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Type 'q()' to quit R. > x <- array(list(0 + ,1 + ,24 + ,14 + ,11 + ,12 + ,24 + ,26 + ,1 + ,1 + ,25 + ,11 + ,7 + ,8 + ,25 + ,23 + ,1 + ,0 + ,17 + ,6 + ,17 + ,8 + ,30 + ,25 + ,0 + ,1 + ,18 + ,12 + ,10 + ,8 + ,19 + ,23 + ,1 + ,0 + ,16 + ,10 + ,12 + ,7 + ,22 + ,29 + ,1 + ,1 + ,20 + ,10 + ,11 + ,4 + ,25 + ,25 + ,1 + ,1 + ,16 + ,11 + ,11 + ,11 + ,23 + ,21 + ,1 + ,1 + ,18 + ,16 + ,12 + ,7 + ,17 + ,22 + ,1 + ,1 + ,17 + ,11 + ,13 + ,7 + ,21 + ,25 + ,0 + ,1 + ,23 + ,13 + ,14 + ,12 + ,19 + ,24 + ,1 + ,1 + ,30 + ,12 + ,16 + ,10 + ,19 + ,18 + ,1 + ,1 + ,18 + ,12 + ,10 + ,8 + ,16 + ,15 + ,0 + ,1 + ,15 + ,11 + ,11 + ,8 + ,23 + ,22 + ,0 + ,1 + ,12 + ,4 + ,15 + ,4 + ,27 + ,28 + ,1 + ,1 + ,21 + ,9 + ,9 + ,9 + ,22 + ,20 + ,0 + ,1 + ,20 + ,8 + ,17 + ,7 + ,22 + ,24 + ,1 + ,1 + ,27 + ,15 + ,11 + ,9 + ,23 + ,21 + ,0 + ,1 + ,34 + ,16 + ,18 + ,11 + ,21 + ,20 + ,1 + ,1 + ,21 + ,9 + ,14 + ,13 + ,19 + ,21 + ,0 + ,1 + ,31 + ,14 + ,10 + ,8 + ,18 + ,23 + ,0 + ,1 + ,19 + ,11 + ,11 + ,8 + ,20 + ,28 + ,1 + ,1 + ,16 + 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+ ,10 + ,20 + ,29 + ,1 + ,1 + ,24 + ,9 + ,13 + ,10 + ,19 + ,15 + ,1 + ,1 + ,25 + ,14 + ,15 + ,11 + ,22 + ,21 + ,1 + ,1 + ,13 + ,8 + ,12 + ,7 + ,14 + ,19 + ,1 + ,1 + ,28 + ,8 + ,16 + ,12 + ,18 + ,24 + ,1 + ,0 + ,25 + ,7 + ,18 + ,11 + ,35 + ,17 + ,1 + ,1 + ,9 + ,6 + ,8 + ,11 + ,29 + ,23 + ,0 + ,1 + ,17 + ,11 + ,9 + ,6 + ,20 + ,19 + ,0 + ,1 + ,25 + ,14 + ,15 + ,9 + ,22 + ,24 + ,1 + ,1 + ,15 + ,8 + ,6 + ,6 + ,20 + ,25 + ,0 + ,1 + ,19 + ,20 + ,8 + ,7 + ,19 + ,25 + ,1 + ,0 + ,15 + ,8 + ,10 + ,4 + ,22 + ,24 + ,1 + ,1 + ,20 + ,11 + ,11 + ,8 + ,24 + ,26 + ,1 + ,1 + ,18 + ,10 + ,14 + ,9 + ,21 + ,26 + ,1 + ,1 + ,33 + ,14 + ,11 + ,8 + ,26 + ,25 + ,1 + ,1 + ,16 + ,9 + ,12 + ,8 + ,16 + ,21 + ,0 + ,1 + ,17 + ,9 + ,11 + ,5 + ,23 + ,26 + ,1 + ,1 + ,16 + ,8 + ,9 + ,4 + ,18 + ,23 + ,0 + ,1 + ,21 + ,10 + ,12 + ,8 + ,16 + ,23 + ,0 + ,1 + ,26 + ,13 + ,20 + ,10 + ,26 + ,22 + ,1 + ,1 + ,18 + ,12 + ,13 + ,9 + ,21 + ,13 + ,1 + ,1 + ,22 + ,13 + ,12 + ,13 + ,22 + ,15 + ,1 + ,1 + ,30 + ,14 + ,9 + ,9 + ,23 + ,14 + ,1 + ,1 + ,24 + ,14 + ,24 + ,20 + ,21 + ,10 + ,1 + ,1 + ,29 + ,16 + ,11 + ,6 + ,27 + ,24 + ,1 + ,1 + ,31 + ,9 + ,17 + ,9 + ,25 + ,19 + ,1 + ,0 + ,20 + ,9 + ,11 + ,7 + ,21 + ,20 + ,1 + ,1 + ,20 + ,7 + ,11 + ,9 + ,26 + ,22 + ,1 + ,1 + ,28 + ,16 + ,16 + ,8 + ,24 + ,24 + ,1 + ,1 + ,17 + ,9 + ,13 + ,6 + ,19 + ,21 + ,0 + ,1 + ,28 + ,14 + ,11 + ,8 + ,24 + ,24 + ,1 + ,1 + ,31 + ,16 + ,19 + ,16 + ,17 + ,20) + ,dim=c(8 + ,120) + ,dimnames=list(c('G' + ,'B' + ,'CM' + ,'D' + ,'PE' + ,'PC' + ,'PS' + ,'O ') + ,1:120)) > y <- array(NA,dim=c(8,120),dimnames=list(c('G','B','CM','D','PE','PC','PS','O '),1:120)) > 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 = '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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "PE" > x[,par1] [1] 11 7 17 10 12 11 11 12 13 14 16 10 11 15 9 17 11 18 14 10 11 15 15 13 16 [26] 13 9 18 18 12 17 9 9 18 12 18 14 15 16 10 11 14 9 17 5 12 12 6 24 12 [51] 12 14 7 12 14 8 11 9 11 10 11 12 9 18 15 12 13 14 10 13 13 11 13 16 11 [76] 16 14 8 9 15 11 21 14 18 12 13 12 19 11 13 15 12 16 18 8 9 15 6 8 10 [101] 11 14 11 12 11 9 12 20 13 12 9 24 11 17 11 11 16 13 11 19 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 24 1 2 2 4 11 7 21 17 11 10 8 7 5 8 2 1 1 2 > colnames(x) [1] "G" "B" "CM" "D" "PE" "PC" "PS" "O." > colnames(x)[par1] [1] "PE" > x[,par1] [1] 11 7 17 10 12 11 11 12 13 14 16 10 11 15 9 17 11 18 14 10 11 15 15 13 16 [26] 13 9 18 18 12 17 9 9 18 12 18 14 15 16 10 11 14 9 17 5 12 12 6 24 12 [51] 12 14 7 12 14 8 11 9 11 10 11 12 9 18 15 12 13 14 10 13 13 11 13 16 11 [76] 16 14 8 9 15 11 21 14 18 12 13 12 19 11 13 15 12 16 18 8 9 15 6 8 10 [101] 11 14 11 12 11 9 12 20 13 12 9 24 11 17 11 11 16 13 11 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/11or61291986224.tab") + } + } > m Conditional inference tree with 3 terminal nodes Response: PE Inputs: G, B, CM, D, PC, PS, O. Number of observations: 120 1) PC <= 9; criterion = 1, statistic = 44.685 2)* weights = 91 1) PC > 9 3) CM <= 23; criterion = 0.995, statistic = 11.4 4)* weights = 11 3) CM > 23 5)* weights = 18 > postscript(file="/var/www/rcomp/tmp/21or61291986224.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/31or61291986224.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 11 17.83333 -6.8333333 2 7 11.80220 -4.8021978 3 17 11.80220 5.1978022 4 10 11.80220 -1.8021978 5 12 11.80220 0.1978022 6 11 11.80220 -0.8021978 7 11 13.00000 -2.0000000 8 12 11.80220 0.1978022 9 13 11.80220 1.1978022 10 14 13.00000 1.0000000 11 16 17.83333 -1.8333333 12 10 11.80220 -1.8021978 13 11 11.80220 -0.8021978 14 15 11.80220 3.1978022 15 9 11.80220 -2.8021978 16 17 11.80220 5.1978022 17 11 11.80220 -0.8021978 18 18 17.83333 0.1666667 19 14 13.00000 1.0000000 20 10 11.80220 -1.8021978 21 11 11.80220 -0.8021978 22 15 11.80220 3.1978022 23 15 11.80220 3.1978022 24 13 11.80220 1.1978022 25 16 11.80220 4.1978022 26 13 11.80220 1.1978022 27 9 11.80220 -2.8021978 28 18 17.83333 0.1666667 29 18 11.80220 6.1978022 30 12 11.80220 0.1978022 31 17 11.80220 5.1978022 32 9 11.80220 -2.8021978 33 9 11.80220 -2.8021978 34 18 17.83333 0.1666667 35 12 11.80220 0.1978022 36 18 17.83333 0.1666667 37 14 11.80220 2.1978022 38 15 11.80220 3.1978022 39 16 11.80220 4.1978022 40 10 11.80220 -1.8021978 41 11 11.80220 -0.8021978 42 14 13.00000 1.0000000 43 9 11.80220 -2.8021978 44 17 11.80220 5.1978022 45 5 11.80220 -6.8021978 46 12 11.80220 0.1978022 47 12 11.80220 0.1978022 48 6 11.80220 -5.8021978 49 24 17.83333 6.1666667 50 12 11.80220 0.1978022 51 12 11.80220 0.1978022 52 14 11.80220 2.1978022 53 7 11.80220 -4.8021978 54 12 11.80220 0.1978022 55 14 11.80220 2.1978022 56 8 11.80220 -3.8021978 57 11 11.80220 -0.8021978 58 9 11.80220 -2.8021978 59 11 11.80220 -0.8021978 60 10 11.80220 -1.8021978 61 11 11.80220 -0.8021978 62 12 11.80220 0.1978022 63 9 11.80220 -2.8021978 64 18 17.83333 0.1666667 65 15 11.80220 3.1978022 66 12 11.80220 0.1978022 67 13 11.80220 1.1978022 68 14 11.80220 2.1978022 69 10 11.80220 -1.8021978 70 13 11.80220 1.1978022 71 13 13.00000 0.0000000 72 11 11.80220 -0.8021978 73 13 11.80220 1.1978022 74 16 13.00000 3.0000000 75 11 11.80220 -0.8021978 76 16 17.83333 -1.8333333 77 14 11.80220 2.1978022 78 8 11.80220 -3.8021978 79 9 11.80220 -2.8021978 80 15 11.80220 3.1978022 81 11 13.00000 -2.0000000 82 21 17.83333 3.1666667 83 14 11.80220 2.1978022 84 18 17.83333 0.1666667 85 12 11.80220 0.1978022 86 13 11.80220 1.1978022 87 12 11.80220 0.1978022 88 19 13.00000 6.0000000 89 11 13.00000 -2.0000000 90 13 17.83333 -4.8333333 91 15 17.83333 -2.8333333 92 12 11.80220 0.1978022 93 16 17.83333 -1.8333333 94 18 17.83333 0.1666667 95 8 13.00000 -5.0000000 96 9 11.80220 -2.8021978 97 15 11.80220 3.1978022 98 6 11.80220 -5.8021978 99 8 11.80220 -3.8021978 100 10 11.80220 -1.8021978 101 11 11.80220 -0.8021978 102 14 11.80220 2.1978022 103 11 11.80220 -0.8021978 104 12 11.80220 0.1978022 105 11 11.80220 -0.8021978 106 9 11.80220 -2.8021978 107 12 11.80220 0.1978022 108 20 17.83333 2.1666667 109 13 11.80220 1.1978022 110 12 13.00000 -1.0000000 111 9 11.80220 -2.8021978 112 24 17.83333 6.1666667 113 11 11.80220 -0.8021978 114 17 11.80220 5.1978022 115 11 11.80220 -0.8021978 116 11 11.80220 -0.8021978 117 16 11.80220 4.1978022 118 13 11.80220 1.1978022 119 11 11.80220 -0.8021978 120 19 17.83333 1.1666667 > 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/4tf8r1291986224.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/57p6i1291986224.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/6iy531291986224.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/7lgmr1291986224.tab") + } > > try(system("convert tmp/21or61291986224.ps tmp/21or61291986224.png",intern=TRUE)) character(0) > try(system("convert tmp/31or61291986224.ps tmp/31or61291986224.png",intern=TRUE)) character(0) > try(system("convert tmp/4tf8r1291986224.ps tmp/4tf8r1291986224.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.48 0.44 3.01