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(18897 + ,22424 + ,19364 + ,19434 + ,22831 + ,23072 + ,37471 + ,14690 + ,17518 + ,22125 + ,18586 + ,18389 + ,22727 + ,22551 + ,36160 + ,13824 + ,8632 + ,7653 + ,8225 + ,8405 + ,8344 + ,8695 + ,9197 + ,9477 + ,832 + ,554 + ,822 + ,854 + ,830 + ,935 + ,1051 + ,1150 + ,3351 + ,3357 + ,3270 + ,3346 + ,3235 + ,3329 + ,3480 + ,3447 + ,8 + ,8 + ,3 + ,4 + ,5 + ,5 + ,4 + ,4 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,1 + ,2 + ,7 + ,10 + ,11 + ,9 + ,10 + ,9 + ,10 + ,9 + ,217 + ,222 + ,204 + ,205 + ,191 + ,197 + ,196 + ,191 + ,911 + ,947 + ,918 + ,939 + ,937 + ,967 + ,1007 + ,962 + ,1932 + ,1901 + ,1862 + ,1921 + ,1823 + ,1879 + ,1982 + ,2003 + ,274 + ,267 + ,270 + ,267 + ,269 + ,271 + ,281 + ,276 + ,131 + ,109 + ,87 + ,66 + ,68 + ,64 + ,76 + ,81 + ,1708 + ,1668 + ,1738 + ,1715 + ,1726 + ,1771 + ,1861 + ,2079 + ,2609 + ,1965 + ,2308 + ,2424 + ,2486 + ,2594 + ,2729 + ,2720 + ,133 + ,32 + ,119 + ,89 + ,93 + ,107 + ,102 + ,23 + ,2476 + ,1933 + ,2189 + ,2335 + ,2393 + 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,2799 + ,3100 + ,645 + ,770 + ,634 + ,680 + ,581 + ,675 + ,814 + ,677 + ,6113 + ,7729 + ,8065 + ,5931 + ,11602 + ,9279 + ,24726 + ,1473 + ,3567 + ,4697 + ,5792 + ,4959 + ,8473 + ,6753 + ,9199 + ,3926 + ,472 + ,241 + ,87 + ,262 + ,330 + ,64 + ,172 + ,-142 + ,1665 + ,2360 + ,1934 + ,584 + ,2229 + ,1972 + ,13856 + ,-2338 + ,328 + ,318 + ,154 + ,6 + ,256 + ,181 + ,1301 + ,-241 + ,0 + ,1 + ,0 + ,0 + ,12 + ,10 + ,21 + ,10 + ,81 + ,112 + ,99 + ,120 + ,302 + ,300 + ,177 + ,259 + ,1322 + ,1286 + ,1317 + ,1325 + ,1314 + ,1322 + ,1308 + ,1370 + ,154 + ,143 + ,156 + ,152 + ,144 + ,151 + ,151 + ,171 + ,1277 + ,1448 + ,1340 + ,1689 + ,1529 + ,1544 + ,1264 + ,1656 + ,1127 + ,2253 + ,486 + ,694 + ,699 + ,1110 + ,1165 + ,1776 + ,456 + ,1356 + ,63 + ,2861 + ,89 + ,82 + ,1019 + ,926 + ,224 + ,200 + ,149 + ,91 + ,165 + ,216 + ,94 + ,131 + ,1444 + ,1990 + ,1445 + ,176 + ,888 + ,2517 + ,413 + ,-264 + ,3 + ,8 + ,4 + ,7 + ,40 + ,38 + ,-64 + ,-10 + ,1444 + ,2084 + ,1443 + ,187 + ,850 + ,2483 + ,489 + ,-231) + ,dim=c(8 + ,69) + ,dimnames=list(c('2010-I' + ,'2010-II' + ,'2010-III' + ,'2010-IV' + ,'2011-I' + ,'2011-II' + ,'2011-III' + ,'2011-IV ') + ,1:69)) > y <- array(NA,dim=c(8,69),dimnames=list(c('2010-I','2010-II','2010-III','2010-IV','2011-I','2011-II','2011-III','2011-IV '),1:69)) > 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 = '5' > 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] "X2011.I" > x[,par1] [1] 22831 22727 8344 830 3235 5 1 10 191 937 1823 269 [13] 68 1726 2486 93 2393 22 1534 11706 7888 367 2860 435 [25] 15 141 80 774 266 38 32 32 3 32 22831 21687 [37] 5817 511 1843 183 655 847 3 156 470 88 308 73 [49] 339 2653 137 2516 581 11602 8473 330 2229 256 12 302 [61] 1314 144 1529 699 89 165 888 40 850 > 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]) 1 3 5 10 12 15 22 32 38 40 68 73 80 1 2 1 1 1 1 1 3 1 1 1 1 1 88 89 93 137 141 144 156 165 183 191 256 266 269 1 1 1 1 1 1 1 1 1 1 1 1 1 302 308 330 339 367 435 470 511 581 655 699 774 830 1 1 1 1 1 1 1 1 1 1 1 1 1 847 850 888 937 1314 1529 1534 1726 1823 1843 2229 2393 2486 1 1 1 1 1 1 1 1 1 1 1 1 1 2516 2653 2860 3235 5817 7888 8344 8473 11602 11706 21687 22727 22831 1 1 1 1 1 1 1 1 1 1 1 1 2 > colnames(x) [1] "X2010.I" "X2010.II" "X2010.III" "X2010.IV" "X2011.I" "X2011.II" [7] "X2011.III" "X2011.IV." > colnames(x)[par1] [1] "X2011.I" > x[,par1] [1] 22831 22727 8344 830 3235 5 1 10 191 937 1823 269 [13] 68 1726 2486 93 2393 22 1534 11706 7888 367 2860 435 [25] 15 141 80 774 266 38 32 32 3 32 22831 21687 [37] 5817 511 1843 183 655 847 3 156 470 88 308 73 [49] 339 2653 137 2516 581 11602 8473 330 2229 256 12 302 [61] 1314 144 1529 699 89 165 888 40 850 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/1leq41355151553.tab") + } + } > m Conditional inference tree with 6 terminal nodes Response: X2011.I Inputs: X2010.I, X2010.II, X2010.III, X2010.IV, X2011.II, X2011.III, X2011.IV. Number of observations: 69 1) X2010.III <= 5890; criterion = 1, statistic = 67.42 2) X2010.III <= 1862; criterion = 1, statistic = 58.167 3) X2010.III <= 747; criterion = 1, statistic = 44.888 4) X2010.III <= 270; criterion = 1, statistic = 19.122 5) X2010.III <= 63; criterion = 1, statistic = 16.228 6)* weights = 13 5) X2010.III > 63 7)* weights = 19 4) X2010.III > 270 8)* weights = 9 3) X2010.III > 747 9)* weights = 11 2) X2010.III > 1862 10)* weights = 10 1) X2010.III > 5890 11)* weights = 7 > postscript(file="/var/wessaorg/rcomp/tmp/2uim71355151553.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/wessaorg/rcomp/tmp/3duvr1355151553.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 22831 17389.71429 5441.2857143 2 22727 17389.71429 5337.2857143 3 8344 17389.71429 -9045.7142857 4 830 1283.72727 -453.7272727 5 3235 4055.00000 -820.0000000 6 5 22.76923 -17.7692308 7 1 22.76923 -21.7692308 8 10 22.76923 -12.7692308 9 191 197.05263 -6.0526316 10 937 1283.72727 -346.7272727 11 1823 1283.72727 539.2727273 12 269 197.05263 71.9473684 13 68 197.05263 -129.0526316 14 1726 1283.72727 442.2727273 15 2486 4055.00000 -1569.0000000 16 93 197.05263 -104.0526316 17 2393 4055.00000 -1662.0000000 18 22 22.76923 -0.7692308 19 1534 1283.72727 250.2727273 20 11706 17389.71429 -5683.7142857 21 7888 4055.00000 3833.0000000 22 367 197.05263 169.9473684 23 2860 4055.00000 -1195.0000000 24 435 197.05263 237.9473684 25 15 22.76923 -7.7692308 26 141 197.05263 -56.0526316 27 80 197.05263 -117.0526316 28 774 486.11111 287.8888889 29 266 197.05263 68.9473684 30 38 486.11111 -448.1111111 31 32 22.76923 9.2307692 32 32 22.76923 9.2307692 33 3 22.76923 -19.7692308 34 32 22.76923 9.2307692 35 22831 17389.71429 5441.2857143 36 21687 17389.71429 4297.2857143 37 5817 4055.00000 1762.0000000 38 511 486.11111 24.8888889 39 1843 1283.72727 559.2727273 40 183 197.05263 -14.0526316 41 655 486.11111 168.8888889 42 847 1283.72727 -436.7272727 43 3 22.76923 -19.7692308 44 156 197.05263 -41.0526316 45 470 486.11111 -16.1111111 46 88 197.05263 -109.0526316 47 308 486.11111 -178.1111111 48 73 197.05263 -124.0526316 49 339 486.11111 -147.1111111 50 2653 4055.00000 -1402.0000000 51 137 197.05263 -60.0526316 52 2516 4055.00000 -1539.0000000 53 581 486.11111 94.8888889 54 11602 17389.71429 -5787.7142857 55 8473 4055.00000 4418.0000000 56 330 197.05263 132.9473684 57 2229 4055.00000 -1826.0000000 58 256 197.05263 58.9473684 59 12 22.76923 -10.7692308 60 302 197.05263 104.9473684 61 1314 1283.72727 30.2727273 62 144 197.05263 -53.0526316 63 1529 1283.72727 245.2727273 64 699 486.11111 212.8888889 65 89 22.76923 66.2307692 66 165 197.05263 -32.0526316 67 888 1283.72727 -395.7272727 68 40 22.76923 17.2307692 69 850 1283.72727 -433.7272727 > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } > postscript(file="/var/wessaorg/rcomp/tmp/4uinp1355151553.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$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/5bdnd1355151553.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$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/wessaorg/rcomp/tmp/6n3f91355151553.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/wessaorg/rcomp/tmp/7ovyo1355151553.tab") + } > > try(system("convert tmp/2uim71355151553.ps tmp/2uim71355151553.png",intern=TRUE)) character(0) > try(system("convert tmp/3duvr1355151553.ps tmp/3duvr1355151553.png",intern=TRUE)) character(0) > try(system("convert tmp/4uinp1355151553.ps tmp/4uinp1355151553.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.133 0.375 4.506