R version 2.12.0 (2010-10-15) Copyright (C) 2010 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-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(13 + ,15 + ,42 + ,14 + ,13 + ,12 + ,18 + ,51 + ,8 + ,13 + ,15 + ,11 + ,42 + ,12 + ,16 + ,12 + ,16 + ,46 + ,7 + ,12 + ,10 + ,12 + ,41 + ,10 + ,11 + ,12 + ,17 + ,49 + ,7 + ,12 + ,15 + ,15 + ,47 + ,16 + ,18 + ,9 + ,19 + ,33 + ,11 + ,11 + ,12 + ,16 + ,33 + ,14 + ,14 + ,11 + ,18 + ,47 + ,6 + ,9 + ,11 + ,10 + ,42 + ,16 + ,14 + ,11 + ,14 + ,32 + ,11 + ,12 + ,15 + ,18 + ,53 + ,16 + ,11 + ,7 + ,18 + ,41 + ,12 + ,12 + ,11 + ,14 + ,41 + ,7 + ,13 + ,11 + ,14 + ,33 + ,13 + ,11 + ,10 + ,12 + ,37 + ,11 + ,12 + ,14 + ,16 + ,43 + ,15 + ,16 + ,10 + ,15 + ,45 + ,7 + ,9 + ,6 + ,13 + ,33 + ,9 + ,11 + ,11 + ,16 + ,49 + ,7 + ,13 + ,15 + ,14 + ,42 + ,14 + ,15 + ,11 + ,9 + ,43 + ,15 + ,10 + ,12 + ,9 + ,37 + ,7 + ,11 + ,14 + ,17 + ,43 + ,15 + ,13 + ,15 + ,13 + ,42 + ,17 + ,16 + ,9 + ,15 + ,43 + ,15 + ,15 + ,13 + ,17 + ,46 + ,14 + ,14 + ,13 + ,16 + ,33 + ,14 + ,14 + ,16 + ,12 + ,42 + ,8 + ,14 + ,13 + ,11 + ,40 + ,8 + ,8 + ,12 + ,16 + ,44 + ,14 + ,13 + ,14 + ,17 + ,42 + ,14 + ,15 + ,11 + ,17 + ,52 + ,8 + ,13 + ,9 + ,16 + ,44 + ,11 + ,11 + ,16 + ,13 + ,45 + ,16 + ,15 + ,12 + ,12 + ,46 + ,10 + ,15 + ,10 + ,12 + ,36 + ,8 + ,9 + ,13 + ,16 + ,45 + ,14 + ,13 + ,16 + ,14 + ,49 + ,16 + ,16 + ,14 + ,12 + ,43 + ,13 + ,13 + ,15 + ,12 + ,43 + ,5 + ,11 + ,5 + ,14 + ,37 + ,8 + ,12 + ,8 + ,8 + ,32 + ,10 + ,12 + ,11 + ,15 + ,45 + ,8 + ,12 + ,16 + ,14 + ,45 + ,13 + ,14 + ,17 + ,11 + ,45 + ,15 + ,14 + ,9 + ,13 + ,45 + ,6 + ,8 + ,9 + ,14 + ,31 + ,12 + ,13 + ,13 + ,15 + ,33 + ,16 + ,16 + ,10 + ,16 + ,44 + ,5 + ,13 + ,6 + ,10 + ,49 + ,15 + ,11 + ,12 + ,11 + ,44 + ,12 + ,14 + ,8 + ,12 + ,41 + ,8 + ,13 + ,14 + ,14 + ,44 + ,13 + ,13 + ,12 + ,15 + ,38 + ,14 + ,13 + ,11 + ,16 + ,33 + ,12 + ,12 + ,16 + ,9 + ,47 + ,16 + ,16 + ,8 + ,11 + ,37 + ,10 + ,15 + ,15 + ,15 + ,48 + ,15 + ,15 + ,7 + ,15 + ,40 + ,8 + ,12 + ,16 + ,13 + ,50 + ,16 + ,14 + ,14 + ,17 + ,54 + ,19 + ,12 + ,16 + ,17 + ,43 + ,14 + ,15 + ,9 + ,15 + ,54 + ,6 + ,12 + ,14 + ,13 + ,44 + ,13 + ,13 + ,11 + ,15 + ,47 + ,15 + ,12 + ,13 + ,13 + ,33 + ,7 + ,12 + ,15 + ,15 + ,45 + ,13 + ,13 + ,5 + ,10 + ,33 + ,4 + ,5 + ,15 + ,15 + ,44 + ,14 + ,13 + ,13 + ,14 + ,47 + ,13 + ,13 + ,11 + ,15 + ,45 + ,11 + ,14 + ,11 + ,16 + ,43 + ,14 + ,17 + ,12 + ,13 + ,33 + ,12 + ,13 + ,12 + ,7 + ,43 + ,15 + ,13 + ,12 + ,13 + ,33 + ,14 + ,12 + ,12 + ,15 + ,46 + ,13 + ,13 + ,14 + ,13 + ,47 + ,8 + ,14 + ,6 + ,16 + ,47 + ,6 + ,11 + ,7 + ,16 + ,0 + ,7 + ,12 + ,14 + ,14 + ,42 + ,13 + ,12 + ,14 + ,12 + ,43 + ,13 + ,16 + ,10 + ,11 + ,44 + ,11 + ,12 + ,13 + ,15 + ,46 + ,5 + ,12 + ,12 + ,14 + ,36 + ,12 + ,12 + ,9 + ,11 + ,42 + ,8 + ,10 + ,12 + ,14 + ,44 + ,11 + ,15 + ,16 + ,15 + ,47 + ,14 + ,15 + ,10 + ,9 + ,41 + ,9 + ,12 + ,14 + ,15 + ,47 + ,10 + ,16 + ,10 + ,17 + ,46 + ,13 + ,15 + ,16 + ,16 + ,47 + ,16 + ,16 + ,15 + ,14 + ,46 + ,16 + ,13 + ,12 + ,15 + ,46 + ,11 + ,12 + ,10 + ,16 + ,36 + ,8 + ,11 + ,8 + ,10 + ,30 + ,4 + ,13 + ,8 + ,17 + ,48 + ,7 + ,10 + ,11 + ,15 + ,45 + ,14 + ,15 + ,13 + ,15 + ,49 + ,11 + ,13 + ,16 + ,13 + ,55 + ,15 + ,15 + ,14 + ,14 + ,11 + ,17 + ,18 + ,11 + ,16 + ,52 + ,5 + ,13 + ,4 + ,11 + ,33 + ,4 + ,10 + ,14 + ,18 + ,47 + ,10 + ,16 + ,9 + ,14 + ,33 + ,11 + ,13 + ,14 + ,14 + ,44 + ,15 + ,15 + ,8 + ,14 + ,42 + ,10 + ,14 + ,8 + ,14 + ,55 + ,9 + ,15 + ,11 + ,15 + ,42 + ,12 + ,14 + ,12 + ,14 + ,46 + ,15 + ,13 + ,11 + ,15 + ,43 + ,7 + ,13 + ,14 + ,15 + ,46 + ,13 + ,15 + ,15 + ,15 + ,47 + ,12 + ,16 + ,16 + ,12 + ,33 + ,14 + ,14 + ,16 + ,19 + ,53 + ,14 + ,14 + ,14 + ,13 + ,42 + ,15 + ,14 + ,14 + ,15 + ,43 + ,12 + ,12 + ,12 + ,15 + ,44 + ,12 + ,13 + ,14 + ,17 + ,55 + ,16 + ,12 + ,8 + ,9 + ,40 + ,9 + ,12 + ,13 + ,15 + ,40 + ,15 + ,14 + ,16 + ,15 + ,46 + ,15 + ,14 + ,12 + ,16 + ,53 + ,6 + ,14 + ,16 + ,12 + ,49 + ,14 + ,16 + ,12 + ,17 + ,44 + ,15 + ,13 + ,11 + ,11 + ,35 + ,10 + ,14 + ,4 + ,15 + ,40 + ,6 + ,4 + ,16 + ,11 + ,44 + ,14 + ,16 + ,15 + ,15 + ,46 + ,12 + ,13 + ,10 + ,17 + ,45 + ,8 + ,16 + ,13 + ,14 + ,53 + ,11 + ,15 + ,15 + ,12 + ,45 + ,13 + ,14 + ,12 + ,14 + ,48 + ,9 + ,13 + ,14 + ,15 + ,46 + ,15 + ,14 + ,7 + ,16 + ,55 + ,13 + ,12 + ,19 + ,16 + ,47 + ,15 + ,15 + ,12 + ,14 + ,43 + ,14 + ,14 + ,12 + ,11 + ,38 + ,16 + ,13 + ,13 + ,12 + ,46 + ,14 + ,14 + ,15 + ,16 + ,53 + ,14 + ,16 + ,8 + ,14 + ,40 + ,10 + ,6 + ,12 + ,13 + ,47 + ,10 + ,13 + ,10 + ,13 + ,47 + ,4 + ,13 + ,8 + ,14 + ,42 + ,8 + ,14 + ,10 + ,16 + ,53 + ,15 + ,15 + ,15 + ,16 + ,43 + ,16 + ,14 + ,16 + ,12 + ,44 + ,12 + ,15 + ,13 + ,11 + ,42 + ,12 + ,13 + ,16 + ,13 + ,51 + ,15 + ,16 + ,9 + ,15 + ,54 + ,9 + ,12 + ,14 + ,13 + ,41 + ,12 + ,15 + ,14 + ,16 + ,51 + ,14 + ,12 + ,12 + ,13 + ,51 + ,11 + ,14) + ,dim=c(5 + ,154) + ,dimnames=list(c('Y1' + ,'X1' + ,'X2' + ,'X3' + ,'X4 ') + ,1:154)) > y <- array(NA,dim=c(5,154),dimnames=list(c('Y1','X1','X2','X3','X4 '),1:154)) > 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 = '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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Y1" > x[,par1] [1] 13 12 15 12 10 12 15 9 12 11 11 11 15 7 11 11 10 14 10 6 11 15 11 12 14 [26] 15 9 13 13 16 13 12 14 11 9 16 12 10 13 16 14 15 5 8 11 16 17 9 9 13 [51] 10 6 12 8 14 12 11 16 8 15 7 16 14 16 9 14 11 13 15 5 15 13 11 11 12 [76] 12 12 12 14 6 7 14 14 10 13 12 9 12 16 10 14 10 16 15 12 10 8 8 11 13 [101] 16 14 11 4 14 9 14 8 8 11 12 11 14 15 16 16 14 14 12 14 8 13 16 12 16 [126] 12 11 4 16 15 10 13 15 12 14 7 19 12 12 13 15 8 12 10 8 10 15 16 13 16 [151] 9 14 14 12 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) [ 4,13) [13,19] 85 69 > colnames(x) [1] "Y1" "X1" "X2" "X3" "X4." > colnames(x)[par1] [1] "Y1" > x[,par1] [1] [13,19] [ 4,13) [13,19] [ 4,13) [ 4,13) [ 4,13) [13,19] [ 4,13) [ 4,13) [10] [ 4,13) [ 4,13) [ 4,13) [13,19] [ 4,13) [ 4,13) [ 4,13) [ 4,13) [13,19] [19] [ 4,13) [ 4,13) [ 4,13) [13,19] [ 4,13) [ 4,13) [13,19] [13,19] [ 4,13) [28] [13,19] [13,19] [13,19] [13,19] [ 4,13) [13,19] [ 4,13) [ 4,13) [13,19] [37] [ 4,13) [ 4,13) [13,19] [13,19] [13,19] [13,19] [ 4,13) [ 4,13) [ 4,13) [46] [13,19] [13,19] [ 4,13) [ 4,13) [13,19] [ 4,13) [ 4,13) [ 4,13) [ 4,13) [55] [13,19] [ 4,13) [ 4,13) [13,19] [ 4,13) [13,19] [ 4,13) [13,19] [13,19] [64] [13,19] [ 4,13) [13,19] [ 4,13) [13,19] [13,19] [ 4,13) [13,19] [13,19] [73] [ 4,13) [ 4,13) [ 4,13) [ 4,13) [ 4,13) [ 4,13) [13,19] [ 4,13) [ 4,13) [82] [13,19] [13,19] [ 4,13) [13,19] [ 4,13) [ 4,13) [ 4,13) [13,19] [ 4,13) [91] [13,19] [ 4,13) [13,19] [13,19] [ 4,13) [ 4,13) [ 4,13) [ 4,13) [ 4,13) [100] [13,19] [13,19] [13,19] [ 4,13) [ 4,13) [13,19] [ 4,13) [13,19] [ 4,13) [109] [ 4,13) [ 4,13) [ 4,13) [ 4,13) [13,19] [13,19] [13,19] [13,19] [13,19] [118] [13,19] [ 4,13) [13,19] [ 4,13) [13,19] [13,19] [ 4,13) [13,19] [ 4,13) [127] [ 4,13) [ 4,13) [13,19] [13,19] [ 4,13) [13,19] [13,19] [ 4,13) [13,19] [136] [ 4,13) [13,19] [ 4,13) [ 4,13) [13,19] [13,19] [ 4,13) [ 4,13) [ 4,13) [145] [ 4,13) [ 4,13) [13,19] [13,19] [13,19] [13,19] [ 4,13) [13,19] [13,19] [154] [ 4,13) Levels: [ 4,13) [13,19] > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/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/rcomp/tmp/1run91292160974.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 1 604 171 2 146 479 [1] 0.7793548 [1] 0.7664 [1] 0.7735714 m.ct.x.pred m.ct.x.actu 1 2 1 53 22 2 19 46 [1] 0.7066667 [1] 0.7076923 [1] 0.7071429 > m Conditional inference tree with 4 terminal nodes Response: as.factor(Y1) Inputs: X1, X2, X3, X4. Number of observations: 154 1) X3 <= 11; criterion = 1, statistic = 37.533 2)* weights = 66 1) X3 > 11 3) X4. <= 13; criterion = 0.997, statistic = 11.521 4) X2 <= 41; criterion = 0.961, statistic = 6.639 5)* weights = 9 4) X2 > 41 6)* weights = 28 3) X4. > 13 7)* weights = 51 > postscript(file="/var/www/rcomp/tmp/213mc1292160974.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/rcomp/tmp/313mc1292160974.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,] 1 1 [3,] 2 2 [4,] 1 1 [5,] 1 1 [6,] 1 1 [7,] 2 2 [8,] 1 1 [9,] 1 2 [10,] 1 1 [11,] 1 2 [12,] 1 1 [13,] 2 2 [14,] 1 1 [15,] 1 1 [16,] 1 1 [17,] 1 1 [18,] 2 2 [19,] 1 1 [20,] 1 1 [21,] 1 1 [22,] 2 2 [23,] 1 2 [24,] 1 1 [25,] 2 2 [26,] 2 2 [27,] 1 2 [28,] 2 2 [29,] 2 2 [30,] 2 1 [31,] 2 1 [32,] 1 2 [33,] 2 2 [34,] 1 1 [35,] 1 1 [36,] 2 2 [37,] 1 1 [38,] 1 1 [39,] 2 2 [40,] 2 2 [41,] 2 2 [42,] 2 1 [43,] 1 1 [44,] 1 1 [45,] 1 1 [46,] 2 2 [47,] 2 2 [48,] 1 1 [49,] 1 1 [50,] 2 2 [51,] 1 1 [52,] 1 2 [53,] 1 2 [54,] 1 1 [55,] 2 2 [56,] 1 1 [57,] 1 1 [58,] 2 2 [59,] 1 1 [60,] 2 2 [61,] 1 1 [62,] 2 2 [63,] 2 2 [64,] 2 2 [65,] 1 1 [66,] 2 2 [67,] 1 2 [68,] 2 1 [69,] 2 2 [70,] 1 1 [71,] 2 2 [72,] 2 2 [73,] 1 1 [74,] 1 2 [75,] 1 1 [76,] 1 2 [77,] 1 1 [78,] 1 2 [79,] 2 1 [80,] 1 1 [81,] 1 1 [82,] 2 2 [83,] 2 2 [84,] 1 1 [85,] 2 1 [86,] 1 1 [87,] 1 1 [88,] 1 1 [89,] 2 2 [90,] 1 1 [91,] 2 1 [92,] 1 2 [93,] 2 2 [94,] 2 2 [95,] 1 1 [96,] 1 1 [97,] 1 1 [98,] 1 1 [99,] 1 2 [100,] 2 1 [101,] 2 2 [102,] 2 2 [103,] 1 1 [104,] 1 1 [105,] 2 1 [106,] 1 1 [107,] 2 2 [108,] 1 1 [109,] 1 1 [110,] 1 2 [111,] 1 2 [112,] 1 1 [113,] 2 2 [114,] 2 2 [115,] 2 2 [116,] 2 2 [117,] 2 2 [118,] 2 2 [119,] 1 2 [120,] 2 2 [121,] 1 1 [122,] 2 2 [123,] 2 2 [124,] 1 1 [125,] 2 2 [126,] 1 2 [127,] 1 1 [128,] 1 1 [129,] 2 2 [130,] 2 2 [131,] 1 1 [132,] 2 1 [133,] 2 2 [134,] 1 1 [135,] 2 2 [136,] 1 2 [137,] 2 2 [138,] 1 2 [139,] 1 1 [140,] 2 2 [141,] 2 2 [142,] 1 1 [143,] 1 1 [144,] 1 1 [145,] 1 1 [146,] 1 2 [147,] 2 2 [148,] 2 2 [149,] 2 2 [150,] 2 2 [151,] 1 1 [152,] 2 2 [153,] 2 2 [154,] 1 1 [ 4,13) [13,19] [ 4,13) 65 20 [13,19] 10 59 > postscript(file="/var/www/rcomp/tmp/4uvlf1292160974.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/rcomp/tmp/5gdkl1292160974.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/rcomp/tmp/6jei91292160974.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/rcomp/tmp/7mwzx1292160974.tab") + } > > try(system("convert tmp/213mc1292160974.ps tmp/213mc1292160974.png",intern=TRUE)) character(0) > try(system("convert tmp/313mc1292160974.ps tmp/313mc1292160974.png",intern=TRUE)) character(0) > try(system("convert tmp/4uvlf1292160974.ps tmp/4uvlf1292160974.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.580 0.680 3.248