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. 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+ ,7 + ,11 + ,9 + ,26 + ,22 + ,2 + ,28 + ,16 + ,16 + ,8 + ,24 + ,24 + ,1 + ,38 + ,11 + ,21 + ,7 + ,29 + ,29 + ,2 + ,22 + ,9 + ,14 + ,6 + ,19 + ,12 + ,2 + ,20 + ,11 + ,20 + ,13 + ,24 + ,20 + ,2 + ,17 + ,9 + ,13 + ,6 + ,19 + ,21 + ,2 + ,28 + ,14 + ,11 + ,8 + ,24 + ,24 + ,2 + ,22 + ,13 + ,15 + ,10 + ,22 + ,22 + ,2 + ,31 + ,16 + ,19 + ,16 + ,17 + ,20) + ,dim=c(7 + ,159) + ,dimnames=list(c('Gender' + ,'Concern_mistakes' + ,'Doubts_actions' + ,'Parental_expectations' + ,'Parental_criticism' + ,'Personal_standards' + ,'Organization') + ,1:159)) > y <- array(NA,dim=c(7,159),dimnames=list(c('Gender','Concern_mistakes','Doubts_actions','Parental_expectations','Parental_criticism','Personal_standards','Organization'),1:159)) > 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 = '2' > #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Concern_mistakes" > x[,par1] [1] 24 25 17 18 18 16 20 16 18 17 23 30 23 18 15 12 21 15 20 31 27 34 21 31 19 [26] 16 20 21 22 17 24 25 26 25 17 32 33 13 32 25 29 22 18 17 20 15 20 33 29 23 [51] 26 18 20 11 28 26 22 17 12 14 17 21 19 18 10 29 31 19 9 20 28 19 30 29 26 [76] 23 13 21 19 28 23 18 21 20 23 21 21 15 28 19 26 10 16 22 19 31 31 29 19 22 [101] 23 15 20 18 23 25 21 24 25 17 13 28 21 25 9 16 19 17 25 20 29 14 22 15 19 [126] 20 15 20 18 33 22 16 17 16 21 26 18 18 17 22 30 30 24 21 21 29 31 20 16 22 [151] 20 28 38 22 20 17 28 22 31 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 2 2 1 2 3 2 7 8 12 12 10 15 13 11 8 4 8 6 1 7 7 4 7 2 3 1 38 1 > colnames(x) [1] "Gender" "Concern_mistakes" "Doubts_actions" [4] "Parental_expectations" "Parental_criticism" "Personal_standards" [7] "Organization" > colnames(x)[par1] [1] "Concern_mistakes" > x[,par1] [1] 24 25 17 18 18 16 20 16 18 17 23 30 23 18 15 12 21 15 20 31 27 34 21 31 19 [26] 16 20 21 22 17 24 25 26 25 17 32 33 13 32 25 29 22 18 17 20 15 20 33 29 23 [51] 26 18 20 11 28 26 22 17 12 14 17 21 19 18 10 29 31 19 9 20 28 19 30 29 26 [76] 23 13 21 19 28 23 18 21 20 23 21 21 15 28 19 26 10 16 22 19 31 31 29 19 22 [101] 23 15 20 18 23 25 21 24 25 17 13 28 21 25 9 16 19 17 25 20 29 14 22 15 19 [126] 20 15 20 18 33 22 16 17 16 21 26 18 18 17 22 30 30 24 21 21 29 31 20 16 22 [151] 20 28 38 22 20 17 28 22 31 > 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/1rjfs1293193545.tab") + } + } > m Conditional inference tree with 5 terminal nodes Response: Concern_mistakes Inputs: Gender, Doubts_actions, Parental_expectations, Parental_criticism, Personal_standards, Organization Number of observations: 159 1) Personal_standards <= 25; criterion = 1, statistic = 28.54 2) Parental_criticism <= 7; criterion = 1, statistic = 22.429 3)* weights = 50 2) Parental_criticism > 7 4) Doubts_actions <= 12; criterion = 1, statistic = 15.524 5)* weights = 52 4) Doubts_actions > 12 6)* weights = 28 1) Personal_standards > 25 7) Doubts_actions <= 10; criterion = 0.997, statistic = 12.056 8)* weights = 13 7) Doubts_actions > 10 9)* weights = 16 > postscript(file="/var/www/html/freestat/rcomp/tmp/2ep7o1293193545.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/3ep7o1293193545.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 24 25.07143 -1.07142857 2 25 20.42308 4.57692308 3 17 21.46154 -4.46153846 4 18 20.42308 -2.42307692 5 18 20.42308 -2.42307692 6 16 18.24000 -2.24000000 7 20 18.24000 1.76000000 8 16 20.42308 -4.42307692 9 18 18.24000 -0.24000000 10 17 18.24000 -1.24000000 11 23 25.07143 -2.07142857 12 30 20.42308 9.57692308 13 23 20.42308 2.57692308 14 18 20.42308 -2.42307692 15 15 20.42308 -5.42307692 16 12 21.46154 -9.46153846 17 21 20.42308 0.57692308 18 15 20.42308 -5.42307692 19 20 18.24000 1.76000000 20 31 25.07143 5.92857143 21 27 25.07143 1.92857143 22 34 25.07143 8.92857143 23 21 20.42308 0.57692308 24 31 25.07143 5.92857143 25 19 20.42308 -1.42307692 26 16 20.42308 -4.42307692 27 20 18.24000 1.76000000 28 21 20.42308 0.57692308 29 22 20.42308 1.57692308 30 17 18.24000 -1.24000000 31 24 18.24000 5.76000000 32 25 29.81250 -4.81250000 33 26 29.81250 -3.81250000 34 25 21.46154 3.53846154 35 17 20.42308 -3.42307692 36 32 29.81250 2.18750000 37 33 29.81250 3.18750000 38 13 18.24000 -5.24000000 39 32 29.81250 2.18750000 40 25 29.81250 -4.81250000 41 29 29.81250 -0.81250000 42 22 20.42308 1.57692308 43 18 20.42308 -2.42307692 44 17 18.24000 -1.24000000 45 20 21.46154 -1.46153846 46 15 20.42308 -5.42307692 47 20 25.07143 -5.07142857 48 33 29.81250 3.18750000 49 29 20.42308 8.57692308 50 23 18.24000 4.76000000 51 26 18.24000 7.76000000 52 18 20.42308 -2.42307692 53 20 20.42308 -0.42307692 54 11 18.24000 -7.24000000 55 28 21.46154 6.53846154 56 26 25.07143 0.92857143 57 22 21.46154 0.53846154 58 17 18.24000 -1.24000000 59 12 18.24000 -6.24000000 60 14 25.07143 -11.07142857 61 17 20.42308 -3.42307692 62 21 18.24000 2.76000000 63 19 18.24000 0.76000000 64 18 25.07143 -7.07142857 65 10 18.24000 -8.24000000 66 29 29.81250 -0.81250000 67 31 20.42308 10.57692308 68 19 21.46154 -2.46153846 69 9 18.24000 -9.24000000 70 20 20.42308 -0.42307692 71 28 18.24000 9.76000000 72 19 18.24000 0.76000000 73 30 21.46154 8.53846154 74 29 25.07143 3.92857143 75 26 18.24000 7.76000000 76 23 20.42308 2.57692308 77 13 18.24000 -5.24000000 78 21 20.42308 0.57692308 79 19 20.42308 -1.42307692 80 28 18.24000 9.76000000 81 23 25.07143 -2.07142857 82 18 20.42308 -2.42307692 83 21 20.42308 0.57692308 84 20 20.42308 -0.42307692 85 23 18.24000 4.76000000 86 21 18.24000 2.76000000 87 21 21.46154 -0.46153846 88 15 25.07143 -10.07142857 89 28 29.81250 -1.81250000 90 19 18.24000 0.76000000 91 26 25.07143 0.92857143 92 10 18.24000 -8.24000000 93 16 18.24000 -2.24000000 94 22 18.24000 3.76000000 95 19 20.42308 -1.42307692 96 31 21.46154 9.53846154 97 31 25.07143 5.92857143 98 29 25.07143 3.92857143 99 19 18.24000 0.76000000 100 22 20.42308 1.57692308 101 23 20.42308 2.57692308 102 15 18.24000 -3.24000000 103 20 20.42308 -0.42307692 104 18 20.42308 -2.42307692 105 23 25.07143 -2.07142857 106 25 18.24000 6.76000000 107 21 18.24000 2.76000000 108 24 20.42308 3.57692308 109 25 25.07143 -0.07142857 110 17 18.24000 -1.24000000 111 13 18.24000 -5.24000000 112 28 20.42308 7.57692308 113 21 20.42308 0.57692308 114 25 21.46154 3.53846154 115 9 21.46154 -12.46153846 116 16 18.24000 -2.24000000 117 19 20.42308 -1.42307692 118 17 18.24000 -1.24000000 119 25 25.07143 -0.07142857 120 20 18.24000 1.76000000 121 29 29.81250 -0.81250000 122 14 18.24000 -4.24000000 123 22 25.07143 -3.07142857 124 15 18.24000 -3.24000000 125 19 18.24000 0.76000000 126 20 20.42308 -0.42307692 127 15 18.24000 -3.24000000 128 20 20.42308 -0.42307692 129 18 20.42308 -2.42307692 130 33 29.81250 3.18750000 131 22 20.42308 1.57692308 132 16 20.42308 -4.42307692 133 17 18.24000 -1.24000000 134 16 18.24000 -2.24000000 135 21 20.42308 0.57692308 136 26 29.81250 -3.81250000 137 18 18.24000 -0.24000000 138 18 20.42308 -2.42307692 139 17 20.42308 -3.42307692 140 22 25.07143 -3.07142857 141 30 25.07143 4.92857143 142 30 29.81250 0.18750000 143 24 25.07143 -1.07142857 144 21 18.24000 2.76000000 145 21 25.07143 -4.07142857 146 29 29.81250 -0.81250000 147 31 20.42308 10.57692308 148 20 18.24000 1.76000000 149 16 20.42308 -4.42307692 150 22 20.42308 1.57692308 151 20 21.46154 -1.46153846 152 28 25.07143 2.92857143 153 38 29.81250 8.18750000 154 22 18.24000 3.76000000 155 20 20.42308 -0.42307692 156 17 18.24000 -1.24000000 157 28 25.07143 2.92857143 158 22 25.07143 -3.07142857 159 31 25.07143 5.92857143 > 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/47g7r1293193545.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/5ah5x1293193545.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/6ez431293193545.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/7oqlo1293193545.tab") + } > try(system("convert tmp/2ep7o1293193545.ps tmp/2ep7o1293193545.png",intern=TRUE)) character(0) > try(system("convert tmp/3ep7o1293193545.ps tmp/3ep7o1293193545.png",intern=TRUE)) character(0) > try(system("convert tmp/47g7r1293193545.ps tmp/47g7r1293193545.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.730 0.792 4.934