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Type 'q()' to quit R. > x <- array(list(25 + ,11 + ,7 + ,8 + ,23 + ,25 + ,17 + ,6 + ,17 + ,8 + ,25 + ,30 + ,18 + ,8 + ,12 + ,9 + ,19 + ,22 + ,16 + ,10 + ,12 + ,7 + ,29 + ,22 + ,20 + ,10 + ,11 + ,4 + ,25 + ,25 + ,16 + ,11 + ,11 + ,11 + ,21 + ,23 + ,18 + ,16 + ,12 + ,7 + ,22 + ,17 + ,17 + ,11 + ,13 + ,7 + ,25 + ,21 + ,30 + ,12 + ,16 + ,10 + ,18 + ,19 + ,23 + ,8 + ,11 + ,10 + ,22 + ,15 + ,18 + ,12 + ,10 + ,8 + ,15 + ,16 + ,21 + ,9 + ,9 + ,9 + ,20 + ,22 + ,31 + ,14 + ,17 + ,11 + ,20 + ,23 + ,27 + ,15 + ,11 + ,9 + ,21 + ,23 + ,21 + ,9 + ,14 + ,13 + ,21 + ,19 + ,16 + ,8 + ,15 + ,9 + ,24 + ,23 + ,20 + ,9 + ,15 + ,6 + ,24 + ,25 + ,17 + ,9 + ,13 + ,6 + ,23 + ,22 + ,25 + ,16 + ,18 + ,16 + ,24 + ,26 + ,26 + ,11 + ,18 + ,5 + ,18 + ,29 + ,25 + ,8 + ,12 + ,7 + ,25 + ,32 + ,17 + ,9 + ,17 + ,9 + ,21 + ,25 + ,32 + ,12 + ,18 + ,12 + ,22 + ,28 + ,22 + ,9 + ,14 + ,9 + ,23 + ,25 + ,17 + ,9 + ,16 + ,5 + ,23 + ,25 + ,20 + ,14 + ,14 + ,10 + ,24 + ,18 + ,29 + ,10 + ,12 + ,8 + ,23 + ,25 + ,23 + ,14 + ,17 + ,7 + 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+ ,19 + ,9 + ,12 + ,7 + ,21 + ,18 + ,15 + ,7 + ,12 + ,6 + ,21 + ,19 + ,23 + ,14 + ,11 + ,10 + ,29 + ,20 + ,17 + ,14 + ,12 + ,6 + ,21 + ,15 + ,21 + ,8 + ,9 + ,11 + ,20 + ,24 + ,17 + ,11 + ,9 + ,6 + ,19 + ,20 + ,25 + ,14 + ,15 + ,9 + ,24 + ,22 + ,20 + ,11 + ,8 + ,4 + ,13 + ,13 + ,19 + ,20 + ,8 + ,7 + ,25 + ,19 + ,20 + ,11 + ,17 + ,8 + ,23 + ,21 + ,17 + ,9 + ,11 + ,5 + ,26 + ,23 + ,21 + ,10 + ,12 + ,8 + ,23 + ,16 + ,26 + ,13 + ,20 + ,10 + ,22 + ,26 + ,17 + ,8 + ,12 + ,9 + ,24 + ,21 + ,21 + ,15 + ,7 + ,5 + ,24 + ,21 + ,28 + ,14 + ,11 + ,8 + ,24 + ,24) + ,dim=c(6 + ,159) + ,dimnames=list(c('CM' + ,'D' + ,'PE' + ,'PC' + ,'O' + ,'PS ') + ,1:159)) > y <- array(NA,dim=c(6,159),dimnames=list(c('CM','D','PE','PC','O','PS '),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 = '0' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "CM" > x[,par1] [1] 25 17 18 16 20 16 18 17 30 23 18 21 31 27 21 16 20 17 25 26 25 17 32 22 17 [26] 20 29 23 20 11 26 22 14 19 20 28 19 30 29 26 23 21 28 23 18 20 21 28 10 22 [51] 31 29 22 23 20 18 25 21 24 25 13 28 25 9 16 19 29 14 22 15 15 20 18 33 22 [76] 16 16 18 18 22 30 30 24 21 29 31 20 16 22 20 28 38 22 20 17 22 31 24 18 23 [101] 15 12 15 20 34 31 19 21 22 24 32 33 13 25 29 18 20 15 33 26 18 28 17 12 17 [126] 21 18 10 29 31 19 9 13 19 21 23 21 15 19 26 16 19 31 19 15 23 17 21 17 25 [151] 20 19 20 17 21 26 17 21 28 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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] "CM" "D" "PE" "PC" "O" "PS." > colnames(x)[par1] [1] "CM" > x[,par1] [1] 25 17 18 16 20 16 18 17 30 23 18 21 31 27 21 16 20 17 25 26 25 17 32 22 17 [26] 20 29 23 20 11 26 22 14 19 20 28 19 30 29 26 23 21 28 23 18 20 21 28 10 22 [51] 31 29 22 23 20 18 25 21 24 25 13 28 25 9 16 19 29 14 22 15 15 20 18 33 22 [76] 16 16 18 18 22 30 30 24 21 29 31 20 16 22 20 28 38 22 20 17 22 31 24 18 23 [101] 15 12 15 20 34 31 19 21 22 24 32 33 13 25 29 18 20 15 33 26 18 28 17 12 17 [126] 21 18 10 29 31 19 9 13 19 21 23 21 15 19 26 16 19 31 19 15 23 17 21 17 25 [151] 20 19 20 17 21 26 17 21 28 > 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/1qd4l1292919744.tab") + } + } > m Conditional inference tree with 6 terminal nodes Response: CM Inputs: D, PE, PC, O, PS. Number of observations: 159 1) PS. <= 25; criterion = 1, statistic = 28.54 2) PC <= 7; criterion = 1, statistic = 22.429 3) PS. <= 22; criterion = 0.955, statistic = 6.782 4)* weights = 38 3) PS. > 22 5)* weights = 12 2) PC > 7 6) D <= 12; criterion = 1, statistic = 15.524 7)* weights = 52 6) D > 12 8)* weights = 28 1) PS. > 25 9) D <= 10; criterion = 0.997, statistic = 12.056 10)* weights = 13 9) D > 10 11)* weights = 16 > postscript(file="/var/www/html/rcomp/tmp/2qd4l1292919744.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/3qd4l1292919744.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 25 20.42308 4.57692308 2 17 21.46154 -4.46153846 3 18 20.42308 -2.42307692 4 16 17.21053 -1.21052632 5 20 21.50000 -1.50000000 6 16 20.42308 -4.42307692 7 18 17.21053 0.78947368 8 17 17.21053 -0.21052632 9 30 20.42308 9.57692308 10 23 20.42308 2.57692308 11 18 20.42308 -2.42307692 12 21 20.42308 0.57692308 13 31 25.07143 5.92857143 14 27 25.07143 1.92857143 15 21 20.42308 0.57692308 16 16 20.42308 -4.42307692 17 20 21.50000 -1.50000000 18 17 17.21053 -0.21052632 19 25 29.81250 -4.81250000 20 26 29.81250 -3.81250000 21 25 21.46154 3.53846154 22 17 20.42308 -3.42307692 23 32 29.81250 2.18750000 24 22 20.42308 1.57692308 25 17 21.50000 -4.50000000 26 20 25.07143 -5.07142857 27 29 20.42308 8.57692308 28 23 21.50000 1.50000000 29 20 20.42308 -0.42307692 30 11 17.21053 -6.21052632 31 26 25.07143 0.92857143 32 22 21.46154 0.53846154 33 14 25.07143 -11.07142857 34 19 21.50000 -2.50000000 35 20 20.42308 -0.42307692 36 28 17.21053 10.78947368 37 19 17.21053 1.78947368 38 30 21.46154 8.53846154 39 29 25.07143 3.92857143 40 26 21.50000 4.50000000 41 23 20.42308 2.57692308 42 21 20.42308 0.57692308 43 28 21.50000 6.50000000 44 23 25.07143 -2.07142857 45 18 20.42308 -2.42307692 46 20 20.42308 -0.42307692 47 21 21.46154 -0.46153846 48 28 29.81250 -1.81250000 49 10 17.21053 -7.21052632 50 22 17.21053 4.78947368 51 31 21.46154 9.53846154 52 29 25.07143 3.92857143 53 22 20.42308 1.57692308 54 23 20.42308 2.57692308 55 20 20.42308 -0.42307692 56 18 20.42308 -2.42307692 57 25 17.21053 7.78947368 58 21 17.21053 3.78947368 59 24 20.42308 3.57692308 60 25 25.07143 -0.07142857 61 13 17.21053 -4.21052632 62 28 20.42308 7.57692308 63 25 21.46154 3.53846154 64 9 21.46154 -12.46153846 65 16 17.21053 -1.21052632 66 19 20.42308 -1.42307692 67 29 29.81250 -0.81250000 68 14 17.21053 -3.21052632 69 22 25.07143 -3.07142857 70 15 17.21053 -2.21052632 71 15 17.21053 -2.21052632 72 20 20.42308 -0.42307692 73 18 20.42308 -2.42307692 74 33 29.81250 3.18750000 75 22 20.42308 1.57692308 76 16 20.42308 -4.42307692 77 16 17.21053 -1.21052632 78 18 17.21053 0.78947368 79 18 20.42308 -2.42307692 80 22 25.07143 -3.07142857 81 30 25.07143 4.92857143 82 30 29.81250 0.18750000 83 24 25.07143 -1.07142857 84 21 25.07143 -4.07142857 85 29 29.81250 -0.81250000 86 31 20.42308 10.57692308 87 20 17.21053 2.78947368 88 16 20.42308 -4.42307692 89 22 20.42308 1.57692308 90 20 21.46154 -1.46153846 91 28 25.07143 2.92857143 92 38 29.81250 8.18750000 93 22 17.21053 4.78947368 94 20 20.42308 -0.42307692 95 17 17.21053 -0.21052632 96 22 25.07143 -3.07142857 97 31 25.07143 5.92857143 98 24 25.07143 -1.07142857 99 18 20.42308 -2.42307692 100 23 25.07143 -2.07142857 101 15 20.42308 -5.42307692 102 12 21.46154 -9.46153846 103 15 20.42308 -5.42307692 104 20 17.21053 2.78947368 105 34 25.07143 8.92857143 106 31 25.07143 5.92857143 107 19 20.42308 -1.42307692 108 21 20.42308 0.57692308 109 22 20.42308 1.57692308 110 24 21.50000 2.50000000 111 32 29.81250 2.18750000 112 33 29.81250 3.18750000 113 13 17.21053 -4.21052632 114 25 29.81250 -4.81250000 115 29 29.81250 -0.81250000 116 18 20.42308 -2.42307692 117 20 21.46154 -1.46153846 118 15 20.42308 -5.42307692 119 33 29.81250 3.18750000 120 26 21.50000 4.50000000 121 18 20.42308 -2.42307692 122 28 21.46154 6.53846154 123 17 21.50000 -4.50000000 124 12 17.21053 -5.21052632 125 17 20.42308 -3.42307692 126 21 21.50000 -0.50000000 127 18 25.07143 -7.07142857 128 10 17.21053 -7.21052632 129 29 29.81250 -0.81250000 130 31 20.42308 10.57692308 131 19 21.46154 -2.46153846 132 9 17.21053 -8.21052632 133 13 17.21053 -4.21052632 134 19 20.42308 -1.42307692 135 21 20.42308 0.57692308 136 23 17.21053 5.78947368 137 21 17.21053 3.78947368 138 15 25.07143 -10.07142857 139 19 17.21053 1.78947368 140 26 25.07143 0.92857143 141 16 17.21053 -1.21052632 142 19 20.42308 -1.42307692 143 31 25.07143 5.92857143 144 19 17.21053 1.78947368 145 15 17.21053 -2.21052632 146 23 25.07143 -2.07142857 147 17 17.21053 -0.21052632 148 21 20.42308 0.57692308 149 17 17.21053 -0.21052632 150 25 25.07143 -0.07142857 151 20 17.21053 2.78947368 152 19 17.21053 1.78947368 153 20 20.42308 -0.42307692 154 17 21.50000 -4.50000000 155 21 20.42308 0.57692308 156 26 29.81250 -3.81250000 157 17 20.42308 -3.42307692 158 21 17.21053 3.78947368 159 28 25.07143 2.92857143 > 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/rcomp/tmp/4043o1292919744.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/5xe1x1292919744.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/6p50i1292919744.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/7t6z61292919744.tab") + } > > try(system("convert tmp/2qd4l1292919744.ps tmp/2qd4l1292919744.png",intern=TRUE)) character(0) > try(system("convert tmp/3qd4l1292919744.ps tmp/3qd4l1292919744.png",intern=TRUE)) character(0) > try(system("convert tmp/4043o1292919744.ps tmp/4043o1292919744.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.084 0.568 9.146