R version 2.13.0 (2011-04-13)
Copyright (C) 2011 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.
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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
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> x <- array(list(229.00,48856.87,1000300.00,38894.00,53029.88,258291900.00,7544.00,40497.17,36129100.00,2592.00,36596.73,7882600.00,160.00,37061.55,385300.00,2073.00,39840.23,3931000.00,6483.00,50608.69,12657200.00,41.00,119660.32,48774000.00,829.00,76893.41,39529600.00,782.00,52288.86,9918700.00,1524.00,50764.75,9191000.00,7104.00,52145.04,37266300.00,1994.00,52509.60,13025100.00,2670.00,57360.74,11164400.00,973.00,61950.96,21304600.00,4125.00,36467.10,7133000.00,176.00,94484.11,36607100.00,66619.00,38666.46,43485600.00,136486.00,40168.91,356407900.00,18947.00,43649.10,81571400.00,43871.00,54290.36,203647600.00,73668.00,27303.67,71188900.00,44392.00,17743.22,10419300.00,19688.00,48363.52,65421400.00,118074.00,46018.40,79003600.00),dim=c(3,25),dimnames=list(c('#Ondernemingen','Personeelskost','Omzet'),1:25))
> y <- array(NA,dim=c(3,25),dimnames=list(c('#Ondernemingen','Personeelskost','Omzet'),1:25))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No 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
#Ondernemingen Personeelskost Omzet
1 229 48856.87 1000300
2 38894 53029.88 258291900
3 7544 40497.17 36129100
4 2592 36596.73 7882600
5 160 37061.55 385300
6 2073 39840.23 3931000
7 6483 50608.69 12657200
8 41 119660.32 48774000
9 829 76893.41 39529600
10 782 52288.86 9918700
11 1524 50764.75 9191000
12 7104 52145.04 37266300
13 1994 52509.60 13025100
14 2670 57360.74 11164400
15 973 61950.96 21304600
16 4125 36467.10 7133000
17 176 94484.11 36607100
18 66619 38666.46 43485600
19 136486 40168.91 356407900
20 18947 43649.10 81571400
21 43871 54290.36 203647600
22 73668 27303.67 71188900
23 44392 17743.22 10419300
24 19688 48363.52 65421400
25 118074 46018.40 79003600
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Personeelskost Omzet
3.658e+04 -5.825e-01 2.930e-04
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-42481 -13305 -7892 7904 85148
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.658e+04 1.459e+04 2.508 0.020 *
Personeelskost -5.825e-01 2.561e-01 -2.274 0.033 *
Omzet 2.930e-04 6.089e-05 4.812 8.31e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 26030 on 22 degrees of freedom
Multiple R-squared: 0.5666, Adjusted R-squared: 0.5272
F-statistic: 14.38 on 2 and 22 DF, p-value: 0.0001012
> 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
+ }
> postscript(file="/var/wessaorg/rcomp/tmp/1tg3g1321714524.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/22cjz1321714524.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3cvd11321714524.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4r3z21321714524.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5q1xy1321714524.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 = 25
Frequency = 1
1 2 3 4 5 6 7
-8187.202 -42481.117 -16034.775 -14982.147 -14946.595 -12453.990 -4328.410
8 9 10 11 12 13 14
18868.449 -2545.905 -8248.322 -8180.867 -10023.281 -7817.958 -3771.034
15 16 17 18 19 20 21
-5765.505 -13305.013 7903.740 39818.319 18870.357 -16110.981 -20758.449
22 23 24 25
32131.255 15092.684 -7891.752 85148.498
> postscript(file="/var/wessaorg/rcomp/tmp/64pci1321714524.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 = 25
Frequency = 1
lag(myerror, k = 1) myerror
0 -8187.202 NA
1 -42481.117 -8187.202
2 -16034.775 -42481.117
3 -14982.147 -16034.775
4 -14946.595 -14982.147
5 -12453.990 -14946.595
6 -4328.410 -12453.990
7 18868.449 -4328.410
8 -2545.905 18868.449
9 -8248.322 -2545.905
10 -8180.867 -8248.322
11 -10023.281 -8180.867
12 -7817.958 -10023.281
13 -3771.034 -7817.958
14 -5765.505 -3771.034
15 -13305.013 -5765.505
16 7903.740 -13305.013
17 39818.319 7903.740
18 18870.357 39818.319
19 -16110.981 18870.357
20 -20758.449 -16110.981
21 32131.255 -20758.449
22 15092.684 32131.255
23 -7891.752 15092.684
24 85148.498 -7891.752
25 NA 85148.498
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -42481.117 -8187.202
[2,] -16034.775 -42481.117
[3,] -14982.147 -16034.775
[4,] -14946.595 -14982.147
[5,] -12453.990 -14946.595
[6,] -4328.410 -12453.990
[7,] 18868.449 -4328.410
[8,] -2545.905 18868.449
[9,] -8248.322 -2545.905
[10,] -8180.867 -8248.322
[11,] -10023.281 -8180.867
[12,] -7817.958 -10023.281
[13,] -3771.034 -7817.958
[14,] -5765.505 -3771.034
[15,] -13305.013 -5765.505
[16,] 7903.740 -13305.013
[17,] 39818.319 7903.740
[18,] 18870.357 39818.319
[19,] -16110.981 18870.357
[20,] -20758.449 -16110.981
[21,] 32131.255 -20758.449
[22,] 15092.684 32131.255
[23,] -7891.752 15092.684
[24,] 85148.498 -7891.752
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -42481.117 -8187.202
2 -16034.775 -42481.117
3 -14982.147 -16034.775
4 -14946.595 -14982.147
5 -12453.990 -14946.595
6 -4328.410 -12453.990
7 18868.449 -4328.410
8 -2545.905 18868.449
9 -8248.322 -2545.905
10 -8180.867 -8248.322
11 -10023.281 -8180.867
12 -7817.958 -10023.281
13 -3771.034 -7817.958
14 -5765.505 -3771.034
15 -13305.013 -5765.505
16 7903.740 -13305.013
17 39818.319 7903.740
18 18870.357 39818.319
19 -16110.981 18870.357
20 -20758.449 -16110.981
21 32131.255 -20758.449
22 15092.684 32131.255
23 -7891.752 15092.684
24 85148.498 -7891.752
> 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/wessaorg/rcomp/tmp/7n5mk1321714524.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8nwwg1321714524.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9czxf1321714524.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10cgfo1321714524.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/11csq31321714524.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/wessaorg/rcomp/tmp/12wp5m1321714524.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/wessaorg/rcomp/tmp/13r3lw1321714524.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/wessaorg/rcomp/tmp/14syeg1321714524.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/wessaorg/rcomp/tmp/15401r1321714525.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/wessaorg/rcomp/tmp/16wx791321714525.tab")
+ }
>
> try(system("convert tmp/1tg3g1321714524.ps tmp/1tg3g1321714524.png",intern=TRUE))
character(0)
> try(system("convert tmp/22cjz1321714524.ps tmp/22cjz1321714524.png",intern=TRUE))
character(0)
> try(system("convert tmp/3cvd11321714524.ps tmp/3cvd11321714524.png",intern=TRUE))
character(0)
> try(system("convert tmp/4r3z21321714524.ps tmp/4r3z21321714524.png",intern=TRUE))
character(0)
> try(system("convert tmp/5q1xy1321714524.ps tmp/5q1xy1321714524.png",intern=TRUE))
character(0)
> try(system("convert tmp/64pci1321714524.ps tmp/64pci1321714524.png",intern=TRUE))
character(0)
> try(system("convert tmp/7n5mk1321714524.ps tmp/7n5mk1321714524.png",intern=TRUE))
character(0)
> try(system("convert tmp/8nwwg1321714524.ps tmp/8nwwg1321714524.png",intern=TRUE))
character(0)
> try(system("convert tmp/9czxf1321714524.ps tmp/9czxf1321714524.png",intern=TRUE))
character(0)
> try(system("convert tmp/10cgfo1321714524.ps tmp/10cgfo1321714524.png",intern=TRUE))
convert: unable to open image `tmp/10cgfo1321714524.ps': No such file or directory @ blob.c/OpenBlob/2480.
convert: missing an image filename `tmp/10cgfo1321714524.png' @ convert.c/ConvertImageCommand/2838.
character(0)
Warning message:
running command 'convert tmp/10cgfo1321714524.ps tmp/10cgfo1321714524.png' had status 1
>
>
> proc.time()
user system elapsed
2.488 0.456 2.960