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)
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(851,280,810,836,265,792,819,281,795,744,274,765,732,251,734,732,273,763,716,257,734,714,276,747,705,257,739,697,250,734,694,264,726,685,259,741,685,251,715,679,256,725,678,243,719,675,250,716,651,253,717,643,258,721,639,253,707,634,245,701,626,244,682,621,257,698,608,247,705,606,243,693,599,259,690,594,246,663,586,244,674,575,238,653,553,241,670,544,234,640),dim=c(3,30),dimnames=list(c('RUNS','AVG','OPS'),1:30))
> y <- array(NA,dim=c(3,30),dimnames=list(c('RUNS','AVG','OPS'),1:30))
> 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'
> #'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
RUNS AVG OPS
1 851 280 810
2 836 265 792
3 819 281 795
4 744 274 765
5 732 251 734
6 732 273 763
7 716 257 734
8 714 276 747
9 705 257 739
10 697 250 734
11 694 264 726
12 685 259 741
13 685 251 715
14 679 256 725
15 678 243 719
16 675 250 716
17 651 253 717
18 643 258 721
19 639 253 707
20 634 245 701
21 626 244 682
22 621 257 698
23 608 247 705
24 606 243 693
25 599 259 690
26 594 246 663
27 586 244 674
28 575 238 653
29 553 241 670
30 544 234 640
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) AVG OPS
-607.5615 -0.7618 2.0481
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-40.164 -9.148 -2.577 15.989 31.093
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -607.5615 75.4117 -8.057 1.17e-08 ***
AVG -0.7618 0.5969 -1.276 0.213
OPS 2.0481 0.1817 11.271 1.03e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 19.71 on 27 degrees of freedom
Multiple R-squared: 0.94, Adjusted R-squared: 0.9356
F-statistic: 211.7 on 2 and 27 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
+ }
[,1] [,2] [,3]
[1,] 0.2016028 0.4032055 0.7983972
[2,] 0.1194975 0.2389949 0.8805025
[3,] 0.1181434 0.2362868 0.8818566
[4,] 0.1527436 0.3054872 0.8472564
[5,] 0.1994759 0.3989518 0.8005241
[6,] 0.2460470 0.4920940 0.7539530
[7,] 0.4049659 0.8099318 0.5950341
[8,] 0.4720157 0.9440313 0.5279843
[9,] 0.4009491 0.8018982 0.5990509
[10,] 0.3619744 0.7239488 0.6380256
[11,] 0.4292034 0.8584068 0.5707966
[12,] 0.3962504 0.7925007 0.6037496
[13,] 0.3939286 0.7878573 0.6060714
[14,] 0.3052936 0.6105872 0.6947064
[15,] 0.2691546 0.5383092 0.7308454
[16,] 0.5992434 0.8015132 0.4007566
[17,] 0.4834106 0.9668211 0.5165894
[18,] 0.4549040 0.9098080 0.5450960
[19,] 0.4606894 0.9213788 0.5393106
> postscript(file="/var/wessaorg/rcomp/tmp/1reb01316887052.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/21jb41316887052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/32cex1316887052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4vq2l1316887052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5ole01316887052.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 = 30
Frequency = 1
1 2 3 4 5 6
12.9272918 23.3651806 12.4104539 -6.4798361 27.4884251 -15.1455067
7 8 9 10 11 12
16.0595013 1.9094352 -5.1809374 -8.2734210 15.7771254 -27.7534209
13 14 15 16 17 18
19.4020921 -3.2695551 -1.8850271 6.5921583 -17.1703913 -29.5535121
19 20 21 22 23 24
-8.6895139 -7.4957557 22.6560653 -5.2093401 -40.1644146 -20.6347459
25 26 27 28 29 30
-9.3009462 31.0934244 -0.9592328 26.4795335 -28.0524199 19.0572900
> postscript(file="/var/wessaorg/rcomp/tmp/61r7l1316887052.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 = 30
Frequency = 1
lag(myerror, k = 1) myerror
0 12.9272918 NA
1 23.3651806 12.9272918
2 12.4104539 23.3651806
3 -6.4798361 12.4104539
4 27.4884251 -6.4798361
5 -15.1455067 27.4884251
6 16.0595013 -15.1455067
7 1.9094352 16.0595013
8 -5.1809374 1.9094352
9 -8.2734210 -5.1809374
10 15.7771254 -8.2734210
11 -27.7534209 15.7771254
12 19.4020921 -27.7534209
13 -3.2695551 19.4020921
14 -1.8850271 -3.2695551
15 6.5921583 -1.8850271
16 -17.1703913 6.5921583
17 -29.5535121 -17.1703913
18 -8.6895139 -29.5535121
19 -7.4957557 -8.6895139
20 22.6560653 -7.4957557
21 -5.2093401 22.6560653
22 -40.1644146 -5.2093401
23 -20.6347459 -40.1644146
24 -9.3009462 -20.6347459
25 31.0934244 -9.3009462
26 -0.9592328 31.0934244
27 26.4795335 -0.9592328
28 -28.0524199 26.4795335
29 19.0572900 -28.0524199
30 NA 19.0572900
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 23.3651806 12.9272918
[2,] 12.4104539 23.3651806
[3,] -6.4798361 12.4104539
[4,] 27.4884251 -6.4798361
[5,] -15.1455067 27.4884251
[6,] 16.0595013 -15.1455067
[7,] 1.9094352 16.0595013
[8,] -5.1809374 1.9094352
[9,] -8.2734210 -5.1809374
[10,] 15.7771254 -8.2734210
[11,] -27.7534209 15.7771254
[12,] 19.4020921 -27.7534209
[13,] -3.2695551 19.4020921
[14,] -1.8850271 -3.2695551
[15,] 6.5921583 -1.8850271
[16,] -17.1703913 6.5921583
[17,] -29.5535121 -17.1703913
[18,] -8.6895139 -29.5535121
[19,] -7.4957557 -8.6895139
[20,] 22.6560653 -7.4957557
[21,] -5.2093401 22.6560653
[22,] -40.1644146 -5.2093401
[23,] -20.6347459 -40.1644146
[24,] -9.3009462 -20.6347459
[25,] 31.0934244 -9.3009462
[26,] -0.9592328 31.0934244
[27,] 26.4795335 -0.9592328
[28,] -28.0524199 26.4795335
[29,] 19.0572900 -28.0524199
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 23.3651806 12.9272918
2 12.4104539 23.3651806
3 -6.4798361 12.4104539
4 27.4884251 -6.4798361
5 -15.1455067 27.4884251
6 16.0595013 -15.1455067
7 1.9094352 16.0595013
8 -5.1809374 1.9094352
9 -8.2734210 -5.1809374
10 15.7771254 -8.2734210
11 -27.7534209 15.7771254
12 19.4020921 -27.7534209
13 -3.2695551 19.4020921
14 -1.8850271 -3.2695551
15 6.5921583 -1.8850271
16 -17.1703913 6.5921583
17 -29.5535121 -17.1703913
18 -8.6895139 -29.5535121
19 -7.4957557 -8.6895139
20 22.6560653 -7.4957557
21 -5.2093401 22.6560653
22 -40.1644146 -5.2093401
23 -20.6347459 -40.1644146
24 -9.3009462 -20.6347459
25 31.0934244 -9.3009462
26 -0.9592328 31.0934244
27 26.4795335 -0.9592328
28 -28.0524199 26.4795335
29 19.0572900 -28.0524199
> 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/7uaux1316887052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8nl8e1316887052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9zkf11316887052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/103q551316887052.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/113j3z1316887052.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/12a5ly1316887052.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/13rzzs1316887052.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/14r6el1316887052.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/15h8j41316887052.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/16trjt1316887052.tab")
+ }
>
> try(system("convert tmp/1reb01316887052.ps tmp/1reb01316887052.png",intern=TRUE))
character(0)
> try(system("convert tmp/21jb41316887052.ps tmp/21jb41316887052.png",intern=TRUE))
character(0)
> try(system("convert tmp/32cex1316887052.ps tmp/32cex1316887052.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vq2l1316887052.ps tmp/4vq2l1316887052.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ole01316887052.ps tmp/5ole01316887052.png",intern=TRUE))
character(0)
> try(system("convert tmp/61r7l1316887052.ps tmp/61r7l1316887052.png",intern=TRUE))
character(0)
> try(system("convert tmp/7uaux1316887052.ps tmp/7uaux1316887052.png",intern=TRUE))
character(0)
> try(system("convert tmp/8nl8e1316887052.ps tmp/8nl8e1316887052.png",intern=TRUE))
character(0)
> try(system("convert tmp/9zkf11316887052.ps tmp/9zkf11316887052.png",intern=TRUE))
character(0)
> try(system("convert tmp/103q551316887052.ps tmp/103q551316887052.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.977 0.470 3.461