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(13 + ,15 + ,2 + ,9 + ,42 + ,12 + ,12 + ,18 + ,1 + ,9 + ,51 + ,15 + ,15 + ,11 + ,1 + ,9 + ,42 + ,14 + ,12 + ,16 + ,1 + ,8 + ,46 + ,10 + ,10 + ,12 + ,2 + ,14 + ,41 + ,10 + ,12 + ,17 + ,2 + ,14 + ,49 + ,9 + ,15 + ,15 + ,1 + ,15 + ,47 + ,18 + ,9 + ,19 + ,1 + ,11 + ,33 + ,11 + ,11 + ,18 + ,1 + ,8 + ,47 + ,12 + ,11 + ,10 + ,2 + ,14 + ,42 + ,11 + ,11 + ,14 + ,1 + ,9 + ,32 + ,15 + ,15 + ,18 + ,1 + ,6 + ,53 + ,17 + ,7 + ,18 + ,2 + ,14 + ,41 + ,14 + ,11 + ,14 + ,2 + ,8 + ,41 + ,24 + ,11 + ,14 + ,1 + ,11 + ,33 + ,7 + ,10 + ,12 + ,1 + ,16 + ,37 + ,18 + ,14 + ,16 + ,2 + ,11 + ,43 + ,11 + ,6 + ,13 + ,2 + ,13 + ,33 + ,14 + ,11 + ,16 + ,1 + ,7 + ,49 + ,18 + ,15 + ,14 + ,2 + ,9 + ,42 + ,12 + ,11 + ,9 + ,1 + ,15 + ,43 + ,11 + ,12 + ,9 + ,2 + ,16 + ,37 + ,5 + ,14 + ,17 + ,1 + ,10 + ,43 + ,12 + ,15 + ,13 + ,2 + ,14 + ,42 + ,11 + ,9 + ,15 + ,2 + ,12 + ,43 + ,10 + ,13 + ,17 + ,1 + ,6 + ,46 + ,11 + ,13 + ,16 + ,2 + ,4 + ,33 + ,15 + ,16 + ,12 + ,1 + ,12 + ,42 + ,16 + 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,15 + ,12 + ,17 + ,1 + ,8 + ,44 + ,10 + ,11 + ,11 + ,1 + ,14 + ,35 + ,14 + ,4 + ,15 + ,1 + ,12 + ,40 + ,16 + ,16 + ,11 + ,1 + ,12 + ,44 + ,18 + ,15 + ,15 + ,1 + ,6 + ,46 + ,6 + ,10 + ,17 + ,1 + ,16 + ,45 + ,16 + ,13 + ,14 + ,1 + ,8 + ,53 + ,11 + ,15 + ,12 + ,2 + ,13 + ,45 + ,20 + ,12 + ,14 + ,1 + ,12 + ,48 + ,10 + ,14 + ,15 + ,2 + ,11 + ,46 + ,16 + ,7 + ,16 + ,1 + ,12 + ,55 + ,15 + ,19 + ,16 + ,1 + ,9 + ,47 + ,14 + ,12 + ,14 + ,1 + ,11 + ,43 + ,7 + ,12 + ,11 + ,2 + ,16 + ,38 + ,9 + ,8 + ,14 + ,2 + ,10 + ,40 + ,12 + ,12 + ,13 + ,1 + ,13 + ,47 + ,12 + ,10 + ,13 + ,1 + ,11 + ,47 + ,13 + ,8 + ,14 + ,2 + ,11 + ,42 + ,17 + ,10 + ,16 + ,2 + ,9 + ,53 + ,11 + ,14 + ,16 + ,2 + ,11 + ,43 + ,11 + ,16 + ,12 + ,1 + ,12 + ,44 + ,14 + ,13 + ,11 + ,1 + ,10 + ,42 + ,13 + ,16 + ,13 + ,1 + ,13 + ,51 + ,12 + ,9 + ,15 + ,1 + ,9 + ,54 + ,11 + ,14 + ,13 + ,2 + ,14 + ,41 + ,15 + ,14 + ,16 + ,2 + ,14 + ,51 + ,11 + ,12 + ,13 + ,1 + ,8 + ,51 + ,13) + ,dim=c(6 + ,143) + ,dimnames=list(c('popularity' + ,'hapiness' + ,'gender' + ,'doubsaboutactions' + ,'belonging' + ,'parentalexpectations') + ,1:143)) > y <- array(NA,dim=c(6,143),dimnames=list(c('popularity','hapiness','gender','doubsaboutactions','belonging','parentalexpectations'),1:143)) > 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 = '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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "belonging" > x[,par1] [1] 42 51 42 46 41 49 47 33 47 42 32 53 41 41 33 37 43 33 49 42 43 37 43 42 43 [26] 46 33 42 40 44 42 52 44 45 46 36 45 49 43 43 37 32 45 45 45 45 31 33 44 49 [51] 44 41 44 38 33 47 37 48 40 50 54 43 54 44 47 33 45 33 44 47 45 43 43 33 46 [76] 47 47 0 43 46 36 42 44 47 41 47 46 47 46 46 36 30 48 45 49 55 11 52 33 47 [101] 33 44 42 55 42 46 46 47 33 53 42 44 55 40 46 53 44 35 40 44 46 45 53 45 48 [126] 46 55 47 43 38 40 47 47 42 53 43 44 42 51 54 41 51 51 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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 11 30 31 32 33 35 36 37 38 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 1 1 1 1 2 12 1 3 4 2 5 6 13 12 13 11 13 15 3 5 1 4 2 5 3 4 > colnames(x) [1] "popularity" "hapiness" "gender" [4] "doubsaboutactions" "belonging" "parentalexpectations" > colnames(x)[par1] [1] "belonging" > x[,par1] [1] 42 51 42 46 41 49 47 33 47 42 32 53 41 41 33 37 43 33 49 42 43 37 43 42 43 [26] 46 33 42 40 44 42 52 44 45 46 36 45 49 43 43 37 32 45 45 45 45 31 33 44 49 [51] 44 41 44 38 33 47 37 48 40 50 54 43 54 44 47 33 45 33 44 47 45 43 43 33 46 [76] 47 47 0 43 46 36 42 44 47 41 47 46 47 46 46 36 30 48 45 49 55 11 52 33 47 [101] 33 44 42 55 42 46 46 47 33 53 42 44 55 40 46 53 44 35 40 44 46 45 53 45 48 [126] 46 55 47 43 38 40 47 47 42 53 43 44 42 51 54 41 51 51 > 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/169dy1292061980.tab") + } + } > m Conditional inference tree with 5 terminal nodes Response: belonging Inputs: popularity, hapiness, gender, doubsaboutactions, parentalexpectations Number of observations: 143 1) popularity <= 8; criterion = 0.997, statistic = 11.612 2)* weights = 21 1) popularity > 8 3) doubsaboutactions <= 15; criterion = 0.993, statistic = 10.269 4) hapiness <= 14; criterion = 0.968, statistic = 7.384 5) popularity <= 11; criterion = 0.961, statistic = 7.055 6)* weights = 13 5) popularity > 11 7)* weights = 40 4) hapiness > 14 8)* weights = 60 3) doubsaboutactions > 15 9)* weights = 9 > postscript(file="/var/www/html/freestat/rcomp/tmp/2yiv11292061980.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/3yiv11292061980.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 42 45.78333 -3.7833333 2 51 45.78333 5.2166667 3 42 44.37500 -2.3750000 4 46 45.78333 0.2166667 5 41 39.15385 1.8461538 6 49 45.78333 3.2166667 7 47 45.78333 1.2166667 8 33 45.78333 -12.7833333 9 47 45.78333 1.2166667 10 42 39.15385 2.8461538 11 32 39.15385 -7.1538462 12 53 45.78333 7.2166667 13 41 38.80952 2.1904762 14 41 39.15385 1.8461538 15 33 39.15385 -6.1538462 16 37 36.11111 0.8888889 17 43 45.78333 -2.7833333 18 33 38.80952 -5.8095238 19 49 45.78333 3.2166667 20 42 44.37500 -2.3750000 21 43 39.15385 3.8461538 22 37 36.11111 0.8888889 23 43 45.78333 -2.7833333 24 42 44.37500 -2.3750000 25 43 45.78333 -2.7833333 26 46 45.78333 0.2166667 27 33 45.78333 -12.7833333 28 42 44.37500 -2.3750000 29 40 44.37500 -4.3750000 30 44 45.78333 -1.7833333 31 42 45.78333 -3.7833333 32 52 45.78333 6.2166667 33 44 45.78333 -1.7833333 34 45 44.37500 0.6250000 35 46 44.37500 1.6250000 36 36 39.15385 -3.1538462 37 45 45.78333 -0.7833333 38 49 44.37500 4.6250000 39 43 44.37500 -1.3750000 40 43 44.37500 -1.3750000 41 37 38.80952 -1.8095238 42 32 38.80952 -6.8095238 43 45 45.78333 -0.7833333 44 45 44.37500 0.6250000 45 45 44.37500 0.6250000 46 45 39.15385 5.8461538 47 31 39.15385 -8.1538462 48 33 45.78333 -12.7833333 49 44 45.78333 -1.7833333 50 49 38.80952 10.1904762 51 44 44.37500 -0.3750000 52 41 38.80952 2.1904762 53 44 44.37500 -0.3750000 54 38 45.78333 -7.7833333 55 33 45.78333 -12.7833333 56 47 44.37500 2.6250000 57 37 38.80952 -1.8095238 58 48 45.78333 2.2166667 59 40 38.80952 1.1904762 60 50 44.37500 5.6250000 61 54 45.78333 8.2166667 62 43 45.78333 -2.7833333 63 54 45.78333 8.2166667 64 44 44.37500 -0.3750000 65 47 45.78333 1.2166667 66 33 44.37500 -11.3750000 67 45 45.78333 -0.7833333 68 33 38.80952 -5.8095238 69 44 45.78333 -1.7833333 70 47 44.37500 2.6250000 71 45 36.11111 8.8888889 72 43 45.78333 -2.7833333 73 43 36.11111 6.8888889 74 33 44.37500 -11.3750000 75 46 45.78333 0.2166667 76 47 44.37500 2.6250000 77 47 38.80952 8.1904762 78 0 38.80952 -38.8095238 79 43 44.37500 -1.3750000 80 46 45.78333 0.2166667 81 36 36.11111 -0.1111111 82 42 39.15385 2.8461538 83 44 44.37500 -0.3750000 84 47 45.78333 1.2166667 85 41 39.15385 1.8461538 86 47 45.78333 1.2166667 87 46 45.78333 0.2166667 88 47 45.78333 1.2166667 89 46 44.37500 1.6250000 90 46 45.78333 0.2166667 91 36 45.78333 -9.7833333 92 30 38.80952 -8.8095238 93 48 38.80952 9.1904762 94 45 45.78333 -0.7833333 95 49 45.78333 3.2166667 96 55 44.37500 10.6250000 97 11 36.11111 -25.1111111 98 52 45.78333 6.2166667 99 33 38.80952 -5.8095238 100 47 45.78333 1.2166667 101 33 36.11111 -3.1111111 102 44 44.37500 -0.3750000 103 42 38.80952 3.1904762 104 55 38.80952 16.1904762 105 42 45.78333 -3.7833333 106 46 44.37500 1.6250000 107 46 45.78333 0.2166667 108 47 45.78333 1.2166667 109 33 44.37500 -11.3750000 110 53 45.78333 7.2166667 111 42 44.37500 -2.3750000 112 44 45.78333 -1.7833333 113 55 45.78333 9.2166667 114 40 38.80952 1.1904762 115 46 45.78333 0.2166667 116 53 45.78333 7.2166667 117 44 45.78333 -1.7833333 118 35 39.15385 -4.1538462 119 40 38.80952 1.1904762 120 44 44.37500 -0.3750000 121 46 45.78333 0.2166667 122 45 36.11111 8.8888889 123 53 44.37500 8.6250000 124 45 44.37500 0.6250000 125 48 44.37500 3.6250000 126 46 45.78333 0.2166667 127 55 38.80952 16.1904762 128 47 45.78333 1.2166667 129 43 44.37500 -1.3750000 130 38 36.11111 1.8888889 131 40 38.80952 1.1904762 132 47 44.37500 2.6250000 133 47 39.15385 7.8461538 134 42 38.80952 3.1904762 135 53 45.78333 7.2166667 136 43 45.78333 -2.7833333 137 44 44.37500 -0.3750000 138 42 44.37500 -2.3750000 139 51 44.37500 6.6250000 140 54 45.78333 8.2166667 141 41 44.37500 -3.3750000 142 51 45.78333 5.2166667 143 51 44.37500 6.6250000 > 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/49ac41292061980.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/551sv1292061980.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/6yb9y1292061980.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/7jbq41292061980.tab") + } > > try(system("convert tmp/2yiv11292061980.ps tmp/2yiv11292061980.png",intern=TRUE)) character(0) > try(system("convert tmp/3yiv11292061980.ps tmp/3yiv11292061980.png",intern=TRUE)) character(0) > try(system("convert tmp/49ac41292061980.ps tmp/49ac41292061980.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.482 0.794 4.641