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)
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> x <- array(list(99.2,96.7,101.0,99.0,98.1,100.1,100.0,100.0,100.0,111.6,104.9,90.6,122.2,104.9,86.5,117.6,109.5,89.7,121.1,110.8,90.6,136.0,112.3,82.8,154.2,109.3,70.1,153.6,105.3,65.4,158.5,101.7,61.3,140.6,95.4,62.5,136.2,96.4,63.6,168.0,97.6,52.6,154.3,102.4,59.7,149.0,101.6,59.5,165.5,103.8,61.3),dim=c(3,17),dimnames=list(c('Cons','Inc','Price'),1:17))
> y <- array(NA,dim=c(3,17),dimnames=list(c('Cons','Inc','Price'),1:17))
> 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
> 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
Cons Inc Price M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 99.2 96.7 101.0 1 0 0 0 0 0 0 0 0 0 0
2 99.0 98.1 100.1 0 1 0 0 0 0 0 0 0 0 0
3 100.0 100.0 100.0 0 0 1 0 0 0 0 0 0 0 0
4 111.6 104.9 90.6 0 0 0 1 0 0 0 0 0 0 0
5 122.2 104.9 86.5 0 0 0 0 1 0 0 0 0 0 0
6 117.6 109.5 89.7 0 0 0 0 0 1 0 0 0 0 0
7 121.1 110.8 90.6 0 0 0 0 0 0 1 0 0 0 0
8 136.0 112.3 82.8 0 0 0 0 0 0 0 1 0 0 0
9 154.2 109.3 70.1 0 0 0 0 0 0 0 0 1 0 0
10 153.6 105.3 65.4 0 0 0 0 0 0 0 0 0 1 0
11 158.5 101.7 61.3 0 0 0 0 0 0 0 0 0 0 1
12 140.6 95.4 62.5 0 0 0 0 0 0 0 0 0 0 0
13 136.2 96.4 63.6 1 0 0 0 0 0 0 0 0 0 0
14 168.0 97.6 52.6 0 1 0 0 0 0 0 0 0 0 0
15 154.3 102.4 59.7 0 0 1 0 0 0 0 0 0 0 0
16 149.0 101.6 59.5 0 0 0 1 0 0 0 0 0 0 0
17 165.5 103.8 61.3 0 0 0 0 1 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Inc Price M1 M2 M3
199.3355 0.2527 -1.3255 3.0543 10.6390 8.0817
M4 M5 M6 M7 M8 M9
4.3513 16.0990 9.4904 13.8549 18.0369 20.1612
M10 M11
14.3422 14.7173
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
1 2 3 4 5 6 7
6.249e+00 -3.083e+00 -1.379e-01 1.495e+00 -5.088e+00 -1.199e-15 1.336e-16
8 9 10 11 12 13 14
1.336e-16 3.556e-16 5.777e-16 -3.105e-16 -8.847e-17 -6.249e+00 3.083e+00
15 16 17
1.379e-01 -1.495e+00 5.088e+00
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 199.3355 229.2294 0.870 0.44851
Inc 0.2527 2.4161 0.105 0.92330
Price -1.3255 0.1243 -10.668 0.00176 **
M1 3.0543 9.3708 0.326 0.76588
M2 10.6390 10.5234 1.011 0.38648
M3 8.0817 16.3095 0.496 0.65426
M4 4.3513 20.6732 0.210 0.84678
M5 16.0990 23.1176 0.696 0.53629
M6 9.4904 35.0657 0.271 0.80422
M7 13.8549 38.0594 0.364 0.73998
M8 18.0369 41.6648 0.433 0.69432
M9 20.1612 34.9102 0.578 0.60408
M10 14.3422 25.9071 0.554 0.61844
M11 14.7173 18.2988 0.804 0.48007
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.15 on 3 degrees of freedom
Multiple R-squared: 0.9828, Adjusted R-squared: 0.908
F-statistic: 13.15 on 13 and 3 DF, p-value: 0.02817
> 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/183zj1324147665.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/23k4a1324147665.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/31rjj1324147665.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4kjua1324147666.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5kiz91324147666.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 = 17
Frequency = 1
1 2 3 4 5
6.248934e+00 -3.082565e+00 -1.379379e-01 1.494550e+00 -5.087696e+00
6 7 8 9 10
-1.198694e-15 1.335737e-16 1.335737e-16 3.556183e-16 5.776629e-16
11 12 13 14 15
-3.105155e-16 -8.847090e-17 -6.248934e+00 3.082565e+00 1.379379e-01
16 17
-1.494550e+00 5.087696e+00
> postscript(file="/var/wessaorg/rcomp/tmp/6p3i91324147666.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 = 17
Frequency = 1
lag(myerror, k = 1) myerror
0 6.248934e+00 NA
1 -3.082565e+00 6.248934e+00
2 -1.379379e-01 -3.082565e+00
3 1.494550e+00 -1.379379e-01
4 -5.087696e+00 1.494550e+00
5 -1.198694e-15 -5.087696e+00
6 1.335737e-16 -1.198694e-15
7 1.335737e-16 1.335737e-16
8 3.556183e-16 1.335737e-16
9 5.776629e-16 3.556183e-16
10 -3.105155e-16 5.776629e-16
11 -8.847090e-17 -3.105155e-16
12 -6.248934e+00 -8.847090e-17
13 3.082565e+00 -6.248934e+00
14 1.379379e-01 3.082565e+00
15 -1.494550e+00 1.379379e-01
16 5.087696e+00 -1.494550e+00
17 NA 5.087696e+00
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.082565e+00 6.248934e+00
[2,] -1.379379e-01 -3.082565e+00
[3,] 1.494550e+00 -1.379379e-01
[4,] -5.087696e+00 1.494550e+00
[5,] -1.198694e-15 -5.087696e+00
[6,] 1.335737e-16 -1.198694e-15
[7,] 1.335737e-16 1.335737e-16
[8,] 3.556183e-16 1.335737e-16
[9,] 5.776629e-16 3.556183e-16
[10,] -3.105155e-16 5.776629e-16
[11,] -8.847090e-17 -3.105155e-16
[12,] -6.248934e+00 -8.847090e-17
[13,] 3.082565e+00 -6.248934e+00
[14,] 1.379379e-01 3.082565e+00
[15,] -1.494550e+00 1.379379e-01
[16,] 5.087696e+00 -1.494550e+00
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.082565e+00 6.248934e+00
2 -1.379379e-01 -3.082565e+00
3 1.494550e+00 -1.379379e-01
4 -5.087696e+00 1.494550e+00
5 -1.198694e-15 -5.087696e+00
6 1.335737e-16 -1.198694e-15
7 1.335737e-16 1.335737e-16
8 3.556183e-16 1.335737e-16
9 5.776629e-16 3.556183e-16
10 -3.105155e-16 5.776629e-16
11 -8.847090e-17 -3.105155e-16
12 -6.248934e+00 -8.847090e-17
13 3.082565e+00 -6.248934e+00
14 1.379379e-01 3.082565e+00
15 -1.494550e+00 1.379379e-01
16 5.087696e+00 -1.494550e+00
> 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/73iee1324147666.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/88bah1324147666.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9ea0i1324147666.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning messages:
1: Not plotting observations with leverage one:
6, 7, 8, 9, 10, 11, 12
2: Not plotting observations with leverage one:
6, 7, 8, 9, 10, 11, 12
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10v4sw1324147666.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11wbgg1324147666.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/12uaqe1324147666.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/13tqoi1324147666.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/14u7sx1324147666.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/15q7cz1324147666.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/16ingw1324147666.tab")
+ }
>
> try(system("convert tmp/183zj1324147665.ps tmp/183zj1324147665.png",intern=TRUE))
character(0)
> try(system("convert tmp/23k4a1324147665.ps tmp/23k4a1324147665.png",intern=TRUE))
character(0)
> try(system("convert tmp/31rjj1324147665.ps tmp/31rjj1324147665.png",intern=TRUE))
character(0)
> try(system("convert tmp/4kjua1324147666.ps tmp/4kjua1324147666.png",intern=TRUE))
character(0)
> try(system("convert tmp/5kiz91324147666.ps tmp/5kiz91324147666.png",intern=TRUE))
character(0)
> try(system("convert tmp/6p3i91324147666.ps tmp/6p3i91324147666.png",intern=TRUE))
character(0)
> try(system("convert tmp/73iee1324147666.ps tmp/73iee1324147666.png",intern=TRUE))
character(0)
> try(system("convert tmp/88bah1324147666.ps tmp/88bah1324147666.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ea0i1324147666.ps tmp/9ea0i1324147666.png",intern=TRUE))
character(0)
> try(system("convert tmp/10v4sw1324147666.ps tmp/10v4sw1324147666.png",intern=TRUE))
convert: unable to open image `tmp/10v4sw1324147666.ps': No such file or directory @ blob.c/OpenBlob/2480.
convert: missing an image filename `tmp/10v4sw1324147666.png' @ convert.c/ConvertImageCommand/2838.
character(0)
Warning message:
running command 'convert tmp/10v4sw1324147666.ps tmp/10v4sw1324147666.png' had status 1
>
>
> proc.time()
user system elapsed
2.585 0.537 3.176