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. Type 'q()' to quit R. > x <- array(list(158258 + ,89 + ,48 + ,18 + ,20465 + ,186930 + ,57 + ,53 + ,20 + ,33629 + ,7215 + ,18 + ,0 + ,0 + ,1423 + ,129098 + ,94 + ,51 + ,27 + ,25629 + ,230587 + ,134 + ,76 + ,31 + ,54002 + ,508313 + ,260 + ,128 + ,36 + ,151036 + ,180745 + ,56 + ,62 + ,23 + ,33287 + ,185559 + ,58 + ,83 + ,30 + ,31172 + ,154581 + ,43 + ,55 + ,30 + ,28113 + ,290658 + ,95 + ,67 + ,26 + ,57803 + ,121844 + ,75 + ,50 + ,24 + ,49830 + ,184039 + ,68 + ,77 + ,30 + ,52143 + ,100324 + ,98 + ,46 + ,22 + ,21055 + ,209427 + ,114 + ,79 + ,25 + ,47007 + ,167592 + ,57 + ,55 + ,18 + ,28735 + ,154593 + ,86 + ,54 + ,22 + ,59147 + ,142018 + ,56 + ,81 + ,33 + ,78950 + ,77855 + ,59 + ,5 + ,15 + ,13497 + ,167047 + ,86 + ,74 + ,34 + ,46154 + ,27997 + ,24 + ,13 + ,18 + ,53249 + ,70824 + ,58 + ,19 + ,15 + ,10726 + ,241082 + ,99 + ,99 + ,30 + ,83700 + ,195820 + ,72 + ,38 + ,25 + ,40400 + ,141899 + ,53 + ,59 + ,34 + ,33797 + ,145433 + ,85 + ,50 + ,21 + ,36205 + ,180241 + ,30 + ,50 + ,21 + ,30165 + 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,13018 + ,0 + ,0 + ,0 + ,0 + ,0 + ,91529 + ,32 + ,46 + ,25 + ,98177 + ,107205 + ,66 + ,25 + ,21 + ,37941 + ,144664 + ,44 + ,51 + ,23 + ,31032 + ,136540 + ,61 + ,59 + ,21 + ,32683 + ,76656 + ,59 + ,36 + ,21 + ,34545 + ,3616 + ,5 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,183065 + ,42 + ,40 + ,23 + ,27525 + ,144636 + ,83 + ,68 + ,33 + ,66856 + ,152826 + ,96 + ,28 + ,28 + ,28549 + ,113273 + ,38 + ,36 + ,23 + ,38610 + ,43410 + ,19 + ,7 + ,1 + ,2781 + ,175774 + ,72 + ,70 + ,29 + ,41211 + ,95401 + ,41 + ,30 + ,18 + ,22698 + ,118893 + ,54 + ,59 + ,32 + ,41194 + ,60493 + ,40 + ,3 + ,12 + ,32689 + ,19764 + ,12 + ,10 + ,2 + ,5752 + ,164062 + ,55 + ,46 + ,21 + ,26757 + ,132696 + ,32 + ,34 + ,28 + ,22527 + ,155088 + ,47 + ,54 + ,29 + ,44810 + ,11796 + ,9 + ,1 + ,2 + ,0 + ,10674 + ,9 + ,0 + ,0 + ,0 + ,142261 + ,56 + ,39 + ,18 + ,100674 + ,6836 + ,3 + ,0 + ,1 + ,0 + ,154206 + ,61 + ,48 + ,21 + ,57786 + ,5118 + ,3 + ,5 + ,0 + ,0 + ,40248 + ,16 + ,8 + ,4 + ,5444 + ,0 + ,0 + ,0 + ,0 + ,0 + ,122641 + ,46 + ,38 + ,25 + ,28470 + ,88837 + ,38 + ,21 + ,26 + ,61849 + ,7131 + ,4 + ,0 + ,0 + ,0 + ,9056 + ,14 + ,0 + ,4 + ,2179 + ,76611 + ,24 + ,15 + ,17 + ,8019 + ,132697 + ,50 + ,50 + ,21 + ,39644 + ,100681 + ,19 + ,17 + ,22 + ,23494) + ,dim=c(5 + ,144) + ,dimnames=list(c('time' + ,'logins' + ,'bloggedcomputations' + ,'reviewedcompendiums' + ,'compendiumcharacters') + ,1:144)) > y <- array(NA,dim=c(5,144),dimnames=list(c('time','logins','bloggedcomputations','reviewedcompendiums','compendiumcharacters'),1:144)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par20 = '' > par19 = '' > par18 = '' > par17 = '' > par16 = '' > par15 = '' > par14 = '' > par13 = '' > par12 = '' > par11 = '' > par10 = '' > par9 = '' > par8 = '' > par7 = '' > par6 = '' > par5 = '' > par4 = 'no' > par3 = '3' > par2 = 'none' > par1 = '1' > 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] "time" > x[,par1] [1] 158258 186930 7215 129098 230587 508313 180745 185559 154581 290658 [11] 121844 184039 100324 209427 167592 154593 142018 77855 167047 27997 [21] 70824 241082 195820 141899 145433 180241 202232 190230 354924 192399 [31] 182286 181590 133801 233686 219428 0 223044 100129 136733 249965 [41] 242379 145794 96404 195891 115335 157787 81293 224049 223789 160344 [51] 48188 152206 294283 235223 195583 145942 208834 93764 151985 190545 [61] 148922 132856 124234 112718 160930 99184 182022 138708 114408 31970 [71] 225558 137011 113612 108641 162203 100098 174768 158459 80934 84971 [81] 80545 287191 62974 130982 75555 162154 224670 115019 105038 155537 [91] 153133 165577 151517 133686 58128 245196 195576 19349 225371 152796 [101] 59117 91762 127987 113552 85338 27676 147984 122417 0 91529 [111] 107205 144664 136540 76656 3616 0 183065 144636 152826 113273 [121] 43410 175774 95401 118893 60493 19764 164062 132696 155088 11796 [131] 10674 142261 6836 154206 5118 40248 0 122641 88837 7131 [141] 9056 76611 132697 100681 > 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]) 0 3616 5118 6836 7131 7215 9056 10674 11796 19349 19764 4 1 1 1 1 1 1 1 1 1 1 27676 27997 31970 40248 43410 48188 58128 59117 60493 62974 70824 1 1 1 1 1 1 1 1 1 1 1 75555 76611 76656 77855 80545 80934 81293 84971 85338 88837 91529 1 1 1 1 1 1 1 1 1 1 1 91762 93764 95401 96404 99184 100098 100129 100324 100681 105038 107205 1 1 1 1 1 1 1 1 1 1 1 108641 112718 113273 113552 113612 114408 115019 115335 118893 121844 122417 1 1 1 1 1 1 1 1 1 1 1 122641 124234 127987 129098 130982 132696 132697 132856 133686 133801 136540 1 1 1 1 1 1 1 1 1 1 1 136733 137011 138708 141899 142018 142261 144636 144664 145433 145794 145942 1 1 1 1 1 1 1 1 1 1 1 147984 148922 151517 151985 152206 152796 152826 153133 154206 154581 154593 1 1 1 1 1 1 1 1 1 1 1 155088 155537 157787 158258 158459 160344 160930 162154 162203 164062 165577 1 1 1 1 1 1 1 1 1 1 1 167047 167592 174768 175774 180241 180745 181590 182022 182286 183065 184039 1 1 1 1 1 1 1 1 1 1 1 185559 186930 190230 190545 192399 195576 195583 195820 195891 202232 208834 1 1 1 1 1 1 1 1 1 1 1 209427 219428 223044 223789 224049 224670 225371 225558 230587 233686 235223 1 1 1 1 1 1 1 1 1 1 1 241082 242379 245196 249965 287191 290658 294283 354924 508313 1 1 1 1 1 1 1 1 1 > colnames(x) [1] "time" "logins" "bloggedcomputations" [4] "reviewedcompendiums" "compendiumcharacters" > colnames(x)[par1] [1] "time" > x[,par1] [1] 158258 186930 7215 129098 230587 508313 180745 185559 154581 290658 [11] 121844 184039 100324 209427 167592 154593 142018 77855 167047 27997 [21] 70824 241082 195820 141899 145433 180241 202232 190230 354924 192399 [31] 182286 181590 133801 233686 219428 0 223044 100129 136733 249965 [41] 242379 145794 96404 195891 115335 157787 81293 224049 223789 160344 [51] 48188 152206 294283 235223 195583 145942 208834 93764 151985 190545 [61] 148922 132856 124234 112718 160930 99184 182022 138708 114408 31970 [71] 225558 137011 113612 108641 162203 100098 174768 158459 80934 84971 [81] 80545 287191 62974 130982 75555 162154 224670 115019 105038 155537 [91] 153133 165577 151517 133686 58128 245196 195576 19349 225371 152796 [101] 59117 91762 127987 113552 85338 27676 147984 122417 0 91529 [111] 107205 144664 136540 76656 3616 0 183065 144636 152826 113273 [121] 43410 175774 95401 118893 60493 19764 164062 132696 155088 11796 [131] 10674 142261 6836 154206 5118 40248 0 122641 88837 7131 [141] 9056 76611 132697 100681 > 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/1k1at1324582206.tab") + } + } > m Conditional inference tree with 6 terminal nodes Response: time Inputs: logins, bloggedcomputations, reviewedcompendiums, compendiumcharacters Number of observations: 144 1) bloggedcomputations <= 26; criterion = 1, statistic = 88.467 2) bloggedcomputations <= 13; criterion = 1, statistic = 23.231 3) logins <= 14; criterion = 1, statistic = 18.134 4)* weights = 13 3) logins > 14 5)* weights = 9 2) bloggedcomputations > 13 6)* weights = 12 1) bloggedcomputations > 26 7) logins <= 110; criterion = 1, statistic = 42.167 8) bloggedcomputations <= 59; criterion = 1, statistic = 19.629 9)* weights = 70 8) bloggedcomputations > 59 10)* weights = 31 7) logins > 110 11)* weights = 9 > postscript(file="/var/wessaorg/rcomp/tmp/2oyvm1324582206.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/3h0an1324582206.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) + } Actuals Forecasts Residuals 1 158258 142228.84 16029.15714 2 186930 142228.84 44701.15714 3 7215 40561.33 -33346.33333 4 129098 142228.84 -13130.84286 5 230587 270510.33 -39923.33333 6 508313 270510.33 237802.66667 7 180745 186796.32 -6051.32258 8 185559 186796.32 -1237.32258 9 154581 142228.84 12352.15714 10 290658 186796.32 103861.67742 11 121844 142228.84 -20384.84286 12 184039 186796.32 -2757.32258 13 100324 142228.84 -41904.84286 14 209427 270510.33 -61083.33333 15 167592 142228.84 25363.15714 16 154593 142228.84 12364.15714 17 142018 186796.32 -44778.32258 18 77855 40561.33 37293.66667 19 167047 186796.32 -19749.32258 20 27997 40561.33 -12564.33333 21 70824 81397.67 -10573.66667 22 241082 186796.32 54285.67742 23 195820 142228.84 53591.15714 24 141899 142228.84 -329.84286 25 145433 142228.84 3204.15714 26 180241 142228.84 38012.15714 27 202232 270510.33 -68278.33333 28 190230 186796.32 3433.67742 29 354924 270510.33 84413.66667 30 192399 142228.84 50170.15714 31 182286 186796.32 -4510.32258 32 181590 186796.32 -5206.32258 33 133801 142228.84 -8427.84286 34 233686 270510.33 -36824.33333 35 219428 186796.32 32631.67742 36 0 7180.00 -7180.00000 37 223044 142228.84 80815.15714 38 100129 142228.84 -42099.84286 39 136733 142228.84 -5495.84286 40 249965 186796.32 63168.67742 41 242379 186796.32 55582.67742 42 145794 142228.84 3565.15714 43 96404 81397.67 15006.33333 44 195891 186796.32 9094.67742 45 115335 142228.84 -26893.84286 46 157787 142228.84 15558.15714 47 81293 81397.67 -104.66667 48 224049 186796.32 37252.67742 49 223789 142228.84 81560.15714 50 160344 186796.32 -26452.32258 51 48188 40561.33 7626.66667 52 152206 186796.32 -34590.32258 53 294283 186796.32 107486.67742 54 235223 142228.84 92994.15714 55 195583 186796.32 8786.67742 56 145942 142228.84 3713.15714 57 208834 142228.84 66605.15714 58 93764 81397.67 12366.33333 59 151985 186796.32 -34811.32258 60 190545 142228.84 48316.15714 61 148922 142228.84 6693.15714 62 132856 142228.84 -9372.84286 63 124234 142228.84 -17994.84286 64 112718 142228.84 -29510.84286 65 160930 142228.84 18701.15714 66 99184 142228.84 -43044.84286 67 182022 186796.32 -4774.32258 68 138708 186796.32 -48088.32258 69 114408 142228.84 -27820.84286 70 31970 40561.33 -8591.33333 71 225558 270510.33 -44952.33333 72 137011 142228.84 -5217.84286 73 113612 186796.32 -73184.32258 74 108641 142228.84 -33587.84286 75 162203 186796.32 -24593.32258 76 100098 142228.84 -42130.84286 77 174768 186796.32 -12028.32258 78 158459 186796.32 -28337.32258 79 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142228.84 -50699.84286 111 107205 81397.67 25807.33333 112 144664 142228.84 2435.15714 113 136540 142228.84 -5688.84286 114 76656 142228.84 -65572.84286 115 3616 7180.00 -3564.00000 116 0 7180.00 -7180.00000 117 183065 142228.84 40836.15714 118 144636 186796.32 -42160.32258 119 152826 142228.84 10597.15714 120 113273 142228.84 -28955.84286 121 43410 40561.33 2848.66667 122 175774 186796.32 -11022.32258 123 95401 142228.84 -46827.84286 124 118893 142228.84 -23335.84286 125 60493 40561.33 19931.66667 126 19764 7180.00 12584.00000 127 164062 142228.84 21833.15714 128 132696 142228.84 -9532.84286 129 155088 142228.84 12859.15714 130 11796 7180.00 4616.00000 131 10674 7180.00 3494.00000 132 142261 142228.84 32.15714 133 6836 7180.00 -344.00000 134 154206 142228.84 11977.15714 135 5118 7180.00 -2062.00000 136 40248 40561.33 -313.33333 137 0 7180.00 -7180.00000 138 122641 142228.84 -19587.84286 139 88837 81397.67 7439.33333 140 7131 7180.00 -49.00000 141 9056 7180.00 1876.00000 142 76611 81397.67 -4786.66667 143 132697 142228.84 -9531.84286 144 100681 81397.67 19283.33333 > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } > postscript(file="/var/wessaorg/rcomp/tmp/48l931324582206.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$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/5xjwh1324582206.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$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/6h5kv1324582206.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/7zo2j1324582206.tab") + } > > try(system("convert tmp/2oyvm1324582206.ps tmp/2oyvm1324582206.png",intern=TRUE)) character(0) > try(system("convert tmp/3h0an1324582206.ps tmp/3h0an1324582206.png",intern=TRUE)) character(0) > try(system("convert tmp/48l931324582206.ps tmp/48l931324582206.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.533 0.301 3.994