R version 2.13.0 (2011-04-13) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) 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. 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+ ,0.69 + ,0.31 + ,3 + ,0.086 + ,23 + ,81 + ,1.0002 + ,3.48 + ,0.74 + ,11.6 + ,6) + ,dim=c(12 + ,500) + ,dimnames=list(c('fixedacidity' + ,'volatileacidity' + ,'citricacid' + ,'residualsugar' + ,'chlorides' + ,'freesulfurdioxide' + ,'totalsulfurdioxide' + ,'density' + ,'pH' + ,'sulphates' + ,'alcohol' + ,'quality') + ,1:500)) > y <- array(NA,dim=c(12,500),dimnames=list(c('fixedacidity','volatileacidity','citricacid','residualsugar','chlorides','freesulfurdioxide','totalsulfurdioxide','density','pH','sulphates','alcohol','quality'),1:500)) > 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 = '12' > 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 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] "quality" > x[,par1] [1] 5 5 5 6 5 5 5 7 7 5 5 5 5 5 5 5 7 5 4 6 6 5 5 5 6 5 5 5 5 6 5 6 5 6 5 6 6 [38] 7 4 5 5 4 6 5 5 4 5 5 5 5 5 6 6 5 6 5 5 5 5 6 5 5 7 5 5 5 5 5 5 6 6 5 5 4 [75] 5 5 5 6 5 4 5 5 5 5 6 5 6 5 5 5 5 6 5 5 4 6 5 5 5 6 6 6 6 5 5 5 5 5 6 5 5 [112] 5 5 6 5 6 6 6 6 6 5 6 5 5 5 5 5 5 7 5 5 5 5 6 6 5 5 5 5 5 5 5 6 5 6 5 5 5 [149] 6 6 6 4 5 5 5 5 5 5 5 6 5 4 6 5 5 5 5 4 6 5 4 6 6 6 5 5 5 6 5 5 5 5 5 5 6 [186] 5 5 5 5 5 5 6 5 5 5 5 5 6 7 4 7 5 5 5 6 7 7 5 5 7 6 6 6 5 6 5 5 5 5 5 6 5 [223] 5 6 4 6 6 5 6 5 7 6 6 5 6 6 6 6 6 6 5 6 6 7 7 6 5 5 6 6 6 6 5 5 6 5 5 5 5 [260] 7 5 4 5 5 5 7 4 8 6 6 6 6 5 5 5 6 6 6 8 7 6 7 5 7 5 5 6 6 7 5 7 5 6 6 6 5 [297] 5 5 5 5 6 6 5 5 5 6 5 6 6 6 6 6 6 5 5 6 5 6 7 6 7 5 5 6 6 6 7 5 6 5 6 6 6 [334] 5 7 7 6 5 6 7 6 6 6 6 6 5 7 6 6 6 6 6 5 5 6 6 5 7 7 6 5 6 5 5 7 6 7 5 5 7 [371] 5 6 6 5 6 7 6 7 6 6 6 6 6 6 5 6 6 6 6 7 8 6 5 5 5 7 5 6 6 5 5 6 6 6 5 6 6 [408] 7 6 4 6 5 5 7 5 5 6 5 6 5 7 7 5 7 5 7 6 6 5 6 7 5 6 5 6 5 6 6 6 5 8 6 7 7 [445] 7 6 5 5 6 6 6 6 6 7 5 8 5 5 7 3 6 5 5 5 6 5 6 6 6 5 5 6 6 5 6 5 5 6 5 6 5 [482] 8 5 5 6 5 5 6 7 6 6 7 7 6 6 8 6 5 8 6 > 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]) [3,6) [6,8] 256 244 > colnames(x) [1] "fixedacidity" "volatileacidity" "citricacid" [4] "residualsugar" "chlorides" "freesulfurdioxide" [7] "totalsulfurdioxide" "density" "pH" [10] "sulphates" "alcohol" "quality" > colnames(x)[par1] [1] "quality" > x[,par1] [1] [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [3,6) [6,8] [6,8] [3,6) [3,6) [3,6) [13] [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [6,8] [6,8] [3,6) [3,6) [3,6) [25] [6,8] [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [6,8] [3,6) [6,8] [3,6) [6,8] [37] [6,8] [6,8] [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [3,6) [3,6) [3,6) [49] [3,6) [3,6) [3,6) [6,8] [6,8] [3,6) [6,8] [3,6) [3,6) [3,6) [3,6) [6,8] [61] [3,6) [3,6) [6,8] [3,6) [3,6) [3,6) [3,6) [3,6) [3,6) [6,8] [6,8] [3,6) [73] [3,6) [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [3,6) [3,6) [3,6) [3,6) [85] [6,8] [3,6) [6,8] [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [3,6) [6,8] [97] [3,6) [3,6) [3,6) [6,8] [6,8] [6,8] [6,8] [3,6) [3,6) [3,6) [3,6) [3,6) [109] [6,8] [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [6,8] [6,8] [6,8] [6,8] [6,8] [121] [3,6) [6,8] [3,6) [3,6) [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [3,6) [133] [3,6) [6,8] [6,8] [3,6) [3,6) [3,6) [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [145] [6,8] [3,6) [3,6) [3,6) [6,8] [6,8] [6,8] [3,6) [3,6) [3,6) [3,6) [3,6) [157] [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [6,8] [3,6) [3,6) [3,6) [3,6) [3,6) [169] [6,8] [3,6) [3,6) [6,8] [6,8] [6,8] [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [181] [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [3,6) [3,6) [3,6) [3,6) [6,8] [193] [3,6) [3,6) [3,6) [3,6) [3,6) [6,8] [6,8] [3,6) [6,8] [3,6) [3,6) [3,6) [205] [6,8] [6,8] [6,8] [3,6) [3,6) [6,8] [6,8] [6,8] [6,8] [3,6) [6,8] [3,6) [217] [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [6,8] [3,6) [6,8] [6,8] [3,6) [229] [6,8] [3,6) [6,8] [6,8] [6,8] [3,6) [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [241] [3,6) [6,8] [6,8] [6,8] [6,8] [6,8] [3,6) [3,6) [6,8] [6,8] [6,8] [6,8] [253] [3,6) [3,6) [6,8] [3,6) [3,6) [3,6) [3,6) [6,8] [3,6) [3,6) [3,6) [3,6) [265] [3,6) [6,8] [3,6) [6,8] [6,8] [6,8] [6,8] [6,8] [3,6) [3,6) [3,6) [6,8] [277] [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [3,6) [6,8] [3,6) [3,6) [6,8] [6,8] [289] [6,8] [3,6) [6,8] [3,6) [6,8] [6,8] [6,8] [3,6) [3,6) [3,6) [3,6) [3,6) [301] [6,8] [6,8] [3,6) [3,6) [3,6) [6,8] [3,6) [6,8] [6,8] [6,8] [6,8] [6,8] [313] [6,8] [3,6) [3,6) [6,8] [3,6) [6,8] [6,8] [6,8] [6,8] [3,6) [3,6) [6,8] [325] [6,8] [6,8] [6,8] [3,6) [6,8] [3,6) [6,8] [6,8] [6,8] [3,6) [6,8] [6,8] [337] [6,8] [3,6) [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [3,6) [6,8] [6,8] [349] [6,8] [6,8] [6,8] [6,8] [3,6) [3,6) [6,8] [6,8] [3,6) [6,8] [6,8] [6,8] [361] [3,6) [6,8] [3,6) [3,6) [6,8] [6,8] [6,8] [3,6) [3,6) [6,8] [3,6) [6,8] [373] [6,8] [3,6) [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [385] [3,6) [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [3,6) [3,6) [3,6) [6,8] [397] [3,6) [6,8] [6,8] [3,6) [3,6) [6,8] [6,8] [6,8] [3,6) [6,8] [6,8] [6,8] [409] [6,8] [3,6) [6,8] [3,6) [3,6) [6,8] [3,6) [3,6) [6,8] [3,6) [6,8] [3,6) [421] [6,8] [6,8] [3,6) [6,8] [3,6) [6,8] [6,8] [6,8] [3,6) [6,8] [6,8] [3,6) [433] [6,8] [3,6) [6,8] [3,6) [6,8] [6,8] [6,8] [3,6) [6,8] [6,8] [6,8] [6,8] [445] [6,8] [6,8] [3,6) [3,6) [6,8] [6,8] [6,8] [6,8] [6,8] [6,8] [3,6) [6,8] [457] [3,6) [3,6) [6,8] [3,6) [6,8] [3,6) [3,6) [3,6) [6,8] [3,6) [6,8] [6,8] [469] [6,8] [3,6) [3,6) [6,8] [6,8] [3,6) [6,8] [3,6) [3,6) [6,8] [3,6) [6,8] [481] [3,6) [6,8] [3,6) [3,6) [6,8] [3,6) [3,6) [6,8] [6,8] [6,8] [6,8] [6,8] [493] [6,8] [6,8] [6,8] [6,8] [6,8] [3,6) [6,8] [6,8] Levels: [3,6) [6,8] > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/1yit01323795783.tab") + } + } > m Conditional inference tree with 8 terminal nodes Response: as.factor(quality) Inputs: fixedacidity, volatileacidity, citricacid, residualsugar, chlorides, freesulfurdioxide, totalsulfurdioxide, density, pH, sulphates, alcohol Number of observations: 500 1) alcohol <= 9.8; criterion = 1, statistic = 65.93 2) volatileacidity <= 0.37; criterion = 1, statistic = 20.931 3)* weights = 41 2) volatileacidity > 0.37 4) totalsulfurdioxide <= 41; criterion = 0.995, statistic = 12.33 5) freesulfurdioxide <= 12; criterion = 0.964, statistic = 8.599 6)* weights = 77 5) freesulfurdioxide > 12 7)* weights = 16 4) totalsulfurdioxide > 41 8) residualsugar <= 5.1; criterion = 0.97, statistic = 8.937 9)* weights = 118 8) residualsugar > 5.1 10)* weights = 7 1) alcohol > 9.8 11) totalsulfurdioxide <= 64; criterion = 1, statistic = 20.147 12) volatileacidity <= 0.55; criterion = 1, statistic = 19.254 13)* weights = 118 12) volatileacidity > 0.55 14)* weights = 73 11) totalsulfurdioxide > 64 15)* weights = 50 > postscript(file="/var/wessaorg/rcomp/tmp/2w4hf1323795783.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/wessaorg/rcomp/tmp/37umq1323795783.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 1 [2,] 1 1 [3,] 1 1 [4,] 2 2 [5,] 1 1 [6,] 1 2 [7,] 1 1 [8,] 2 2 [9,] 2 1 [10,] 1 1 [11,] 1 1 [12,] 1 1 [13,] 1 2 [14,] 1 1 [15,] 1 1 [16,] 1 1 [17,] 2 1 [18,] 1 1 [19,] 1 1 [20,] 2 2 [21,] 2 2 [22,] 1 1 [23,] 1 1 [24,] 1 1 [25,] 2 2 [26,] 1 1 [27,] 1 1 [28,] 1 1 [29,] 1 2 [30,] 2 1 [31,] 1 1 [32,] 2 2 [33,] 1 1 [34,] 2 1 [35,] 1 2 [36,] 2 1 [37,] 2 2 [38,] 2 2 [39,] 1 1 [40,] 1 1 [41,] 1 1 [42,] 1 1 [43,] 2 2 [44,] 1 2 [45,] 1 1 [46,] 1 1 [47,] 1 1 [48,] 1 2 [49,] 1 1 [50,] 1 2 [51,] 1 1 [52,] 2 1 [53,] 2 1 [54,] 1 1 [55,] 2 1 [56,] 1 1 [57,] 1 1 [58,] 1 1 [59,] 1 2 [60,] 2 1 [61,] 1 1 [62,] 1 1 [63,] 2 1 [64,] 1 1 [65,] 1 2 [66,] 1 2 [67,] 1 1 [68,] 1 2 [69,] 1 1 [70,] 2 2 [71,] 2 2 [72,] 1 1 [73,] 1 1 [74,] 1 1 [75,] 1 2 [76,] 1 2 [77,] 1 2 [78,] 2 2 [79,] 1 1 [80,] 1 1 [81,] 1 1 [82,] 1 1 [83,] 1 1 [84,] 1 1 [85,] 2 2 [86,] 1 2 [87,] 2 1 [88,] 1 1 [89,] 1 1 [90,] 1 1 [91,] 1 1 [92,] 2 1 [93,] 1 1 [94,] 1 1 [95,] 1 1 [96,] 2 1 [97,] 1 2 [98,] 1 1 [99,] 1 1 [100,] 2 2 [101,] 2 2 [102,] 2 2 [103,] 2 2 [104,] 1 1 [105,] 1 1 [106,] 1 1 [107,] 1 1 [108,] 1 1 [109,] 2 2 [110,] 1 1 [111,] 1 1 [112,] 1 1 [113,] 1 1 [114,] 2 2 [115,] 1 1 [116,] 2 2 [117,] 2 2 [118,] 2 1 [119,] 2 2 [120,] 2 1 [121,] 1 1 [122,] 2 2 [123,] 1 1 [124,] 1 1 [125,] 1 1 [126,] 1 1 [127,] 1 2 [128,] 1 2 [129,] 2 2 [130,] 1 1 [131,] 1 1 [132,] 1 1 [133,] 1 1 [134,] 2 2 [135,] 2 2 [136,] 1 1 [137,] 1 1 [138,] 1 1 [139,] 1 1 [140,] 1 1 [141,] 1 1 [142,] 1 1 [143,] 2 2 [144,] 1 1 [145,] 2 2 [146,] 1 1 [147,] 1 1 [148,] 1 1 [149,] 2 2 [150,] 2 2 [151,] 2 2 [152,] 1 1 [153,] 1 1 [154,] 1 1 [155,] 1 1 [156,] 1 1 [157,] 1 1 [158,] 1 1 [159,] 1 1 [160,] 2 1 [161,] 1 1 [162,] 1 1 [163,] 2 2 [164,] 1 1 [165,] 1 1 [166,] 1 1 [167,] 1 1 [168,] 1 1 [169,] 2 2 [170,] 1 1 [171,] 1 1 [172,] 2 1 [173,] 2 1 [174,] 2 2 [175,] 1 1 [176,] 1 1 [177,] 1 1 [178,] 2 2 [179,] 1 1 [180,] 1 1 [181,] 1 1 [182,] 1 1 [183,] 1 1 [184,] 1 1 [185,] 2 1 [186,] 1 2 [187,] 1 1 [188,] 1 1 [189,] 1 1 [190,] 1 1 [191,] 1 1 [192,] 2 2 [193,] 1 1 [194,] 1 1 [195,] 1 1 [196,] 1 1 [197,] 1 2 [198,] 2 2 [199,] 2 1 [200,] 1 2 [201,] 2 2 [202,] 1 2 [203,] 1 1 [204,] 1 2 [205,] 2 2 [206,] 2 2 [207,] 2 2 [208,] 1 1 [209,] 1 1 [210,] 2 2 [211,] 2 2 [212,] 2 2 [213,] 2 2 [214,] 1 1 [215,] 2 1 [216,] 1 1 [217,] 1 2 [218,] 1 1 [219,] 1 1 [220,] 1 1 [221,] 2 2 [222,] 1 1 [223,] 1 1 [224,] 2 2 [225,] 1 2 [226,] 2 2 [227,] 2 1 [228,] 1 1 [229,] 2 2 [230,] 1 2 [231,] 2 1 [232,] 2 2 [233,] 2 2 [234,] 1 2 [235,] 2 1 [236,] 2 2 [237,] 2 2 [238,] 2 2 [239,] 2 2 [240,] 2 1 [241,] 1 1 [242,] 2 2 [243,] 2 1 [244,] 2 2 [245,] 2 2 [246,] 2 2 [247,] 1 1 [248,] 1 1 [249,] 2 1 [250,] 2 2 [251,] 2 2 [252,] 2 2 [253,] 1 2 [254,] 1 1 [255,] 2 2 [256,] 1 1 [257,] 1 2 [258,] 1 1 [259,] 1 1 [260,] 2 2 [261,] 1 2 [262,] 1 1 [263,] 1 2 [264,] 1 2 [265,] 1 2 [266,] 2 2 [267,] 1 1 [268,] 2 2 [269,] 2 1 [270,] 2 2 [271,] 2 2 [272,] 2 2 [273,] 1 1 [274,] 1 1 [275,] 1 1 [276,] 2 2 [277,] 2 1 [278,] 2 2 [279,] 2 2 [280,] 2 2 [281,] 2 2 [282,] 2 2 [283,] 1 1 [284,] 2 2 [285,] 1 1 [286,] 1 1 [287,] 2 2 [288,] 2 2 [289,] 2 2 [290,] 1 1 [291,] 2 2 [292,] 1 2 [293,] 2 2 [294,] 2 2 [295,] 2 2 [296,] 1 1 [297,] 1 1 [298,] 1 1 [299,] 1 1 [300,] 1 1 [301,] 2 2 [302,] 2 2 [303,] 1 2 [304,] 1 1 [305,] 1 1 [306,] 2 1 [307,] 1 1 [308,] 2 1 [309,] 2 1 [310,] 2 2 [311,] 2 1 [312,] 2 1 [313,] 2 1 [314,] 1 1 [315,] 1 1 [316,] 2 2 [317,] 1 1 [318,] 2 1 [319,] 2 2 [320,] 2 1 [321,] 2 2 [322,] 1 1 [323,] 1 1 [324,] 2 1 [325,] 2 1 [326,] 2 1 [327,] 2 2 [328,] 1 2 [329,] 2 2 [330,] 1 1 [331,] 2 2 [332,] 2 2 [333,] 2 1 [334,] 1 2 [335,] 2 2 [336,] 2 2 [337,] 2 2 [338,] 1 2 [339,] 2 1 [340,] 2 2 [341,] 2 2 [342,] 2 2 [343,] 2 1 [344,] 2 1 [345,] 2 2 [346,] 1 2 [347,] 2 2 [348,] 2 2 [349,] 2 2 [350,] 2 1 [351,] 2 2 [352,] 2 1 [353,] 1 1 [354,] 1 1 [355,] 2 1 [356,] 2 2 [357,] 1 2 [358,] 2 2 [359,] 2 2 [360,] 2 1 [361,] 1 1 [362,] 2 2 [363,] 1 2 [364,] 1 2 [365,] 2 2 [366,] 2 2 [367,] 2 2 [368,] 1 1 [369,] 1 2 [370,] 2 2 [371,] 1 2 [372,] 2 2 [373,] 2 2 [374,] 1 1 [375,] 2 2 [376,] 2 2 [377,] 2 2 [378,] 2 2 [379,] 2 2 [380,] 2 2 [381,] 2 2 [382,] 2 2 [383,] 2 2 [384,] 2 2 [385,] 1 1 [386,] 2 1 [387,] 2 1 [388,] 2 1 [389,] 2 1 [390,] 2 2 [391,] 2 1 [392,] 2 2 [393,] 1 2 [394,] 1 1 [395,] 1 2 [396,] 2 2 [397,] 1 1 [398,] 2 2 [399,] 2 2 [400,] 1 1 [401,] 1 1 [402,] 2 2 [403,] 2 2 [404,] 2 2 [405,] 1 2 [406,] 2 2 [407,] 2 2 [408,] 2 2 [409,] 2 2 [410,] 1 1 [411,] 2 1 [412,] 1 1 [413,] 1 1 [414,] 2 2 [415,] 1 1 [416,] 1 1 [417,] 2 2 [418,] 1 1 [419,] 2 2 [420,] 1 2 [421,] 2 1 [422,] 2 2 [423,] 1 2 [424,] 2 2 [425,] 1 2 [426,] 2 2 [427,] 2 2 [428,] 2 2 [429,] 1 1 [430,] 2 2 [431,] 2 2 [432,] 1 1 [433,] 2 2 [434,] 1 1 [435,] 2 2 [436,] 1 1 [437,] 2 2 [438,] 2 2 [439,] 2 2 [440,] 1 1 [441,] 2 2 [442,] 2 2 [443,] 2 2 [444,] 2 2 [445,] 2 2 [446,] 2 2 [447,] 1 1 [448,] 1 2 [449,] 2 2 [450,] 2 2 [451,] 2 2 [452,] 2 2 [453,] 2 2 [454,] 2 2 [455,] 1 1 [456,] 2 2 [457,] 1 2 [458,] 1 1 [459,] 2 2 [460,] 1 1 [461,] 2 2 [462,] 1 1 [463,] 1 2 [464,] 1 1 [465,] 2 2 [466,] 1 2 [467,] 2 2 [468,] 2 2 [469,] 2 2 [470,] 1 1 [471,] 1 2 [472,] 2 2 [473,] 2 1 [474,] 1 2 [475,] 2 2 [476,] 1 2 [477,] 1 2 [478,] 2 2 [479,] 1 2 [480,] 2 2 [481,] 1 2 [482,] 2 2 [483,] 1 2 [484,] 1 2 [485,] 2 2 [486,] 1 2 [487,] 1 2 [488,] 2 2 [489,] 2 1 [490,] 2 2 [491,] 2 2 [492,] 2 2 [493,] 2 2 [494,] 2 1 [495,] 2 1 [496,] 2 2 [497,] 2 2 [498,] 1 1 [499,] 2 2 [500,] 2 1 [3,6) [6,8] [3,6) 192 64 [6,8] 60 184 > postscript(file="/var/wessaorg/rcomp/tmp/4pr5y1323795783.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$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/5ts9a1323795783.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$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/wessaorg/rcomp/tmp/6v5w61323795783.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/wessaorg/rcomp/tmp/7p6tg1323795783.tab") + } > > try(system("convert tmp/2w4hf1323795783.ps tmp/2w4hf1323795783.png",intern=TRUE)) character(0) > try(system("convert tmp/37umq1323795783.ps tmp/37umq1323795783.png",intern=TRUE)) character(0) > try(system("convert tmp/4pr5y1323795783.ps tmp/4pr5y1323795783.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 11.874 0.374 17.188