R version 2.12.0 (2010-10-15) Copyright (C) 2010 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(1221.53 + ,2617.2 + ,10168.52 + ,6957.61 + ,23448.78 + ,1180.55 + ,2506.13 + ,9937.04 + ,6688.49 + ,23007.99 + ,1183.26 + ,2679.07 + ,9202.45 + ,6601.37 + ,23096.32 + ,1141.2 + ,2589.73 + ,9369.35 + ,6229.02 + ,22358.17 + ,1049.33 + ,2457.46 + ,8824.06 + ,5925.22 + ,20536.49 + ,1101.6 + ,2517.3 + ,9537.3 + ,6147.97 + ,21029.81 + ,1030.71 + ,2386.53 + ,9382.64 + ,5965.52 + ,20128.99 + ,1089.41 + ,2453.37 + ,9768.7 + ,5964.33 + ,19765.19 + ,1186.69 + ,2529.66 + ,11057.4 + ,6135.7 + ,21108.59 + ,1169.43 + ,2475.14 + ,11089.94 + ,6153.55 + ,21239.35 + ,1104.49 + ,2525.93 + ,10126.03 + ,5598.46 + ,20608.7 + ,1073.87 + ,2480.93 + ,10198.04 + ,5608.79 + ,20121.99 + ,1115.1 + ,2229.85 + ,10546.44 + ,5957.43 + ,21872.5 + ,1095.63 + ,2169.14 + ,9345.55 + ,5625.95 + ,21821.5 + ,1036.19 + ,2030.98 + ,10034.74 + ,5414.96 + ,21752.87 + ,1057.08 + ,2071.37 + ,10133.23 + ,5675.16 + ,20955.25 + ,1020.62 + ,1953.35 + ,10492.53 + ,5458.04 + ,19724.19 + ,987.48 + ,1748.74 + ,10356.83 + ,5332.14 + ,20573.33 + ,919.32 + ,1696.58 + ,9958.44 + ,4808.64 + ,18378.73 + ,919.14 + ,1900.09 + ,9522.5 + ,4940.82 + ,18171 + ,872.81 + ,1908.64 + ,8828.26 + ,4769.45 + ,15520.99 + ,797.87 + ,1881.46 + ,8109.53 + ,4084.76 + ,13576.02 + ,735.09 + ,2100.18 + ,7568.42 + ,3843.74 + ,12811.57 + ,825.88 + ,2672.2 + ,7994.05 + ,4338.35 + ,13278.21 + ,903.25 + ,3136 + ,8859.56 + ,4810.2 + ,14387.48 + ,896.24 + ,2994.38 + ,8512.27 + ,4669.44 + ,13888.24 + ,968.75 + ,3168.22 + ,8576.98 + ,4987.97 + ,13968.67 + ,1166.36 + ,3751.41 + ,11259.86 + ,5831.02 + ,18016.21 + ,1282.83 + ,3925.43 + ,13072.87 + ,6422.3 + ,21261.89 + ,1267.38 + ,3719.52 + ,13376.81 + ,6479.56 + ,22731.1 + ,1280 + ,3757.12 + ,13481.38 + ,6418.32 + ,22102.01 + ,1400.38 + ,3722.23 + ,14338.54 + ,7096.79 + ,24533.12 + ,1385.59 + ,4127.47 + ,13849.99 + ,6948.82 + ,25755.35 + ,1322.7 + ,4162.5 + ,12525.54 + ,6534.97 + ,22849.2 + ,1330.63 + ,4441.82 + ,13603.02 + ,6748.13 + ,24331.67 + ,1378.55 + ,4325.29 + ,13592.47 + ,6851.75 + ,23455.74 + ,1468.36 + ,4350.83 + ,15307.78 + ,8067.32 + ,27812.65 + ,1481.14 + ,4384.47 + ,15680.67 + ,7870.52 + ,28643.61 + ,1549.38 + ,4639.4 + ,16737.63 + ,8019.22 + ,31352.58 + ,1526.75 + ,4697.86 + ,16785.69 + ,7861.51 + ,27142.47 + ,1473.99 + ,4614.76 + ,16569.09 + ,7638.17 + ,23984.14 + ,1455.27 + ,4471.65 + ,17248.89 + ,7584.14 + ,23184.94 + ,1503.35 + ,4305.23 + ,18138.36 + ,8007.32 + ,21772.73 + ,1530.62 + ,4433.57 + ,17875.75 + ,7883.04 + ,20634.47 + ,1482.37 + ,4388.53 + ,17400.41 + ,7408.87 + ,20318.98 + ,1420.86 + ,4140.3 + ,17287.65 + ,6917.03 + ,19800.93 + ,1406.82 + ,4144.38 + ,17604.12 + ,6715.44 + ,19651.51 + ,1438.24 + ,4070.78 + ,17383.42 + ,6789.11 + ,20106.42 + ,1418.3 + ,3906.01 + ,17225.83 + ,6596.92 + ,19964.72 + ,1400.63 + ,3795.91 + ,16274.33 + ,6309.19 + ,18960.48 + ,1377.94 + ,3703.32 + ,16399.39 + ,6268.92 + ,18324.35 + ,1335.85 + ,3675.8 + ,16127.58 + ,6004.33 + ,17543.05 + ,1303.82 + ,3911.06 + ,16140.76 + ,5859.57 + ,17392.27 + ,1276.66 + ,3912.28 + ,15456.81 + ,5681.97 + ,16971.34 + ,1270.2 + ,3839.25 + ,15505.18 + ,5683.31 + ,16267.62 + ,1270.09 + ,3744.63 + ,15467.33 + ,5692.86 + ,15857.89 + ,1310.61 + ,3549.25 + ,16906.23 + ,6009.89 + ,16661.3 + ,1294.87 + ,3394.14 + ,17059.66 + ,5970.08 + ,15805.04 + ,1280.66 + ,3264.26 + ,16205.43 + ,5796.04 + ,15918.48 + ,1280.08 + ,3328.8 + ,16649.82 + ,5674.15 + ,15753.14 + ,1248.29 + ,3223.98 + ,16111.43 + ,5408.26 + ,14876.43 + ,1249.48 + ,3228.01 + ,14872.15 + ,5193.4 + ,14937.14 + ,1207.01 + ,3112.83 + ,13606.5 + ,4929.07 + ,14386.37 + ,1228.81 + ,3051.67 + ,13574.3 + ,5044.12 + ,15428.52 + ,1220.33 + ,3039.71 + ,12413.6 + ,4829.69 + ,14903.55 + ,1234.18 + ,3125.67 + ,11899.6 + ,4886.5 + ,14880.98 + ,1191.33 + ,3106.54 + ,11584.01 + ,4586.28 + ,14201.06 + ,1191.5 + ,11276.59 + ,4460.63 + ,13867.07 + ,1156.85 + ,11008.9 + ,4184.84 + ,13908.97 + ,1180.59 + ,11668.95 + ,4348.77 + ,13516.88 + ,1203.6 + ,11740.6 + ,4350.49 + ,14195.35 + ,1181.27 + ,11387.59 + ,4254.85 + ,13721.69) + ,dim=c(5 + ,72) + ,dimnames=list(c('S&P' + ,'Bel20' + ,'Nikkei' + ,'DAX' + ,'HangSeng') + ,1:72)) > y <- array(NA,dim=c(5,72),dimnames=list(c('S&P','Bel20','Nikkei','DAX','HangSeng'),1:72)) > 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 = '5' > par2 = 'quantiles' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "S.P" > x[,par1] [1] 1221.53 1180.55 1183.26 1141.20 1049.33 1101.60 1030.71 1089.41 [9] 1186.69 1169.43 1104.49 1073.87 1115.10 1095.63 1036.19 1057.08 [17] 1020.62 987.48 919.32 919.14 872.81 797.87 735.09 825.88 [25] 903.25 896.24 968.75 1166.36 1282.83 1267.38 1280.00 1400.38 [33] 1385.59 1322.70 1330.63 1378.55 1468.36 1481.14 1549.38 1526.75 [41] 1473.99 1455.27 1503.35 1530.62 1482.37 1420.86 1406.82 1438.24 [49] 1418.30 1400.63 1377.94 1335.85 1303.82 1276.66 1270.20 1270.09 [57] 1310.61 1294.87 1280.66 1280.08 1248.29 1249.48 1207.01 1228.81 [65] 1220.33 1234.18 1191.33 1191.50 11008.90 4348.77 14195.35 1221.53 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) [ 735, 1074) [1074, 1207) [1207, 1283) [1283, 1421) [1421,14195] 15 14 15 14 14 > colnames(x) [1] "S.P" "Bel20" "Nikkei" "DAX" "HangSeng" > colnames(x)[par1] [1] "S.P" > x[,par1] [1] [1207, 1283) [1074, 1207) [1074, 1207) [1074, 1207) [ 735, 1074) [6] [1074, 1207) [ 735, 1074) [1074, 1207) [1074, 1207) [1074, 1207) [11] [1074, 1207) [1074, 1207) [1074, 1207) [1074, 1207) [ 735, 1074) [16] [ 735, 1074) [ 735, 1074) [ 735, 1074) [ 735, 1074) [ 735, 1074) [21] [ 735, 1074) [ 735, 1074) [ 735, 1074) [ 735, 1074) [ 735, 1074) [26] [ 735, 1074) [ 735, 1074) [1074, 1207) [1283, 1421) [1207, 1283) [31] [1207, 1283) [1283, 1421) [1283, 1421) [1283, 1421) [1283, 1421) [36] [1283, 1421) [1421,14195] [1421,14195] [1421,14195] [1421,14195] [41] [1421,14195] [1421,14195] [1421,14195] [1421,14195] [1421,14195] [46] [1421,14195] [1283, 1421) [1421,14195] [1283, 1421) [1283, 1421) [51] [1283, 1421) [1283, 1421) [1283, 1421) [1207, 1283) [1207, 1283) [56] [1207, 1283) [1283, 1421) [1283, 1421) [1207, 1283) [1207, 1283) [61] [1207, 1283) [1207, 1283) [1207, 1283) [1207, 1283) [1207, 1283) [66] [1207, 1283) [1074, 1207) [1074, 1207) [1421,14195] [1421,14195] [71] [1421,14195] [1207, 1283) Levels: [ 735, 1074) [1074, 1207) [1207, 1283) [1283, 1421) [1421,14195] > 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/1aqns1293227956.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 3 4 5 1 121 13 1 0 0 2 63 53 7 1 0 3 12 15 89 20 0 4 0 0 29 57 46 5 10 7 0 1 100 [1] 0.8962963 [1] 0.4274194 [1] 0.6544118 [1] 0.4318182 [1] 0.8474576 [1] 0.6511628 m.ct.x.pred m.ct.x.actu 1 2 3 4 5 1 11 3 1 0 0 2 9 4 3 0 0 3 0 1 6 7 0 4 0 0 1 5 2 5 0 1 2 1 18 [1] 0.7333333 [1] 0.25 [1] 0.4285714 [1] 0.625 [1] 0.8181818 [1] 0.5866667 > m Conditional inference tree with 7 terminal nodes Response: as.factor(S.P) Inputs: Bel20, Nikkei, DAX, HangSeng Number of observations: 72 1) Nikkei <= 10492.53; criterion = 1, statistic = 39.742 2) Nikkei <= 10034.74; criterion = 0.996, statistic = 16.437 3) Nikkei <= 8859.56; criterion = 0.992, statistic = 12.482 4)* weights = 10 3) Nikkei > 8859.56 5)* weights = 10 2) Nikkei > 10034.74 6)* weights = 7 1) Nikkei > 10492.53 7) Nikkei <= 11899.6; criterion = 1, statistic = 21.089 8)* weights = 7 7) Nikkei > 11899.6 9) Bel20 <= 4162.5; criterion = 1, statistic = 24.473 10) DAX <= 5796.04; criterion = 0.995, statistic = 13.318 11)* weights = 10 10) DAX > 5796.04 12)* weights = 16 9) Bel20 > 4162.5 13)* weights = 12 > postscript(file="/var/www/rcomp/tmp/2aqns1293227956.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/3aqns1293227956.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,] 3 1 [2,] 2 2 [3,] 2 2 [4,] 2 2 [5,] 1 1 [6,] 2 2 [7,] 1 2 [8,] 2 2 [9,] 2 2 [10,] 2 2 [11,] 2 1 [12,] 2 1 [13,] 2 2 [14,] 2 2 [15,] 1 2 [16,] 1 1 [17,] 1 1 [18,] 1 1 [19,] 1 2 [20,] 1 2 [21,] 1 1 [22,] 1 1 [23,] 1 1 [24,] 1 1 [25,] 1 1 [26,] 1 1 [27,] 1 1 [28,] 2 2 [29,] 4 4 [30,] 3 4 [31,] 3 4 [32,] 4 4 [33,] 4 4 [34,] 4 4 [35,] 4 5 [36,] 4 5 [37,] 5 5 [38,] 5 5 [39,] 5 5 [40,] 5 5 [41,] 5 5 [42,] 5 5 [43,] 5 5 [44,] 5 5 [45,] 5 5 [46,] 5 4 [47,] 4 4 [48,] 5 4 [49,] 4 4 [50,] 4 4 [51,] 4 4 [52,] 4 4 [53,] 4 4 [54,] 3 3 [55,] 3 3 [56,] 3 3 [57,] 4 4 [58,] 4 4 [59,] 3 3 [60,] 3 3 [61,] 3 3 [62,] 3 3 [63,] 3 3 [64,] 3 3 [65,] 3 3 [66,] 3 2 [67,] 2 2 [68,] 2 1 [69,] 5 5 [70,] 5 1 [71,] 5 2 [72,] 3 1 [ 735, 1074) [1074, 1207) [1207, 1283) [1283, 1421) [1421,14195] [ 735, 1074) 11 4 0 0 0 [1074, 1207) 3 11 0 0 0 [1207, 1283) 2 1 10 2 0 [1283, 1421) 0 0 0 12 2 [1421,14195] 1 1 0 2 10 > postscript(file="/var/www/rcomp/tmp/4kz4v1293227956.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/5yr241293227956.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/6ri1o1293227956.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/7u0hu1293227956.tab") + } > > try(system("convert tmp/2aqns1293227956.ps tmp/2aqns1293227956.png",intern=TRUE)) character(0) > try(system("convert tmp/3aqns1293227956.ps tmp/3aqns1293227956.png",intern=TRUE)) character(0) > try(system("convert tmp/4kz4v1293227956.ps tmp/4kz4v1293227956.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.690 0.690 3.357