R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 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(9.1 + ,4.5 + ,1.0 + ,-1.0 + ,1989.3 + ,9.0 + ,4.3 + ,1.0 + ,3.0 + ,2097.8 + ,9.0 + ,4.3 + ,1.3 + ,2.0 + ,2154.9 + ,8.9 + ,4.2 + ,1.1 + ,3.0 + ,2152.2 + ,8.8 + ,4.0 + ,0.8 + ,5.0 + ,2250.3 + ,8.7 + ,3.8 + ,0.7 + ,5.0 + ,2346.9 + ,8.5 + ,4.1 + ,0.7 + ,3.0 + ,2525.6 + ,8.3 + ,4.2 + ,0.9 + ,2.0 + ,2409.4 + ,8.1 + ,4.0 + ,1.3 + ,1.0 + ,2394.4 + ,7.9 + ,4.3 + ,1.4 + ,-4.0 + ,2401.3 + ,7.8 + ,4.7 + ,1.6 + ,1.0 + ,2354.3 + ,7.6 + ,5.0 + ,2.1 + ,1.0 + ,2450.4 + ,7.4 + ,5.1 + ,0.3 + ,6.0 + ,2504.7 + ,7.2 + ,5.4 + ,2.1 + ,3.0 + ,2661.4 + ,7.0 + ,5.4 + ,2.5 + ,2.0 + ,2880.4 + ,7.0 + ,5.4 + ,2.3 + ,2.0 + ,3064.4 + ,6.8 + ,5.5 + ,2.4 + ,2.0 + ,3141.1 + ,6.8 + ,5.8 + ,3.0 + ,-8.0 + ,3327.7 + ,6.7 + ,5.7 + ,1.7 + ,0.0 + ,3565.0 + ,6.8 + ,5.5 + ,3.5 + ,-2.0 + ,3403.1 + ,6.7 + ,5.6 + ,4.0 + ,3.0 + ,3149.9 + ,6.7 + ,5.6 + ,3.7 + ,5.0 + ,3006.8 + ,6.7 + ,5.5 + ,3.7 + ,8.0 + ,3230.7 + ,6.5 + ,5.5 + ,3.0 + ,8.0 + ,3361.1 + ,6.3 + ,5.7 + ,2.7 + ,9.0 + ,3484.7 + ,6.3 + 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,7.2 + ,4.0 + ,1.3 + ,-2.0 + ,3161.7 + ,7.0 + ,4.1 + ,1.2 + ,-2.0 + ,3257.2 + ,7.0 + ,4.2 + ,1.4 + ,-2.0 + ,3277.0 + ,7.2 + ,4.5 + ,2.2 + ,2.0 + ,3295.3 + ,7.2 + ,4.6 + ,2.9 + ,1.0 + ,3364.0 + ,7.2 + ,4.5 + ,3.1 + ,-8.0 + ,3494.2 + ,7.0 + ,4.5 + ,3.5 + ,-1.0 + ,3667.0 + ,6.9 + ,4.5 + ,3.6 + ,1.0 + ,3813.1 + ,6.8 + ,4.4 + ,4.4 + ,-1.0 + ,3918.0 + ,6.8 + ,4.3 + ,4.1 + ,2.0 + ,3895.5 + ,6.8 + ,4.5 + ,5.1 + ,2.0 + ,3801.1 + ,6.9 + ,4.1 + ,5.8 + ,1.0 + ,3570.1 + ,7.2 + ,4.1 + ,5.9 + ,-1.0 + ,3701.6 + ,7.2 + ,4.3 + ,5.4 + ,-2.0 + ,3862.3 + ,7.2 + ,4.4 + ,5.5 + ,-2.0 + ,3970.1 + ,7.1 + ,4.7 + ,4.8 + ,-1.0 + ,4138.5 + ,7.2 + ,5.0 + ,3.2 + ,-8.0 + ,4199.8 + ,7.3 + ,4.7 + ,2.7 + ,-4.0 + ,4290.9 + ,7.5 + ,4.5 + ,2.1 + ,-6.0 + ,4443.9 + ,7.6 + ,4.5 + ,1.9 + ,-3.0 + ,4502.6 + ,7.7 + ,4.5 + ,0.6 + ,-3.0 + ,4357.0 + ,7.7 + ,5.5 + ,0.7 + ,-7.0 + ,4591.3 + ,7.7 + ,4.5 + ,-0.2 + ,-9.0 + ,4697.0 + ,7.8 + ,4.4 + ,-1.0 + ,-11.0 + ,4621.4 + ,8.0 + ,4.2 + ,-1.7 + ,-13.0 + ,4562.8 + ,8.1 + ,3.9 + ,-0.7 + ,-11.0 + ,4202.5 + ,8.1 + ,3.9 + ,-1.0 + ,-9.0 + ,4296.5 + ,8.0 + ,4.2 + ,-0.9 + ,-17.0 + ,4435.2 + ,8.1 + ,4.0 + ,0.0 + ,-22.0 + ,4105.2 + ,8.2 + ,3.8 + ,0.3 + ,-25.0 + ,4116.7 + ,8.3 + ,3.7 + ,0.8 + ,-20.0 + ,3844.5 + ,8.4 + ,3.7 + ,0.8 + ,-24.0 + ,3721.0 + ,8.4 + ,3.7 + ,1.9 + ,-24.0 + ,3674.4 + ,8.4 + ,3.7 + ,2.1 + ,-22.0 + ,3857.6 + ,8.5 + ,3.7 + ,2.5 + ,-19.0 + ,3801.1 + ,8.5 + ,3.8 + ,2.7 + ,-18.0 + ,3504.4 + ,8.6 + ,3.7 + ,2.4 + ,-17.0 + ,3032.6 + ,8.6 + ,3.5 + ,2.4 + ,-11.0 + ,3047.0 + ,8.5 + ,3.5 + ,2.9 + ,-11.0 + ,2962.3 + ,8.5 + ,3.1 + ,3.1 + ,-12.0 + ,2197.8) + ,dim=c(5 + ,142) + ,dimnames=list(c('Werkloosheid' + ,'rente' + ,'inflatie' + ,'consumer' + ,'Bel20') + ,1:142)) > y <- array(NA,dim=c(5,142),dimnames=list(c('Werkloosheid','rente','inflatie','consumer','Bel20'),1:142)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par2 = 'No' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(rpart) > library(partykit) Loading required package: grid Loading required package: mvtnorm > par1 <- as.numeric(par1) > autoprune <- function ( tree, method='Minimum CV'){ + xerr <- tree$cptable[,'xerror'] + cpmin.id <- which.min(xerr) + if (method == 'Minimum CV Error plus 1 SD'){ + xstd <- tree$cptable[,'xstd'] + errt <- xerr[cpmin.id] + xstd[cpmin.id] + cpSE1.min <- which.min( errt < xerr ) + mycp <- (tree$cptable[,'CP'])[cpSE1.min] + } + if (method == 'Minimum CV') { + mycp <- (tree$cptable[,'CP'])[cpmin.id] + } + return (mycp) + } > conf.multi.mat <- function(true, new) + { + if ( all( is.na(match( levels(true),levels(new) ) )) ) + stop ( 'conflict of vector levels') + multi.t <- list() + for (mylev in levels(true) ) { + true.tmp <- true + new.tmp <- new + left.lev <- levels (true.tmp)[- match(mylev,levels(true) ) ] + levels(true.tmp) <- list ( mylev = mylev, all = left.lev ) + levels(new.tmp) <- list ( mylev = mylev, all = left.lev ) + curr.t <- conf.mat ( true.tmp , new.tmp ) + multi.t[[mylev]] <- curr.t + multi.t[[mylev]]$precision <- + round( curr.t$conf[1,1] / sum( curr.t$conf[1,] ), 2 ) + } + return (multi.t) + } > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > m <- rpart(as.data.frame(x1)) > par2 [1] "No" > if (par2 != 'No') { + mincp <- autoprune(m,method=par2) + print(mincp) + m <- prune(m,cp=mincp) + } > m$cptable CP nsplit rel error xerror xstd 1 0.46342707 0 1.0000000 1.0097373 0.08914323 2 0.11615138 1 0.5365729 0.5808614 0.08342364 3 0.10928640 2 0.4204216 0.5723365 0.08824364 4 0.09321131 3 0.3111351 0.5052046 0.08345345 5 0.02887390 4 0.2179238 0.3142595 0.05538650 6 0.02237926 5 0.1890499 0.2906437 0.04784444 7 0.01093358 6 0.1666707 0.2429473 0.04530050 8 0.01000000 7 0.1557371 0.2425865 0.04532449 > postscript(file="/var/www/html/rcomp/tmp/1xtcf1293225124.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(as.party(m),tp_args=list(id=FALSE)) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2xtcf1293225124.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plotcp(m) > dev.off() null device 1 > cbind(y=m$y,pred=predict(m),res=residuals(m)) y pred res 1 9.1 7.731579 1.36842105 2 9.0 8.587500 0.41250000 3 9.0 8.587500 0.41250000 4 8.9 8.587500 0.31250000 5 8.8 8.587500 0.21250000 6 8.7 8.587500 0.11250000 7 8.5 8.150000 0.35000000 8 8.3 8.150000 0.15000000 9 8.1 8.150000 -0.05000000 10 7.9 8.150000 -0.25000000 11 7.8 7.731579 0.06842105 12 7.6 7.187500 0.41250000 13 7.4 7.731579 -0.33157895 14 7.2 6.709524 0.49047619 15 7.0 6.709524 0.29047619 16 7.0 6.709524 0.29047619 17 6.8 6.709524 0.09047619 18 6.8 6.709524 0.09047619 19 6.7 7.731579 -1.03157895 20 6.8 6.709524 0.09047619 21 6.7 6.709524 -0.00952381 22 6.7 6.709524 -0.00952381 23 6.7 6.709524 -0.00952381 24 6.5 6.709524 -0.20952381 25 6.3 6.709524 -0.40952381 26 6.3 6.709524 -0.40952381 27 6.3 6.709524 -0.40952381 28 6.5 6.709524 -0.20952381 29 6.6 6.709524 -0.10952381 30 6.5 6.709524 -0.20952381 31 6.3 6.709524 -0.40952381 32 6.3 7.187500 -0.88750000 33 6.5 6.709524 -0.20952381 34 7.0 6.709524 0.29047619 35 7.1 6.709524 0.39047619 36 7.3 6.709524 0.59047619 37 7.3 7.187500 0.11250000 38 7.4 7.187500 0.21250000 39 7.4 7.187500 0.21250000 40 7.3 7.731579 -0.43157895 41 7.4 7.731579 -0.33157895 42 7.5 7.731579 -0.23157895 43 7.7 7.731579 -0.03157895 44 7.7 7.731579 -0.03157895 45 7.7 7.731579 -0.03157895 46 7.7 7.731579 -0.03157895 47 7.7 7.731579 -0.03157895 48 7.8 7.731579 0.06842105 49 8.0 7.731579 0.26842105 50 8.1 8.150000 -0.05000000 51 8.1 7.731579 0.36842105 52 8.2 7.731579 0.46842105 53 8.2 8.150000 0.05000000 54 8.2 8.150000 0.05000000 55 8.1 8.150000 -0.05000000 56 8.1 8.150000 -0.05000000 57 8.2 8.150000 0.05000000 58 8.3 8.472727 -0.17272727 59 8.3 8.150000 0.15000000 60 8.4 8.150000 0.25000000 61 8.5 8.150000 0.35000000 62 8.5 8.150000 0.35000000 63 8.4 8.150000 0.25000000 64 8.0 8.150000 -0.15000000 65 7.9 8.150000 -0.25000000 66 8.1 8.150000 -0.05000000 67 8.5 8.587500 -0.08750000 68 8.8 8.587500 0.21250000 69 8.8 8.587500 0.21250000 70 8.6 8.587500 0.01250000 71 8.3 8.587500 -0.28750000 72 8.3 8.587500 -0.28750000 73 8.3 8.587500 -0.28750000 74 8.4 8.587500 -0.18750000 75 8.4 8.587500 -0.18750000 76 8.5 8.587500 -0.08750000 77 8.6 8.587500 0.01250000 78 8.6 8.587500 0.01250000 79 8.6 8.587500 0.01250000 80 8.6 8.587500 0.01250000 81 8.6 8.587500 0.01250000 82 8.5 8.587500 -0.08750000 83 8.4 8.587500 -0.18750000 84 8.4 8.587500 -0.18750000 85 8.4 8.472727 -0.07272727 86 8.5 8.472727 0.02727273 87 8.5 8.472727 0.02727273 88 8.6 8.472727 0.12727273 89 8.6 8.472727 0.12727273 90 8.4 8.472727 -0.07272727 91 8.2 8.472727 -0.27272727 92 8.0 8.150000 -0.15000000 93 8.0 8.150000 -0.15000000 94 8.0 8.150000 -0.15000000 95 8.0 8.150000 -0.15000000 96 7.9 8.150000 -0.25000000 97 7.9 8.150000 -0.25000000 98 7.8 7.136364 0.66363636 99 7.8 8.150000 -0.35000000 100 8.0 8.150000 -0.15000000 101 7.8 8.150000 -0.35000000 102 7.4 7.136364 0.26363636 103 7.2 7.136364 0.06363636 104 7.0 7.136364 -0.13636364 105 7.0 7.136364 -0.13636364 106 7.2 7.187500 0.01250000 107 7.2 7.187500 0.01250000 108 7.2 7.187500 0.01250000 109 7.0 7.187500 -0.18750000 110 6.9 7.187500 -0.28750000 111 6.8 7.136364 -0.33636364 112 6.8 7.136364 -0.33636364 113 6.8 7.187500 -0.38750000 114 6.9 7.136364 -0.23636364 115 7.2 7.136364 0.06363636 116 7.2 7.136364 0.06363636 117 7.2 7.136364 0.06363636 118 7.1 7.187500 -0.08750000 119 7.2 7.187500 0.01250000 120 7.3 7.187500 0.11250000 121 7.5 7.187500 0.31250000 122 7.6 7.187500 0.41250000 123 7.7 7.731579 -0.03157895 124 7.7 7.731579 -0.03157895 125 7.7 7.731579 -0.03157895 126 7.8 8.150000 -0.35000000 127 8.0 8.150000 -0.15000000 128 8.1 8.150000 -0.05000000 129 8.1 8.150000 -0.05000000 130 8.0 8.150000 -0.15000000 131 8.1 8.150000 -0.05000000 132 8.2 8.150000 0.05000000 133 8.3 8.150000 0.15000000 134 8.4 8.150000 0.25000000 135 8.4 8.150000 0.25000000 136 8.4 8.150000 0.25000000 137 8.5 8.150000 0.35000000 138 8.5 8.150000 0.35000000 139 8.6 8.472727 0.12727273 140 8.6 8.472727 0.12727273 141 8.5 8.472727 0.02727273 142 8.5 8.587500 -0.08750000 > myr <- residuals(m) > myp <- predict(m) > postscript(file="/var/www/html/rcomp/tmp/3xtcf1293225124.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow=c(2,2)) > plot(myr,ylab='residuals') > plot(density(myr),main='Residual Kernel Density') > plot(myp,myr,xlab='predicted',ylab='residuals',main='Predicted vs Residuals') > plot(density(myp),main='Prediction Kernel Density') > par(op) > dev.off() null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Model Performance',6,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'#',header=TRUE) > a<-table.element(a,'Complexity',header=TRUE) > a<-table.element(a,'split',header=TRUE) > a<-table.element(a,'relative error',header=TRUE) > a<-table.element(a,'CV error',header=TRUE) > a<-table.element(a,'CV S.D.',header=TRUE) > a<-table.row.end(a) > for (i in 1:length(m$cptable[,1])) { + a<-table.row.start(a) + a<-table.element(a,i,header=TRUE) + a<-table.element(a,round(m$cptable[i,'CP'],3)) + a<-table.element(a,m$cptable[i,'nsplit']) + a<-table.element(a,round(m$cptable[i,'rel error'],3)) + a<-table.element(a,round(m$cptable[i,'xerror'],3)) + a<-table.element(a,round(m$cptable[i,'xstd'],3)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/4t3s61293225124.tab") > > try(system("convert tmp/1xtcf1293225124.ps tmp/1xtcf1293225124.png",intern=TRUE)) character(0) > try(system("convert tmp/2xtcf1293225124.ps tmp/2xtcf1293225124.png",intern=TRUE)) character(0) > try(system("convert tmp/3xtcf1293225124.ps tmp/3xtcf1293225124.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.533 0.562 3.413