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Type 'q()' to quit R. > x <- array(list(13 + ,13 + ,14 + ,13 + ,3 + ,12 + ,12 + ,8 + ,13 + ,5 + ,15 + ,10 + ,12 + ,16 + ,6 + ,12 + ,9 + ,7 + ,12 + ,6 + ,10 + ,10 + ,10 + ,11 + ,5 + ,12 + ,12 + ,7 + ,12 + ,3 + ,15 + ,13 + ,16 + ,18 + ,8 + ,9 + ,12 + ,11 + ,11 + ,4 + ,11 + ,5 + ,16 + ,14 + ,6 + ,12 + ,12 + ,14 + ,14 + ,4 + ,11 + ,6 + ,6 + ,9 + ,4 + ,15 + ,11 + ,16 + ,11 + ,5 + ,11 + ,12 + ,11 + ,12 + ,6 + ,7 + ,14 + ,12 + ,12 + ,4 + ,11 + ,14 + ,7 + ,13 + ,6 + ,11 + ,12 + ,13 + ,11 + ,4 + ,10 + ,12 + ,11 + ,12 + ,6 + ,6 + ,7 + ,9 + ,11 + ,4 + ,11 + ,9 + ,7 + ,13 + ,2 + ,15 + ,11 + ,14 + ,15 + ,7 + ,11 + ,11 + ,15 + ,10 + ,5 + ,12 + ,12 + ,7 + ,11 + ,4 + ,14 + ,12 + ,15 + ,13 + ,6 + ,15 + ,11 + ,17 + ,16 + ,6 + ,13 + ,8 + ,14 + ,14 + ,5 + ,13 + ,9 + ,14 + ,14 + ,6 + ,16 + ,12 + ,8 + ,14 + ,4 + ,13 + ,10 + ,8 + ,8 + ,4 + ,12 + ,10 + ,14 + ,13 + ,7 + ,11 + ,8 + ,8 + ,13 + ,4 + ,9 + ,12 + ,11 + ,11 + ,4 + ,16 + ,11 + ,16 + ,15 + ,6 + ,12 + ,12 + ,10 + ,15 + ,6 + ,10 + ,7 + ,8 + ,9 + ,5 + ,13 + ,11 + ,14 + ,13 + ,6 + ,16 + ,11 + ,16 + ,16 + ,7 + ,14 + ,12 + ,13 + ,13 + ,6 + ,15 + ,9 + ,5 + ,11 + ,3 + ,5 + ,15 + ,8 + ,12 + ,3 + ,8 + ,11 + ,10 + ,12 + ,4 + ,11 + ,11 + ,8 + ,12 + ,6 + ,16 + ,11 + ,13 + ,14 + ,7 + ,9 + ,15 + ,6 + ,8 + ,4 + ,9 + ,11 + ,12 + ,13 + ,5 + ,13 + ,12 + ,16 + ,16 + ,6 + ,10 + ,12 + ,5 + ,13 + ,6 + ,6 + ,9 + ,15 + ,11 + ,6 + ,12 + ,12 + ,12 + ,14 + ,5 + ,8 + ,12 + ,8 + ,13 + ,4 + ,14 + ,13 + ,13 + ,13 + ,5 + ,12 + ,11 + ,14 + ,13 + ,5 + ,11 + ,9 + ,12 + ,12 + ,4 + ,16 + ,9 + ,16 + ,16 + ,6 + ,8 + ,11 + ,10 + ,15 + ,2 + ,15 + ,11 + ,15 + ,15 + ,8 + ,7 + ,12 + ,8 + ,12 + ,3 + ,16 + ,12 + ,16 + ,14 + ,6 + ,14 + ,9 + ,19 + ,12 + ,6 + ,9 + ,9 + ,6 + ,12 + ,5 + ,14 + ,12 + ,13 + ,13 + ,5 + ,11 + ,12 + ,15 + ,12 + ,6 + ,13 + ,12 + ,7 + ,12 + ,5 + ,15 + ,12 + ,13 + ,13 + ,6 + ,5 + ,14 + ,4 + ,5 + ,2 + ,15 + ,11 + ,14 + ,13 + ,5 + ,13 + ,12 + ,13 + ,13 + ,5 + ,11 + ,11 + ,11 + ,14 + ,5 + ,11 + ,6 + ,14 + ,17 + ,6 + ,12 + ,10 + ,12 + ,13 + ,6 + ,12 + ,12 + ,15 + ,13 + ,6 + ,12 + ,13 + ,14 + ,12 + ,5 + ,12 + ,8 + ,13 + ,13 + ,5 + ,14 + ,12 + ,8 + ,14 + ,4 + ,6 + ,12 + ,6 + ,11 + ,2 + ,7 + ,12 + ,7 + ,12 + ,4 + ,14 + ,6 + ,13 + ,12 + ,6 + ,14 + ,11 + ,13 + ,16 + ,6 + ,10 + ,10 + ,11 + ,12 + ,5 + ,13 + ,12 + ,5 + ,12 + ,3 + ,12 + ,13 + ,12 + ,12 + ,6 + ,9 + ,11 + ,8 + ,10 + ,4 + ,12 + ,7 + ,11 + ,15 + ,5 + ,16 + ,11 + ,14 + ,15 + ,8 + ,10 + ,11 + ,9 + ,12 + ,4 + ,14 + ,11 + ,10 + ,16 + ,6 + ,10 + ,11 + ,13 + ,15 + ,6 + ,16 + ,12 + ,16 + ,16 + ,7 + ,15 + ,10 + ,16 + ,13 + ,6 + ,12 + ,11 + ,11 + ,12 + ,5 + ,10 + ,12 + ,8 + ,11 + ,4 + ,8 + ,7 + ,4 + ,13 + ,6 + ,8 + ,13 + ,7 + ,10 + ,3 + ,11 + ,8 + ,14 + ,15 + ,5 + ,13 + ,12 + ,11 + ,13 + ,6 + ,16 + ,11 + ,17 + ,16 + ,7 + ,16 + ,12 + ,15 + ,15 + ,7 + ,14 + ,14 + ,17 + ,18 + ,6 + ,11 + ,10 + ,5 + ,13 + ,3 + ,4 + ,10 + ,4 + ,10 + ,2 + ,14 + ,13 + ,10 + ,16 + ,8 + ,9 + ,10 + ,11 + ,13 + ,3 + ,8 + ,10 + ,10 + ,14 + ,3 + ,8 + ,7 + ,9 + ,15 + ,4 + ,11 + ,10 + ,12 + ,14 + ,5 + ,12 + ,8 + ,15 + ,13 + ,7 + ,11 + ,12 + ,7 + ,13 + ,6 + ,14 + ,12 + ,13 + ,15 + ,6 + ,16 + ,11 + ,14 + ,14 + ,6 + ,15 + ,12 + ,12 + ,16 + ,7 + ,16 + ,12 + ,14 + ,14 + ,6 + ,14 + ,12 + ,15 + ,14 + ,6 + ,11 + ,12 + ,8 + ,16 + ,6 + ,14 + ,11 + ,12 + ,12 + ,4 + ,12 + ,12 + ,12 + ,13 + ,4 + ,14 + ,11 + ,16 + ,12 + ,5 + ,8 + ,11 + ,9 + ,12 + ,4 + ,13 + ,13 + ,15 + ,14 + ,6 + ,16 + ,12 + ,15 + ,14 + ,6 + ,12 + ,12 + ,6 + ,14 + ,5 + ,16 + ,12 + ,14 + ,16 + ,8 + ,12 + ,12 + ,15 + ,13 + ,6 + ,11 + ,8 + ,10 + ,14 + ,5 + ,4 + ,8 + ,6 + ,4 + ,4 + ,16 + ,12 + ,14 + ,16 + ,8 + ,15 + ,11 + ,12 + ,13 + ,6 + ,10 + ,12 + ,8 + ,16 + ,4 + ,13 + ,13 + ,11 + ,15 + ,6 + ,15 + ,12 + ,13 + ,14 + ,6 + ,12 + ,12 + ,9 + ,13 + ,4 + ,14 + ,11 + ,15 + ,14 + ,6 + ,7 + ,12 + ,13 + ,12 + ,3 + ,19 + ,12 + ,15 + ,15 + ,6 + ,12 + ,10 + ,14 + ,14 + ,5 + ,12 + ,11 + ,16 + ,13 + ,4 + ,13 + ,12 + ,14 + ,14 + ,6 + ,15 + ,12 + ,14 + ,16 + ,4 + ,8 + ,10 + ,10 + ,6 + ,4 + ,12 + ,12 + ,10 + ,13 + ,4 + ,10 + ,13 + ,4 + ,13 + ,6 + ,8 + ,12 + ,8 + ,14 + ,5 + ,16 + ,12 + ,12 + ,15 + ,8 + ,13 + ,11 + ,12 + ,13 + ,7 + ,9 + ,11 + ,9 + ,12 + ,4 + ,14 + ,10 + ,12 + ,15 + ,6 + ,14 + ,11 + ,14 + ,12 + ,6 + ,12 + ,11 + ,11 + ,14 + ,2) + ,dim=c(5 + ,146) + ,dimnames=list(c('Popularity' + ,'Findingfriends' + ,'Knowingpeople' + ,'Liked' + ,'Celebrity ') + ,1:146)) > y <- array(NA,dim=c(5,146),dimnames=list(c('Popularity','Findingfriends','Knowingpeople','Liked','Celebrity '),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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "Popularity" > x[,par1] [1] 13 12 15 12 10 12 15 9 11 12 11 15 11 7 11 11 10 6 11 15 11 12 14 15 13 [26] 13 16 13 12 11 9 16 12 10 13 16 14 15 5 8 11 16 9 9 13 10 6 12 8 14 [51] 12 11 16 8 15 7 16 14 9 14 11 13 15 5 15 13 11 11 12 12 12 12 14 6 7 [76] 14 14 10 13 12 9 12 16 10 14 10 16 15 12 10 8 8 11 13 16 16 14 11 4 14 [101] 9 8 8 11 12 11 14 16 15 16 14 11 14 12 14 8 13 16 12 16 12 11 4 16 15 [126] 10 13 15 12 14 7 19 12 12 13 15 8 12 10 8 16 13 9 14 14 12 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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] "Popularity" "Findingfriends" "Knowingpeople" "Liked" [5] "Celebrity." > colnames(x)[par1] [1] "Popularity" > x[,par1] [1] C2 C2 C2 C2 C1 C2 C2 C1 C1 C2 C1 C2 C1 C1 C1 C1 C1 C1 C1 C2 C1 C2 C2 C2 C2 [26] C2 C2 C2 C2 C1 C1 C2 C2 C1 C2 C2 C2 C2 C1 C1 C1 C2 C1 C1 C2 C1 C1 C2 C1 C2 [51] C2 C1 C2 C1 C2 C1 C2 C2 C1 C2 C1 C2 C2 C1 C2 C2 C1 C1 C2 C2 C2 C2 C2 C1 C1 [76] C2 C2 C1 C2 C2 C1 C2 C2 C1 C2 C1 C2 C2 C2 C1 C1 C1 C1 C2 C2 C2 C2 C1 C1 C2 [101] C1 C1 C1 C1 C2 C1 C2 C2 C2 C2 C2 C1 C2 C2 C2 C1 C2 C2 C2 C2 C2 C1 C1 C2 C2 [126] C1 C2 C2 C2 C2 C1 C2 C2 C2 C2 C2 C1 C2 C1 C1 C2 C2 C1 C2 C2 C2 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/1a88y1292017219.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 1 410 120 2 194 599 [1] 0.7735849 [1] 0.7553594 [1] 0.7626606 m.ct.x.pred m.ct.x.actu 1 2 1 40 10 2 16 71 [1] 0.8 [1] 0.816092 [1] 0.810219 > m Conditional inference tree with 4 terminal nodes Response: as.factor(Popularity) Inputs: Findingfriends, Knowingpeople, Liked, Celebrity. Number of observations: 146 1) Knowingpeople <= 11; criterion = 1, statistic = 38.04 2)* weights = 66 1) Knowingpeople > 11 3) Celebrity. <= 5; criterion = 0.982, statistic = 8.108 4)* weights = 26 3) Celebrity. > 5 5) Findingfriends <= 9; criterion = 0.995, statistic = 10.325 6)* weights = 8 5) Findingfriends > 9 7)* weights = 46 > postscript(file="/var/www/html/rcomp/tmp/23hpj1292017219.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/33hpj1292017219.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 1 [3,] 2 2 [4,] 2 1 [5,] 1 1 [6,] 2 1 [7,] 2 2 [8,] 1 1 [9,] 1 2 [10,] 2 2 [11,] 1 1 [12,] 2 2 [13,] 1 1 [14,] 1 2 [15,] 1 1 [16,] 1 2 [17,] 1 1 [18,] 1 1 [19,] 1 1 [20,] 2 2 [21,] 1 2 [22,] 2 1 [23,] 2 2 [24,] 2 2 [25,] 2 2 [26,] 2 2 [27,] 2 1 [28,] 2 1 [29,] 2 2 [30,] 1 1 [31,] 1 1 [32,] 2 2 [33,] 2 1 [34,] 1 1 [35,] 2 2 [36,] 2 2 [37,] 2 2 [38,] 2 1 [39,] 1 1 [40,] 1 1 [41,] 1 1 [42,] 2 2 [43,] 1 1 [44,] 1 2 [45,] 2 2 [46,] 1 1 [47,] 1 2 [48,] 2 2 [49,] 1 1 [50,] 2 2 [51,] 2 2 [52,] 1 2 [53,] 2 2 [54,] 1 1 [55,] 2 2 [56,] 1 1 [57,] 2 2 [58,] 2 2 [59,] 1 1 [60,] 2 2 [61,] 1 2 [62,] 2 1 [63,] 2 2 [64,] 1 1 [65,] 2 2 [66,] 2 2 [67,] 1 1 [68,] 1 2 [69,] 2 2 [70,] 2 2 [71,] 2 2 [72,] 2 2 [73,] 2 1 [74,] 1 1 [75,] 1 1 [76,] 2 2 [77,] 2 2 [78,] 1 1 [79,] 2 1 [80,] 2 2 [81,] 1 1 [82,] 2 1 [83,] 2 2 [84,] 1 1 [85,] 2 1 [86,] 1 2 [87,] 2 2 [88,] 2 2 [89,] 2 1 [90,] 1 1 [91,] 1 1 [92,] 1 1 [93,] 1 2 [94,] 2 1 [95,] 2 2 [96,] 2 2 [97,] 2 2 [98,] 1 1 [99,] 1 1 [100,] 2 1 [101,] 1 1 [102,] 1 1 [103,] 1 1 [104,] 1 2 [105,] 2 2 [106,] 1 1 [107,] 2 2 [108,] 2 2 [109,] 2 2 [110,] 2 2 [111,] 2 2 [112,] 1 1 [113,] 2 2 [114,] 2 2 [115,] 2 2 [116,] 1 1 [117,] 2 2 [118,] 2 2 [119,] 2 1 [120,] 2 2 [121,] 2 2 [122,] 1 1 [123,] 1 1 [124,] 2 2 [125,] 2 2 [126,] 1 1 [127,] 2 1 [128,] 2 2 [129,] 2 1 [130,] 2 2 [131,] 1 2 [132,] 2 2 [133,] 2 2 [134,] 2 2 [135,] 2 2 [136,] 2 2 [137,] 1 1 [138,] 2 1 [139,] 1 1 [140,] 1 1 [141,] 2 2 [142,] 2 2 [143,] 1 1 [144,] 2 2 [145,] 2 2 [146,] 2 1 C1 C2 C1 45 13 C2 21 67 > postscript(file="/var/www/html/rcomp/tmp/4d8731292017219.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/5hr5r1292017219.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/67ub41292017219.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/7djli1292017219.tab") + } > > try(system("convert tmp/23hpj1292017219.ps tmp/23hpj1292017219.png",intern=TRUE)) character(0) > try(system("convert tmp/33hpj1292017219.ps tmp/33hpj1292017219.png",intern=TRUE)) character(0) > try(system("convert tmp/4d8731292017219.ps tmp/4d8731292017219.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.721 0.601 5.844