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Type 'q()' to quit R. > x <- array(list(22 + ,1 + ,27 + ,5 + ,26 + ,49 + ,35 + ,23 + ,1 + ,36 + ,4 + ,25 + ,45 + ,34 + ,27 + ,1 + ,25 + ,4 + ,17 + ,54 + ,13 + ,19 + ,1 + ,27 + ,3 + ,37 + ,36 + ,35 + ,15 + ,2 + ,25 + ,3 + ,35 + ,36 + ,28 + ,29 + ,2 + ,44 + ,3 + ,15 + ,53 + ,32 + ,25 + ,1 + ,50 + ,4 + ,27 + ,46 + ,35 + ,25 + ,1 + ,41 + ,4 + ,36 + ,42 + ,36 + ,21 + ,1 + ,48 + ,5 + ,25 + ,41 + ,27 + ,22 + ,2 + ,43 + ,4 + ,30 + ,45 + ,29 + ,22 + ,2 + ,47 + ,2 + ,27 + ,47 + ,27 + ,24 + ,2 + ,41 + ,3 + ,33 + ,42 + ,28 + ,22 + ,1 + ,44 + ,2 + ,29 + ,45 + ,29 + ,23 + ,2 + ,47 + ,5 + ,30 + ,40 + ,28 + ,19 + ,2 + ,40 + ,3 + ,25 + ,45 + ,30 + ,19 + ,2 + ,46 + ,3 + ,23 + ,40 + ,25 + ,21 + ,1 + ,28 + ,3 + ,26 + ,42 + ,15 + ,20 + ,1 + ,56 + ,3 + ,24 + ,45 + ,33 + ,23 + ,2 + ,49 + ,4 + ,35 + ,47 + ,31 + ,11 + ,2 + ,25 + ,4 + ,39 + ,31 + ,37 + ,21 + ,2 + ,41 + ,4 + ,23 + ,46 + ,37 + ,19 + ,2 + ,26 + ,3 + ,32 + ,34 + ,34 + ,21 + ,1 + ,50 + ,5 + ,29 + ,43 + ,32 + ,23 + ,1 + ,47 + ,4 + ,26 + ,45 + ,21 + 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,1:195)) > y <- array(NA,dim=c(7,195),dimnames=list(c('Behoefte_affiliatie','geslacht','leeftijd','opleiding','Neuroticisme','Extraversie','Openheid'),1:195)) > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Behoefte_affiliatie" > x[,par1] [1] 22 23 27 19 15 29 25 25 21 22 22 24 22 23 19 19 21 20 23 11 21 19 21 23 19 [26] 22 19 23 29 27 18 30 26 20 22 20 21 18 21 27 18 24 24 17 22 21 23 19 22 19 [51] 24 22 26 22 23 27 21 16 21 18 25 20 24 20 24 23 23 22 22 20 14 21 23 17 25 [76] 10 25 23 27 16 19 23 19 19 26 19 22 21 22 20 20 20 21 21 14 28 24 24 24 19 [101] 19 14 29 22 21 15 23 24 20 25 25 19 23 22 19 24 21 19 21 18 24 7 24 24 23 [126] 24 27 20 20 22 19 18 14 24 29 25 24 20 18 25 21 21 21 23 18 23 13 23 17 24 [151] 16 23 20 24 15 20 27 27 19 22 16 21 18 22 18 24 24 19 26 28 23 22 20 20 27 [176] 19 23 19 21 13 18 19 23 30 22 23 22 22 23 27 23 18 24 19 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 7 10 11 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 1 1 1 2 4 3 4 3 12 24 17 21 23 25 22 9 4 10 2 4 2 > colnames(x) [1] "Behoefte_affiliatie" "geslacht" "leeftijd" [4] "opleiding" "Neuroticisme" "Extraversie" [7] "Openheid" > colnames(x)[par1] [1] "Behoefte_affiliatie" > x[,par1] [1] 22 23 27 19 15 29 25 25 21 22 22 24 22 23 19 19 21 20 23 11 21 19 21 23 19 [26] 22 19 23 29 27 18 30 26 20 22 20 21 18 21 27 18 24 24 17 22 21 23 19 22 19 [51] 24 22 26 22 23 27 21 16 21 18 25 20 24 20 24 23 23 22 22 20 14 21 23 17 25 [76] 10 25 23 27 16 19 23 19 19 26 19 22 21 22 20 20 20 21 21 14 28 24 24 24 19 [101] 19 14 29 22 21 15 23 24 20 25 25 19 23 22 19 24 21 19 21 18 24 7 24 24 23 [126] 24 27 20 20 22 19 18 14 24 29 25 24 20 18 25 21 21 21 23 18 23 13 23 17 24 [151] 16 23 20 24 15 20 27 27 19 22 16 21 18 22 18 24 24 19 26 28 23 22 20 20 27 [176] 19 23 19 21 13 18 19 23 30 22 23 22 22 23 27 23 18 24 19 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/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/rcomp/tmp/1pw6h1293467606.tab") + } + } > m Conditional inference tree with 3 terminal nodes Response: Behoefte_affiliatie Inputs: geslacht, leeftijd, opleiding, Neuroticisme, Extraversie, Openheid Number of observations: 194 1) Extraversie <= 36; criterion = 1, statistic = 43.781 2)* weights = 26 1) Extraversie > 36 3) Extraversie <= 50; criterion = 0.998, statistic = 13.149 4)* weights = 143 3) Extraversie > 50 5)* weights = 25 > postscript(file="/var/www/html/rcomp/tmp/2pw6h1293467606.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/rcomp/tmp/3zn521293467606.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 22 21.62937 0.3706294 2 23 21.62937 1.3706294 3 27 24.40000 2.6000000 4 19 17.69231 1.3076923 5 15 17.69231 -2.6923077 6 29 24.40000 4.6000000 7 25 21.62937 3.3706294 8 25 21.62937 3.3706294 9 21 21.62937 -0.6293706 10 22 21.62937 0.3706294 11 22 21.62937 0.3706294 12 24 21.62937 2.3706294 13 22 21.62937 0.3706294 14 23 21.62937 1.3706294 15 19 21.62937 -2.6293706 16 19 21.62937 -2.6293706 17 21 21.62937 -0.6293706 18 20 21.62937 -1.6293706 19 23 21.62937 1.3706294 20 11 17.69231 -6.6923077 21 21 21.62937 -0.6293706 22 19 17.69231 1.3076923 23 21 21.62937 -0.6293706 24 23 21.62937 1.3706294 25 19 21.62937 -2.6293706 26 22 24.40000 -2.4000000 27 19 21.62937 -2.6293706 28 23 21.62937 1.3706294 29 29 21.62937 7.3706294 30 27 21.62937 5.3706294 31 18 21.62937 -3.6293706 32 30 24.40000 5.6000000 33 26 21.62937 4.3706294 34 20 21.62937 -1.6293706 35 22 21.62937 0.3706294 36 20 21.62937 -1.6293706 37 21 21.62937 -0.6293706 38 18 21.62937 -3.6293706 39 21 17.69231 3.3076923 40 27 24.40000 2.6000000 41 18 21.62937 -3.6293706 42 24 21.62937 2.3706294 43 24 21.62937 2.3706294 44 17 17.69231 -0.6923077 45 22 21.62937 0.3706294 46 21 21.62937 -0.6293706 47 23 21.62937 1.3706294 48 19 24.40000 -5.4000000 49 22 24.40000 -2.4000000 50 19 21.62937 -2.6293706 51 24 24.40000 -0.4000000 52 22 21.62937 0.3706294 53 26 17.69231 8.3076923 54 22 24.40000 -2.4000000 55 23 21.62937 1.3706294 56 27 24.40000 2.6000000 57 21 21.62937 -0.6293706 58 16 17.69231 -1.6923077 59 21 24.40000 -3.4000000 60 18 21.62937 -3.6293706 61 25 21.62937 3.3706294 62 20 21.62937 -1.6293706 63 24 21.62937 2.3706294 64 20 24.40000 -4.4000000 65 24 21.62937 2.3706294 66 23 21.62937 1.3706294 67 23 21.62937 1.3706294 68 22 21.62937 0.3706294 69 22 21.62937 0.3706294 70 20 21.62937 -1.6293706 71 14 17.69231 -3.6923077 72 21 17.69231 3.3076923 73 23 21.62937 1.3706294 74 17 21.62937 -4.6293706 75 25 24.40000 0.6000000 76 10 17.69231 -7.6923077 77 25 24.40000 0.6000000 78 23 24.40000 -1.4000000 79 27 21.62937 5.3706294 80 16 21.62937 -5.6293706 81 19 17.69231 1.3076923 82 23 21.62937 1.3706294 83 19 21.62937 -2.6293706 84 19 21.62937 -2.6293706 85 26 24.40000 1.6000000 86 19 17.69231 1.3076923 87 22 21.62937 0.3706294 88 21 21.62937 -0.6293706 89 22 21.62937 0.3706294 90 20 21.62937 -1.6293706 91 20 21.62937 -1.6293706 92 20 17.69231 2.3076923 93 21 21.62937 -0.6293706 94 21 21.62937 -0.6293706 95 14 21.62937 -7.6293706 96 28 21.62937 6.3706294 97 24 21.62937 2.3706294 98 24 24.40000 -0.4000000 99 24 21.62937 2.3706294 100 19 21.62937 -2.6293706 101 19 21.62937 -2.6293706 102 14 17.69231 -3.6923077 103 29 21.62937 7.3706294 104 22 21.62937 0.3706294 105 21 21.62937 -0.6293706 106 15 21.62937 -6.6293706 107 23 21.62937 1.3706294 108 24 17.69231 6.3076923 109 20 24.40000 -4.4000000 110 25 21.62937 3.3706294 111 25 21.62937 3.3706294 112 19 17.69231 1.3076923 113 23 21.62937 1.3706294 114 22 21.62937 0.3706294 115 19 21.62937 -2.6293706 116 24 21.62937 2.3706294 117 21 21.62937 -0.6293706 118 19 21.62937 -2.6293706 119 21 21.62937 -0.6293706 120 18 17.69231 0.3076923 121 24 21.62937 2.3706294 122 7 17.69231 -10.6923077 123 24 21.62937 2.3706294 124 24 21.62937 2.3706294 125 23 17.69231 5.3076923 126 24 24.40000 -0.4000000 127 27 24.40000 2.6000000 128 20 21.62937 -1.6293706 129 20 21.62937 -1.6293706 130 22 21.62937 0.3706294 131 19 21.62937 -2.6293706 132 18 21.62937 -3.6293706 133 14 21.62937 -7.6293706 134 24 21.62937 2.3706294 135 29 24.40000 4.6000000 136 25 21.62937 3.3706294 137 24 21.62937 2.3706294 138 20 21.62937 -1.6293706 139 18 21.62937 -3.6293706 140 25 21.62937 3.3706294 141 21 21.62937 -0.6293706 142 21 21.62937 -0.6293706 143 21 21.62937 -0.6293706 144 23 21.62937 1.3706294 145 18 21.62937 -3.6293706 146 23 21.62937 1.3706294 147 13 17.69231 -4.6923077 148 23 17.69231 5.3076923 149 17 17.69231 -0.6923077 150 24 21.62937 2.3706294 151 16 21.62937 -5.6293706 152 23 21.62937 1.3706294 153 20 21.62937 -1.6293706 154 24 21.62937 2.3706294 155 15 17.69231 -2.6923077 156 20 21.62937 -1.6293706 157 27 21.62937 5.3706294 158 27 21.62937 5.3706294 159 19 21.62937 -2.6293706 160 22 21.62937 0.3706294 161 16 21.62937 -5.6293706 162 21 21.62937 -0.6293706 163 18 17.69231 0.3076923 164 22 21.62937 0.3706294 165 18 21.62937 -3.6293706 166 24 24.40000 -0.4000000 167 24 21.62937 2.3706294 168 19 21.62937 -2.6293706 169 26 21.62937 4.3706294 170 28 24.40000 3.6000000 171 23 21.62937 1.3706294 172 22 17.69231 4.3076923 173 20 21.62937 -1.6293706 174 20 21.62937 -1.6293706 175 27 21.62937 5.3706294 176 19 21.62937 -2.6293706 177 23 21.62937 1.3706294 178 19 21.62937 -2.6293706 179 21 21.62937 -0.6293706 180 13 21.62937 -8.6293706 181 18 21.62937 -3.6293706 182 19 21.62937 -2.6293706 183 23 21.62937 1.3706294 184 30 21.62937 8.3706294 185 22 24.40000 -2.4000000 186 23 24.40000 -1.4000000 187 22 21.62937 0.3706294 188 22 21.62937 0.3706294 189 23 21.62937 1.3706294 190 27 21.62937 5.3706294 191 23 21.62937 1.3706294 192 18 21.62937 -3.6293706 193 24 21.62937 2.3706294 194 19 21.62937 -2.6293706 > 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/rcomp/tmp/4axmn1293467606.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/rcomp/tmp/5vxlt1293467606.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/rcomp/tmp/6zgkz1293467606.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/rcomp/tmp/7apjj1293467606.tab") + } > > try(system("convert tmp/2pw6h1293467606.ps tmp/2pw6h1293467606.png",intern=TRUE)) character(0) > try(system("convert tmp/3zn521293467606.ps tmp/3zn521293467606.png",intern=TRUE)) character(0) > try(system("convert tmp/4axmn1293467606.ps tmp/4axmn1293467606.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.446 0.603 8.501