R version 2.8.0 (2008-10-20) Copyright (C) 2008 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. Natural language support but running in an English locale 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 + ,13 + ,14 + ,13 + ,3 + ,12 + ,12 + ,8 + ,13 + ,5 + ,15 + ,10 + ,12 + ,16 + ,6 + ,12 + ,9 + ,7 + ,12 + ,6 + ,10 + ,10 + ,10 + ,11 + ,5 + ,12 + ,12 + ,7 + ,12 + ,3 + ,15 + ,13 + ,16 + ,18 + ,8 + ,9 + ,12 + ,11 + ,11 + ,4 + ,12 + ,12 + ,14 + ,14 + ,4 + ,11 + ,6 + ,6 + ,9 + ,4 + ,11 + ,5 + ,16 + ,14 + ,6 + ,11 + ,12 + ,11 + ,12 + ,6 + ,15 + ,11 + ,16 + ,11 + ,5 + ,7 + ,14 + ,12 + ,12 + ,4 + ,11 + ,14 + ,7 + ,13 + ,6 + ,11 + ,12 + ,13 + ,11 + ,4 + ,10 + ,12 + ,11 + ,12 + ,6 + ,14 + ,11 + ,15 + ,16 + ,6 + ,10 + ,11 + ,7 + ,9 + ,4 + ,6 + ,7 + ,9 + ,11 + ,4 + ,11 + ,9 + ,7 + ,13 + ,2 + ,15 + ,11 + ,14 + ,15 + ,7 + ,11 + ,11 + ,15 + ,10 + ,5 + ,12 + ,12 + ,7 + ,11 + ,4 + ,14 + ,12 + ,15 + ,13 + ,6 + ,15 + ,11 + ,17 + ,16 + ,6 + ,9 + ,11 + ,15 + ,15 + ,7 + ,13 + ,8 + ,14 + ,14 + ,5 + ,13 + ,9 + ,14 + ,14 + ,6 + ,16 + ,12 + ,8 + ,14 + ,4 + ,13 + ,10 + ,8 + ,8 + ,4 + ,12 + ,10 + ,14 + ,13 + ,7 + ,14 + ,12 + ,14 + ,15 + ,7 + ,11 + ,8 + ,8 + ,13 + ,4 + ,9 + ,12 + ,11 + ,11 + ,4 + ,16 + ,11 + ,16 + ,15 + ,6 + ,12 + ,12 + ,10 + ,15 + ,6 + ,10 + ,7 + ,8 + ,9 + ,5 + ,13 + ,11 + ,14 + ,13 + ,6 + ,16 + ,11 + ,16 + ,16 + ,7 + ,14 + ,12 + ,13 + ,13 + ,6 + ,15 + ,9 + ,5 + ,11 + ,3 + ,5 + ,15 + ,8 + ,12 + ,3 + ,8 + ,11 + ,10 + ,12 + ,4 + ,11 + ,11 + ,8 + ,12 + ,6 + ,16 + ,11 + ,13 + ,14 + ,7 + ,17 + ,11 + ,15 + ,14 + ,5 + ,9 + ,15 + ,6 + ,8 + ,4 + ,9 + ,11 + ,12 + ,13 + ,5 + ,13 + ,12 + ,16 + ,16 + ,6 + ,10 + ,12 + ,5 + ,13 + ,6 + ,6 + ,9 + ,15 + ,11 + ,6 + ,12 + ,12 + ,12 + ,14 + ,5 + ,8 + ,12 + ,8 + ,13 + ,4 + ,14 + ,13 + ,13 + ,13 + ,5 + ,12 + ,11 + ,14 + ,13 + ,5 + ,11 + ,9 + ,12 + ,12 + ,4 + ,16 + ,9 + ,16 + ,16 + ,6 + ,8 + ,11 + ,10 + ,15 + ,2 + ,15 + ,11 + ,15 + ,15 + ,8 + ,7 + ,12 + ,8 + ,12 + ,3 + ,16 + ,12 + ,16 + ,14 + ,6 + ,14 + ,9 + ,19 + ,12 + ,6 + ,16 + ,11 + ,14 + ,15 + ,6 + ,9 + ,9 + ,6 + ,12 + ,5 + ,14 + ,12 + ,13 + ,13 + ,5 + ,11 + ,12 + ,15 + ,12 + ,6 + ,13 + ,12 + ,7 + ,12 + ,5 + ,15 + ,12 + ,13 + ,13 + ,6 + ,5 + ,14 + ,4 + ,5 + ,2 + ,15 + ,11 + ,14 + ,13 + ,5 + ,13 + ,12 + ,13 + ,13 + ,5 + ,11 + ,11 + ,11 + ,14 + ,5 + ,11 + ,6 + ,14 + ,17 + ,6 + ,12 + ,10 + ,12 + ,13 + ,6 + ,12 + ,12 + ,15 + ,13 + ,6 + ,12 + ,13 + ,14 + ,12 + ,5 + ,12 + ,8 + ,13 + ,13 + ,5 + ,14 + ,12 + ,8 + ,14 + ,4 + ,6 + ,12 + ,6 + ,11 + ,2 + ,7 + ,12 + ,7 + ,12 + ,4 + ,14 + ,6 + ,13 + ,12 + ,6 + ,14 + ,11 + ,13 + ,16 + ,6 + ,10 + ,10 + ,11 + ,12 + ,5 + ,13 + ,12 + ,5 + ,12 + ,3 + ,12 + ,13 + ,12 + ,12 + ,6 + ,9 + ,11 + ,8 + ,10 + ,4 + ,12 + ,7 + ,11 + ,15 + ,5 + ,16 + ,11 + ,14 + ,15 + ,8 + ,10 + ,11 + ,9 + ,12 + ,4 + ,14 + ,11 + ,10 + ,16 + ,6 + ,10 + ,11 + ,13 + ,15 + ,6 + ,16 + ,12 + ,16 + ,16 + ,7 + ,15 + ,10 + ,16 + ,13 + ,6 + ,12 + ,11 + ,11 + ,12 + ,5 + ,10 + ,12 + ,8 + ,11 + ,4 + ,8 + ,7 + ,4 + ,13 + ,6 + ,8 + ,13 + ,7 + ,10 + ,3 + ,11 + ,8 + ,14 + ,15 + ,5 + ,13 + ,12 + ,11 + ,13 + ,6 + ,16 + ,11 + ,17 + ,16 + ,7 + ,16 + ,12 + ,15 + ,15 + ,7 + ,14 + ,14 + ,17 + ,18 + ,6 + ,11 + ,10 + ,5 + ,13 + ,3 + ,4 + ,10 + ,4 + ,10 + ,2 + ,14 + ,13 + ,10 + ,16 + ,8 + ,9 + ,10 + ,11 + ,13 + ,3 + ,14 + ,11 + ,15 + ,15 + ,8 + ,8 + ,10 + ,10 + ,14 + ,3 + ,8 + ,7 + ,9 + ,15 + ,4 + ,11 + ,10 + ,12 + ,14 + ,5 + ,12 + ,8 + ,15 + ,13 + ,7 + ,11 + ,12 + ,7 + ,13 + ,6 + ,14 + ,12 + ,13 + ,15 + ,6 + ,15 + ,12 + ,12 + ,16 + ,7 + ,16 + ,11 + ,14 + ,14 + ,6 + ,16 + ,12 + ,14 + ,14 + ,6 + ,11 + ,12 + ,8 + ,16 + ,6 + ,14 + ,12 + ,15 + ,14 + ,6 + ,14 + ,11 + ,12 + ,12 + ,4 + ,12 + ,12 + ,12 + ,13 + ,4 + ,14 + ,11 + ,16 + ,12 + ,5 + ,8 + ,11 + ,9 + ,12 + ,4 + ,13 + ,13 + ,15 + ,14 + ,6 + ,16 + ,12 + ,15 + ,14 + ,6 + ,12 + ,12 + ,6 + ,14 + ,5 + ,16 + ,12 + ,14 + ,16 + ,8 + ,12 + ,12 + ,15 + ,13 + ,6 + ,11 + ,8 + ,10 + ,14 + ,5 + ,4 + ,8 + ,6 + ,4 + ,4 + ,16 + ,12 + ,14 + ,16 + ,8 + ,15 + ,11 + ,12 + ,13 + ,6 + ,10 + ,12 + ,8 + ,16 + ,4 + ,13 + ,13 + ,11 + ,15 + ,6 + ,15 + ,12 + ,13 + ,14 + ,6 + ,12 + ,12 + ,9 + ,13 + ,4 + ,14 + ,11 + ,15 + ,14 + ,6 + ,7 + ,12 + ,13 + ,12 + ,3 + ,19 + ,12 + ,15 + ,15 + ,6 + ,12 + ,10 + ,14 + ,14 + ,5 + ,12 + ,11 + ,16 + ,13 + ,4 + ,13 + ,12 + ,14 + ,14 + ,6 + ,15 + ,12 + ,14 + ,16 + ,4 + ,8 + ,10 + ,10 + ,6 + ,4 + ,12 + ,12 + ,10 + ,13 + ,4 + ,10 + ,13 + ,4 + ,13 + ,6 + ,8 + ,12 + ,8 + ,14 + ,5 + ,10 + ,15 + ,15 + ,15 + ,6 + ,15 + ,11 + ,16 + ,14 + ,6 + ,16 + ,12 + ,12 + ,15 + ,8 + ,13 + ,11 + ,12 + ,13 + ,7 + ,16 + ,12 + ,15 + ,16 + ,7 + ,9 + ,11 + ,9 + ,12 + ,4 + ,14 + ,10 + ,12 + ,15 + ,6 + ,14 + ,11 + ,14 + ,12 + ,6 + ,12 + ,11 + ,11 + ,14 + ,2) + ,dim=c(5 + ,156) + ,dimnames=list(c('Popularity' + ,'FindingFriends' + ,'KnowingPeople' + ,'Liked' + ,'Celebrity') + ,1:156)) > y <- array(NA,dim=c(5,156),dimnames=list(c('Popularity','FindingFriends','KnowingPeople','Liked','Celebrity'),1:156)) > 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 = '' > par2 = 'none' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Popularity" > x[,par1] [1] 13 12 15 12 10 12 15 9 12 11 11 11 15 7 11 11 10 14 10 6 11 15 11 12 14 [26] 15 9 13 13 16 13 12 14 11 9 16 12 10 13 16 14 15 5 8 11 16 17 9 9 13 [51] 10 6 12 8 14 12 11 16 8 15 7 16 14 16 9 14 11 13 15 5 15 13 11 11 12 [76] 12 12 12 14 6 7 14 14 10 13 12 9 12 16 10 14 10 16 15 12 10 8 8 11 13 [101] 16 16 14 11 4 14 9 14 8 8 11 12 11 14 15 16 16 11 14 14 12 14 8 13 16 [126] 12 16 12 11 4 16 15 10 13 15 12 14 7 19 12 12 13 15 8 12 10 8 10 15 16 [151] 13 16 9 14 14 12 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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 5 6 7 8 9 10 11 12 13 14 15 16 17 19 2 2 3 4 10 9 12 19 25 14 21 15 18 1 1 > colnames(x) [1] "Popularity" "FindingFriends" "KnowingPeople" "Liked" [5] "Celebrity" > colnames(x)[par1] [1] "Popularity" > 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 16 14 11 4 14 9 14 8 8 11 12 11 14 15 16 16 11 14 14 12 14 8 13 16 [126] 12 16 12 11 4 16 15 10 13 15 12 14 7 19 12 12 13 15 8 12 10 8 10 15 16 [151] 13 16 9 14 14 12 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/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/freestat/rcomp/tmp/10cpr1292942763.tab") + } + } > m Conditional inference tree with 5 terminal nodes Response: Popularity Inputs: FindingFriends, KnowingPeople, Liked, Celebrity Number of observations: 156 1) Celebrity <= 4; criterion = 1, statistic = 55.809 2) Liked <= 12; criterion = 0.986, statistic = 8.463 3)* weights = 31 2) Liked > 12 4)* weights = 19 1) Celebrity > 4 5) KnowingPeople <= 11; criterion = 1, statistic = 28.43 6)* weights = 27 5) KnowingPeople > 11 7) Liked <= 13; criterion = 0.995, statistic = 10.379 8)* weights = 29 7) Liked > 13 9)* weights = 50 > postscript(file="/var/www/html/freestat/rcomp/tmp/2al7u1292942763.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/freestat/rcomp/tmp/3al7u1292942763.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 13 11.263158 1.73684211 2 12 11.148148 0.85185185 3 15 14.320000 0.68000000 4 12 11.148148 0.85185185 5 10 11.148148 -1.14814815 6 12 8.935484 3.06451613 7 15 14.320000 0.68000000 8 9 8.935484 0.06451613 9 12 11.263158 0.73684211 10 11 8.935484 2.06451613 11 11 14.320000 -3.32000000 12 11 11.148148 -0.14814815 13 15 12.793103 2.20689655 14 7 8.935484 -1.93548387 15 11 11.148148 -0.14814815 16 11 8.935484 2.06451613 17 10 11.148148 -1.14814815 18 14 14.320000 -0.32000000 19 10 8.935484 1.06451613 20 6 8.935484 -2.93548387 21 11 11.263158 -0.26315789 22 15 14.320000 0.68000000 23 11 12.793103 -1.79310345 24 12 8.935484 3.06451613 25 14 12.793103 1.20689655 26 15 14.320000 0.68000000 27 9 14.320000 -5.32000000 28 13 14.320000 -1.32000000 29 13 14.320000 -1.32000000 30 16 11.263158 4.73684211 31 13 8.935484 4.06451613 32 12 12.793103 -0.79310345 33 14 14.320000 -0.32000000 34 11 11.263158 -0.26315789 35 9 8.935484 0.06451613 36 16 14.320000 1.68000000 37 12 11.148148 0.85185185 38 10 11.148148 -1.14814815 39 13 12.793103 0.20689655 40 16 14.320000 1.68000000 41 14 12.793103 1.20689655 42 15 8.935484 6.06451613 43 5 8.935484 -3.93548387 44 8 8.935484 -0.93548387 45 11 11.148148 -0.14814815 46 16 14.320000 1.68000000 47 17 14.320000 2.68000000 48 9 8.935484 0.06451613 49 9 12.793103 -3.79310345 50 13 14.320000 -1.32000000 51 10 11.148148 -1.14814815 52 6 12.793103 -6.79310345 53 12 14.320000 -2.32000000 54 8 11.263158 -3.26315789 55 14 12.793103 1.20689655 56 12 12.793103 -0.79310345 57 11 8.935484 2.06451613 58 16 14.320000 1.68000000 59 8 11.263158 -3.26315789 60 15 14.320000 0.68000000 61 7 8.935484 -1.93548387 62 16 14.320000 1.68000000 63 14 12.793103 1.20689655 64 16 14.320000 1.68000000 65 9 11.148148 -2.14814815 66 14 12.793103 1.20689655 67 11 12.793103 -1.79310345 68 13 11.148148 1.85185185 69 15 12.793103 2.20689655 70 5 8.935484 -3.93548387 71 15 12.793103 2.20689655 72 13 12.793103 0.20689655 73 11 11.148148 -0.14814815 74 11 14.320000 -3.32000000 75 12 12.793103 -0.79310345 76 12 12.793103 -0.79310345 77 12 12.793103 -0.79310345 78 12 12.793103 -0.79310345 79 14 11.263158 2.73684211 80 6 8.935484 -2.93548387 81 7 8.935484 -1.93548387 82 14 12.793103 1.20689655 83 14 14.320000 -0.32000000 84 10 11.148148 -1.14814815 85 13 8.935484 4.06451613 86 12 12.793103 -0.79310345 87 9 8.935484 0.06451613 88 12 11.148148 0.85185185 89 16 14.320000 1.68000000 90 10 8.935484 1.06451613 91 14 11.148148 2.85185185 92 10 14.320000 -4.32000000 93 16 14.320000 1.68000000 94 15 12.793103 2.20689655 95 12 11.148148 0.85185185 96 10 8.935484 1.06451613 97 8 11.148148 -3.14814815 98 8 8.935484 -0.93548387 99 11 14.320000 -3.32000000 100 13 11.148148 1.85185185 101 16 14.320000 1.68000000 102 16 14.320000 1.68000000 103 14 14.320000 -0.32000000 104 11 11.263158 -0.26315789 105 4 8.935484 -4.93548387 106 14 11.148148 2.85185185 107 9 11.263158 -2.26315789 108 14 14.320000 -0.32000000 109 8 11.263158 -3.26315789 110 8 11.263158 -3.26315789 111 11 14.320000 -3.32000000 112 12 12.793103 -0.79310345 113 11 11.148148 -0.14814815 114 14 14.320000 -0.32000000 115 15 14.320000 0.68000000 116 16 14.320000 1.68000000 117 16 14.320000 1.68000000 118 11 11.148148 -0.14814815 119 14 14.320000 -0.32000000 120 14 8.935484 5.06451613 121 12 11.263158 0.73684211 122 14 12.793103 1.20689655 123 8 8.935484 -0.93548387 124 13 14.320000 -1.32000000 125 16 14.320000 1.68000000 126 12 11.148148 0.85185185 127 16 14.320000 1.68000000 128 12 12.793103 -0.79310345 129 11 11.148148 -0.14814815 130 4 8.935484 -4.93548387 131 16 14.320000 1.68000000 132 15 12.793103 2.20689655 133 10 11.263158 -1.26315789 134 13 11.148148 1.85185185 135 15 14.320000 0.68000000 136 12 11.263158 0.73684211 137 14 14.320000 -0.32000000 138 7 8.935484 -1.93548387 139 19 14.320000 4.68000000 140 12 14.320000 -2.32000000 141 12 11.263158 0.73684211 142 13 14.320000 -1.32000000 143 15 11.263158 3.73684211 144 8 8.935484 -0.93548387 145 12 11.263158 0.73684211 146 10 11.148148 -1.14814815 147 8 11.148148 -3.14814815 148 10 14.320000 -4.32000000 149 15 14.320000 0.68000000 150 16 14.320000 1.68000000 151 13 12.793103 0.20689655 152 16 14.320000 1.68000000 153 9 8.935484 0.06451613 154 14 14.320000 -0.32000000 155 14 12.793103 1.20689655 156 12 11.263158 0.73684211 > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } > postscript(file="/var/www/html/freestat/rcomp/tmp/4lv6f1292942763.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/freestat/rcomp/tmp/5ov421292942763.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/freestat/rcomp/tmp/6se2q1292942763.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/freestat/rcomp/tmp/7de1w1292942763.tab") + } > > try(system("convert tmp/2al7u1292942763.ps tmp/2al7u1292942763.png",intern=TRUE)) character(0) > try(system("convert tmp/3al7u1292942763.ps tmp/3al7u1292942763.png",intern=TRUE)) character(0) > try(system("convert tmp/4lv6f1292942763.ps tmp/4lv6f1292942763.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.495 0.746 4.636