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(1 + ,1 + ,4 + ,0 + ,2 + ,1 + ,1 + ,0 + ,0 + ,2 + ,0 + ,1 + ,4 + ,1 + ,1.5 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,0 + ,1 + ,2 + ,1 + ,1 + ,0 + ,1 + ,2 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,1 + ,4 + ,1 + ,2 + ,1 + ,1 + ,1 + ,0 + ,2 + ,0 + ,0 + ,4 + ,0 + ,2 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,1 + ,2 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,NA + ,NA + ,1 + ,1 + ,0 + ,1 + ,2 + ,1 + ,1 + ,1 + ,0 + ,2 + ,1 + ,1 + ,0 + ,1 + ,0.5 + ,0 + ,1 + ,0 + ,1 + ,2 + ,0 + ,0 + ,2 + ,1 + ,0 + ,1 + ,1 + ,2 + ,1 + ,2 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,2 + ,NA + ,NA + ,1 + ,0 + ,0 + ,NA + ,NA + ,1 + ,1 + ,3 + ,1 + ,2 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,NA + ,NA + ,0 + ,0 + ,0 + ,NA + ,NA + ,0 + ,0 + ,1 + ,0 + ,2 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0.5 + ,1 + ,1 + ,4 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,0.5 + ,0 + ,0 + ,1 + ,NA + ,NA + ,0 + ,0 + ,0 + ,1 + ,0.5 + ,1 + ,1 + ,0 + ,NA + ,NA + ,1 + ,1 + ,4 + ,0 + ,2 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,4 + ,1 + ,2 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,1 + ,4 + ,1 + ,2 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,0.5 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,4 + ,1 + ,2 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,1 + ,1 + ,4 + ,1 + ,2 + ,0 + ,0 + ,4 + ,0 + ,0.5 + ,0 + ,1 + ,0 + ,1 + ,2 + ,1 + ,1 + ,1 + ,1 + ,2 + ,0 + ,1 + ,0 + ,1 + ,2 + ,0 + ,0 + ,4 + ,NA + ,NA + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,2 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0.5 + ,0 + ,1 + ,4 + ,NA + ,NA + ,0 + ,0 + ,4 + ,0 + ,2 + ,0 + ,0 + ,0 + ,NA + ,NA + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,4 + ,1 + ,2 + ,1 + ,1 + ,0 + ,1 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,2 + ,1 + ,2 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,4 + ,1 + ,1 + ,1 + ,1 + ,4 + ,1 + ,2 + ,0 + ,1 + ,2 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,2 + ,1 + ,0 + ,0 + ,1 + ,2 + ,0 + ,0 + ,1 + ,1 + ,2 + ,1 + ,1 + ,2 + ,1 + ,2 + ,1 + ,0 + ,0 + ,1 + ,2 + ,1 + ,1 + ,2 + ,1 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,0 + ,0 + ,4 + ,1 + ,2 + ,0 + ,0 + ,4 + ,1 + ,2 + ,1 + ,0 + ,0 + ,1 + ,2 + ,0 + ,0 + ,0 + ,NA + ,NA + ,0 + ,0 + ,4 + ,1 + ,2 + ,1 + ,0 + ,0 + ,NA + ,NA + ,1 + ,1 + ,4 + ,1 + ,2 + ,0 + ,0 + ,2 + ,1 + ,2 + ,0 + ,0 + ,2 + ,NA + ,NA + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,1 + ,2 + ,1 + ,1 + ,4 + ,NA + ,NA + ,0 + ,1 + ,0 + ,1 + ,2 + ,1 + ,1 + ,0 + ,1 + ,2 + ,1 + ,1 + ,0 + ,1 + ,2 + ,1 + ,1 + ,4 + ,1 + ,2 + ,1 + ,1 + ,4 + ,1 + ,2 + ,0 + ,0 + ,0 + ,NA + ,NA + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,2 + ,0 + ,1 + ,1 + ,0 + ,0) + ,dim=c(5 + ,105) + ,dimnames=list(c('pre' + ,'post1' + ,'post2' + ,'post3' + ,'post4') + ,1:105)) > y <- array(NA,dim=c(5,105),dimnames=list(c('pre','post1','post2','post3','post4'),1:105)) > 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 = '1' > 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] "pre" > x[,par1] [1] 1 1 0 0 1 1 1 0 0 1 0 0 0 0 0 1 1 1 0 0 1 1 0 1 1 1 1 0 0 1 1 1 0 0 0 1 1 [38] 0 0 1 1 1 1 1 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1 0 0 0 0 [75] 1 1 0 1 1 1 0 0 0 1 0 0 1 1 0 0 1 1 1 0 1 1 1 1 0 0 1 0 0 0 0 > 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]) 0 1 56 49 > colnames(x) [1] "pre" "post1" "post2" "post3" "post4" > colnames(x)[par1] [1] "pre" > x[,par1] [1] 1 1 0 0 1 1 1 0 0 1 0 0 0 0 0 1 1 1 0 0 1 1 0 1 1 1 1 0 0 1 1 1 0 0 0 1 1 [38] 0 0 1 1 1 1 1 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1 0 0 0 0 [75] 1 1 0 1 1 1 0 0 0 1 0 0 1 1 0 0 1 1 1 0 1 1 1 1 0 0 1 0 0 0 0 > 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/1qev41354876766.tab") + } + } > m Conditional inference tree with 3 terminal nodes Response: pre Inputs: post1, post2, post3, post4 Number of observations: 105 1) post1 <= 0; criterion = 1, statistic = 15.549 2)* weights = 38 1) post1 > 0 3) post4 <= 0; criterion = 0.994, statistic = 10.23 4)* weights = 16 3) post4 > 0 5)* weights = 51 > postscript(file="/var/wessaorg/rcomp/tmp/247jy1354876766.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/3s3bu1354876766.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 1 0.7254902 0.2745098 2 1 0.7254902 0.2745098 3 0 0.7254902 -0.7254902 4 0 0.2105263 -0.2105263 5 1 0.7254902 0.2745098 6 1 0.7254902 0.2745098 7 1 0.7254902 0.2745098 8 0 0.7254902 -0.7254902 9 0 0.7254902 -0.7254902 10 1 0.7254902 0.2745098 11 0 0.2105263 -0.2105263 12 0 0.2500000 -0.2500000 13 0 0.2500000 -0.2500000 14 0 0.7254902 -0.7254902 15 0 0.2105263 -0.2105263 16 1 0.7254902 0.2745098 17 1 0.7254902 0.2745098 18 1 0.7254902 0.2745098 19 0 0.7254902 -0.7254902 20 0 0.2105263 -0.2105263 21 1 0.7254902 0.2745098 22 1 0.2500000 0.7500000 23 0 0.2105263 -0.2105263 24 1 0.2105263 0.7894737 25 1 0.7254902 0.2745098 26 1 0.2105263 0.7894737 27 1 0.7254902 0.2745098 28 0 0.2105263 -0.2105263 29 0 0.2105263 -0.2105263 30 1 0.7254902 0.2745098 31 1 0.2105263 0.7894737 32 1 0.7254902 0.2745098 33 0 0.2105263 -0.2105263 34 0 0.2105263 -0.2105263 35 0 0.2105263 -0.2105263 36 1 0.7254902 0.2745098 37 1 0.7254902 0.2745098 38 0 0.2500000 -0.2500000 39 0 0.7254902 -0.7254902 40 1 0.7254902 0.2745098 41 1 0.7254902 0.2745098 42 1 0.7254902 0.2745098 43 1 0.2500000 0.7500000 44 1 0.7254902 0.2745098 45 0 0.2105263 -0.2105263 46 0 0.7254902 -0.7254902 47 0 0.2500000 -0.2500000 48 1 0.7254902 0.2745098 49 1 0.7254902 0.2745098 50 0 0.2105263 -0.2105263 51 0 0.7254902 -0.7254902 52 1 0.7254902 0.2745098 53 0 0.7254902 -0.7254902 54 0 0.2105263 -0.2105263 55 0 0.2500000 -0.2500000 56 0 0.2500000 -0.2500000 57 0 0.7254902 -0.7254902 58 0 0.7254902 -0.7254902 59 0 0.2105263 -0.2105263 60 0 0.2105263 -0.2105263 61 0 0.2500000 -0.2500000 62 1 0.7254902 0.2745098 63 1 0.7254902 0.2745098 64 1 0.2105263 0.7894737 65 0 0.2105263 -0.2105263 66 0 0.7254902 -0.7254902 67 0 0.7254902 -0.7254902 68 0 0.2105263 -0.2105263 69 1 0.7254902 0.2745098 70 1 0.7254902 0.2745098 71 0 0.2500000 -0.2500000 72 0 0.2500000 -0.2500000 73 0 0.2500000 -0.2500000 74 0 0.2500000 -0.2500000 75 1 0.7254902 0.2745098 76 1 0.2105263 0.7894737 77 0 0.2105263 -0.2105263 78 1 0.7254902 0.2745098 79 1 0.2105263 0.7894737 80 1 0.7254902 0.2745098 81 0 0.2105263 -0.2105263 82 0 0.2105263 -0.2105263 83 0 0.2105263 -0.2105263 84 1 0.2105263 0.7894737 85 0 0.2105263 -0.2105263 86 0 0.2105263 -0.2105263 87 1 0.2105263 0.7894737 88 1 0.7254902 0.2745098 89 0 0.2105263 -0.2105263 90 0 0.2105263 -0.2105263 91 1 0.2500000 0.7500000 92 1 0.7254902 0.2745098 93 1 0.7254902 0.2745098 94 0 0.7254902 -0.7254902 95 1 0.7254902 0.2745098 96 1 0.7254902 0.2745098 97 1 0.7254902 0.2745098 98 1 0.7254902 0.2745098 99 0 0.2105263 -0.2105263 100 0 0.2105263 -0.2105263 101 1 0.2500000 0.7500000 102 0 0.2105263 -0.2105263 103 0 0.2105263 -0.2105263 104 0 0.2105263 -0.2105263 105 0 0.2500000 -0.2500000 > 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/43q7u1354876766.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$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/5djw61354876767.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$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/67aeo1354876767.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/7mnxr1354876767.tab") + } > > try(system("convert tmp/247jy1354876766.ps tmp/247jy1354876766.png",intern=TRUE)) character(0) > try(system("convert tmp/3s3bu1354876766.ps tmp/3s3bu1354876766.png",intern=TRUE)) character(0) > try(system("convert tmp/43q7u1354876766.ps tmp/43q7u1354876766.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.046 0.476 4.500