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Type 'q()' to quit R. > x <- array(list(127476 + ,20 + ,17 + ,59 + ,22622 + ,130358 + ,38 + ,17 + ,50 + ,73570 + ,7215 + ,0 + ,0 + ,0 + ,1929 + ,112861 + ,49 + ,22 + ,51 + ,36294 + ,210171 + ,74 + ,30 + ,112 + ,62378 + ,393802 + ,104 + ,31 + ,118 + ,167760 + ,117604 + ,37 + ,19 + ,59 + ,52443 + ,126029 + ,53 + ,25 + ,90 + ,57283 + ,99729 + ,42 + ,30 + ,50 + ,36614 + ,256310 + ,62 + ,26 + ,79 + ,93268 + ,113066 + ,50 + ,20 + ,49 + ,35439 + ,156212 + ,65 + ,25 + ,74 + ,72405 + ,69952 + ,28 + ,15 + ,32 + ,24044 + ,152673 + ,48 + ,22 + ,82 + ,55909 + ,125841 + ,42 + ,12 + ,43 + ,44689 + ,125769 + ,47 + ,19 + ,65 + ,49319 + ,123467 + ,71 + ,28 + ,111 + ,62075 + ,56232 + ,0 + ,12 + ,36 + ,2341 + ,108244 + ,50 + ,28 + ,89 + ,40551 + ,22762 + ,12 + ,13 + ,28 + ,11621 + ,48554 + ,16 + ,14 + ,35 + ,18741 + ,178697 + ,76 + ,27 + ,78 + ,84202 + ,139115 + ,29 + ,25 + ,67 + ,15334 + ,93773 + ,38 + ,30 + ,61 + ,28024 + ,133398 + ,50 + ,21 + ,58 + ,53306 + ,113933 + ,33 + ,17 + ,49 + ,37918 + ,144781 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,66016 + ,43 + ,22 + ,45 + ,30002 + ,57359 + ,18 + ,17 + ,63 + ,19360 + ,96933 + ,41 + ,18 + ,48 + ,43320 + ,70369 + ,45 + ,21 + ,70 + ,35513 + ,65494 + ,29 + ,17 + ,32 + ,23536 + ,3616 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,143931 + ,32 + ,20 + ,72 + ,54438 + ,109894 + ,58 + ,26 + ,56 + ,56812 + ,122973 + ,17 + ,26 + ,64 + ,33838 + ,84336 + ,24 + ,20 + ,77 + ,32366 + ,43410 + ,7 + ,1 + ,3 + ,13 + ,136250 + ,62 + ,24 + ,73 + ,55082 + ,79015 + ,30 + ,14 + ,37 + ,31334 + ,92937 + ,49 + ,26 + ,54 + ,16612 + ,57586 + ,3 + ,12 + ,32 + ,5084 + ,19764 + ,10 + ,2 + ,4 + ,9927 + ,105757 + ,42 + ,16 + ,55 + ,47413 + ,96410 + ,18 + ,22 + ,81 + ,27389 + ,113402 + ,40 + ,28 + ,90 + ,30425 + ,11796 + ,1 + ,2 + ,1 + ,0 + ,7627 + ,0 + ,0 + ,0 + ,0 + ,121085 + ,29 + ,17 + ,38 + ,33510 + ,6836 + ,0 + ,1 + ,0 + ,0 + ,139563 + ,46 + ,17 + ,36 + ,40389 + ,5118 + ,5 + ,0 + ,0 + ,0 + ,40248 + ,8 + ,4 + ,7 + ,6012 + ,0 + ,0 + ,0 + ,0 + ,0 + ,95079 + ,21 + ,25 + ,75 + ,22205 + ,80750 + ,21 + ,26 + ,52 + ,17231 + ,7131 + ,0 + ,0 + ,0 + ,0 + ,4194 + ,0 + ,0 + ,0 + ,0 + ,60378 + ,15 + ,15 + ,45 + ,11017 + ,96971 + ,40 + ,18 + ,60 + ,46741 + ,83484 + ,17 + ,19 + ,48 + ,39869) + ,dim=c(5 + ,144) + ,dimnames=list(c('Time' + ,'Blogged' + ,'Reviewed' + ,'Feedback' + ,'Writing ') + ,1:144)) > y <- array(NA,dim=c(5,144),dimnames=list(c('Time','Blogged','Reviewed','Feedback','Writing '),1:144)) > 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 = '3' > par2 = 'none' > 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 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] 127476 130358 7215 112861 210171 393802 117604 126029 99729 256310 [11] 113066 156212 69952 152673 125841 125769 123467 56232 108244 22762 [21] 48554 178697 139115 93773 133398 113933 144781 140711 283337 158146 [31] 123344 157640 91279 189374 167915 0 175403 92342 100023 178277 [41] 145062 110980 86039 120821 95535 109894 61554 156520 159121 129362 [51] 48188 91198 229864 180317 150640 104416 165098 63205 100056 137214 [61] 99630 84557 91199 83419 101723 94982 129700 110708 81518 31970 [71] 192268 87611 77890 83261 116290 56544 116173 111488 60138 73422 [81] 67751 213351 51185 97181 45100 115801 185664 71960 76441 103613 [91] 98707 126527 136781 105863 38775 179984 164808 19349 146824 108660 [101] 43803 47062 110845 92517 58660 27676 98550 43284 0 66016 [111] 57359 96933 70369 65494 3616 0 143931 109894 122973 84336 [121] 43410 136250 79015 92937 57586 19764 105757 96410 113402 11796 [131] 7627 121085 6836 139563 5118 40248 0 95079 80750 7131 [141] 4194 60378 96971 83484 > 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 4194 5118 6836 7131 7215 7627 11796 19349 19764 4 1 1 1 1 1 1 1 1 1 1 22762 27676 31970 38775 40248 43284 43410 43803 45100 47062 48188 1 1 1 1 1 1 1 1 1 1 1 48554 51185 56232 56544 57359 57586 58660 60138 60378 61554 63205 1 1 1 1 1 1 1 1 1 1 1 65494 66016 67751 69952 70369 71960 73422 76441 77890 79015 80750 1 1 1 1 1 1 1 1 1 1 1 81518 83261 83419 83484 84336 84557 86039 87611 91198 91199 91279 1 1 1 1 1 1 1 1 1 1 1 92342 92517 92937 93773 94982 95079 95535 96410 96933 96971 97181 1 1 1 1 1 1 1 1 1 1 1 98550 98707 99630 99729 100023 100056 101723 103613 104416 105757 105863 1 1 1 1 1 1 1 1 1 1 1 108244 108660 109894 110708 110845 110980 111488 112861 113066 113402 113933 1 1 2 1 1 1 1 1 1 1 1 115801 116173 116290 117604 120821 121085 122973 123344 123467 125769 125841 1 1 1 1 1 1 1 1 1 1 1 126029 126527 127476 129362 129700 130358 133398 136250 136781 137214 139115 1 1 1 1 1 1 1 1 1 1 1 139563 140711 143931 144781 145062 146824 150640 152673 156212 156520 157640 1 1 1 1 1 1 1 1 1 1 1 158146 159121 164808 165098 167915 175403 178277 178697 179984 180317 185664 1 1 1 1 1 1 1 1 1 1 1 189374 192268 210171 213351 229864 256310 283337 393802 1 1 1 1 1 1 1 1 > colnames(x) [1] "Time" "Blogged" "Reviewed" "Feedback" "Writing.." > colnames(x)[par1] [1] "Time" > x[,par1] [1] 127476 130358 7215 112861 210171 393802 117604 126029 99729 256310 [11] 113066 156212 69952 152673 125841 125769 123467 56232 108244 22762 [21] 48554 178697 139115 93773 133398 113933 144781 140711 283337 158146 [31] 123344 157640 91279 189374 167915 0 175403 92342 100023 178277 [41] 145062 110980 86039 120821 95535 109894 61554 156520 159121 129362 [51] 48188 91198 229864 180317 150640 104416 165098 63205 100056 137214 [61] 99630 84557 91199 83419 101723 94982 129700 110708 81518 31970 [71] 192268 87611 77890 83261 116290 56544 116173 111488 60138 73422 [81] 67751 213351 51185 97181 45100 115801 185664 71960 76441 103613 [91] 98707 126527 136781 105863 38775 179984 164808 19349 146824 108660 [101] 43803 47062 110845 92517 58660 27676 98550 43284 0 66016 [111] 57359 96933 70369 65494 3616 0 143931 109894 122973 84336 [121] 43410 136250 79015 92937 57586 19764 105757 96410 113402 11796 [131] 7627 121085 6836 139563 5118 40248 0 95079 80750 7131 [141] 4194 60378 96971 83484 > 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/1coyy1323875455.tab") + } + } > m Conditional inference tree with 7 terminal nodes Response: Time Inputs: Blogged, Reviewed, Feedback, Writing.. Number of observations: 144 1) Writing.. <= 32615; criterion = 1, statistic = 104.282 2) Feedback <= 20; criterion = 1, statistic = 37.965 3) Blogged <= 1; criterion = 0.997, statistic = 11.342 4)* weights = 11 3) Blogged > 1 5)* weights = 10 2) Feedback > 20 6) Blogged <= 17; criterion = 0.999, statistic = 14.314 7)* weights = 11 6) Blogged > 17 8)* weights = 29 1) Writing.. > 32615 9) Writing.. <= 57283; criterion = 1, statistic = 47.497 10)* weights = 61 9) Writing.. > 57283 11) Writing.. <= 78907; criterion = 0.995, statistic = 10.257 12)* weights = 14 11) Writing.. > 78907 13)* weights = 8 > postscript(file="/var/www/rcomp/tmp/2hsb41323875455.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/34dxq1323875455.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 127476 90379.000 37097.00000 2 130358 160563.000 -30205.00000 3 7215 4401.364 2813.63636 4 112861 116200.328 -3339.32787 5 210171 160563.000 49608.00000 6 393802 223837.250 169964.75000 7 117604 116200.328 1403.67213 8 126029 116200.328 9828.67213 9 99729 116200.328 -16471.32787 10 256310 223837.250 32472.75000 11 113066 116200.328 -3134.32787 12 156212 160563.000 -4351.00000 13 69952 90379.000 -20427.00000 14 152673 116200.328 36472.67213 15 125841 116200.328 9640.67213 16 125769 116200.328 9568.67213 17 123467 160563.000 -37096.00000 18 56232 49909.636 6322.36364 19 108244 116200.328 -7956.32787 20 22762 49909.636 -27147.63636 21 48554 49909.636 -1355.63636 22 178697 223837.250 -45140.25000 23 139115 90379.000 48736.00000 24 93773 90379.000 3394.00000 25 133398 116200.328 17197.67213 26 113933 116200.328 -2267.32787 27 144781 116200.328 28580.67213 28 140711 223837.250 -83126.25000 29 283337 223837.250 59499.75000 30 158146 160563.000 -2417.00000 31 123344 116200.328 7143.67213 32 157640 160563.000 -2923.00000 33 91279 90379.000 900.00000 34 189374 90379.000 98995.00000 35 167915 160563.000 7352.00000 36 0 4401.364 -4401.36364 37 175403 116200.328 59202.67213 38 92342 90379.000 1963.00000 39 100023 116200.328 -16177.32787 40 178277 223837.250 -45560.25000 41 145062 116200.328 28861.67213 42 110980 116200.328 -5220.32787 43 86039 116200.328 -30161.32787 44 120821 116200.328 4620.67213 45 95535 116200.328 -20665.32787 46 109894 116200.328 -6306.32787 47 61554 49909.636 11644.36364 48 156520 116200.328 40319.67213 49 159121 160563.000 -1442.00000 50 129362 116200.328 13161.67213 51 48188 49909.636 -1721.63636 52 91198 90379.000 819.00000 53 229864 223837.250 6026.75000 54 180317 116200.328 64116.67213 55 150640 160563.000 -9923.00000 56 104416 116200.328 -11784.32787 57 165098 116200.328 48897.67213 58 63205 90379.000 -27174.00000 59 100056 116200.328 -16144.32787 60 137214 90379.000 46835.00000 61 99630 116200.328 -16570.32787 62 84557 116200.328 -31643.32787 63 91199 116200.328 -25001.32787 64 83419 116200.328 -32781.32787 65 101723 116200.328 -14477.32787 66 94982 116200.328 -21218.32787 67 129700 223837.250 -94137.25000 68 110708 116200.328 -5492.32787 69 81518 116200.328 -34682.32787 70 31970 49909.636 -17939.63636 71 192268 160563.000 31705.00000 72 87611 116200.328 -28589.32787 73 77890 116200.328 -38310.32787 74 83261 90379.000 -7118.00000 75 116290 116200.328 89.67213 76 56544 49909.636 6634.36364 77 116173 116200.328 -27.32787 78 111488 160563.000 -49075.00000 79 60138 49909.636 10228.36364 80 73422 90379.000 -16957.00000 81 67751 90379.000 -22628.00000 82 213351 116200.328 97150.67213 83 51185 33261.200 17923.80000 84 97181 116200.328 -19019.32787 85 45100 49909.636 -4809.63636 86 115801 116200.328 -399.32787 87 185664 160563.000 25101.00000 88 71960 90379.000 -18419.00000 89 76441 90379.000 -13938.00000 90 103613 116200.328 -12587.32787 91 98707 116200.328 -17493.32787 92 126527 116200.328 10326.67213 93 136781 116200.328 20580.67213 94 105863 90379.000 15484.00000 95 38775 33261.200 5513.80000 96 179984 160563.000 19421.00000 97 164808 160563.000 4245.00000 98 19349 33261.200 -13912.20000 99 146824 116200.328 30623.67213 100 108660 116200.328 -7540.32787 101 43803 33261.200 10541.80000 102 47062 90379.000 -43317.00000 103 110845 90379.000 20466.00000 104 92517 116200.328 -23683.32787 105 58660 90379.000 -31719.00000 106 27676 33261.200 -5585.20000 107 98550 116200.328 -17650.32787 108 43284 33261.200 10022.80000 109 0 4401.364 -4401.36364 110 66016 90379.000 -24363.00000 111 57359 90379.000 -33020.00000 112 96933 116200.328 -19267.32787 113 70369 116200.328 -45831.32787 114 65494 90379.000 -24885.00000 115 3616 4401.364 -785.36364 116 0 4401.364 -4401.36364 117 143931 116200.328 27730.67213 118 109894 116200.328 -6306.32787 119 122973 116200.328 6772.67213 120 84336 90379.000 -6043.00000 121 43410 33261.200 10148.80000 122 136250 116200.328 20049.67213 123 79015 90379.000 -11364.00000 124 92937 90379.000 2558.00000 125 57586 49909.636 7676.36364 126 19764 33261.200 -13497.20000 127 105757 116200.328 -10443.32787 128 96410 90379.000 6031.00000 129 113402 90379.000 23023.00000 130 11796 4401.364 7394.63636 131 7627 4401.364 3225.63636 132 121085 116200.328 4884.67213 133 6836 4401.364 2434.63636 134 139563 116200.328 23362.67213 135 5118 33261.200 -28143.20000 136 40248 33261.200 6986.80000 137 0 4401.364 -4401.36364 138 95079 90379.000 4700.00000 139 80750 90379.000 -9629.00000 140 7131 4401.364 2729.63636 141 4194 4401.364 -207.36364 142 60378 49909.636 10468.36364 143 96971 116200.328 -19229.32787 144 83484 116200.328 -32716.32787 > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } > postscript(file="/var/www/rcomp/tmp/4p3uz1323875455.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/506ul1323875455.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/69e211323875455.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/7ivs91323875455.tab") + } > > try(system("convert tmp/2hsb41323875455.ps tmp/2hsb41323875455.png",intern=TRUE)) character(0) > try(system("convert tmp/34dxq1323875455.ps tmp/34dxq1323875455.png",intern=TRUE)) character(0) > try(system("convert tmp/4p3uz1323875455.ps tmp/4p3uz1323875455.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.640 0.130 2.732