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. Type 'q()' to quit R. > x <- array(list(14 + ,11 + ,23 + ,8 + ,1 + ,6 + ,7 + ,22 + ,24 + ,4 + ,2 + ,5 + ,22 + ,23 + ,24 + ,7 + ,2 + ,20 + ,12 + ,21 + ,21 + ,4 + ,2 + ,12 + ,15 + ,19 + ,21 + ,4 + ,2 + ,11 + ,9 + ,12 + ,19 + ,5 + ,2 + ,12 + ,20 + ,24 + ,12 + ,15 + ,1 + ,11 + ,10 + ,21 + ,21 + ,5 + ,1 + ,9 + ,12 + ,21 + ,25 + ,7 + ,2 + ,13 + ,23 + ,26 + ,27 + ,4 + ,2 + ,9 + ,10 + ,18 + ,21 + ,4 + ,1 + ,14 + ,11 + ,21 + ,27 + ,7 + ,1 + ,12 + ,20 + ,22 + ,20 + ,8 + ,1 + ,18 + ,11 + ,26 + ,16 + ,4 + ,2 + ,9 + ,22 + ,20 + ,26 + ,8 + ,1 + ,15 + ,19 + ,20 + ,24 + ,4 + ,2 + ,12 + ,20 + ,26 + ,25 + ,5 + ,2 + ,12 + ,16 + ,27 + ,25 + ,16 + ,1 + ,12 + ,12 + ,27 + ,27 + ,7 + ,1 + ,15 + ,14 + ,16 + ,23 + ,4 + ,2 + ,11 + ,14 + ,26 + ,22 + ,6 + ,1 + ,13 + ,9 + ,20 + ,10 + ,4 + ,1 + ,10 + ,19 + ,25 + ,25 + ,5 + ,2 + ,17 + ,17 + ,16 + ,18 + ,4 + ,1 + ,13 + ,14 + ,20 + ,21 + ,4 + ,1 + ,17 + ,19 + ,20 + ,20 + ,6 + ,1 + ,15 + ,20 + ,24 + ,18 + ,4 + ,1 + ,13 + ,20 + ,24 + ,25 + ,4 + ,1 + ,17 + ,9 + ,22 + ,28 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,18 + ,25 + ,5 + ,2 + ,12) + ,dim=c(6 + ,148) + ,dimnames=list(c('I/Exp.Stimulation' + ,'E/Introjected' + ,'E/Ext.Regulation' + ,'Amotivation' + ,'gender' + ,'PE') + ,1:148)) > y <- array(NA,dim=c(6,148),dimnames=list(c('I/Exp.Stimulation','E/Introjected','E/Ext.Regulation','Amotivation','gender','PE'),1:148)) > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "E.Introjected" > x[,par1] [1] 11 22 23 21 19 12 24 21 21 26 18 21 22 26 20 20 26 27 27 16 26 20 25 16 20 [26] 20 24 24 22 18 21 17 15 28 23 19 15 26 20 11 17 16 21 18 17 21 18 16 13 28 [51] 25 24 15 21 11 27 23 21 16 20 21 10 18 20 21 24 26 23 22 13 27 24 19 17 16 [76] 20 8 16 17 23 18 24 17 20 22 22 20 18 21 23 28 19 22 17 25 22 21 15 20 25 [101] 21 24 23 22 14 11 22 22 6 15 26 26 20 26 15 25 22 20 18 23 22 23 17 20 21 [126] 23 25 25 21 22 18 18 18 21 21 25 24 24 28 24 22 22 20 25 13 21 23 18 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 6 8 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 1 1 1 4 1 3 1 6 7 8 12 4 16 19 16 11 11 9 9 4 4 > colnames(x) [1] "I.Exp.Stimulation" "E.Introjected" "E.Ext.Regulation" [4] "Amotivation" "gender" "PE" > colnames(x)[par1] [1] "E.Introjected" > x[,par1] [1] 11 22 23 21 19 12 24 21 21 26 18 21 22 26 20 20 26 27 27 16 26 20 25 16 20 [26] 20 24 24 22 18 21 17 15 28 23 19 15 26 20 11 17 16 21 18 17 21 18 16 13 28 [51] 25 24 15 21 11 27 23 21 16 20 21 10 18 20 21 24 26 23 22 13 27 24 19 17 16 [76] 20 8 16 17 23 18 24 17 20 22 22 20 18 21 23 28 19 22 17 25 22 21 15 20 25 [101] 21 24 23 22 14 11 22 22 6 15 26 26 20 26 15 25 22 20 18 23 22 23 17 20 21 [126] 23 25 25 21 22 18 18 18 21 21 25 24 24 28 24 22 22 20 25 13 21 23 18 > 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/1evgg1292936162.tab") + } + } > m Conditional inference tree with 2 terminal nodes Response: E.Introjected Inputs: I.Exp.Stimulation, E.Ext.Regulation, Amotivation, gender, PE Number of observations: 148 1) I.Exp.Stimulation <= 18; criterion = 0.961, statistic = 7.054 2)* weights = 122 1) I.Exp.Stimulation > 18 3)* weights = 26 > postscript(file="/var/www/html/freestat/rcomp/tmp/2evgg1292936162.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/3evgg1292936162.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 19.89344 -8.8934426 2 22 19.89344 2.1065574 3 23 23.19231 -0.1923077 4 21 19.89344 1.1065574 5 19 19.89344 -0.8934426 6 12 19.89344 -7.8934426 7 24 23.19231 0.8076923 8 21 19.89344 1.1065574 9 21 19.89344 1.1065574 10 26 23.19231 2.8076923 11 18 19.89344 -1.8934426 12 21 19.89344 1.1065574 13 22 23.19231 -1.1923077 14 26 19.89344 6.1065574 15 20 23.19231 -3.1923077 16 20 23.19231 -3.1923077 17 26 23.19231 2.8076923 18 27 19.89344 7.1065574 19 27 19.89344 7.1065574 20 16 19.89344 -3.8934426 21 26 19.89344 6.1065574 22 20 19.89344 0.1065574 23 25 23.19231 1.8076923 24 16 19.89344 -3.8934426 25 20 19.89344 0.1065574 26 20 23.19231 -3.1923077 27 24 23.19231 0.8076923 28 24 23.19231 0.8076923 29 22 19.89344 2.1065574 30 18 19.89344 -1.8934426 31 21 19.89344 1.1065574 32 17 19.89344 -2.8934426 33 15 19.89344 -4.8934426 34 28 23.19231 4.8076923 35 23 19.89344 3.1065574 36 19 19.89344 -0.8934426 37 15 19.89344 -4.8934426 38 26 23.19231 2.8076923 39 20 19.89344 0.1065574 40 11 19.89344 -8.8934426 41 17 19.89344 -2.8934426 42 16 19.89344 -3.8934426 43 21 19.89344 1.1065574 44 18 19.89344 -1.8934426 45 17 19.89344 -2.8934426 46 21 19.89344 1.1065574 47 18 19.89344 -1.8934426 48 16 19.89344 -3.8934426 49 13 19.89344 -6.8934426 50 28 19.89344 8.1065574 51 25 19.89344 5.1065574 52 24 19.89344 4.1065574 53 15 19.89344 -4.8934426 54 21 19.89344 1.1065574 55 11 19.89344 -8.8934426 56 27 19.89344 7.1065574 57 23 19.89344 3.1065574 58 21 19.89344 1.1065574 59 16 19.89344 -3.8934426 60 20 19.89344 0.1065574 61 21 19.89344 1.1065574 62 10 19.89344 -9.8934426 63 18 23.19231 -5.1923077 64 20 19.89344 0.1065574 65 21 19.89344 1.1065574 66 24 19.89344 4.1065574 67 26 19.89344 6.1065574 68 23 23.19231 -0.1923077 69 22 19.89344 2.1065574 70 13 19.89344 -6.8934426 71 27 23.19231 3.8076923 72 24 19.89344 4.1065574 73 19 23.19231 -4.1923077 74 17 19.89344 -2.8934426 75 16 19.89344 -3.8934426 76 20 23.19231 -3.1923077 77 8 19.89344 -11.8934426 78 16 19.89344 -3.8934426 79 17 19.89344 -2.8934426 80 23 23.19231 -0.1923077 81 18 19.89344 -1.8934426 82 24 23.19231 0.8076923 83 17 19.89344 -2.8934426 84 20 19.89344 0.1065574 85 22 19.89344 2.1065574 86 22 19.89344 2.1065574 87 20 19.89344 0.1065574 88 18 19.89344 -1.8934426 89 21 19.89344 1.1065574 90 23 19.89344 3.1065574 91 28 23.19231 4.8076923 92 19 19.89344 -0.8934426 93 22 19.89344 2.1065574 94 17 19.89344 -2.8934426 95 25 19.89344 5.1065574 96 22 19.89344 2.1065574 97 21 19.89344 1.1065574 98 15 19.89344 -4.8934426 99 20 19.89344 0.1065574 100 25 19.89344 5.1065574 101 21 19.89344 1.1065574 102 24 19.89344 4.1065574 103 23 19.89344 3.1065574 104 22 19.89344 2.1065574 105 14 19.89344 -5.8934426 106 11 19.89344 -8.8934426 107 22 19.89344 2.1065574 108 22 19.89344 2.1065574 109 6 19.89344 -13.8934426 110 15 19.89344 -4.8934426 111 26 19.89344 6.1065574 112 26 23.19231 2.8076923 113 20 19.89344 0.1065574 114 26 19.89344 6.1065574 115 15 19.89344 -4.8934426 116 25 19.89344 5.1065574 117 22 19.89344 2.1065574 118 20 19.89344 0.1065574 119 18 19.89344 -1.8934426 120 23 19.89344 3.1065574 121 22 19.89344 2.1065574 122 23 19.89344 3.1065574 123 17 23.19231 -6.1923077 124 20 19.89344 0.1065574 125 21 19.89344 1.1065574 126 23 19.89344 3.1065574 127 25 19.89344 5.1065574 128 25 19.89344 5.1065574 129 21 19.89344 1.1065574 130 22 19.89344 2.1065574 131 18 19.89344 -1.8934426 132 18 19.89344 -1.8934426 133 18 23.19231 -5.1923077 134 21 19.89344 1.1065574 135 21 19.89344 1.1065574 136 25 19.89344 5.1065574 137 24 19.89344 4.1065574 138 24 19.89344 4.1065574 139 28 23.19231 4.8076923 140 24 23.19231 0.8076923 141 22 19.89344 2.1065574 142 22 19.89344 2.1065574 143 20 19.89344 0.1065574 144 25 19.89344 5.1065574 145 13 19.89344 -6.8934426 146 21 19.89344 1.1065574 147 23 19.89344 3.1065574 148 18 19.89344 -1.8934426 > 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/4zwx41292936162.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/53eva1292936162.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/6oecg1292936162.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/7zotj1292936162.tab") + } > > try(system("convert tmp/2evgg1292936162.ps tmp/2evgg1292936162.png",intern=TRUE)) character(0) > try(system("convert tmp/3evgg1292936162.ps tmp/3evgg1292936162.png",intern=TRUE)) character(0) > try(system("convert tmp/4zwx41292936162.ps tmp/4zwx41292936162.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.808 0.843 21.273