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Type 'q()' to quit R. > x <- array(list(10102 + ,3.4 + ,8863 + ,8626 + ,8366 + ,12008 + ,8463 + ,4.8 + ,10102 + ,8863 + ,8626 + ,9169 + ,9114 + ,6.5 + ,8463 + ,10102 + ,8863 + ,8788 + ,8563 + ,8.5 + ,9114 + ,8463 + ,10102 + ,8417 + ,8872 + ,15.1 + ,8563 + ,9114 + ,8463 + ,8247 + ,8301 + ,15.7 + ,8872 + ,8563 + ,9114 + ,8197 + ,8301 + ,18.7 + ,8301 + ,8872 + ,8563 + ,8236 + ,8278 + ,19.2 + ,8301 + ,8301 + ,8872 + ,8253 + ,7736 + ,12.9 + ,8278 + ,8301 + ,8301 + ,7733 + ,7973 + ,14.4 + ,7736 + ,8278 + ,8301 + ,8366 + ,8268 + ,6.2 + ,7973 + ,7736 + ,8278 + ,8626 + ,9476 + ,3.3 + ,8268 + ,7973 + ,7736 + ,8863 + ,11100 + ,4.6 + ,9476 + ,8268 + ,7973 + ,10102 + ,8962 + ,7.1 + ,11100 + ,9476 + ,8268 + ,8463 + ,9173 + ,7.8 + ,8962 + ,11100 + ,9476 + ,9114 + ,8738 + ,9.9 + ,9173 + ,8962 + ,11100 + ,8563 + ,8459 + ,13.6 + ,8738 + ,9173 + ,8962 + ,8872 + ,8078 + ,17.1 + ,8459 + ,8738 + ,9173 + ,8301 + ,8411 + ,17.8 + ,8078 + ,8459 + ,8738 + ,8301 + ,8291 + ,18.6 + ,8411 + ,8078 + ,8459 + ,8278 + ,7810 + ,14.7 + ,8291 + ,8411 + ,8078 + ,7736 + ,8616 + ,10.5 + ,7810 + ,8291 + ,8411 + ,7973 + ,8312 + ,8.6 + ,8616 + ,7810 + ,8291 + ,8268 + ,9692 + ,4.4 + ,8312 + ,8616 + ,7810 + ,9476 + ,9911 + ,2.3 + ,9692 + ,8312 + ,8616 + ,11100 + ,8915 + ,2.8 + ,9911 + ,9692 + ,8312 + ,8962 + ,9452 + ,8.8 + ,8915 + ,9911 + ,9692 + ,9173 + ,9112 + ,10.7 + ,9452 + ,8915 + ,9911 + ,8738 + ,8472 + ,13.9 + ,9112 + ,9452 + ,8915 + ,8459 + ,8230 + ,19.3 + ,8472 + ,9112 + ,9452 + ,8078 + ,8384 + ,19.5 + ,8230 + ,8472 + ,9112 + ,8411 + ,8625 + ,20.4 + ,8384 + ,8230 + ,8472 + ,8291 + ,8221 + ,15.3 + ,8625 + ,8384 + ,8230 + ,7810 + ,8649 + ,7.9 + ,8221 + ,8625 + ,8384 + ,8616 + ,8625 + ,8.3 + ,8649 + ,8221 + ,8625 + ,8312 + ,10443 + ,4.5 + ,8625 + ,8649 + ,8221 + ,9692 + ,10357 + ,3.2 + ,10443 + ,8625 + ,8649 + ,9911 + ,8586 + ,5 + ,10357 + ,10443 + ,8625 + ,8915 + ,8892 + ,6.6 + ,8586 + ,10357 + ,10443 + ,9452 + ,8329 + ,11.1 + ,8892 + ,8586 + ,10357 + ,9112 + ,8101 + ,12.8 + ,8329 + ,8892 + ,8586 + ,8472 + ,7922 + ,16.3 + ,8101 + ,8329 + ,8892 + ,8230 + ,8120 + ,17.4 + ,7922 + ,8101 + ,8329 + ,8384 + ,7838 + ,18.9 + ,8120 + ,7922 + ,8101 + ,8625 + ,7735 + ,15.8 + ,7838 + ,8120 + ,7922 + ,8221 + ,8406 + ,11.7 + ,7735 + ,7838 + ,8120 + ,8649 + ,8209 + ,6.4 + ,8406 + ,7735 + ,7838 + ,8625 + ,9451 + ,2.9 + ,8209 + ,8406 + ,7735 + ,10443 + ,10041 + ,4.7 + ,9451 + ,8209 + ,8406 + ,10357 + ,9411 + ,2.4 + ,10041 + ,9451 + ,8209 + ,8586 + ,10405 + ,7.2 + ,9411 + ,10041 + ,9451 + ,8892 + ,8467 + ,10.7 + ,10405 + ,9411 + ,10041 + ,8329 + ,8464 + ,13.4 + ,8467 + ,10405 + ,9411 + ,8101 + ,8102 + ,18.3 + ,8464 + ,8467 + ,10405 + ,7922 + ,7627 + ,18.4 + ,8102 + ,8464 + ,8467 + ,8120 + ,7513 + ,16.8 + ,7627 + ,8102 + ,8464 + ,7838 + ,7510 + ,16.6 + ,7513 + ,7627 + ,8102 + ,7735 + ,8291 + ,14.1 + ,7510 + ,7513 + ,7627 + ,8406 + ,8064 + ,6.1 + ,8291 + ,7510 + ,7513 + ,8209 + ,9383 + ,3.5 + ,8064 + ,8291 + ,7510 + ,9451 + ,9706 + ,1.7 + ,9383 + ,8064 + ,8291 + ,10041 + ,8579 + ,2.3 + ,9706 + ,9383 + ,8064 + ,9411 + ,9474 + ,4.5 + ,8579 + ,9706 + ,9383 + ,10405 + ,8318 + ,9.3 + ,9474 + ,8579 + ,9706 + ,8467 + ,8213 + ,14.2 + ,8318 + ,9474 + ,8579 + ,8464 + ,8059 + ,17.3 + ,8213 + ,8318 + ,9474 + ,8102 + ,9111 + ,23 + ,8059 + ,8213 + ,8318 + ,7627 + ,7708 + ,16.3 + ,9111 + ,8059 + ,8213 + ,7513 + ,7680 + ,18.4 + ,7708 + ,9111 + ,8059 + ,7510 + ,8014 + ,14.2 + ,7680 + ,7708 + ,9111 + ,8291 + ,8007 + ,9.1 + ,8014 + ,7680 + ,7708 + ,8064 + ,8718 + ,5.9 + ,8007 + ,8014 + ,7680 + ,9383 + ,9486 + ,7.2 + ,8718 + ,8007 + ,8014 + ,9706 + ,9113 + ,6.8 + ,9486 + ,8718 + ,8007 + ,8579 + ,9025 + ,8 + ,9113 + ,9486 + ,8718 + ,9474 + ,8476 + ,14.3 + ,9025 + ,9113 + ,9486 + ,8318 + ,7952 + ,14.6 + ,8476 + ,9025 + ,9113 + ,8213 + ,7759 + ,17.5 + ,7952 + ,8476 + ,9025 + ,8059 + ,7835 + ,17.2 + ,7759 + ,7952 + ,8476 + ,9111 + ,7600 + ,17.2 + ,7835 + ,7759 + ,7952 + ,7708 + ,7651 + ,14.1 + ,7600 + ,7835 + ,7759 + ,7680 + ,8319 + ,10.4 + ,7651 + ,7600 + ,7835 + ,8014 + ,8812 + ,6.8 + ,8319 + ,7651 + ,7600 + ,8007 + ,8630 + ,4.1 + ,8812 + ,8319 + ,7651 + ,8718) + ,dim=c(6 + ,84) + ,dimnames=list(c('S' + ,'T' + ,'S1' + ,'S2' + ,'S3' + ,'S12') + ,1:84)) > y <- array(NA,dim=c(6,84),dimnames=list(c('S','T','S1','S2','S3','S12'),1:84)) > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "S" > x[,par1] [1] 10102 8463 9114 8563 8872 8301 8301 8278 7736 7973 8268 9476 [13] 11100 8962 9173 8738 8459 8078 8411 8291 7810 8616 8312 9692 [25] 9911 8915 9452 9112 8472 8230 8384 8625 8221 8649 8625 10443 [37] 10357 8586 8892 8329 8101 7922 8120 7838 7735 8406 8209 9451 [49] 10041 9411 10405 8467 8464 8102 7627 7513 7510 8291 8064 9383 [61] 9706 8579 9474 8318 8213 8059 9111 7708 7680 8014 8007 8718 [73] 9486 9113 9025 8476 7952 7759 7835 7600 7651 8319 8812 8630 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 7510 7513 7600 7627 7651 7680 7708 7735 7736 7759 7810 7835 7838 1 1 1 1 1 1 1 1 1 1 1 1 1 7922 7952 7973 8007 8014 8059 8064 8078 8101 8102 8120 8209 8213 1 1 1 1 1 1 1 1 1 1 1 1 1 8221 8230 8268 8278 8291 8301 8312 8318 8319 8329 8384 8406 8411 1 1 1 1 2 2 1 1 1 1 1 1 1 8459 8463 8464 8467 8472 8476 8563 8579 8586 8616 8625 8630 8649 1 1 1 1 1 1 1 1 1 1 2 1 1 8718 8738 8812 8872 8892 8915 8962 9025 9111 9112 9113 9114 9173 1 1 1 1 1 1 1 1 1 1 1 1 1 9383 9411 9451 9452 9474 9476 9486 9692 9706 9911 10041 10102 10357 1 1 1 1 1 1 1 1 1 1 1 1 1 10405 10443 11100 1 1 1 > colnames(x) [1] "S" "T" "S1" "S2" "S3" "S12" > colnames(x)[par1] [1] "S" > x[,par1] [1] 10102 8463 9114 8563 8872 8301 8301 8278 7736 7973 8268 9476 [13] 11100 8962 9173 8738 8459 8078 8411 8291 7810 8616 8312 9692 [25] 9911 8915 9452 9112 8472 8230 8384 8625 8221 8649 8625 10443 [37] 10357 8586 8892 8329 8101 7922 8120 7838 7735 8406 8209 9451 [49] 10041 9411 10405 8467 8464 8102 7627 7513 7510 8291 8064 9383 [61] 9706 8579 9474 8318 8213 8059 9111 7708 7680 8014 8007 8718 [73] 9486 9113 9025 8476 7952 7759 7835 7600 7651 8319 8812 8630 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/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/freestat/rcomp/tmp/188cj1292406121.tab") + } + } > m Conditional inference tree with 4 terminal nodes Response: S Inputs: T, S1, S2, S3, S12 Number of observations: 84 1) S12 <= 9474; criterion = 1, statistic = 48.431 2) S12 <= 8472; criterion = 1, statistic = 25.058 3) S1 <= 8291; criterion = 0.995, statistic = 10.648 4)* weights = 23 3) S1 > 8291 5)* weights = 24 2) S12 > 8472 6)* weights = 26 1) S12 > 9474 7)* weights = 11 > postscript(file="/var/www/html/freestat/rcomp/tmp/21ztm1292406121.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/freestat/rcomp/tmp/31ztm1292406121.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 10102 9978.455 123.54545 2 8463 8814.538 -351.53846 3 9114 8814.538 299.46154 4 8563 8364.333 198.66667 5 8872 8364.333 507.66667 6 8301 8364.333 -63.33333 7 8301 8364.333 -63.33333 8 8278 8364.333 -86.33333 9 7736 7996.174 -260.17391 10 7973 7996.174 -23.17391 11 8268 8814.538 -546.53846 12 9476 8814.538 661.46154 13 11100 9978.455 1121.54545 14 8962 8364.333 597.66667 15 9173 8814.538 358.46154 16 8738 8814.538 -76.53846 17 8459 8814.538 -355.53846 18 8078 8364.333 -286.33333 19 8411 7996.174 414.82609 20 8291 8364.333 -73.33333 21 7810 7996.174 -186.17391 22 8616 7996.174 619.82609 23 8312 8364.333 -52.33333 24 9692 9978.455 -286.45455 25 9911 9978.455 -67.45455 26 8915 8814.538 100.46154 27 9452 8814.538 637.46154 28 9112 8814.538 297.46154 29 8472 8364.333 107.66667 30 8230 8364.333 -134.33333 31 8384 7996.174 387.82609 32 8625 8364.333 260.66667 33 8221 8364.333 -143.33333 34 8649 8814.538 -165.53846 35 8625 8364.333 260.66667 36 10443 9978.455 464.54545 37 10357 9978.455 378.54545 38 8586 8814.538 -228.53846 39 8892 8814.538 77.46154 40 8329 8814.538 -485.53846 41 8101 8364.333 -263.33333 42 7922 7996.174 -74.17391 43 8120 7996.174 123.82609 44 7838 8814.538 -976.53846 45 7735 7996.174 -261.17391 46 8406 8814.538 -408.53846 47 8209 8814.538 -605.53846 48 9451 9978.455 -527.45455 49 10041 9978.455 62.54545 50 9411 8814.538 596.46154 51 10405 8814.538 1590.46154 52 8467 8364.333 102.66667 53 8464 8364.333 99.66667 54 8102 8364.333 -262.33333 55 7627 7996.174 -369.17391 56 7513 7996.174 -483.17391 57 7510 7996.174 -486.17391 58 8291 7996.174 294.82609 59 8064 7996.174 67.82609 60 9383 8814.538 568.46154 61 9706 9978.455 -272.45455 62 8579 8814.538 -235.53846 63 9474 9978.455 -504.45455 64 8318 8364.333 -46.33333 65 8213 8364.333 -151.33333 66 8059 7996.174 62.82609 67 9111 7996.174 1114.82609 68 7708 8364.333 -656.33333 69 7680 7996.174 -316.17391 70 8014 7996.174 17.82609 71 8007 7996.174 10.82609 72 8718 8814.538 -96.53846 73 9486 9978.455 -492.45455 74 9113 8814.538 298.46154 75 9025 8814.538 210.46154 76 8476 8364.333 111.66667 77 7952 8364.333 -412.33333 78 7759 7996.174 -237.17391 79 7835 8814.538 -979.53846 80 7600 7996.174 -396.17391 81 7651 7996.174 -345.17391 82 8319 7996.174 322.82609 83 8812 8364.333 447.66667 84 8630 8814.538 -184.53846 > 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/html/freestat/rcomp/tmp/4t9bp1292406121.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/freestat/rcomp/tmp/5t1741292406121.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/freestat/rcomp/tmp/63s6p1292406121.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/freestat/rcomp/tmp/7pa4u1292406121.tab") + } > > try(system("convert tmp/21ztm1292406121.ps tmp/21ztm1292406121.png",intern=TRUE)) character(0) > try(system("convert tmp/31ztm1292406121.ps tmp/31ztm1292406121.png",intern=TRUE)) character(0) > try(system("convert tmp/4t9bp1292406121.ps tmp/4t9bp1292406121.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.874 0.734 4.064