R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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> x <- array(list(5.5865,4.6052,.9809,5.5951,4.6328,.9700,5.6032,4.6549,.9528,5.6164,4.6681,.9486,5.6215,4.6691,.9458,5.6366,4.6738,.9563,5.6563,4.6932,.9639,5.6671,4.7050,.9578,5.6788,4.7167,.9613,5.6958,4.7371,.9609,5.7044,4.7510,.9536,5.7197,4.7681,.9547,5.7456,4.7808,.9613,5.7614,4.7999,.9647,5.7770,4.8219,.9574,5.8003,4.8434,.9570,5.8177,4.8691,.9563,5.8424,4.8888,.9547,5.8576,4.9082,.9490,5.8786,4.9409,.9462,5.8880,4.9656,.9219,5.9113,4.9774,.9384,5.9399,5.0013,.9423,5.9512,5.0291,.9270),dim=c(3,24),dimnames=list(c('lnM1b','lnBa','lnm-1'),1:24))
> y <- array(NA,dim=c(3,24),dimnames=list(c('lnM1b','lnBa','lnm-1'),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 = 'Do not include Seasonal Dummies'
> par1 = '1'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '1'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 ()
> #Author: root
> #To cite this work: Wessa P., (2013), Multiple Regression (v1.0.29) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_multipleregression.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following objects 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
lnM1b lnBa lnm-1
1 5.5865 4.6052 0.9809
2 5.5951 4.6328 0.9700
3 5.6032 4.6549 0.9528
4 5.6164 4.6681 0.9486
5 5.6215 4.6691 0.9458
6 5.6366 4.6738 0.9563
7 5.6563 4.6932 0.9639
8 5.6671 4.7050 0.9578
9 5.6788 4.7167 0.9613
10 5.6958 4.7371 0.9609
11 5.7044 4.7510 0.9536
12 5.7197 4.7681 0.9547
13 5.7456 4.7808 0.9613
14 5.7614 4.7999 0.9647
15 5.7770 4.8219 0.9574
16 5.8003 4.8434 0.9570
17 5.8177 4.8691 0.9563
18 5.8424 4.8888 0.9547
19 5.8576 4.9082 0.9490
20 5.8786 4.9409 0.9462
21 5.8880 4.9656 0.9219
22 5.9113 4.9774 0.9384
23 5.9399 5.0013 0.9423
24 5.9512 5.0291 0.9270
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) lnBa `lnm-1`
0.2285 0.9782 0.8684
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.0077452 -0.0020405 0.0001394 0.0024900 0.0055435
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.228546 0.118184 1.934 0.0667 .
lnBa 0.978240 0.008814 110.983 < 2e-16 ***
`lnm-1` 0.868360 0.088107 9.856 2.5e-09 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.003717 on 21 degrees of freedom
Multiple R-squared: 0.9991, Adjusted R-squared: 0.999
F-statistic: 1.129e+04 on 2 and 21 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
+ }
> postscript(file="/var/wessaorg/rcomp/tmp/1xas51424030466.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2d10v1424030466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3jhv11424030466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4u7rl1424030466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5apic1424030466.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 = 24
Frequency = 1
1 2 3 4 5
0.0011890500 -0.0077452447 -0.0063285488 -0.0023942027 0.0041589665
6 7 8 9 10
0.0055434543 -0.0003339402 0.0042198267 0.0014351576 -0.0011735936
11 12 13 14 15
0.0001679019 -0.0022151981 0.0055299756 -0.0003068332 0.0001109185
16 17 18 19 20
0.0027261034 -0.0044068115 0.0024112377 0.0035830367 -0.0049740011
21 22 23 24
0.0013646297 -0.0012065487 0.0006269104 -0.0019822464
> postscript(file="/var/wessaorg/rcomp/tmp/6680e1424030466.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 = 24
Frequency = 1
lag(myerror, k = 1) myerror
0 0.0011890500 NA
1 -0.0077452447 0.0011890500
2 -0.0063285488 -0.0077452447
3 -0.0023942027 -0.0063285488
4 0.0041589665 -0.0023942027
5 0.0055434543 0.0041589665
6 -0.0003339402 0.0055434543
7 0.0042198267 -0.0003339402
8 0.0014351576 0.0042198267
9 -0.0011735936 0.0014351576
10 0.0001679019 -0.0011735936
11 -0.0022151981 0.0001679019
12 0.0055299756 -0.0022151981
13 -0.0003068332 0.0055299756
14 0.0001109185 -0.0003068332
15 0.0027261034 0.0001109185
16 -0.0044068115 0.0027261034
17 0.0024112377 -0.0044068115
18 0.0035830367 0.0024112377
19 -0.0049740011 0.0035830367
20 0.0013646297 -0.0049740011
21 -0.0012065487 0.0013646297
22 0.0006269104 -0.0012065487
23 -0.0019822464 0.0006269104
24 NA -0.0019822464
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.0077452447 0.0011890500
[2,] -0.0063285488 -0.0077452447
[3,] -0.0023942027 -0.0063285488
[4,] 0.0041589665 -0.0023942027
[5,] 0.0055434543 0.0041589665
[6,] -0.0003339402 0.0055434543
[7,] 0.0042198267 -0.0003339402
[8,] 0.0014351576 0.0042198267
[9,] -0.0011735936 0.0014351576
[10,] 0.0001679019 -0.0011735936
[11,] -0.0022151981 0.0001679019
[12,] 0.0055299756 -0.0022151981
[13,] -0.0003068332 0.0055299756
[14,] 0.0001109185 -0.0003068332
[15,] 0.0027261034 0.0001109185
[16,] -0.0044068115 0.0027261034
[17,] 0.0024112377 -0.0044068115
[18,] 0.0035830367 0.0024112377
[19,] -0.0049740011 0.0035830367
[20,] 0.0013646297 -0.0049740011
[21,] -0.0012065487 0.0013646297
[22,] 0.0006269104 -0.0012065487
[23,] -0.0019822464 0.0006269104
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.0077452447 0.0011890500
2 -0.0063285488 -0.0077452447
3 -0.0023942027 -0.0063285488
4 0.0041589665 -0.0023942027
5 0.0055434543 0.0041589665
6 -0.0003339402 0.0055434543
7 0.0042198267 -0.0003339402
8 0.0014351576 0.0042198267
9 -0.0011735936 0.0014351576
10 0.0001679019 -0.0011735936
11 -0.0022151981 0.0001679019
12 0.0055299756 -0.0022151981
13 -0.0003068332 0.0055299756
14 0.0001109185 -0.0003068332
15 0.0027261034 0.0001109185
16 -0.0044068115 0.0027261034
17 0.0024112377 -0.0044068115
18 0.0035830367 0.0024112377
19 -0.0049740011 0.0035830367
20 0.0013646297 -0.0049740011
21 -0.0012065487 0.0013646297
22 0.0006269104 -0.0012065487
23 -0.0019822464 0.0006269104
> 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/7s3x21424030466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8vf801424030466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9t8b91424030466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/106y2b1424030466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
+ if (rownames(mysum$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/117rqp1424030466.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$coefficients)[i],header=TRUE)
+ a<-table.element(a,signif(mysum$coefficients[i,1],6))
+ a<-table.element(a, signif(mysum$coefficients[i,2],6))
+ a<-table.element(a, signif(mysum$coefficients[i,3],4))
+ a<-table.element(a, signif(mysum$coefficients[i,4],6))
+ a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12tfq41424030466.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, signif(sqrt(mysum$r.squared),6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, signif(mysum$r.squared,6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, signif(mysum$adj.r.squared,6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[1],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[2],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[3],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, signif(mysum$sigma,6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, signif(sum(myerror*myerror),6))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13w84s1424030466.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,signif(x[i],6))
+ a<-table.element(a,signif(x[i]-mysum$resid[i],6))
+ a<-table.element(a,signif(mysum$resid[i],6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14b2yw1424030466.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,signif(gqarr[mypoint-kp3+1,1],6))
+ a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
+ a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/15wznk1424030466.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,signif(numsignificant1,6))
+ a<-table.element(a,signif(numsignificant1/numgqtests,6))
+ 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,signif(numsignificant5,6))
+ a<-table.element(a,signif(numsignificant5/numgqtests,6))
+ 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,signif(numsignificant10,6))
+ a<-table.element(a,signif(numsignificant10/numgqtests,6))
+ 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/16htku1424030466.tab")
+ }
>
> try(system("convert tmp/1xas51424030466.ps tmp/1xas51424030466.png",intern=TRUE))
character(0)
> try(system("convert tmp/2d10v1424030466.ps tmp/2d10v1424030466.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jhv11424030466.ps tmp/3jhv11424030466.png",intern=TRUE))
character(0)
> try(system("convert tmp/4u7rl1424030466.ps tmp/4u7rl1424030466.png",intern=TRUE))
character(0)
> try(system("convert tmp/5apic1424030466.ps tmp/5apic1424030466.png",intern=TRUE))
character(0)
> try(system("convert tmp/6680e1424030466.ps tmp/6680e1424030466.png",intern=TRUE))
character(0)
> try(system("convert tmp/7s3x21424030466.ps tmp/7s3x21424030466.png",intern=TRUE))
character(0)
> try(system("convert tmp/8vf801424030466.ps tmp/8vf801424030466.png",intern=TRUE))
character(0)
> try(system("convert tmp/9t8b91424030466.ps tmp/9t8b91424030466.png",intern=TRUE))
character(0)
> try(system("convert tmp/106y2b1424030466.ps tmp/106y2b1424030466.png",intern=TRUE))
convert.im6: unable to open image `tmp/106y2b1424030466.ps': No such file or directory @ error/blob.c/OpenBlob/2638.
convert.im6: no images defined `tmp/106y2b1424030466.png' @ error/convert.c/ConvertImageCommand/3044.
character(0)
attr(,"status")
[1] 1
Warning message:
running command 'convert tmp/106y2b1424030466.ps tmp/106y2b1424030466.png' had status 1
>
>
> proc.time()
user system elapsed
3.786 0.612 4.443