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Type 'q()' to quit R. > x <- array(list(3 + ,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 + ,11 + ,5 + ,16 + ,14 + ,6 + ,12 + ,12 + ,14 + ,14 + ,4 + ,11 + ,6 + ,6 + ,9 + ,4 + ,15 + ,11 + ,16 + ,11 + ,5 + ,11 + ,12 + ,11 + ,12 + ,6 + ,7 + ,14 + ,12 + ,12 + ,4 + ,11 + ,14 + ,7 + ,13 + ,6 + ,11 + ,12 + ,13 + ,11 + ,4 + ,10 + ,12 + ,11 + ,12 + ,6 + ,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 + ,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 + ,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 + ,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 + ,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 + ,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 + ,16 + ,11 + ,14 + ,14 + ,6 + ,15 + ,12 + ,12 + ,16 + ,7 + ,16 + ,12 + ,14 + ,14 + ,6 + ,14 + ,12 + ,15 + ,14 + ,6 + ,11 + ,12 + ,8 + ,16 + ,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 + ,16 + ,12 + ,12 + ,15 + ,8 + ,13 + ,11 + ,12 + ,13 + ,7 + ,9 + ,11 + ,9 + ,12 + ,4 + ,14 + ,10 + ,12 + ,15 + ,6 + ,14 + ,11 + ,14 + ,12 + ,6 + ,12 + ,11 + ,11 + ,14 + ,2) + ,dim=c(5 + ,146) + ,dimnames=list(c('Popularity' + ,'Findingfriends' + ,'Knowingpeople' + ,'Liked' + ,'Celebrity ') + ,1:146)) > y <- array(NA,dim=c(5,146),dimnames=list(c('Popularity','Findingfriends','Knowingpeople','Liked','Celebrity '),1:146)) > 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 = '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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Popularity" > x[,par1] [1] 3 12 15 12 10 12 15 9 11 12 11 15 11 7 11 11 10 6 11 15 11 12 14 15 13 [26] 13 16 13 12 11 9 16 12 10 13 16 14 15 5 8 11 16 9 9 13 10 6 12 8 14 [51] 12 11 16 8 15 7 16 14 9 14 11 13 15 5 15 13 11 11 12 12 12 12 14 6 7 [76] 14 14 10 13 12 9 12 16 10 14 10 16 15 12 10 8 8 11 13 16 16 14 11 4 14 [101] 9 8 8 11 12 11 14 16 15 16 14 11 14 12 14 8 13 16 12 16 12 11 4 16 15 [126] 10 13 15 12 14 7 19 12 12 13 15 8 12 10 8 16 13 9 14 14 12 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 3 4 5 6 7 8 9 10 11 12 13 14 15 16 19 1 2 2 3 4 10 8 10 19 25 13 18 14 16 1 > colnames(x) [1] "Popularity" "Findingfriends" "Knowingpeople" "Liked" [5] "Celebrity." > colnames(x)[par1] [1] "Popularity" > x[,par1] [1] 3 12 15 12 10 12 15 9 11 12 11 15 11 7 11 11 10 6 11 15 11 12 14 15 13 [26] 13 16 13 12 11 9 16 12 10 13 16 14 15 5 8 11 16 9 9 13 10 6 12 8 14 [51] 12 11 16 8 15 7 16 14 9 14 11 13 15 5 15 13 11 11 12 12 12 12 14 6 7 [76] 14 14 10 13 12 9 12 16 10 14 10 16 15 12 10 8 8 11 13 16 16 14 11 4 14 [101] 9 8 8 11 12 11 14 16 15 16 14 11 14 12 14 8 13 16 12 16 12 11 4 16 15 [126] 10 13 15 12 14 7 19 12 12 13 15 8 12 10 8 16 13 9 14 14 12 > 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/1sr3s1323801143.tab") + } + } > m Conditional inference tree with 5 terminal nodes Response: Popularity Inputs: Findingfriends, Knowingpeople, Liked, Celebrity. Number of observations: 146 1) Celebrity. <= 4; criterion = 1, statistic = 57.929 2) Liked <= 12; criterion = 0.96, statistic = 6.602 3)* weights = 30 2) Liked > 12 4)* weights = 19 1) Celebrity. > 4 5) Knowingpeople <= 11; criterion = 1, statistic = 28.453 6)* weights = 27 5) Knowingpeople > 11 7) Celebrity. <= 6; criterion = 0.999, statistic = 12.689 8)* weights = 54 7) Celebrity. > 6 9)* weights = 16 > postscript(file="/var/www/rcomp/tmp/2j1y61323801143.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/3cso21323801143.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 3 10.73684 -7.7368421 2 12 11.14815 0.8518519 3 15 13.35185 1.6481481 4 12 11.14815 0.8518519 5 10 11.14815 -1.1481481 6 12 8.90000 3.1000000 7 15 15.06250 -0.0625000 8 9 8.90000 0.1000000 9 11 13.35185 -2.3518519 10 12 10.73684 1.2631579 11 11 8.90000 2.1000000 12 15 13.35185 1.6481481 13 11 11.14815 -0.1481481 14 7 8.90000 -1.9000000 15 11 11.14815 -0.1481481 16 11 8.90000 2.1000000 17 10 11.14815 -1.1481481 18 6 8.90000 -2.9000000 19 11 10.73684 0.2631579 20 15 15.06250 -0.0625000 21 11 13.35185 -2.3518519 22 12 8.90000 3.1000000 23 14 13.35185 0.6481481 24 15 13.35185 1.6481481 25 13 13.35185 -0.3518519 26 13 13.35185 -0.3518519 27 16 10.73684 5.2631579 28 13 8.90000 4.1000000 29 12 15.06250 -3.0625000 30 11 10.73684 0.2631579 31 9 8.90000 0.1000000 32 16 13.35185 2.6481481 33 12 11.14815 0.8518519 34 10 11.14815 -1.1481481 35 13 13.35185 -0.3518519 36 16 15.06250 0.9375000 37 14 13.35185 0.6481481 38 15 8.90000 6.1000000 39 5 8.90000 -3.9000000 40 8 8.90000 -0.9000000 41 11 11.14815 -0.1481481 42 16 15.06250 0.9375000 43 9 8.90000 0.1000000 44 9 13.35185 -4.3518519 45 13 13.35185 -0.3518519 46 10 11.14815 -1.1481481 47 6 13.35185 -7.3518519 48 12 13.35185 -1.3518519 49 8 10.73684 -2.7368421 50 14 13.35185 0.6481481 51 12 13.35185 -1.3518519 52 11 8.90000 2.1000000 53 16 13.35185 2.6481481 54 8 10.73684 -2.7368421 55 15 15.06250 -0.0625000 56 7 8.90000 -1.9000000 57 16 13.35185 2.6481481 58 14 13.35185 0.6481481 59 9 11.14815 -2.1481481 60 14 13.35185 0.6481481 61 11 13.35185 -2.3518519 62 13 11.14815 1.8518519 63 15 13.35185 1.6481481 64 5 8.90000 -3.9000000 65 15 13.35185 1.6481481 66 13 13.35185 -0.3518519 67 11 11.14815 -0.1481481 68 11 13.35185 -2.3518519 69 12 13.35185 -1.3518519 70 12 13.35185 -1.3518519 71 12 13.35185 -1.3518519 72 12 13.35185 -1.3518519 73 14 10.73684 3.2631579 74 6 8.90000 -2.9000000 75 7 8.90000 -1.9000000 76 14 13.35185 0.6481481 77 14 13.35185 0.6481481 78 10 11.14815 -1.1481481 79 13 8.90000 4.1000000 80 12 13.35185 -1.3518519 81 9 8.90000 0.1000000 82 12 11.14815 0.8518519 83 16 15.06250 0.9375000 84 10 8.90000 1.1000000 85 14 11.14815 2.8518519 86 10 13.35185 -3.3518519 87 16 15.06250 0.9375000 88 15 13.35185 1.6481481 89 12 11.14815 0.8518519 90 10 8.90000 1.1000000 91 8 11.14815 -3.1481481 92 8 8.90000 -0.9000000 93 11 13.35185 -2.3518519 94 13 11.14815 1.8518519 95 16 15.06250 0.9375000 96 16 15.06250 0.9375000 97 14 13.35185 0.6481481 98 11 10.73684 0.2631579 99 4 8.90000 -4.9000000 100 14 11.14815 2.8518519 101 9 10.73684 -1.7368421 102 8 10.73684 -2.7368421 103 8 10.73684 -2.7368421 104 11 13.35185 -2.3518519 105 12 15.06250 -3.0625000 106 11 11.14815 -0.1481481 107 14 13.35185 0.6481481 108 16 13.35185 2.6481481 109 15 15.06250 -0.0625000 110 16 13.35185 2.6481481 111 14 13.35185 0.6481481 112 11 11.14815 -0.1481481 113 14 8.90000 5.1000000 114 12 10.73684 1.2631579 115 14 13.35185 0.6481481 116 8 8.90000 -0.9000000 117 13 13.35185 -0.3518519 118 16 13.35185 2.6481481 119 12 11.14815 0.8518519 120 16 15.06250 0.9375000 121 12 13.35185 -1.3518519 122 11 11.14815 -0.1481481 123 4 8.90000 -4.9000000 124 16 15.06250 0.9375000 125 15 13.35185 1.6481481 126 10 10.73684 -0.7368421 127 13 11.14815 1.8518519 128 15 13.35185 1.6481481 129 12 10.73684 1.2631579 130 14 13.35185 0.6481481 131 7 8.90000 -1.9000000 132 19 13.35185 5.6481481 133 12 13.35185 -1.3518519 134 12 10.73684 1.2631579 135 13 13.35185 -0.3518519 136 15 10.73684 4.2631579 137 8 8.90000 -0.9000000 138 12 10.73684 1.2631579 139 10 11.14815 -1.1481481 140 8 11.14815 -3.1481481 141 16 15.06250 0.9375000 142 13 15.06250 -2.0625000 143 9 8.90000 0.1000000 144 14 13.35185 0.6481481 145 14 13.35185 0.6481481 146 12 10.73684 1.2631579 > 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/rcomp/tmp/4g2oi1323801143.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/53cfj1323801143.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/6fkvz1323801143.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/71ldo1323801143.tab") + } > > try(system("convert tmp/2j1y61323801143.ps tmp/2j1y61323801143.png",intern=TRUE)) character(0) > try(system("convert tmp/3cso21323801143.ps tmp/3cso21323801143.png",intern=TRUE)) character(0) > try(system("convert tmp/4g2oi1323801143.ps tmp/4g2oi1323801143.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.000 0.120 3.118