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.
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 = '2'
> #'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
Personeel omzet t
1 187 408 1
2 2 5 2
3 1 2 3
4 133 250 4
5 10 16 5
6 55 159 6
7 70 336 7
8 46 138 8
9 105 97 9
10 321 1272 10
11 17 88 11
12 104 201 12
13 35 102 13
14 76 127 14
15 103 209 15
16 178 247 16
17 31 145 17
18 1347 3517 18
19 14 27 19
20 91 101 20
21 1 2 21
22 2 5 22
23 65 100 23
24 9 34 24
25 418 1418 25
26 82 206 26
27 117 130 27
28 137 865 28
29 162 229 29
30 1 1 30
31 87 229 31
32 3 17 32
33 16 92 33
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) omzet t
14.8547 0.3507 -0.4333
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-169.09 -13.74 -3.95 25.04 106.50
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 14.8547 20.9845 0.708 0.484
omzet 0.3507 0.0154 22.779 <2e-16 ***
t -0.4334 1.0539 -0.411 0.684
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 57.61 on 30 degrees of freedom
Multiple R-squared: 0.9454, Adjusted R-squared: 0.9417
F-statistic: 259.5 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,] 0.01517502 0.03035003 0.9848250
[2,] 0.05879779 0.11759559 0.9412022
[3,] 0.03049304 0.06098607 0.9695070
[4,] 0.11908740 0.23817481 0.8809126
[5,] 0.19074489 0.38148978 0.8092551
[6,] 0.12685937 0.25371874 0.8731406
[7,] 0.10324716 0.20649432 0.8967528
[8,] 0.06280898 0.12561795 0.9371910
[9,] 0.03916091 0.07832181 0.9608391
[10,] 0.02344988 0.04689977 0.9765501
[11,] 0.04907516 0.09815032 0.9509248
[12,] 0.04616183 0.09232365 0.9538382
[13,] 0.64554181 0.70891639 0.3544582
[14,] 0.55737811 0.88524378 0.4426219
[15,] 0.48750254 0.97500508 0.5124975
[16,] 0.40322107 0.80644214 0.5967789
[17,] 0.33891444 0.67782889 0.6610856
[18,] 0.23585172 0.47170344 0.7641483
[19,] 0.25484187 0.50968374 0.7451581
[20,] 0.50475507 0.99048986 0.4952449
[21,] 0.44745916 0.89491831 0.5525408
[22,] 0.31118946 0.62237892 0.6888105
> postscript(file="/var/wessaorg/rcomp/tmp/1fbpa1322059278.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2c4o11322059278.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3xntv1322059278.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4ya5v1322059278.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/54lm81322059278.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
29.488860 -13.741575 -13.256096 32.201118 -8.299343 -13.017556
7 8 9 10 11 12
-59.659916 -13.785945 60.026523 -135.624633 -23.950389 23.852705
13 14 15 16 17 18
-9.993636 22.671957 21.347068 83.453428 -27.340782 106.497717
19 20 21 22 23 24
-2.090280 49.390512 -5.455828 -5.074611 25.041267 -7.378510
25 26 27 28 29 30
-83.328101 6.166029 68.253354 -169.085307 79.399739 -1.204984
31 32 33
5.266435 -3.949651 -16.819569
> postscript(file="/var/wessaorg/rcomp/tmp/69p9k1322059278.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 29.488860 NA
1 -13.741575 29.488860
2 -13.256096 -13.741575
3 32.201118 -13.256096
4 -8.299343 32.201118
5 -13.017556 -8.299343
6 -59.659916 -13.017556
7 -13.785945 -59.659916
8 60.026523 -13.785945
9 -135.624633 60.026523
10 -23.950389 -135.624633
11 23.852705 -23.950389
12 -9.993636 23.852705
13 22.671957 -9.993636
14 21.347068 22.671957
15 83.453428 21.347068
16 -27.340782 83.453428
17 106.497717 -27.340782
18 -2.090280 106.497717
19 49.390512 -2.090280
20 -5.455828 49.390512
21 -5.074611 -5.455828
22 25.041267 -5.074611
23 -7.378510 25.041267
24 -83.328101 -7.378510
25 6.166029 -83.328101
26 68.253354 6.166029
27 -169.085307 68.253354
28 79.399739 -169.085307
29 -1.204984 79.399739
30 5.266435 -1.204984
31 -3.949651 5.266435
32 -16.819569 -3.949651
33 NA -16.819569
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -13.741575 29.488860
[2,] -13.256096 -13.741575
[3,] 32.201118 -13.256096
[4,] -8.299343 32.201118
[5,] -13.017556 -8.299343
[6,] -59.659916 -13.017556
[7,] -13.785945 -59.659916
[8,] 60.026523 -13.785945
[9,] -135.624633 60.026523
[10,] -23.950389 -135.624633
[11,] 23.852705 -23.950389
[12,] -9.993636 23.852705
[13,] 22.671957 -9.993636
[14,] 21.347068 22.671957
[15,] 83.453428 21.347068
[16,] -27.340782 83.453428
[17,] 106.497717 -27.340782
[18,] -2.090280 106.497717
[19,] 49.390512 -2.090280
[20,] -5.455828 49.390512
[21,] -5.074611 -5.455828
[22,] 25.041267 -5.074611
[23,] -7.378510 25.041267
[24,] -83.328101 -7.378510
[25,] 6.166029 -83.328101
[26,] 68.253354 6.166029
[27,] -169.085307 68.253354
[28,] 79.399739 -169.085307
[29,] -1.204984 79.399739
[30,] 5.266435 -1.204984
[31,] -3.949651 5.266435
[32,] -16.819569 -3.949651
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -13.741575 29.488860
2 -13.256096 -13.741575
3 32.201118 -13.256096
4 -8.299343 32.201118
5 -13.017556 -8.299343
6 -59.659916 -13.017556
7 -13.785945 -59.659916
8 60.026523 -13.785945
9 -135.624633 60.026523
10 -23.950389 -135.624633
11 23.852705 -23.950389
12 -9.993636 23.852705
13 22.671957 -9.993636
14 21.347068 22.671957
15 83.453428 21.347068
16 -27.340782 83.453428
17 106.497717 -27.340782
18 -2.090280 106.497717
19 49.390512 -2.090280
20 -5.455828 49.390512
21 -5.074611 -5.455828
22 25.041267 -5.074611
23 -7.378510 25.041267
24 -83.328101 -7.378510
25 6.166029 -83.328101
26 68.253354 6.166029
27 -169.085307 68.253354
28 79.399739 -169.085307
29 -1.204984 79.399739
30 5.266435 -1.204984
31 -3.949651 5.266435
32 -16.819569 -3.949651
> 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/7fsi81322059278.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/83oqi1322059278.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/90ftd1322059278.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10khfh1322059278.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1159d31322059278.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/12jizn1322059279.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/134lwd1322059279.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/14a6yq1322059279.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/15ygz21322059279.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/165pk51322059279.tab")
+ }
>
> try(system("convert tmp/1fbpa1322059278.ps tmp/1fbpa1322059278.png",intern=TRUE))
character(0)
> try(system("convert tmp/2c4o11322059278.ps tmp/2c4o11322059278.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xntv1322059278.ps tmp/3xntv1322059278.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ya5v1322059278.ps tmp/4ya5v1322059278.png",intern=TRUE))
character(0)
> try(system("convert tmp/54lm81322059278.ps tmp/54lm81322059278.png",intern=TRUE))
character(0)
> try(system("convert tmp/69p9k1322059278.ps tmp/69p9k1322059278.png",intern=TRUE))
character(0)
> try(system("convert tmp/7fsi81322059278.ps tmp/7fsi81322059278.png",intern=TRUE))
character(0)
> try(system("convert tmp/83oqi1322059278.ps tmp/83oqi1322059278.png",intern=TRUE))
character(0)
> try(system("convert tmp/90ftd1322059278.ps tmp/90ftd1322059278.png",intern=TRUE))
character(0)
> try(system("convert tmp/10khfh1322059278.ps tmp/10khfh1322059278.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.087 0.466 3.590