R version 2.12.1 (2010-12-16)
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(408,187,5,2,2,1,250,133,16,10,159,55,336,70,138,46,97,105,1272,321,88,17,201,104,102,35,127,76,209,103,247,178,145,31,3517,1347,27,14,101,91,2,1,5,2,100,65,34,9,1418,418,206,82,130,117,865,137,229,162,1,1,229,87,17,3,92,16),dim=c(2,33),dimnames=list(c('omzet','Personeel'),1:33))
> y <- array(NA,dim=c(2,33),dimnames=list(c('omzet','Personeel'),1:33))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), 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: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> 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]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
omzet Personeel t
1 408 187 1
2 5 2 2
3 2 1 3
4 250 133 4
5 16 10 5
6 159 55 6
7 336 70 7
8 138 46 8
9 97 105 9
10 1272 321 10
11 88 17 11
12 201 104 12
13 102 35 13
14 127 76 14
15 209 103 15
16 247 178 16
17 145 31 17
18 3517 1347 18
19 27 14 19
20 101 91 20
21 2 1 21
22 5 2 22
23 100 65 23
24 34 9 24
25 1418 418 25
26 206 82 26
27 130 117 27
28 865 137 28
29 229 162 29
30 1 1 30
31 229 87 31
32 17 3 32
33 92 16 33
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Personeel t
-24.481 2.696 1.303
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-229.16 -72.88 -8.29 27.41 483.72
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -24.4813 58.4896 -0.419 0.679
Personeel 2.6955 0.1183 22.779 <2e-16 ***
t 1.3026 2.9203 0.446 0.659
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 159.7 on 30 degrees of freedom
Multiple R-squared: 0.9454, Adjusted R-squared: 0.9418
F-statistic: 259.8 on 2 and 30 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.007054435 0.01410887 0.9929456
[2,] 0.036363037 0.07272607 0.9636370
[3,] 0.016754766 0.03350953 0.9832452
[4,] 0.053981379 0.10796276 0.9460186
[5,] 0.483387017 0.96677403 0.5166130
[6,] 0.375770741 0.75154148 0.6242293
[7,] 0.364854122 0.72970824 0.6351459
[8,] 0.269257631 0.53851526 0.7307424
[9,] 0.213632832 0.42726566 0.7863672
[10,] 0.157877784 0.31575557 0.8421222
[11,] 0.247310670 0.49462134 0.7526893
[12,] 0.207318619 0.41463724 0.7926814
[13,] 0.252874188 0.50574838 0.7471258
[14,] 0.176131455 0.35226291 0.8238685
[15,] 0.144920343 0.28984069 0.8550797
[16,] 0.092656378 0.18531276 0.9073436
[17,] 0.055900074 0.11180015 0.9440999
[18,] 0.031292228 0.06258446 0.9687078
[19,] 0.016261739 0.03252348 0.9837383
[20,] 0.024819868 0.04963974 0.9751801
[21,] 0.010754873 0.02150975 0.9892451
[22,] 0.022650312 0.04530062 0.9773497
> postscript(file="/var/www/rcomp/tmp/1u4b11322059986.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2p3pe1322059986.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3sg0h1322059986.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4p7zs1322059986.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5qhdr1322059986.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 33
Frequency = 1
1 2 3 4 5 6
-72.882684 21.485127 19.878081 -89.232529 7.013319 27.412560
7 8 9 10 11 12
162.677266 28.067077 -173.270899 418.195186 52.329345 -70.483067
13 14 15 16 17 18
15.204943 -71.613754 -63.695235 -229.161460 63.776761 -112.824230
19 20 21 22 23 24
-11.004597 -145.861853 -3.568017 -4.566094 -80.686133 2.960176
25 26 27 28 29 30
283.191765 -24.417580 -196.063184 483.723944 -220.966505 -16.291066
31 32 33
-21.407962 -8.287219 30.368518
> postscript(file="/var/www/rcomp/tmp/69t201322059986.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 33
Frequency = 1
lag(myerror, k = 1) myerror
0 -72.882684 NA
1 21.485127 -72.882684
2 19.878081 21.485127
3 -89.232529 19.878081
4 7.013319 -89.232529
5 27.412560 7.013319
6 162.677266 27.412560
7 28.067077 162.677266
8 -173.270899 28.067077
9 418.195186 -173.270899
10 52.329345 418.195186
11 -70.483067 52.329345
12 15.204943 -70.483067
13 -71.613754 15.204943
14 -63.695235 -71.613754
15 -229.161460 -63.695235
16 63.776761 -229.161460
17 -112.824230 63.776761
18 -11.004597 -112.824230
19 -145.861853 -11.004597
20 -3.568017 -145.861853
21 -4.566094 -3.568017
22 -80.686133 -4.566094
23 2.960176 -80.686133
24 283.191765 2.960176
25 -24.417580 283.191765
26 -196.063184 -24.417580
27 483.723944 -196.063184
28 -220.966505 483.723944
29 -16.291066 -220.966505
30 -21.407962 -16.291066
31 -8.287219 -21.407962
32 30.368518 -8.287219
33 NA 30.368518
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 21.485127 -72.882684
[2,] 19.878081 21.485127
[3,] -89.232529 19.878081
[4,] 7.013319 -89.232529
[5,] 27.412560 7.013319
[6,] 162.677266 27.412560
[7,] 28.067077 162.677266
[8,] -173.270899 28.067077
[9,] 418.195186 -173.270899
[10,] 52.329345 418.195186
[11,] -70.483067 52.329345
[12,] 15.204943 -70.483067
[13,] -71.613754 15.204943
[14,] -63.695235 -71.613754
[15,] -229.161460 -63.695235
[16,] 63.776761 -229.161460
[17,] -112.824230 63.776761
[18,] -11.004597 -112.824230
[19,] -145.861853 -11.004597
[20,] -3.568017 -145.861853
[21,] -4.566094 -3.568017
[22,] -80.686133 -4.566094
[23,] 2.960176 -80.686133
[24,] 283.191765 2.960176
[25,] -24.417580 283.191765
[26,] -196.063184 -24.417580
[27,] 483.723944 -196.063184
[28,] -220.966505 483.723944
[29,] -16.291066 -220.966505
[30,] -21.407962 -16.291066
[31,] -8.287219 -21.407962
[32,] 30.368518 -8.287219
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 21.485127 -72.882684
2 19.878081 21.485127
3 -89.232529 19.878081
4 7.013319 -89.232529
5 27.412560 7.013319
6 162.677266 27.412560
7 28.067077 162.677266
8 -173.270899 28.067077
9 418.195186 -173.270899
10 52.329345 418.195186
11 -70.483067 52.329345
12 15.204943 -70.483067
13 -71.613754 15.204943
14 -63.695235 -71.613754
15 -229.161460 -63.695235
16 63.776761 -229.161460
17 -112.824230 63.776761
18 -11.004597 -112.824230
19 -145.861853 -11.004597
20 -3.568017 -145.861853
21 -4.566094 -3.568017
22 -80.686133 -4.566094
23 2.960176 -80.686133
24 283.191765 2.960176
25 -24.417580 283.191765
26 -196.063184 -24.417580
27 483.723944 -196.063184
28 -220.966505 483.723944
29 -16.291066 -220.966505
30 -21.407962 -16.291066
31 -8.287219 -21.407962
32 30.368518 -8.287219
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/75rel1322059987.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8sgnm1322059987.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9lyoa1322059987.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/102dpu1322059987.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/11tqcj1322059987.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/12xbbo1322059987.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/13spg21322059987.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/14ii3o1322059987.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/15aia21322059987.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/16zxpk1322059987.tab")
+ }
>
> try(system("convert tmp/1u4b11322059986.ps tmp/1u4b11322059986.png",intern=TRUE))
character(0)
> try(system("convert tmp/2p3pe1322059986.ps tmp/2p3pe1322059986.png",intern=TRUE))
character(0)
> try(system("convert tmp/3sg0h1322059986.ps tmp/3sg0h1322059986.png",intern=TRUE))
character(0)
> try(system("convert tmp/4p7zs1322059986.ps tmp/4p7zs1322059986.png",intern=TRUE))
character(0)
> try(system("convert tmp/5qhdr1322059986.ps tmp/5qhdr1322059986.png",intern=TRUE))
character(0)
> try(system("convert tmp/69t201322059986.ps tmp/69t201322059986.png",intern=TRUE))
character(0)
> try(system("convert tmp/75rel1322059987.ps tmp/75rel1322059987.png",intern=TRUE))
character(0)
> try(system("convert tmp/8sgnm1322059987.ps tmp/8sgnm1322059987.png",intern=TRUE))
character(0)
> try(system("convert tmp/9lyoa1322059987.ps tmp/9lyoa1322059987.png",intern=TRUE))
character(0)
> try(system("convert tmp/102dpu1322059987.ps tmp/102dpu1322059987.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.876 0.656 4.508