R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'demo()' for some demos, 'help()' for on-line help, or
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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 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> par3 <- '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, 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
Cons Inc Price M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 99.2 96.7 101.0 1 0 0 0 0 0 0 0 0 0 0 1
2 99.0 98.1 100.1 0 1 0 0 0 0 0 0 0 0 0 2
3 100.0 100.0 100.0 0 0 1 0 0 0 0 0 0 0 0 3
4 111.6 104.9 90.6 0 0 0 1 0 0 0 0 0 0 0 4
5 122.2 104.9 86.5 0 0 0 0 1 0 0 0 0 0 0 5
6 117.6 109.5 89.7 0 0 0 0 0 1 0 0 0 0 0 6
7 121.1 110.8 90.6 0 0 0 0 0 0 1 0 0 0 0 7
8 136.0 112.3 82.8 0 0 0 0 0 0 0 1 0 0 0 8
9 154.2 109.3 70.1 0 0 0 0 0 0 0 0 1 0 0 9
10 153.6 105.3 65.4 0 0 0 0 0 0 0 0 0 1 0 10
11 158.5 101.7 61.3 0 0 0 0 0 0 0 0 0 0 1 11
12 140.6 95.4 62.5 0 0 0 0 0 0 0 0 0 0 0 12
13 136.2 96.4 63.6 1 0 0 0 0 0 0 0 0 0 0 13
14 168.0 97.6 52.6 0 1 0 0 0 0 0 0 0 0 0 14
15 154.3 102.4 59.7 0 0 1 0 0 0 0 0 0 0 0 15
16 149.0 101.6 59.5 0 0 0 1 0 0 0 0 0 0 0 16
17 165.5 103.8 61.3 0 0 0 0 1 0 0 0 0 0 0 17
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Inc Price M1 M2 M3
141.6481 0.6601 -1.1396 1.9058 9.4669 4.2939
M4 M5 M6 M7 M8 M9
0.0205 10.9336 2.2908 5.3580 9.7790 14.8864
M10 M11 t
10.9705 12.9742 0.6003
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
1 2 3 4 5 6 7
6.313e+00 -3.999e+00 2.061e-01 1.533e+00 -4.053e+00 -5.126e-16 -2.906e-16
8 9 10 11 12 13 14
1.535e-16 3.756e-16 1.042e-15 -6.852e-17 -6.852e-17 -6.313e+00 3.999e+00
15 16 17
-2.061e-01 -1.533e+00 4.053e+00
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 141.6481 371.2203 0.382 0.740
Inc 0.6601 3.4015 0.194 0.864
Price -1.1396 0.8105 -1.406 0.295
M1 1.9058 12.3464 0.154 0.891
M2 9.4669 13.6719 0.692 0.560
M3 4.2939 25.5292 0.168 0.882
M4 0.0205 31.1173 0.001 1.000
M5 10.9336 35.6377 0.307 0.788
M6 2.2908 52.4101 0.044 0.969
M7 5.3580 58.6529 0.091 0.936
M8 9.7790 61.5339 0.159 0.888
M9 14.8864 47.8565 0.311 0.785
M10 10.9704 34.4777 0.318 0.780
M11 12.9742 23.3391 0.556 0.634
t 0.6003 2.5715 0.233 0.837
Residual standard error: 8.64 on 2 degrees of freedom
Multiple R-squared: 0.9832, Adjusted R-squared: 0.8657
F-statistic: 8.367 on 14 and 2 DF, p-value: 0.1118
> 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/fisher/rcomp/tmp/1jdkg1352548039.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/2nvtq1352548039.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3hoet1352548039.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4vbdc1352548039.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5vrzx1352548039.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
6.312576e+00 -3.998591e+00 2.060699e-01 1.532796e+00 -4.052851e+00
6 7 8 9 10
-5.126108e-16 -2.905662e-16 1.535230e-16 3.755676e-16 1.041701e-15
11 12 13 14 15
-6.852158e-17 -6.852158e-17 -6.312576e+00 3.998591e+00 -2.060699e-01
16 17
-1.532796e+00 4.052851e+00
> postscript(file="/var/fisher/rcomp/tmp/602cb1352548039.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 6.312576e+00 NA
1 -3.998591e+00 6.312576e+00
2 2.060699e-01 -3.998591e+00
3 1.532796e+00 2.060699e-01
4 -4.052851e+00 1.532796e+00
5 -5.126108e-16 -4.052851e+00
6 -2.905662e-16 -5.126108e-16
7 1.535230e-16 -2.905662e-16
8 3.755676e-16 1.535230e-16
9 1.041701e-15 3.755676e-16
10 -6.852158e-17 1.041701e-15
11 -6.852158e-17 -6.852158e-17
12 -6.312576e+00 -6.852158e-17
13 3.998591e+00 -6.312576e+00
14 -2.060699e-01 3.998591e+00
15 -1.532796e+00 -2.060699e-01
16 4.052851e+00 -1.532796e+00
17 NA 4.052851e+00
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.998591e+00 6.312576e+00
[2,] 2.060699e-01 -3.998591e+00
[3,] 1.532796e+00 2.060699e-01
[4,] -4.052851e+00 1.532796e+00
[5,] -5.126108e-16 -4.052851e+00
[6,] -2.905662e-16 -5.126108e-16
[7,] 1.535230e-16 -2.905662e-16
[8,] 3.755676e-16 1.535230e-16
[9,] 1.041701e-15 3.755676e-16
[10,] -6.852158e-17 1.041701e-15
[11,] -6.852158e-17 -6.852158e-17
[12,] -6.312576e+00 -6.852158e-17
[13,] 3.998591e+00 -6.312576e+00
[14,] -2.060699e-01 3.998591e+00
[15,] -1.532796e+00 -2.060699e-01
[16,] 4.052851e+00 -1.532796e+00
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.998591e+00 6.312576e+00
2 2.060699e-01 -3.998591e+00
3 1.532796e+00 2.060699e-01
4 -4.052851e+00 1.532796e+00
5 -5.126108e-16 -4.052851e+00
6 -2.905662e-16 -5.126108e-16
7 1.535230e-16 -2.905662e-16
8 3.755676e-16 1.535230e-16
9 1.041701e-15 3.755676e-16
10 -6.852158e-17 1.041701e-15
11 -6.852158e-17 -6.852158e-17
12 -6.312576e+00 -6.852158e-17
13 3.998591e+00 -6.312576e+00
14 -2.060699e-01 3.998591e+00
15 -1.532796e+00 -2.060699e-01
16 4.052851e+00 -1.532796e+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/fisher/rcomp/tmp/7jrla1352548039.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/8blsp1352548039.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/9uqwi1352548039.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning messages:
1: Not plotting observations with leverage one:
6, 7, 8, 9, 10, 11, 12
2: Not plotting observations with leverage one:
6, 7, 8, 9, 10, 11, 12
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/1018631352548039.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/fisher/rcomp/tmp/1158mu1352548039.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/fisher/rcomp/tmp/12jj8v1352548039.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/fisher/rcomp/tmp/13iilc1352548039.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/fisher/rcomp/tmp/14wdap1352548039.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/fisher/rcomp/tmp/151y0q1352548039.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/fisher/rcomp/tmp/16lt421352548040.tab")
+ }
>
> try(system("convert tmp/1jdkg1352548039.ps tmp/1jdkg1352548039.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nvtq1352548039.ps tmp/2nvtq1352548039.png",intern=TRUE))
character(0)
> try(system("convert tmp/3hoet1352548039.ps tmp/3hoet1352548039.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vbdc1352548039.ps tmp/4vbdc1352548039.png",intern=TRUE))
character(0)
> try(system("convert tmp/5vrzx1352548039.ps tmp/5vrzx1352548039.png",intern=TRUE))
character(0)
> try(system("convert tmp/602cb1352548039.ps tmp/602cb1352548039.png",intern=TRUE))
character(0)
> try(system("convert tmp/7jrla1352548039.ps tmp/7jrla1352548039.png",intern=TRUE))
character(0)
> try(system("convert tmp/8blsp1352548039.ps tmp/8blsp1352548039.png",intern=TRUE))
character(0)
> try(system("convert tmp/9uqwi1352548039.ps tmp/9uqwi1352548039.png",intern=TRUE))
character(0)
> try(system("convert tmp/1018631352548039.ps tmp/1018631352548039.png",intern=TRUE))
convert: unable to open image `tmp/1018631352548039.ps': @ error/blob.c/OpenBlob/2587.
convert: missing an image filename `tmp/1018631352548039.png' @ error/convert.c/ConvertImageCommand/3011.
character(0)
attr(,"status")
[1] 1
Warning message:
running command 'convert tmp/1018631352548039.ps tmp/1018631352548039.png' had status 1
>
>
> proc.time()
user system elapsed
4.971 1.057 6.030