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Type 'q()' to quit R. > x <- array(list(2 + ,24 + ,14 + ,11 + ,12 + ,24 + ,26 + ,2 + ,25 + ,11 + ,7 + ,8 + ,25 + ,23 + ,2 + ,17 + ,6 + ,17 + ,8 + ,30 + ,25 + ,1 + ,18 + ,12 + ,10 + ,8 + ,19 + ,23 + ,2 + ,18 + ,8 + ,12 + ,9 + ,22 + ,19 + ,2 + ,16 + ,10 + ,12 + ,7 + ,22 + ,29 + ,2 + ,20 + ,10 + ,11 + ,4 + ,25 + ,25 + ,2 + ,16 + ,11 + ,11 + ,11 + ,23 + ,21 + ,2 + ,18 + ,16 + ,12 + ,7 + ,17 + ,22 + ,2 + ,17 + ,11 + ,13 + ,7 + ,21 + ,25 + ,1 + ,23 + ,13 + ,14 + ,12 + ,19 + ,24 + ,2 + ,30 + ,12 + ,16 + ,10 + ,19 + ,18 + ,1 + ,23 + ,8 + ,11 + ,10 + ,15 + ,22 + ,2 + ,18 + ,12 + ,10 + ,8 + ,16 + ,15 + ,2 + ,15 + ,11 + ,11 + ,8 + ,23 + ,22 + ,1 + ,12 + ,4 + ,15 + ,4 + ,27 + ,28 + ,1 + ,21 + ,9 + ,9 + ,9 + ,22 + ,20 + ,2 + ,15 + ,8 + ,11 + ,8 + ,14 + ,12 + ,1 + ,20 + ,8 + ,17 + ,7 + ,22 + ,24 + ,2 + ,31 + ,14 + ,17 + ,11 + ,23 + ,20 + ,1 + ,27 + ,15 + ,11 + ,9 + ,23 + ,21 + ,2 + ,34 + ,16 + ,18 + ,11 + ,21 + ,20 + ,2 + ,21 + ,9 + ,14 + ,13 + ,19 + ,21 + ,2 + ,31 + ,14 + ,10 + ,8 + ,18 + ,23 + ,1 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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 = '3' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Gender" > x[,par1] [1] 2 2 2 1 2 2 2 2 2 2 1 2 1 2 2 1 1 2 1 2 1 2 2 2 1 2 1 2 2 1 2 1 2 2 1 1 1 [38] 1 2 1 1 2 1 1 2 2 2 2 2 1 2 1 1 2 1 2 2 2 1 2 1 1 2 2 2 1 2 1 2 1 1 2 2 1 [75] 1 2 2 2 1 1 1 1 2 1 2 2 1 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 2 1 2 1 2 1 1 2 2 [112] 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 1 2 2 2 1 1 2 1 1 2 1 1 2 2 1 2 1 2 1 2 2 1 [149] 1 1 2 2 1 2 2 2 2 2 2 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 1 2 61 98 > colnames(x) [1] "Gender" "Concern_Mistakes" "Doubts_actions" [4] "Parental_Expectations" "Parental_Criticism" "Personal_Standards" [7] "Organization" > colnames(x)[par1] [1] "Gender" > x[,par1] [1] 2 2 2 1 2 2 2 2 2 2 1 2 1 2 2 1 1 2 1 2 1 2 2 2 1 2 1 2 2 1 2 1 2 2 1 1 1 [38] 1 2 1 1 2 1 1 2 2 2 2 2 1 2 1 1 2 1 2 2 2 1 2 1 1 2 2 2 1 2 1 2 1 1 2 2 1 [75] 1 2 2 2 1 1 1 1 2 1 2 2 1 2 2 2 2 2 2 2 2 2 2 2 1 1 2 1 2 1 2 1 2 1 1 2 2 [112] 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 1 2 2 2 1 1 2 1 1 2 1 1 2 2 1 2 1 2 1 2 2 1 [149] 1 1 2 2 1 2 2 2 2 2 2 > 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/1co3w1323975600.tab") + } + } > m Conditional inference tree with 1 terminal nodes Response: Gender Inputs: Concern_Mistakes, Doubts_actions, Parental_Expectations, Parental_Criticism, Personal_Standards, Organization Number of observations: 159 1)* weights = 159 > postscript(file="/var/wessaorg/rcomp/tmp/22z9v1323975600.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/3p20s1323975600.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 2 1.616352 0.3836478 2 2 1.616352 0.3836478 3 2 1.616352 0.3836478 4 1 1.616352 -0.6163522 5 2 1.616352 0.3836478 6 2 1.616352 0.3836478 7 2 1.616352 0.3836478 8 2 1.616352 0.3836478 9 2 1.616352 0.3836478 10 2 1.616352 0.3836478 11 1 1.616352 -0.6163522 12 2 1.616352 0.3836478 13 1 1.616352 -0.6163522 14 2 1.616352 0.3836478 15 2 1.616352 0.3836478 16 1 1.616352 -0.6163522 17 1 1.616352 -0.6163522 18 2 1.616352 0.3836478 19 1 1.616352 -0.6163522 20 2 1.616352 0.3836478 21 1 1.616352 -0.6163522 22 2 1.616352 0.3836478 23 2 1.616352 0.3836478 24 2 1.616352 0.3836478 25 1 1.616352 -0.6163522 26 2 1.616352 0.3836478 27 1 1.616352 -0.6163522 28 2 1.616352 0.3836478 29 2 1.616352 0.3836478 30 1 1.616352 -0.6163522 31 2 1.616352 0.3836478 32 1 1.616352 -0.6163522 33 2 1.616352 0.3836478 34 2 1.616352 0.3836478 35 1 1.616352 -0.6163522 36 1 1.616352 -0.6163522 37 1 1.616352 -0.6163522 38 1 1.616352 -0.6163522 39 2 1.616352 0.3836478 40 1 1.616352 -0.6163522 41 1 1.616352 -0.6163522 42 2 1.616352 0.3836478 43 1 1.616352 -0.6163522 44 1 1.616352 -0.6163522 45 2 1.616352 0.3836478 46 2 1.616352 0.3836478 47 2 1.616352 0.3836478 48 2 1.616352 0.3836478 49 2 1.616352 0.3836478 50 1 1.616352 -0.6163522 51 2 1.616352 0.3836478 52 1 1.616352 -0.6163522 53 1 1.616352 -0.6163522 54 2 1.616352 0.3836478 55 1 1.616352 -0.6163522 56 2 1.616352 0.3836478 57 2 1.616352 0.3836478 58 2 1.616352 0.3836478 59 1 1.616352 -0.6163522 60 2 1.616352 0.3836478 61 1 1.616352 -0.6163522 62 1 1.616352 -0.6163522 63 2 1.616352 0.3836478 64 2 1.616352 0.3836478 65 2 1.616352 0.3836478 66 1 1.616352 -0.6163522 67 2 1.616352 0.3836478 68 1 1.616352 -0.6163522 69 2 1.616352 0.3836478 70 1 1.616352 -0.6163522 71 1 1.616352 -0.6163522 72 2 1.616352 0.3836478 73 2 1.616352 0.3836478 74 1 1.616352 -0.6163522 75 1 1.616352 -0.6163522 76 2 1.616352 0.3836478 77 2 1.616352 0.3836478 78 2 1.616352 0.3836478 79 1 1.616352 -0.6163522 80 1 1.616352 -0.6163522 81 1 1.616352 -0.6163522 82 1 1.616352 -0.6163522 83 2 1.616352 0.3836478 84 1 1.616352 -0.6163522 85 2 1.616352 0.3836478 86 2 1.616352 0.3836478 87 1 1.616352 -0.6163522 88 2 1.616352 0.3836478 89 2 1.616352 0.3836478 90 2 1.616352 0.3836478 91 2 1.616352 0.3836478 92 2 1.616352 0.3836478 93 2 1.616352 0.3836478 94 2 1.616352 0.3836478 95 2 1.616352 0.3836478 96 2 1.616352 0.3836478 97 2 1.616352 0.3836478 98 2 1.616352 0.3836478 99 1 1.616352 -0.6163522 100 1 1.616352 -0.6163522 101 2 1.616352 0.3836478 102 1 1.616352 -0.6163522 103 2 1.616352 0.3836478 104 1 1.616352 -0.6163522 105 2 1.616352 0.3836478 106 1 1.616352 -0.6163522 107 2 1.616352 0.3836478 108 1 1.616352 -0.6163522 109 1 1.616352 -0.6163522 110 2 1.616352 0.3836478 111 2 1.616352 0.3836478 112 2 1.616352 0.3836478 113 2 1.616352 0.3836478 114 1 1.616352 -0.6163522 115 2 1.616352 0.3836478 116 1 1.616352 -0.6163522 117 2 1.616352 0.3836478 118 2 1.616352 0.3836478 119 2 1.616352 0.3836478 120 2 1.616352 0.3836478 121 2 1.616352 0.3836478 122 2 1.616352 0.3836478 123 2 1.616352 0.3836478 124 2 1.616352 0.3836478 125 2 1.616352 0.3836478 126 2 1.616352 0.3836478 127 1 1.616352 -0.6163522 128 2 1.616352 0.3836478 129 2 1.616352 0.3836478 130 2 1.616352 0.3836478 131 1 1.616352 -0.6163522 132 1 1.616352 -0.6163522 133 2 1.616352 0.3836478 134 1 1.616352 -0.6163522 135 1 1.616352 -0.6163522 136 2 1.616352 0.3836478 137 1 1.616352 -0.6163522 138 1 1.616352 -0.6163522 139 2 1.616352 0.3836478 140 2 1.616352 0.3836478 141 1 1.616352 -0.6163522 142 2 1.616352 0.3836478 143 1 1.616352 -0.6163522 144 2 1.616352 0.3836478 145 1 1.616352 -0.6163522 146 2 1.616352 0.3836478 147 2 1.616352 0.3836478 148 1 1.616352 -0.6163522 149 1 1.616352 -0.6163522 150 1 1.616352 -0.6163522 151 2 1.616352 0.3836478 152 2 1.616352 0.3836478 153 1 1.616352 -0.6163522 154 2 1.616352 0.3836478 155 2 1.616352 0.3836478 156 2 1.616352 0.3836478 157 2 1.616352 0.3836478 158 2 1.616352 0.3836478 159 2 1.616352 0.3836478 > 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/4xcqk1323975600.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/5jo1n1323975600.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/6kdw81323975600.tab") + } Warning message: In cor(result$Forecasts, result$Actuals) : the standard deviation is zero > 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/7hebr1323975600.tab") + } > > try(system("convert tmp/22z9v1323975600.ps tmp/22z9v1323975600.png",intern=TRUE)) character(0) > try(system("convert tmp/3p20s1323975600.ps tmp/3p20s1323975600.png",intern=TRUE)) character(0) > try(system("convert tmp/4xcqk1323975600.ps tmp/4xcqk1323975600.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.115 0.330 4.598