R version 2.9.0 (2009-04-17) Copyright (C) 2009 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. 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(1 + ,41 + ,25 + ,15 + ,9 + ,3 + ,1 + ,38 + ,25 + ,15 + ,9 + ,4 + ,1 + ,37 + ,19 + ,14 + ,9 + ,4 + ,1 + ,42 + ,18 + ,10 + ,8 + ,4 + ,1 + ,40 + ,23 + ,18 + ,15 + ,3 + ,1 + ,43 + ,25 + ,14 + ,9 + ,4 + ,1 + ,40 + ,23 + ,11 + ,11 + ,4 + ,1 + ,45 + ,30 + ,17 + ,6 + ,5 + ,1 + ,45 + ,32 + ,21 + ,10 + ,4 + ,1 + ,44 + ,25 + ,7 + ,11 + ,4 + ,1 + ,42 + ,26 + ,18 + ,16 + ,4 + ,1 + ,32 + ,25 + ,13 + ,11 + ,5 + ,1 + ,32 + ,25 + ,13 + ,11 + ,5 + ,1 + ,41 + ,35 + ,18 + ,7 + ,4 + ,1 + ,38 + ,20 + ,12 + ,10 + ,4 + ,1 + ,38 + ,21 + ,9 + ,9 + ,4 + ,1 + ,24 + ,23 + ,11 + ,15 + ,3 + ,1 + ,46 + ,17 + ,11 + ,6 + ,5 + ,1 + ,42 + ,27 + ,16 + ,12 + ,4 + ,1 + ,46 + ,25 + ,12 + ,10 + ,4 + ,1 + ,43 + ,18 + ,14 + ,14 + ,5 + ,1 + ,38 + ,22 + ,13 + ,9 + ,4 + ,1 + ,39 + ,23 + ,17 + ,14 + ,4 + ,1 + ,40 + ,25 + ,13 + ,14 + ,3 + ,1 + ,37 + ,19 + ,13 + ,9 + ,2 + ,1 + ,41 + ,20 + ,12 + ,8 + ,4 + ,1 + ,46 + ,26 + ,12 + ,10 + ,4 + ,1 + ,26 + ,16 + ,12 + ,9 + ,3 + ,1 + ,37 + ,22 + ,9 + ,9 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+ ,9 + ,8 + ,5 + ,0 + ,28 + ,15 + ,12 + ,14 + ,4 + ,0 + ,35 + ,21 + ,11 + ,9 + ,2 + ,0 + ,38 + ,21 + ,14 + ,16 + ,4 + ,0 + ,42 + ,13 + ,8 + ,11 + ,4 + ,0 + ,36 + ,20 + ,11 + ,12 + ,3 + ,0 + ,37 + ,22 + ,11 + ,8 + ,4 + ,0 + ,38 + ,19 + ,12 + ,7 + ,3 + ,0 + ,43 + ,26 + ,20 + ,13 + ,4 + ,0 + ,35 + ,19 + ,8 + ,20 + ,2 + ,0 + ,36 + ,20 + ,11 + ,11 + ,4 + ,0 + ,33 + ,14 + ,15 + ,10 + ,2 + ,0 + ,39 + ,17 + ,12 + ,16 + ,4 + ,0 + ,32 + ,29 + ,12 + ,12 + ,4 + ,0 + ,45 + ,21 + ,12 + ,8 + ,3 + ,0 + ,35 + ,19 + ,11 + ,10 + ,4 + ,0 + ,38 + ,17 + ,9 + ,11 + ,3 + ,0 + ,36 + ,19 + ,8 + ,14 + ,3 + ,0 + ,42 + ,17 + ,12 + ,10 + ,3 + ,0 + ,41 + ,19 + ,13 + ,12 + ,4 + ,0 + ,47 + ,21 + ,17 + ,11 + ,3 + ,0 + ,35 + ,20 + ,16 + ,11 + ,3 + ,0 + ,43 + ,20 + ,11 + ,14 + ,3 + ,0 + ,40 + ,29 + ,9 + ,16 + ,4 + ,0 + ,46 + ,23 + ,11 + ,9 + ,4 + ,0 + ,44 + ,23 + ,11 + ,11 + ,5 + ,0 + ,35 + ,19 + ,13 + ,9 + ,3 + ,0 + ,29 + ,22 + ,15 + ,14 + ,4) + ,dim=c(6 + ,146) + ,dimnames=list(c('Gender' + ,'StudyForCareer' + ,'PersonalStandards' + ,'ParentalExpectation' + ,'Doubts' + ,'LeaderPreference') + ,1:146)) > y <- array(NA,dim=c(6,146),dimnames=list(c('Gender','StudyForCareer','PersonalStandards','ParentalExpectation','Doubts','LeaderPreference'),1:146)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par4 = 'yes' > par3 = '2' > par2 = 'equal' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Gender" > x[,par1] [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [75] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) C1 C2 58 88 > colnames(x) [1] "Gender" "StudyForCareer" "PersonalStandards" [4] "ParentalExpectation" "Doubts" "LeaderPreference" > colnames(x)[par1] [1] "Gender" > x[,par1] [1] C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 [26] C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 [51] C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 [76] C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 [101] C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 [126] C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 Levels: C1 C2 > 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/1h8bv1292162859.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 1 156 370 2 111 687 [1] 0.2965779 [1] 0.8609023 [1] 0.636707 m.ct.x.pred m.ct.x.actu 1 2 1 7 47 2 18 64 [1] 0.1296296 [1] 0.7804878 [1] 0.5220588 > m Conditional inference tree with 2 terminal nodes Response: as.factor(Gender) Inputs: StudyForCareer, PersonalStandards, ParentalExpectation, Doubts, LeaderPreference Number of observations: 146 1) ParentalExpectation <= 11; criterion = 0.959, statistic = 6.965 2)* weights = 56 1) ParentalExpectation > 11 3)* weights = 90 > postscript(file="/var/www/html/rcomp/tmp/2shsg1292162859.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/3shsg1292162859.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,] 2 2 [2,] 2 2 [3,] 2 2 [4,] 2 1 [5,] 2 2 [6,] 2 2 [7,] 2 1 [8,] 2 2 [9,] 2 2 [10,] 2 1 [11,] 2 2 [12,] 2 2 [13,] 2 2 [14,] 2 2 [15,] 2 2 [16,] 2 1 [17,] 2 1 [18,] 2 1 [19,] 2 2 [20,] 2 2 [21,] 2 2 [22,] 2 2 [23,] 2 2 [24,] 2 2 [25,] 2 2 [26,] 2 2 [27,] 2 2 [28,] 2 2 [29,] 2 1 [30,] 2 2 [31,] 2 2 [32,] 2 2 [33,] 2 2 [34,] 2 1 [35,] 2 2 [36,] 2 1 [37,] 2 2 [38,] 2 1 [39,] 2 1 [40,] 2 2 [41,] 2 2 [42,] 2 2 [43,] 2 1 [44,] 2 2 [45,] 2 2 [46,] 2 1 [47,] 2 1 [48,] 2 1 [49,] 2 2 [50,] 2 2 [51,] 2 2 [52,] 2 2 [53,] 2 2 [54,] 2 1 [55,] 2 2 [56,] 2 2 [57,] 2 2 [58,] 2 2 [59,] 2 2 [60,] 2 2 [61,] 2 2 [62,] 2 1 [63,] 2 2 [64,] 2 2 [65,] 2 2 [66,] 2 1 [67,] 2 2 [68,] 2 2 [69,] 2 1 [70,] 2 1 [71,] 2 1 [72,] 2 2 [73,] 2 1 [74,] 2 2 [75,] 2 2 [76,] 2 2 [77,] 2 2 [78,] 2 1 [79,] 2 2 [80,] 2 2 [81,] 2 2 [82,] 2 2 [83,] 2 2 [84,] 2 2 [85,] 2 1 [86,] 2 2 [87,] 2 1 [88,] 2 2 [89,] 1 1 [90,] 1 1 [91,] 1 1 [92,] 1 1 [93,] 1 2 [94,] 1 2 [95,] 1 2 [96,] 1 1 [97,] 1 1 [98,] 1 2 [99,] 1 2 [100,] 1 1 [101,] 1 1 [102,] 1 1 [103,] 1 2 [104,] 1 1 [105,] 1 2 [106,] 1 2 [107,] 1 2 [108,] 1 1 [109,] 1 2 [110,] 1 1 [111,] 1 2 [112,] 1 1 [113,] 1 1 [114,] 1 2 [115,] 1 1 [116,] 1 1 [117,] 1 2 [118,] 1 1 [119,] 1 1 [120,] 1 2 [121,] 1 1 [122,] 1 2 [123,] 1 1 [124,] 1 1 [125,] 1 1 [126,] 1 2 [127,] 1 2 [128,] 1 1 [129,] 1 1 [130,] 1 2 [131,] 1 2 [132,] 1 2 [133,] 1 2 [134,] 1 1 [135,] 1 1 [136,] 1 1 [137,] 1 2 [138,] 1 2 [139,] 1 2 [140,] 1 2 [141,] 1 1 [142,] 1 1 [143,] 1 1 [144,] 1 1 [145,] 1 2 [146,] 1 2 C1 C2 C1 31 27 C2 25 63 > postscript(file="/var/www/html/rcomp/tmp/439sj1292162859.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/56r8p1292162859.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/6rspd1292162859.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/7dani1292162859.tab") + } > > try(system("convert tmp/2shsg1292162859.ps tmp/2shsg1292162859.png",intern=TRUE)) character(0) > try(system("convert tmp/3shsg1292162859.ps tmp/3shsg1292162859.png",intern=TRUE)) character(0) > try(system("convert tmp/439sj1292162859.ps tmp/439sj1292162859.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.689 0.458 5.634