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Type 'q()' to quit R. > x <- array(list(8 + ,350 + ,165 + ,3693 + ,11.5 + ,8 + ,318 + ,150 + ,3436 + ,11 + ,8 + ,302 + ,140 + ,3449 + ,10.5 + ,8 + ,429 + ,198 + ,4341 + ,10 + ,8 + ,440 + ,215 + ,4312 + ,8.5 + ,8 + ,455 + ,225 + ,4425 + ,10 + ,8 + ,383 + ,170 + ,3563 + ,10 + ,8 + ,340 + ,160 + ,3609 + ,8 + ,8 + ,455 + ,225 + ,3086 + ,10 + ,4 + ,113 + ,95 + ,2372 + ,15 + ,6 + ,199 + ,97 + ,2774 + ,15.5 + ,4 + ,97 + ,46 + ,1835 + ,20.5 + ,4 + ,110 + ,87 + ,2672 + ,17.5 + ,4 + ,104 + ,95 + ,2375 + ,17.5 + ,4 + ,121 + ,113 + ,2234 + ,12.5 + ,8 + ,360 + ,215 + ,4615 + ,14 + ,8 + ,307 + ,200 + ,4376 + ,15 + ,8 + ,304 + ,193 + ,4732 + ,18.5 + ,4 + ,97 + ,88 + ,2130 + ,14.5 + ,4 + ,113 + ,95 + ,2228 + ,14 + ,6 + ,250 + ,100 + ,3329 + ,15.5 + ,6 + ,232 + ,100 + ,3288 + ,15.5 + ,8 + ,350 + ,165 + ,4209 + ,12 + ,8 + ,318 + ,150 + ,4096 + ,13 + ,8 + ,400 + ,170 + ,4746 + ,12 + ,8 + ,400 + ,175 + ,5140 + ,12 + ,4 + ,140 + ,72 + ,2408 + ,19 + ,6 + ,250 + ,100 + ,3282 + ,15 + ,4 + ,122 + ,86 + ,2220 + 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,17.3 + ,4 + ,140 + ,86 + ,2790 + ,15.6 + ,4 + ,135 + ,84 + ,2295 + ,11.6 + ,4 + ,120 + ,79 + ,2625 + ,18.6) + ,dim=c(5 + ,240) + ,dimnames=list(c('cylinders' + ,'engine.displacement' + ,'horsepower' + ,'weight' + ,'acceleration ') + ,1:240)) > y <- array(NA,dim=c(5,240),dimnames=list(c('cylinders','engine.displacement','horsepower','weight','acceleration '),1:240)) > 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 = '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 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] "acceleration." > x[,par1] [1] 11.5 11.0 10.5 10.0 8.5 10.0 10.0 8.0 10.0 15.0 15.5 20.5 17.5 17.5 12.5 [16] 14.0 15.0 18.5 14.5 14.0 15.5 15.5 12.0 13.0 12.0 12.0 19.0 15.0 14.0 14.0 [31] 14.5 19.0 19.0 20.5 17.0 16.5 12.0 13.5 13.0 11.0 13.5 12.5 13.5 14.0 16.0 [46] 14.5 18.0 16.0 14.5 15.0 13.0 11.5 14.5 12.5 12.0 13.0 11.0 11.0 16.5 18.0 [61] 16.5 16.0 14.0 12.5 15.0 19.5 16.5 18.5 14.0 13.0 9.5 15.5 14.0 11.0 14.0 [76] 11.0 16.5 16.0 16.5 21.0 17.0 18.0 14.0 14.5 16.0 15.5 15.5 14.5 19.0 14.5 [91] 14.0 15.0 16.0 16.0 19.5 11.5 14.0 13.5 21.0 19.0 19.0 13.5 12.0 17.0 16.0 [106] 13.5 16.5 14.5 15.0 17.0 13.5 17.5 16.9 14.9 15.3 13.0 13.9 12.8 14.5 17.6 [121] 22.2 22.1 17.7 16.2 17.8 17.0 16.4 15.7 13.2 16.7 12.1 15.0 14.0 14.8 18.6 [136] 16.8 12.5 13.7 16.9 17.7 11.1 11.4 14.5 14.5 18.2 15.8 15.9 16.4 14.5 12.8 [151] 21.5 14.4 18.6 13.2 12.8 18.2 15.8 17.2 17.2 16.7 18.7 13.2 13.4 13.7 16.5 [166] 14.7 14.5 17.6 15.9 13.6 15.8 14.9 16.6 18.2 17.3 16.6 15.4 13.2 15.2 14.3 [181] 15.0 14.0 15.2 15.0 24.8 22.2 14.9 19.2 16.0 11.3 13.2 14.7 15.5 16.4 18.1 [196] 20.1 15.8 15.5 15.0 15.2 14.4 19.2 19.9 13.8 15.3 15.1 15.7 16.4 12.6 12.9 [211] 16.4 16.1 19.4 17.3 14.9 16.2 14.2 14.8 20.4 13.8 15.8 17.1 16.6 18.6 18.0 [226] 16.0 18.0 15.3 17.6 14.7 14.5 14.5 15.7 16.4 17.0 13.9 17.3 15.6 11.6 18.6 > 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]) [ 8.0,15.3) [15.3,24.8] 122 118 > colnames(x) [1] "cylinders" "engine.displacement" "horsepower" [4] "weight" "acceleration." > colnames(x)[par1] [1] "acceleration." > x[,par1] [1] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [7] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [13] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [19] [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [25] [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [31] [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [37] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [43] [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [49] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [55] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [61] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [67] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [73] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [79] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [85] [15.3,24.8] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) [91] [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [97] [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [103] [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) [109] [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [115] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [121] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [127] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [133] [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [139] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [145] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [151] [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [157] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [163] [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [169] [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [175] [15.3,24.8] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [181] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [187] [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [193] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [199] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [205] [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [211] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [217] [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [223] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [15.3,24.8] [229] [15.3,24.8] [ 8.0,15.3) [ 8.0,15.3) [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [235] [15.3,24.8] [ 8.0,15.3) [15.3,24.8] [15.3,24.8] [ 8.0,15.3) [15.3,24.8] Levels: [ 8.0,15.3) [15.3,24.8] > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/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/rcomp/tmp/179h21292339860.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 1 671 415 2 69 1001 [1] 0.6178637 [1] 0.935514 [1] 0.7755102 m.ct.x.pred m.ct.x.actu 1 2 1 79 55 2 10 100 [1] 0.5895522 [1] 0.9090909 [1] 0.7336066 > m Conditional inference tree with 4 terminal nodes Response: as.factor(acceleration.) Inputs: cylinders, engine.displacement, horsepower, weight Number of observations: 240 1) horsepower <= 110; criterion = 1, statistic = 65.018 2) weight <= 2815; criterion = 0.969, statistic = 7.089 3) horsepower <= 90; criterion = 1, statistic = 22.365 4)* weights = 90 3) horsepower > 90 5)* weights = 23 2) weight > 2815 6)* weights = 51 1) horsepower > 110 7)* weights = 76 > postscript(file="/var/www/rcomp/tmp/279h21292339860.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/rcomp/tmp/3hjgn1292339860.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,] 1 1 [5,] 1 1 [6,] 1 1 [7,] 1 1 [8,] 1 1 [9,] 1 1 [10,] 1 1 [11,] 2 1 [12,] 2 2 [13,] 2 2 [14,] 2 1 [15,] 1 1 [16,] 1 1 [17,] 1 1 [18,] 2 1 [19,] 1 2 [20,] 1 1 [21,] 2 2 [22,] 2 2 [23,] 1 1 [24,] 1 1 [25,] 1 1 [26,] 1 1 [27,] 2 2 [28,] 1 2 [29,] 1 2 [30,] 1 2 [31,] 1 2 [32,] 2 2 [33,] 2 2 [34,] 2 2 [35,] 2 2 [36,] 2 2 [37,] 1 1 [38,] 1 1 [39,] 1 1 [40,] 1 1 [41,] 1 1 [42,] 1 1 [43,] 1 1 [44,] 1 1 [45,] 2 1 [46,] 1 1 [47,] 2 2 [48,] 2 2 [49,] 1 1 [50,] 1 2 [51,] 1 1 [52,] 1 1 [53,] 1 1 [54,] 1 1 [55,] 1 1 [56,] 1 1 [57,] 1 1 [58,] 1 1 [59,] 2 2 [60,] 2 2 [61,] 2 2 [62,] 2 2 [63,] 1 1 [64,] 1 1 [65,] 1 1 [66,] 2 2 [67,] 2 1 [68,] 2 2 [69,] 1 1 [70,] 1 1 [71,] 1 1 [72,] 2 2 [73,] 1 1 [74,] 1 1 [75,] 1 1 [76,] 1 1 [77,] 2 2 [78,] 2 2 [79,] 2 2 [80,] 2 2 [81,] 2 2 [82,] 2 2 [83,] 1 1 [84,] 1 1 [85,] 2 1 [86,] 2 1 [87,] 2 2 [88,] 1 2 [89,] 2 2 [90,] 1 2 [91,] 1 2 [92,] 1 1 [93,] 2 2 [94,] 2 2 [95,] 2 2 [96,] 1 1 [97,] 1 1 [98,] 1 1 [99,] 2 2 [100,] 2 2 [101,] 2 2 [102,] 1 2 [103,] 1 1 [104,] 2 2 [105,] 2 2 [106,] 1 1 [107,] 2 2 [108,] 1 2 [109,] 1 1 [110,] 2 2 [111,] 1 1 [112,] 2 2 [113,] 2 2 [114,] 1 1 [115,] 2 2 [116,] 1 1 [117,] 1 1 [118,] 1 1 [119,] 1 2 [120,] 2 2 [121,] 2 2 [122,] 2 2 [123,] 2 2 [124,] 2 2 [125,] 2 2 [126,] 2 2 [127,] 2 2 [128,] 2 2 [129,] 1 1 [130,] 2 1 [131,] 1 1 [132,] 1 1 [133,] 1 1 [134,] 1 2 [135,] 2 2 [136,] 2 2 [137,] 1 1 [138,] 1 1 [139,] 2 2 [140,] 2 2 [141,] 1 1 [142,] 1 1 [143,] 1 1 [144,] 1 2 [145,] 2 2 [146,] 2 2 [147,] 2 2 [148,] 2 2 [149,] 1 1 [150,] 1 1 [151,] 2 2 [152,] 1 2 [153,] 2 2 [154,] 1 1 [155,] 1 1 [156,] 2 2 [157,] 2 2 [158,] 2 2 [159,] 2 2 [160,] 2 2 [161,] 2 2 [162,] 1 1 [163,] 1 1 [164,] 1 1 [165,] 2 2 [166,] 1 1 [167,] 1 2 [168,] 2 2 [169,] 2 2 [170,] 1 1 [171,] 2 1 [172,] 1 2 [173,] 2 2 [174,] 2 2 [175,] 2 2 [176,] 2 2 [177,] 2 1 [178,] 1 1 [179,] 1 1 [180,] 1 1 [181,] 1 1 [182,] 1 2 [183,] 1 2 [184,] 1 2 [185,] 2 2 [186,] 2 2 [187,] 1 2 [188,] 2 2 [189,] 2 2 [190,] 1 1 [191,] 1 2 [192,] 1 2 [193,] 2 2 [194,] 2 2 [195,] 2 2 [196,] 2 2 [197,] 2 2 [198,] 2 2 [199,] 1 1 [200,] 1 2 [201,] 1 1 [202,] 2 2 [203,] 2 2 [204,] 1 2 [205,] 2 2 [206,] 1 2 [207,] 2 2 [208,] 2 2 [209,] 1 1 [210,] 1 2 [211,] 2 2 [212,] 2 2 [213,] 2 2 [214,] 2 2 [215,] 1 2 [216,] 2 2 [217,] 1 2 [218,] 1 1 [219,] 2 2 [220,] 1 1 [221,] 2 2 [222,] 2 2 [223,] 2 2 [224,] 2 2 [225,] 2 2 [226,] 2 2 [227,] 2 2 [228,] 2 2 [229,] 2 2 [230,] 1 2 [231,] 1 2 [232,] 1 2 [233,] 2 2 [234,] 2 2 [235,] 2 2 [236,] 1 1 [237,] 2 2 [238,] 2 2 [239,] 1 2 [240,] 2 2 [ 8.0,15.3) [15.3,24.8] [ 8.0,15.3) 89 33 [15.3,24.8] 10 108 > postscript(file="/var/www/rcomp/tmp/4ssf81292339860.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/rcomp/tmp/5wtee1292339860.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/rcomp/tmp/662vz1292339860.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/rcomp/tmp/7r2cn1292339860.tab") + } > > try(system("convert tmp/279h21292339860.ps tmp/279h21292339860.png",intern=TRUE)) character(0) > try(system("convert tmp/3hjgn1292339860.ps tmp/3hjgn1292339860.png",intern=TRUE)) character(0) > try(system("convert tmp/4ssf81292339860.ps tmp/4ssf81292339860.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.750 0.770 3.483