1.188,1.40] [1.188,1.40] [1.188,1.40] [0.903,1.19) [0.903,1.19) [566] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [571] [0.903,1.19) [1.188,1.40] [0.903,1.19) [0.903,1.19) [0.903,1.19) [576] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [581] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [586] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [591] [1.188,1.40] [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [596] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [601] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [606] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [611] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [616] [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [621] [0.903,1.19) [0.903,1.19) [0.903,1.19) [1.188,1.40] [0.903,1.19) [626] [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [0.903,1.19) [631] [0.903,1.19) [0.903,1.19) Levels: [0.903,1.19) [1.188,1.40] > 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/1a3bp1293281904.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 1 2500 377 2 465 2368 [1] 0.8689607 [1] 0.835863 [1] 0.8525394 m.ct.x.pred m.ct.x.actu 1 2 1 251 42 2 63 254 [1] 0.8566553 [1] 0.8012618 [1] 0.8278689 > m Conditional inference tree with 13 terminal nodes Response: as.factor(acceleration...) Inputs: cylinders, engine.displacement, horsepower, weight Number of observations: 632 1) horsepower <= 2.041; criterion = 1, statistic = 176.385 2) cylinders <= 0.602; criterion = 1, statistic = 17.748 3) horsepower <= 1.954; criterion = 1, statistic = 33.649 4) horsepower <= 1.785; criterion = 0.974, statistic = 7.401 5)* weights = 30 4) horsepower > 1.785 6) weight <= 3.377; criterion = 1, statistic = 15.971 7) engine.displacement <= 1.991; criterion = 1, statistic = 16.262 8) horsepower <= 1.845; criterion = 0.982, statistic = 8.029 9) weight <= 3.287; criterion = 0.972, statistic = 7.285 10)* weights = 15 9) weight > 3.287 11)* weights = 53 8) horsepower > 1.845 12) weight <= 3.315; criterion = 0.989, statistic = 9.002 13)* weights = 10 12) weight > 3.315 14)* weights = 32 7) engine.displacement > 1.991 15)* weights = 47 6) weight > 3.377 16)* weights = 75 3) horsepower > 1.954 17)* weights = 53 2) cylinders > 0.602 18) weight <= 3.449; criterion = 1, statistic = 20.191 19)* weights = 13 18) weight > 3.449 20)* weights = 112 1) horsepower > 2.041 21) engine.displacement <= 2.484; criterion = 0.999, statistic = 14.636 22) weight <= 3.625; criterion = 0.991, statistic = 9.358 23)* weights = 58 22) weight > 3.625 24)* weights = 9 21) engine.displacement > 2.484 25)* weights = 125 > postscript(file="/var/www/html/rcomp/tmp/2a3bp1293281904.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/3a3bp1293281904.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,] 1 1 [2,] 1 1 [3,] 1 1 [4,] 1 1 [5,] 1 1 [6,] 1 1 [7,] 1 1 [8,] 1 1 [9,] 1 1 [10,] 1 1 [11,] 2 1 [12,] 2 2 [13,] 2 2 [14,] 2 1 [15,] 1 1 [16,] 1 1 [17,] 1 1 [18,] 2 2 [19,] 1 2 [20,] 1 1 [21,] 2 2 [22,] 2 2 [23,] 1 1 [24,] 1 1 [25,] 1 1 [26,] 1 1 [27,] 2 2 [28,] 1 2 [29,] 1 1 [30,] 1 1 [31,] 1 1 [32,] 2 1 [33,] 2 2 [34,] 2 2 [35,] 2 2 [36,] 2 1 [37,] 1 1 [38,] 1 1 [39,] 1 1 [40,] 1 1 [41,] 1 1 [42,] 1 1 [43,] 1 1 [44,] 1 1 [45,] 2 2 [46,] 1 1 [47,] 2 2 [48,] 2 2 [49,] 1 1 [50,] 1 2 [51,] 1 1 [52,] 1 1 [53,] 1 1 [54,] 1 1 [55,] 1 1 [56,] 1 1 [57,] 1 1 [58,] 1 1 [59,] 2 2 [60,] 2 2 [61,] 2 2 [62,] 2 2 [63,] 1 1 [64,] 1 1 [65,] 1 1 [66,] 2 2 [67,] 2 1 [68,] 2 1 [69,] 1 1 [70,] 1 1 [71,] 1 1 [72,] 2 1 [73,] 1 1 [74,] 1 1 [75,] 1 1 [76,] 1 1 [77,] 2 2 [78,] 2 2 [79,] 2 2 [80,] 2 1 [81,] 2 2 [82,] 2 2 [83,] 1 1 [84,] 1 1 [85,] 2 2 [86,] 2 2 [87,] 2 2 [88,] 1 2 [89,] 2 2 [90,] 1 2 [91,] 1 1 [92,] 1 1 [93,] 2 2 [94,] 2 2 [95,] 2 2 [96,] 1 1 [97,] 1 1 [98,] 1 1 [99,] 2 2 [100,] 2 2 [101,] 2 2 [102,] 1 2 [103,] 1 1 [104,] 2 2 [105,] 2 2 [106,] 1 1 [107,] 2 2 [108,] 1 2 [109,] 1 1 [110,] 2 2 [111,] 1 1 [112,] 2 2 [113,] 2 1 [114,] 1 1 [115,] 1 1 [116,] 1 1 [117,] 1 1 [118,] 1 1 [119,] 1 2 [120,] 2 2 [121,] 2 2 [122,] 2 2 [123,] 2 2 [124,] 2 2 [125,] 2 2 [126,] 2 2 [127,] 2 2 [128,] 2 1 [129,] 1 1 [130,] 2 1 [131,] 1 1 [132,] 1 1 [133,] 1 1 [134,] 1 1 [135,] 2 2 [136,] 2 2 [137,] 1 1 [138,] 1 1 [139,] 2 2 [140,] 2 2 [141,] 1 1 [142,] 1 1 [143,] 1 1 [144,] 1 1 [145,] 2 2 [146,] 2 2 [147,] 2 2 [148,] 2 2 [149,] 1 1 [150,] 1 1 [151,] 2 2 [152,] 1 1 [153,] 2 2 [154,] 1 1 [155,] 1 1 [156,] 2 2 [157,] 2 2 [158,] 2 2 [159,] 2 2 [160,] 2 2 [161,] 2 2 [162,] 1 1 [163,] 1 1 [164,] 1 1 [165,] 2 2 [166,] 1 1 [167,] 1 1 [168,] 2 2 [169,] 2 2 [170,] 1 1 [171,] 2 1 [172,] 1 1 [173,] 2 2 [174,] 2 2 [175,] 2 2 [176,] 2 2 [177,] 2 1 [178,] 1 1 [179,] 1 1 [180,] 1 1 [181,] 1 1 [182,] 1 1 [183,] 1 2 [184,] 1 2 [185,] 2 2 [186,] 2 2 [187,] 1 1 [188,] 2 2 [189,] 2 2 [190,] 1 1 [191,] 1 2 [192,] 1 2 [193,] 2 2 [194,] 2 2 [195,] 2 2 [196,] 2 2 [197,] 2 2 [198,] 2 2 [199,] 1 1 [200,] 1 1 [201,] 1 1 [202,] 2 2 [203,] 2 2 [204,] 1 1 [205,] 1 1 [206,] 1 2 [207,] 2 2 [208,] 2 2 [209,] 1 1 [210,] 1 1 [211,] 2 1 [212,] 2 2 [213,] 2 2 [214,] 2 2 [215,] 1 1 [216,] 2 2 [217,] 1 1 [218,] 1 1 [219,] 2 2 [220,] 1 1 [221,] 2 2 [222,] 2 2 [223,] 2 2 [224,] 2 2 [225,] 2 2 [226,] 2 2 [227,] 2 2 [228,] 1 1 [229,] 2 2 [230,] 1 1 [231,] 1 1 [232,] 1 1 [233,] 2 2 [234,] 2 2 [235,] 2 2 [236,] 1 1 [237,] 2 2 [238,] 2 2 [239,] 1 1 [240,] 2 2 [241,] 2 1 [242,] 2 2 [243,] 2 2 [244,] 2 2 [245,] 2 1 [246,] 2 2 [247,] 2 2 [248,] 1 1 [249,] 2 2 [250,] 1 1 [251,] 2 2 [252,] 2 2 [253,] 2 2 [254,] 2 1 [255,] 1 1 [256,] 1 1 [257,] 2 2 [258,] 2 1 [259,] 1 1 [260,] 1 1 [261,] 1 1 [262,] 1 1 [263,] 1 1 [264,] 2 2 [265,] 2 2 [266,] 2 2 [267,] 2 2 [268,] 2 2 [269,] 1 2 [270,] 2 2 [271,] 2 2 [272,] 2 2 [273,] 1 2 [274,] 2 2 [275,] 1 1 [276,] 2 2 [277,] 2 2 [278,] 2 2 [279,] 2 2 [280,] 1 1 [281,] 2 2 [282,] 2 2 [283,] 2 2 [284,] 2 2 [285,] 2 2 [286,] 2 2 [287,] 2 2 [288,] 2 2 [289,] 2 2 [290,] 2 2 [291,] 2 2 [292,] 2 2 [293,] 1 1 [294,] 2 2 [295,] 2 2 [296,] 2 2 [297,] 2 2 [298,] 2 2 [299,] 2 2 [300,] 2 2 [301,] 2 2 [302,] 2 2 [303,] 2 2 [304,] 1 1 [305,] 1 2 [306,] 1 2 [307,] 1 1 [308,] 2 2 [309,] 2 2 [310,] 1 2 [311,] 2 2 [312,] 1 2 [313,] 1 2 [314,] 2 2 [315,] 1 2 [316,] 2 2 [317,] 1 1 [318,] 1 1 [319,] 2 2 [320,] 2 2 [321,] 2 1 [322,] 1 1 [323,] 1 2 [324,] 2 2 [325,] 2 2 [326,] 2 2 [327,] 2 2 [328,] 1 2 [329,] 1 1 [330,] 1 1 [331,] 1 1 [332,] 1 1 [333,] 1 1 [334,] 1 1 [335,] 2 2 [336,] 1 1 [337,] 2 1 [338,] 2 2 [339,] 2 1 [340,] 1 1 [341,] 1 1 [342,] 1 1 [343,] 2 1 [344,] 1 1 [345,] 2 2 [346,] 2 2 [347,] 2 1 [348,] 2 2 [349,] 2 2 [350,] 1 1 [351,] 2 1 [352,] 2 2 [353,] 2 1 [354,] 2 1 [355,] 1 1 [356,] 2 1 [357,] 1 2 [358,] 1 1 [359,] 2 1 [360,] 1 1 [361,] 2 2 [362,] 2 1 [363,] 1 1 [364,] 1 1 [365,] 2 1 [366,] 2 1 [367,] 2 2 [368,] 1 1 [369,] 2 1 [370,] 2 2 [371,] 2 2 [372,] 2 2 [373,] 1 1 [374,] 2 2 [375,] 2 2 [376,] 1 1 [377,] 1 2 [378,] 1 1 [379,] 2 2 [380,] 2 2 [381,] 1 1 [382,] 1 1 [383,] 2 2 [384,] 1 2 [385,] 1 1 [386,] 2 2 [387,] 1 1 [388,] 2 2 [389,] 2 2 [390,] 2 2 [391,] 2 1 [392,] 1 2 [393,] 1 1 [394,] 1 2 [395,] 1 1 [396,] 2 2 [397,] 1 1 [398,] 1 1 [399,] 2 1 [400,] 2 2 [401,] 1 1 [402,] 1 1 [403,] 2 2 [404,] 1 1 [405,] 1 1 [406,] 2 2 [407,] 1 1 [408,] 2 2 [409,] 2 2 [410,] 2 2 [411,] 2 2 [412,] 1 1 [413,] 1 1 [414,] 1 1 [415,] 1 2 [416,] 2 2 [417,] 1 1 [418,] 2 2 [419,] 2 2 [420,] 1 1 [421,] 1 1 [422,] 1 1 [423,] 2 2 [424,] 1 2 [425,] 2 2 [426,] 1 1 [427,] 1 1 [428,] 2 2 [429,] 2 2 [430,] 2 1 [431,] 2 2 [432,] 2 1 [433,] 1 1 [434,] 2 2 [435,] 2 1 [436,] 1 1 [437,] 1 1 [438,] 1 1 [439,] 2 2 [440,] 2 2 [441,] 1 1 [442,] 2 2 [443,] 2 1 [444,] 2 1 [445,] 2 2 [446,] 2 2 [447,] 1 1 [448,] 2 2 [449,] 2 2 [450,] 1 1 [451,] 2 2 [452,] 2 2 [453,] 1 1 [454,] 1 1 [455,] 2 2 [456,] 2 2 [457,] 1 1 [458,] 2 2 [459,] 2 2 [460,] 2 2 [461,] 1 2 [462,] 2 2 [463,] 2 2 [464,] 1 2 [465,] 2 2 [466,] 2 2 [467,] 2 2 [468,] 2 2 [469,] 2 2 [470,] 1 2 [471,] 2 2 [472,] 2 2 [473,] 2 2 [474,] 1 1 [475,] 2 2 [476,] 2 2 [477,] 1 2 [478,] 1 1 [479,] 2 1 [480,] 2 2 [481,] 2 2 [482,] 2 2 [483,] 1 1 [484,] 2 2 [485,] 2 2 [486,] 1 1 [487,] 2 2 [488,] 2 2 [489,] 1 2 [490,] 2 2 [491,] 1 2 [492,] 1 1 [493,] 2 2 [494,] 2 2 [495,] 2 2 [496,] 2 2 [497,] 2 2 [498,] 1 2 [499,] 2 2 [500,] 2 2 [501,] 2 2 [502,] 2 2 [503,] 1 2 [504,] 2 2 [505,] 2 2 [506,] 2 2 [507,] 2 2 [508,] 1 1 [509,] 1 1 [510,] 2 1 [511,] 2 2 [512,] 2 2 [513,] 2 2 [514,] 1 1 [515,] 2 2 [516,] 2 2 [517,] 1 1 [518,] 1 1 [519,] 2 2 [520,] 1 1 [521,] 1 1 [522,] 2 2 [523,] 2 2 [524,] 1 1 [525,] 2 2 [526,] 2 2 [527,] 2 2 [528,] 2 2 [529,] 1 1 [530,] 1 1 [531,] 2 2 [532,] 1 1 [533,] 1 1 [534,] 2 2 [535,] 2 2 [536,] 2 2 [537,] 2 2 [538,] 2 2 [539,] 2 2 [540,] 1 1 [541,] 1 1 [542,] 1 1 [543,] 1 1 [544,] 1 1 [545,] 2 2 [546,] 2 2 [547,] 1 1 [548,] 1 1 [549,] 1 1 [550,] 1 1 [551,] 2 2 [552,] 2 2 [553,] 2 1 [554,] 1 1 [555,] 1 1 [556,] 1 1 [557,] 1 1 [558,] 1 1 [559,] 1 1 [560,] 1 1 [561,] 2 2 [562,] 2 1 [563,] 2 2 [564,] 1 1 [565,] 1 1 [566,] 1 1 [567,] 1 1 [568,] 1 1 [569,] 1 1 [570,] 1 1 [571,] 1 1 [572,] 2 2 [573,] 1 1 [574,] 1 1 [575,] 1 1 [576,] 1 1 [577,] 1 1 [578,] 1 1 [579,] 1 1 [580,] 1 1 [581,] 1 1 [582,] 1 1 [583,] 1 1 [584,] 1 1 [585,] 1 1 [586,] 1 1 [587,] 1 1 [588,] 1 1 [589,] 1 1 [590,] 1 1 [591,] 2 2 [592,] 1 1 [593,] 1 1 [594,] 2 2 [595,] 1 2 [596,] 1 1 [597,] 1 1 [598,] 1 1 [599,] 1 1 [600,] 1 1 [601,] 1 1 [602,] 1 1 [603,] 1 1 [604,] 1 1 [605,] 1 1 [606,] 1 1 [607,] 1 1 [608,] 1 1 [609,] 1 1 [610,] 1 1 [611,] 1 1 [612,] 1 1 [613,] 1 1 [614,] 1 1 [615,] 1 1 [616,] 1 1 [617,] 1 1 [618,] 1 1 [619,] 2 2 [620,] 1 1 [621,] 1 1 [622,] 1 1 [623,] 1 1 [624,] 2 2 [625,] 1 1 [626,] 1 1 [627,] 1 1 [628,] 1 1 [629,] 1 1 [630,] 1 1 [631,] 1 1 [632,] 1 1 [0.903,1.19) [1.188,1.40] [0.903,1.19) 278 39 [1.188,1.40] 43 272 > postscript(file="/var/www/html/rcomp/tmp/43cas1293281904.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/5zmp11293281904.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/624oo1293281904.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/7izug1293281904.tab") + } > > try(system("convert tmp/2a3bp1293281904.ps tmp/2a3bp1293281904.png",intern=TRUE)) character(0) > try(system("convert tmp/3a3bp1293281904.ps tmp/3a3bp1293281904.png",intern=TRUE)) character(0) > try(system("convert tmp/43cas1293281904.ps tmp/43cas1293281904.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.653 0.571 11.759