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Type 'q()' to quit R. > x <- array(list(0 + ,1 + ,24 + ,14 + ,11 + ,12 + ,24 + ,26 + ,1 + ,1 + ,25 + ,11 + ,7 + ,8 + ,25 + ,23 + ,1 + ,0 + ,17 + ,6 + ,17 + ,8 + ,30 + ,25 + ,0 + ,1 + ,18 + ,12 + ,10 + ,8 + ,19 + ,23 + ,1 + ,0 + ,16 + ,10 + ,12 + ,7 + ,22 + ,29 + ,1 + ,1 + ,20 + ,10 + ,11 + ,4 + ,25 + ,25 + ,1 + ,1 + ,16 + ,11 + ,11 + ,11 + ,23 + ,21 + ,1 + ,1 + ,18 + ,16 + ,12 + ,7 + ,17 + ,22 + ,1 + ,1 + ,17 + ,11 + ,13 + ,7 + ,21 + ,25 + ,0 + ,1 + ,23 + ,13 + ,14 + ,12 + ,19 + ,24 + ,1 + ,1 + ,30 + ,12 + ,16 + ,10 + ,19 + ,18 + ,1 + ,1 + ,18 + ,12 + ,10 + ,8 + ,16 + ,15 + ,0 + ,1 + ,15 + ,11 + ,11 + ,8 + ,23 + ,22 + ,0 + ,1 + ,12 + ,4 + ,15 + ,4 + ,27 + ,28 + ,1 + ,1 + ,21 + ,9 + ,9 + ,9 + ,22 + ,20 + ,0 + ,1 + ,20 + ,8 + ,17 + ,7 + ,22 + ,24 + ,1 + ,1 + ,27 + ,15 + ,11 + ,9 + ,23 + ,21 + ,0 + ,1 + ,34 + ,16 + ,18 + ,11 + ,21 + ,20 + ,1 + ,1 + ,21 + ,9 + ,14 + ,13 + ,19 + ,21 + ,0 + ,1 + ,31 + ,14 + ,10 + ,8 + ,18 + ,23 + ,0 + ,1 + ,19 + ,11 + ,11 + ,8 + ,20 + ,28 + ,1 + ,1 + ,16 + 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+ ,10 + ,20 + ,29 + ,1 + ,1 + ,24 + ,9 + ,13 + ,10 + ,19 + ,15 + ,1 + ,1 + ,25 + ,14 + ,15 + ,11 + ,22 + ,21 + ,1 + ,1 + ,13 + ,8 + ,12 + ,7 + ,14 + ,19 + ,1 + ,1 + ,28 + ,8 + ,16 + ,12 + ,18 + ,24 + ,1 + ,0 + ,25 + ,7 + ,18 + ,11 + ,35 + ,17 + ,1 + ,1 + ,9 + ,6 + ,8 + ,11 + ,29 + ,23 + ,0 + ,1 + ,17 + ,11 + ,9 + ,6 + ,20 + ,19 + ,0 + ,1 + ,25 + ,14 + ,15 + ,9 + ,22 + ,24 + ,1 + ,1 + ,15 + ,8 + ,6 + ,6 + ,20 + ,25 + ,0 + ,1 + ,19 + ,20 + ,8 + ,7 + ,19 + ,25 + ,1 + ,0 + ,15 + ,8 + ,10 + ,4 + ,22 + ,24 + ,1 + ,1 + ,20 + ,11 + ,11 + ,8 + ,24 + ,26 + ,1 + ,1 + ,18 + ,10 + ,14 + ,9 + ,21 + ,26 + ,1 + ,1 + ,33 + ,14 + ,11 + ,8 + ,26 + ,25 + ,1 + ,1 + ,16 + ,9 + ,12 + ,8 + ,16 + ,21 + ,0 + ,1 + ,17 + ,9 + ,11 + ,5 + ,23 + ,26 + ,1 + ,1 + ,16 + ,8 + ,9 + ,4 + ,18 + ,23 + ,0 + ,1 + ,21 + ,10 + ,12 + ,8 + ,16 + ,23 + ,0 + ,1 + ,26 + ,13 + ,20 + ,10 + ,26 + ,22 + ,1 + ,1 + ,18 + ,12 + ,13 + ,9 + ,21 + ,13 + ,1 + ,1 + ,22 + ,13 + ,12 + ,13 + ,22 + ,15 + ,1 + ,1 + ,30 + ,14 + ,9 + ,9 + ,23 + ,14 + ,1 + ,1 + ,24 + ,14 + ,24 + ,20 + ,21 + ,10 + ,1 + ,1 + ,29 + ,16 + ,11 + ,6 + ,27 + ,24 + ,1 + ,1 + ,31 + ,9 + ,17 + ,9 + ,25 + ,19 + ,1 + ,0 + ,20 + ,9 + ,11 + ,7 + ,21 + ,20 + ,1 + ,1 + ,20 + ,7 + ,11 + ,9 + ,26 + ,22 + ,1 + ,1 + ,28 + ,16 + ,16 + ,8 + ,24 + ,24 + ,1 + ,1 + ,17 + ,9 + ,13 + ,6 + ,19 + ,21 + ,0 + ,1 + ,28 + ,14 + ,11 + ,8 + ,2 + ,24 + ,1 + ,1 + ,31 + ,16 + ,19 + ,16 + ,17 + ,20) + ,dim=c(8 + ,120) + ,dimnames=list(c('G' + ,'B' + ,'CM' + ,'D' + ,'PE' + ,'PC' + ,'PS' + ,'O ') + ,1:120)) > y <- array(NA,dim=c(8,120),dimnames=list(c('G','B','CM','D','PE','PC','PS','O '),1:120)) > 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 = '2' > par2 = 'quantiles' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "PE" > x[,par1] [1] 11 7 17 10 12 11 11 12 13 14 16 10 11 15 9 17 11 18 14 10 11 15 15 13 16 [26] 13 9 18 18 12 17 9 9 18 12 18 14 15 16 10 11 14 9 17 5 12 12 6 24 12 [51] 12 14 7 12 14 8 11 9 11 10 11 12 9 18 15 12 13 14 10 13 13 11 13 16 11 [76] 16 14 8 9 15 11 21 14 18 12 13 12 19 11 13 15 12 16 18 8 9 15 6 8 10 [101] 11 14 11 12 11 9 12 20 13 12 9 24 11 17 11 11 16 13 11 19 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) [ 5,13) [13,24] 65 55 > colnames(x) [1] "G" "B" "CM" "D" "PE" "PC" "PS" "O." > colnames(x)[par1] [1] "PE" > x[,par1] [1] [ 5,13) [ 5,13) [13,24] [ 5,13) [ 5,13) [ 5,13) [ 5,13) [ 5,13) [13,24] [10] [13,24] [13,24] [ 5,13) [ 5,13) [13,24] [ 5,13) [13,24] [ 5,13) [13,24] [19] [13,24] [ 5,13) [ 5,13) [13,24] [13,24] [13,24] [13,24] [13,24] [ 5,13) [28] [13,24] [13,24] [ 5,13) [13,24] [ 5,13) [ 5,13) [13,24] [ 5,13) [13,24] [37] [13,24] [13,24] [13,24] [ 5,13) [ 5,13) [13,24] [ 5,13) [13,24] [ 5,13) [46] [ 5,13) [ 5,13) [ 5,13) [13,24] [ 5,13) [ 5,13) [13,24] [ 5,13) [ 5,13) [55] [13,24] [ 5,13) [ 5,13) [ 5,13) [ 5,13) [ 5,13) [ 5,13) [ 5,13) [ 5,13) [64] [13,24] [13,24] [ 5,13) [13,24] [13,24] [ 5,13) [13,24] [13,24] [ 5,13) [73] [13,24] [13,24] [ 5,13) [13,24] [13,24] [ 5,13) [ 5,13) [13,24] [ 5,13) [82] [13,24] [13,24] [13,24] [ 5,13) [13,24] [ 5,13) [13,24] [ 5,13) [13,24] [91] [13,24] [ 5,13) [13,24] [13,24] [ 5,13) [ 5,13) [13,24] [ 5,13) [ 5,13) [100] [ 5,13) [ 5,13) [13,24] [ 5,13) [ 5,13) [ 5,13) [ 5,13) [ 5,13) [13,24] [109] [13,24] [ 5,13) [ 5,13) [13,24] [ 5,13) [13,24] [ 5,13) [ 5,13) [13,24] [118] [13,24] [ 5,13) [13,24] Levels: [ 5,13) [13,24] > 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/16zsx1291987177.tab") + } + } > m Conditional inference tree with 2 terminal nodes Response: as.factor(PE) Inputs: G, B, CM, D, PC, PS, O. Number of observations: 120 1) PC <= 8; criterion = 1, statistic = 16.792 2)* weights = 74 1) PC > 8 3)* weights = 46 > postscript(file="/var/www/html/rcomp/tmp/26zsx1291987177.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/36zsx1291987177.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) + } > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } [,1] [,2] [1,] 1 2 [2,] 1 1 [3,] 2 1 [4,] 1 1 [5,] 1 1 [6,] 1 1 [7,] 1 2 [8,] 1 1 [9,] 2 1 [10,] 2 2 [11,] 2 2 [12,] 1 1 [13,] 1 1 [14,] 2 1 [15,] 1 2 [16,] 2 1 [17,] 1 2 [18,] 2 2 [19,] 2 2 [20,] 1 1 [21,] 1 1 [22,] 2 2 [23,] 2 1 [24,] 2 2 [25,] 2 2 [26,] 2 1 [27,] 1 1 [28,] 2 2 [29,] 2 1 [30,] 1 1 [31,] 2 2 [32,] 1 1 [33,] 1 1 [34,] 2 2 [35,] 1 1 [36,] 2 2 [37,] 2 2 [38,] 2 1 [39,] 2 1 [40,] 1 1 [41,] 1 1 [42,] 2 2 [43,] 1 1 [44,] 2 1 [45,] 1 1 [46,] 1 1 [47,] 1 1 [48,] 1 1 [49,] 2 2 [50,] 1 1 [51,] 1 1 [52,] 2 1 [53,] 1 1 [54,] 1 2 [55,] 2 1 [56,] 1 2 [57,] 1 1 [58,] 1 1 [59,] 1 1 [60,] 1 1 [61,] 1 1 [62,] 1 1 [63,] 1 1 [64,] 2 2 [65,] 2 1 [66,] 1 1 [67,] 2 1 [68,] 2 2 [69,] 1 1 [70,] 2 1 [71,] 2 2 [72,] 1 1 [73,] 2 1 [74,] 2 2 [75,] 1 1 [76,] 2 2 [77,] 2 1 [78,] 1 1 [79,] 1 1 [80,] 2 1 [81,] 1 2 [82,] 2 2 [83,] 2 2 [84,] 2 2 [85,] 1 1 [86,] 2 1 [87,] 1 1 [88,] 2 2 [89,] 1 2 [90,] 2 2 [91,] 2 2 [92,] 1 1 [93,] 2 2 [94,] 2 2 [95,] 1 2 [96,] 1 1 [97,] 2 2 [98,] 1 1 [99,] 1 1 [100,] 1 1 [101,] 1 1 [102,] 2 2 [103,] 1 1 [104,] 1 1 [105,] 1 1 [106,] 1 1 [107,] 1 1 [108,] 2 2 [109,] 2 2 [110,] 1 2 [111,] 1 2 [112,] 2 2 [113,] 1 1 [114,] 2 2 [115,] 1 1 [116,] 1 2 [117,] 2 1 [118,] 2 1 [119,] 1 1 [120,] 2 2 [ 5,13) [13,24] [ 5,13) 53 12 [13,24] 21 34 > postscript(file="/var/www/html/rcomp/tmp/4z9ai1291987177.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/5298o1291987177.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/6os7c1291987177.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/79a5i1291987177.tab") + } > > try(system("convert tmp/26zsx1291987177.ps tmp/26zsx1291987177.png",intern=TRUE)) character(0) > try(system("convert tmp/36zsx1291987177.ps tmp/36zsx1291987177.png",intern=TRUE)) character(0) > try(system("convert tmp/4z9ai1291987177.ps tmp/4z9ai1291987177.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.128 0.475 5.582