R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(4.803,0,4.672,0,4.560,0,4.289,0,3.961,0,3.943,0,3.932,0,3.816,0,3.834,0,4.130,0,4.467,0,4.447,0,4.683,1,4.441,1,4.465,1,4.187,1,3.991,1,3.816,1,3.903,1,3.784,1,3.817,1,4.189,1,4.345,1,4.183,1),dim=c(2,24),dimnames=list(c('Y','X'),1:24))
> y <- array(NA,dim=c(2,24),dimnames=list(c('Y','X'),1:24))
> 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 = 'Include Monthly 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
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> 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
Y X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 4.803 0 1 0 0 0 0 0 0 0 0 0 0
2 4.672 0 0 1 0 0 0 0 0 0 0 0 0
3 4.560 0 0 0 1 0 0 0 0 0 0 0 0
4 4.289 0 0 0 0 1 0 0 0 0 0 0 0
5 3.961 0 0 0 0 0 1 0 0 0 0 0 0
6 3.943 0 0 0 0 0 0 1 0 0 0 0 0
7 3.932 0 0 0 0 0 0 0 1 0 0 0 0
8 3.816 0 0 0 0 0 0 0 0 1 0 0 0
9 3.834 0 0 0 0 0 0 0 0 0 1 0 0
10 4.130 0 0 0 0 0 0 0 0 0 0 1 0
11 4.467 0 0 0 0 0 0 0 0 0 0 0 1
12 4.447 0 0 0 0 0 0 0 0 0 0 0 0
13 4.683 1 1 0 0 0 0 0 0 0 0 0 0
14 4.441 1 0 1 0 0 0 0 0 0 0 0 0
15 4.465 1 0 0 1 0 0 0 0 0 0 0 0
16 4.187 1 0 0 0 1 0 0 0 0 0 0 0
17 3.991 1 0 0 0 0 1 0 0 0 0 0 0
18 3.816 1 0 0 0 0 0 1 0 0 0 0 0
19 3.903 1 0 0 0 0 0 0 1 0 0 0 0
20 3.784 1 0 0 0 0 0 0 0 1 0 0 0
21 3.817 1 0 0 0 0 0 0 0 0 1 0 0
22 4.189 1 0 0 0 0 0 0 0 0 0 1 0
23 4.345 1 0 0 0 0 0 0 0 0 0 0 1
24 4.183 1 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
4.3588 -0.0875 0.4280 0.2415 0.1975 -0.0770
M5 M6 M7 M8 M9 M10
-0.3390 -0.4355 -0.3975 -0.5150 -0.4895 -0.1555
M11
0.0910
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-8.825e-02 -2.813e-02 -3.946e-17 2.813e-02 8.825e-02
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.35875 0.05025 86.740 < 2e-16 ***
X -0.08750 0.02787 -3.139 0.009423 **
M1 0.42800 0.06828 6.269 6.10e-05 ***
M2 0.24150 0.06828 3.537 0.004657 **
M3 0.19750 0.06828 2.893 0.014637 *
M4 -0.07700 0.06828 -1.128 0.283421
M5 -0.33900 0.06828 -4.965 0.000425 ***
M6 -0.43550 0.06828 -6.378 5.23e-05 ***
M7 -0.39750 0.06828 -5.822 0.000116 ***
M8 -0.51500 0.06828 -7.543 1.14e-05 ***
M9 -0.48950 0.06828 -7.169 1.82e-05 ***
M10 -0.15550 0.06828 -2.277 0.043729 *
M11 0.09100 0.06828 1.333 0.209545
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.06828 on 11 degrees of freedom
Multiple R-squared: 0.9779, Adjusted R-squared: 0.9538
F-statistic: 40.54 on 12 and 11 DF, p-value: 2.464e-07
> 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/www/html/rcomp/tmp/12mg71290941885.ps",horizontal=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/22mg71290941885.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/rcomp/tmp/3vefa1290941885.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4vefa1290941885.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5vefa1290941885.ps",horizontal=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 = 24
Frequency = 1
1 2 3 4 5 6 7 8
0.01625 0.07175 0.00375 0.00725 -0.05875 0.01975 -0.02925 -0.02775
9 10 11 12 13 14 15 16
-0.03525 -0.07325 0.01725 0.08825 -0.01625 -0.07175 -0.00375 -0.00725
17 18 19 20 21 22 23 24
0.05875 -0.01975 0.02925 0.02775 0.03525 0.07325 -0.01725 -0.08825
> postscript(file="/var/www/html/rcomp/tmp/6o5ed1290941885.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 24
Frequency = 1
lag(myerror, k = 1) myerror
0 0.01625 NA
1 0.07175 0.01625
2 0.00375 0.07175
3 0.00725 0.00375
4 -0.05875 0.00725
5 0.01975 -0.05875
6 -0.02925 0.01975
7 -0.02775 -0.02925
8 -0.03525 -0.02775
9 -0.07325 -0.03525
10 0.01725 -0.07325
11 0.08825 0.01725
12 -0.01625 0.08825
13 -0.07175 -0.01625
14 -0.00375 -0.07175
15 -0.00725 -0.00375
16 0.05875 -0.00725
17 -0.01975 0.05875
18 0.02925 -0.01975
19 0.02775 0.02925
20 0.03525 0.02775
21 0.07325 0.03525
22 -0.01725 0.07325
23 -0.08825 -0.01725
24 NA -0.08825
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.07175 0.01625
[2,] 0.00375 0.07175
[3,] 0.00725 0.00375
[4,] -0.05875 0.00725
[5,] 0.01975 -0.05875
[6,] -0.02925 0.01975
[7,] -0.02775 -0.02925
[8,] -0.03525 -0.02775
[9,] -0.07325 -0.03525
[10,] 0.01725 -0.07325
[11,] 0.08825 0.01725
[12,] -0.01625 0.08825
[13,] -0.07175 -0.01625
[14,] -0.00375 -0.07175
[15,] -0.00725 -0.00375
[16,] 0.05875 -0.00725
[17,] -0.01975 0.05875
[18,] 0.02925 -0.01975
[19,] 0.02775 0.02925
[20,] 0.03525 0.02775
[21,] 0.07325 0.03525
[22,] -0.01725 0.07325
[23,] -0.08825 -0.01725
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.07175 0.01625
2 0.00375 0.07175
3 0.00725 0.00375
4 -0.05875 0.00725
5 0.01975 -0.05875
6 -0.02925 0.01975
7 -0.02775 -0.02925
8 -0.03525 -0.02775
9 -0.07325 -0.03525
10 0.01725 -0.07325
11 0.08825 0.01725
12 -0.01625 0.08825
13 -0.07175 -0.01625
14 -0.00375 -0.07175
15 -0.00725 -0.00375
16 0.05875 -0.00725
17 -0.01975 0.05875
18 0.02925 -0.01975
19 0.02775 0.02925
20 0.03525 0.02775
21 0.07325 0.03525
22 -0.01725 0.07325
23 -0.08825 -0.01725
> 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/html/rcomp/tmp/7gwdy1290941885.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8gwdy1290941885.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9gwdy1290941885.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
hat values (leverages) are all = 0.5416667
and there are no factor predictors; no plot no. 5
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10r5d11290941885.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/html/rcomp/tmp/11uotp1290941885.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/html/rcomp/tmp/12ypad1290941885.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/html/rcomp/tmp/13ug7l1290941885.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/html/rcomp/tmp/14xh691290941885.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/html/rcomp/tmp/15jhmx1290941885.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/html/rcomp/tmp/1640ll1290941885.tab")
+ }
>
> try(system("convert tmp/12mg71290941885.ps tmp/12mg71290941885.png",intern=TRUE))
character(0)
> try(system("convert tmp/22mg71290941885.ps tmp/22mg71290941885.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vefa1290941885.ps tmp/3vefa1290941885.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vefa1290941885.ps tmp/4vefa1290941885.png",intern=TRUE))
character(0)
> try(system("convert tmp/5vefa1290941885.ps tmp/5vefa1290941885.png",intern=TRUE))
character(0)
> try(system("convert tmp/6o5ed1290941885.ps tmp/6o5ed1290941885.png",intern=TRUE))
character(0)
> try(system("convert tmp/7gwdy1290941885.ps tmp/7gwdy1290941885.png",intern=TRUE))
character(0)
> try(system("convert tmp/8gwdy1290941885.ps tmp/8gwdy1290941885.png",intern=TRUE))
character(0)
> try(system("convert tmp/9gwdy1290941885.ps tmp/9gwdy1290941885.png",intern=TRUE))
character(0)
> try(system("convert tmp/10r5d11290941885.ps tmp/10r5d11290941885.png",intern=TRUE))
convert: unable to open image `tmp/10r5d11290941885.ps': No such file or directory.
convert: missing an image filename `tmp/10r5d11290941885.png'.
character(0)
>
>
> proc.time()
user system elapsed
1.969 1.387 9.430