R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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.
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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
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> x <- array(list(97.3,332.9,90.45,341.6,80.64,333.4,80.58,348.2,75.82,344.7,85.59,344.7,89.35,329.3,89.42,323.5,104.73,323.2,95.32,317.4,89.27,330.1,90.44,329.2,86.97,334.9,79.98,315.8,81.22,315.4,87.35,319.6,83.64,317.3,82.22,313.8,94.4,315.8,102.18,311.3),dim=c(2,20),dimnames=list(c('Colombia','USA'),1:20))
> y <- array(NA,dim=c(2,20),dimnames=list(c('Colombia','USA'),1:20))
> 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 = '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
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
USA Colombia M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 332.9 97.30 1 0 0 0 0 0 0 0 0 0 0
2 341.6 90.45 0 1 0 0 0 0 0 0 0 0 0
3 333.4 80.64 0 0 1 0 0 0 0 0 0 0 0
4 348.2 80.58 0 0 0 1 0 0 0 0 0 0 0
5 344.7 75.82 0 0 0 0 1 0 0 0 0 0 0
6 344.7 85.59 0 0 0 0 0 1 0 0 0 0 0
7 329.3 89.35 0 0 0 0 0 0 1 0 0 0 0
8 323.5 89.42 0 0 0 0 0 0 0 1 0 0 0
9 323.2 104.73 0 0 0 0 0 0 0 0 1 0 0
10 317.4 95.32 0 0 0 0 0 0 0 0 0 1 0
11 330.1 89.27 0 0 0 0 0 0 0 0 0 0 1
12 329.2 90.44 0 0 0 0 0 0 0 0 0 0 0
13 334.9 86.97 1 0 0 0 0 0 0 0 0 0 0
14 315.8 79.98 0 1 0 0 0 0 0 0 0 0 0
15 315.4 81.22 0 0 1 0 0 0 0 0 0 0 0
16 319.6 87.35 0 0 0 1 0 0 0 0 0 0 0
17 317.3 83.64 0 0 0 0 1 0 0 0 0 0 0
18 313.8 82.22 0 0 0 0 0 1 0 0 0 0 0
19 315.8 94.40 0 0 0 0 0 0 1 0 0 0 0
20 311.3 102.18 0 0 0 0 0 0 0 1 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Colombia M1 M2 M3 M4
379.0712 -0.5514 5.6347 -3.3812 -10.0441 1.1295
M5 M6 M7 M8 M9 M10
-4.1058 -3.5536 -5.8587 -8.8443 1.8799 -9.1090
M11
0.2548
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.638e+01 -6.228e+00 -8.327e-17 6.228e+00 1.638e+01
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 379.0712 92.1986 4.111 0.00451 **
Colombia -0.5514 1.0035 -0.549 0.59975
M1 5.6347 19.9539 0.282 0.78582
M2 -3.3812 20.5611 -0.164 0.87403
M3 -10.0441 22.0532 -0.455 0.66258
M4 1.1295 20.9161 0.054 0.95844
M5 -4.1058 22.6004 -0.182 0.86099
M6 -3.5536 20.9349 -0.170 0.87001
M7 -5.8587 19.9333 -0.294 0.77735
M8 -8.8443 20.5960 -0.429 0.68053
M9 1.8799 27.0677 0.069 0.94657
M10 -9.1090 23.4734 -0.388 0.70950
M11 0.2548 22.9869 0.011 0.99146
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 16.23 on 7 degrees of freedom
Multiple R-squared: 0.2682, Adjusted R-squared: -0.9862
F-statistic: 0.2138 on 12 and 7 DF, p-value: 0.9903
> 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/1r5at1290683422.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2r5at1290683422.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3kwsw1290683422.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4kwsw1290683422.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5kwsw1290683422.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 = 20
Frequency = 1
1 2 3 4 5
1.848126e+00 1.578673e+01 8.840086e+00 1.243342e+01 1.154392e+01
6 7 8 9 10
1.637916e+01 5.357644e+00 2.581889e+00 -4.496403e-15 -5.551115e-17
11 12 13 14 15
-1.110223e-16 2.414735e-14 -1.848126e+00 -1.578673e+01 -8.840086e+00
16 17 18 19 20
-1.243342e+01 -1.154392e+01 -1.637916e+01 -5.357644e+00 -2.581889e+00
> postscript(file="/var/www/html/rcomp/tmp/6u59h1290683422.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 = 20
Frequency = 1
lag(myerror, k = 1) myerror
0 1.848126e+00 NA
1 1.578673e+01 1.848126e+00
2 8.840086e+00 1.578673e+01
3 1.243342e+01 8.840086e+00
4 1.154392e+01 1.243342e+01
5 1.637916e+01 1.154392e+01
6 5.357644e+00 1.637916e+01
7 2.581889e+00 5.357644e+00
8 -4.496403e-15 2.581889e+00
9 -5.551115e-17 -4.496403e-15
10 -1.110223e-16 -5.551115e-17
11 2.414735e-14 -1.110223e-16
12 -1.848126e+00 2.414735e-14
13 -1.578673e+01 -1.848126e+00
14 -8.840086e+00 -1.578673e+01
15 -1.243342e+01 -8.840086e+00
16 -1.154392e+01 -1.243342e+01
17 -1.637916e+01 -1.154392e+01
18 -5.357644e+00 -1.637916e+01
19 -2.581889e+00 -5.357644e+00
20 NA -2.581889e+00
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.578673e+01 1.848126e+00
[2,] 8.840086e+00 1.578673e+01
[3,] 1.243342e+01 8.840086e+00
[4,] 1.154392e+01 1.243342e+01
[5,] 1.637916e+01 1.154392e+01
[6,] 5.357644e+00 1.637916e+01
[7,] 2.581889e+00 5.357644e+00
[8,] -4.496403e-15 2.581889e+00
[9,] -5.551115e-17 -4.496403e-15
[10,] -1.110223e-16 -5.551115e-17
[11,] 2.414735e-14 -1.110223e-16
[12,] -1.848126e+00 2.414735e-14
[13,] -1.578673e+01 -1.848126e+00
[14,] -8.840086e+00 -1.578673e+01
[15,] -1.243342e+01 -8.840086e+00
[16,] -1.154392e+01 -1.243342e+01
[17,] -1.637916e+01 -1.154392e+01
[18,] -5.357644e+00 -1.637916e+01
[19,] -2.581889e+00 -5.357644e+00
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.578673e+01 1.848126e+00
2 8.840086e+00 1.578673e+01
3 1.243342e+01 8.840086e+00
4 1.154392e+01 1.243342e+01
5 1.637916e+01 1.154392e+01
6 5.357644e+00 1.637916e+01
7 2.581889e+00 5.357644e+00
8 -4.496403e-15 2.581889e+00
9 -5.551115e-17 -4.496403e-15
10 -1.110223e-16 -5.551115e-17
11 2.414735e-14 -1.110223e-16
12 -1.848126e+00 2.414735e-14
13 -1.578673e+01 -1.848126e+00
14 -8.840086e+00 -1.578673e+01
15 -1.243342e+01 -8.840086e+00
16 -1.154392e+01 -1.243342e+01
17 -1.637916e+01 -1.154392e+01
18 -5.357644e+00 -1.637916e+01
19 -2.581889e+00 -5.357644e+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/www/html/rcomp/tmp/75w821290683422.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/85w821290683422.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/95w821290683422.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning messages:
1: Not plotting observations with leverage one:
9, 10, 11, 12
2: Not plotting observations with leverage one:
9, 10, 11, 12
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10gopn1290683422.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/111o6b1290683422.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/12n7my1290683422.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/131hk71290683422.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/144h1d1290683422.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/15qihj1290683422.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/16b0gp1290683422.tab")
+ }
>
> try(system("convert tmp/1r5at1290683422.ps tmp/1r5at1290683422.png",intern=TRUE))
character(0)
> try(system("convert tmp/2r5at1290683422.ps tmp/2r5at1290683422.png",intern=TRUE))
character(0)
> try(system("convert tmp/3kwsw1290683422.ps tmp/3kwsw1290683422.png",intern=TRUE))
character(0)
> try(system("convert tmp/4kwsw1290683422.ps tmp/4kwsw1290683422.png",intern=TRUE))
character(0)
> try(system("convert tmp/5kwsw1290683422.ps tmp/5kwsw1290683422.png",intern=TRUE))
character(0)
> try(system("convert tmp/6u59h1290683422.ps tmp/6u59h1290683422.png",intern=TRUE))
character(0)
> try(system("convert tmp/75w821290683422.ps tmp/75w821290683422.png",intern=TRUE))
character(0)
> try(system("convert tmp/85w821290683422.ps tmp/85w821290683422.png",intern=TRUE))
character(0)
> try(system("convert tmp/95w821290683422.ps tmp/95w821290683422.png",intern=TRUE))
character(0)
> try(system("convert tmp/10gopn1290683422.ps tmp/10gopn1290683422.png",intern=TRUE))
convert: unable to open image `tmp/10gopn1290683422.ps': No such file or directory.
convert: missing an image filename `tmp/10gopn1290683422.png'.
character(0)
>
>
> proc.time()
user system elapsed
2.008 1.446 5.797