R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(1.2935,123.10,1.2811,123.08,1.2773,122.52,1.2602,119.30,1.2542,119.87,1.2634,122.07,1.2653,121.92,1.2660,121.93,1.2675,122.17,1.2525,120.34,1.2530,121.81,1.2747,124.77,1.2891,127.89,1.2756,124.29,1.2770,124.86,1.2870,127.40,1.2820,127.35,1.2822,126.38),dim=c(2,18),dimnames=list(c('dollar','yen'),1:18))
> y <- array(NA,dim=c(2,18),dimnames=list(c('dollar','yen'),1:18))
> 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'
> #'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
dollar yen M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 1.2935 123.10 1 0 0 0 0 0 0 0 0 0 0 1
2 1.2811 123.08 0 1 0 0 0 0 0 0 0 0 0 2
3 1.2773 122.52 0 0 1 0 0 0 0 0 0 0 0 3
4 1.2602 119.30 0 0 0 1 0 0 0 0 0 0 0 4
5 1.2542 119.87 0 0 0 0 1 0 0 0 0 0 0 5
6 1.2634 122.07 0 0 0 0 0 1 0 0 0 0 0 6
7 1.2653 121.92 0 0 0 0 0 0 1 0 0 0 0 7
8 1.2660 121.93 0 0 0 0 0 0 0 1 0 0 0 8
9 1.2675 122.17 0 0 0 0 0 0 0 0 1 0 0 9
10 1.2525 120.34 0 0 0 0 0 0 0 0 0 1 0 10
11 1.2530 121.81 0 0 0 0 0 0 0 0 0 0 1 11
12 1.2747 124.77 0 0 0 0 0 0 0 0 0 0 0 12
13 1.2891 127.89 1 0 0 0 0 0 0 0 0 0 0 13
14 1.2756 124.29 0 1 0 0 0 0 0 0 0 0 0 14
15 1.2770 124.86 0 0 1 0 0 0 0 0 0 0 0 15
16 1.2870 127.40 0 0 0 1 0 0 0 0 0 0 0 16
17 1.2820 127.35 0 0 0 0 1 0 0 0 0 0 0 17
18 1.2822 126.38 0 0 0 0 0 1 0 0 0 0 0 18
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) yen M1 M2 M3 M4
0.6823292 0.0048460 0.0079753 0.0048189 0.0046169 0.0037368
M5 M6 M7 M8 M9 M10
-0.0020009 0.0007411 -0.0007002 0.0009736 0.0023329 -0.0027767
M11 t
-0.0083780 -0.0010223
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
1 2 3 4 5 6 7
7.673e-03 -4.518e-04 -3.138e-04 9.279e-05 -1.909e-03 -5.090e-03 -6.505e-19
8 9 10 11 12 13 14
2.168e-19 -4.337e-19 2.168e-19 -1.518e-18 4.337e-18 -7.673e-03 4.518e-04
15 16 17 18
3.138e-04 -9.279e-05 1.909e-03 5.090e-03
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.6823292 0.1856033 3.676 0.0213 *
yen 0.0048460 0.0015445 3.138 0.0349 *
M1 0.0079753 0.0092911 0.858 0.4391
M2 0.0048189 0.0082918 0.581 0.5923
M3 0.0046169 0.0082159 0.562 0.6041
M4 0.0037368 0.0082419 0.453 0.6738
M5 -0.0020009 0.0082501 -0.243 0.8203
M6 0.0007411 0.0082014 0.090 0.9323
M7 -0.0007002 0.0096537 -0.073 0.9457
M8 0.0009736 0.0097077 0.100 0.9249
M9 0.0023329 0.0097211 0.240 0.8221
M10 -0.0027767 0.0109936 -0.253 0.8130
M11 -0.0083780 0.0102261 -0.819 0.4586
t -0.0010223 0.0006852 -1.492 0.2100
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.006661 on 4 degrees of freedom
Multiple R-squared: 0.9345, Adjusted R-squared: 0.7217
F-statistic: 4.392 on 13 and 4 DF, p-value: 0.08202
> 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/1j63z1227787849.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2svc61227787849.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3lbbe1227787849.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4oezi1227787849.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5tenz1227787849.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 = 18
Frequency = 1
1 2 3 4 5
7.672623e-03 -4.517543e-04 -3.137527e-04 9.278658e-05 -1.909480e-03
6 7 8 9 10
-5.090422e-03 -6.505213e-19 2.168404e-19 -4.336809e-19 2.168404e-19
11 12 13 14 15
-1.517883e-18 4.336809e-18 -7.672623e-03 4.517543e-04 3.137527e-04
16 17 18
-9.278658e-05 1.909480e-03 5.090422e-03
> postscript(file="/var/www/html/rcomp/tmp/6pu5t1227787849.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 = 18
Frequency = 1
lag(myerror, k = 1) myerror
0 7.672623e-03 NA
1 -4.517543e-04 7.672623e-03
2 -3.137527e-04 -4.517543e-04
3 9.278658e-05 -3.137527e-04
4 -1.909480e-03 9.278658e-05
5 -5.090422e-03 -1.909480e-03
6 -6.505213e-19 -5.090422e-03
7 2.168404e-19 -6.505213e-19
8 -4.336809e-19 2.168404e-19
9 2.168404e-19 -4.336809e-19
10 -1.517883e-18 2.168404e-19
11 4.336809e-18 -1.517883e-18
12 -7.672623e-03 4.336809e-18
13 4.517543e-04 -7.672623e-03
14 3.137527e-04 4.517543e-04
15 -9.278658e-05 3.137527e-04
16 1.909480e-03 -9.278658e-05
17 5.090422e-03 1.909480e-03
18 NA 5.090422e-03
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.517543e-04 7.672623e-03
[2,] -3.137527e-04 -4.517543e-04
[3,] 9.278658e-05 -3.137527e-04
[4,] -1.909480e-03 9.278658e-05
[5,] -5.090422e-03 -1.909480e-03
[6,] -6.505213e-19 -5.090422e-03
[7,] 2.168404e-19 -6.505213e-19
[8,] -4.336809e-19 2.168404e-19
[9,] 2.168404e-19 -4.336809e-19
[10,] -1.517883e-18 2.168404e-19
[11,] 4.336809e-18 -1.517883e-18
[12,] -7.672623e-03 4.336809e-18
[13,] 4.517543e-04 -7.672623e-03
[14,] 3.137527e-04 4.517543e-04
[15,] -9.278658e-05 3.137527e-04
[16,] 1.909480e-03 -9.278658e-05
[17,] 5.090422e-03 1.909480e-03
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.517543e-04 7.672623e-03
2 -3.137527e-04 -4.517543e-04
3 9.278658e-05 -3.137527e-04
4 -1.909480e-03 9.278658e-05
5 -5.090422e-03 -1.909480e-03
6 -6.505213e-19 -5.090422e-03
7 2.168404e-19 -6.505213e-19
8 -4.336809e-19 2.168404e-19
9 2.168404e-19 -4.336809e-19
10 -1.517883e-18 2.168404e-19
11 4.336809e-18 -1.517883e-18
12 -7.672623e-03 4.336809e-18
13 4.517543e-04 -7.672623e-03
14 3.137527e-04 4.517543e-04
15 -9.278658e-05 3.137527e-04
16 1.909480e-03 -9.278658e-05
17 5.090422e-03 1.909480e-03
> 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/7t34y1227787849.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8d3x21227787849.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/97f3m1227787849.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning message:
In dropInf(r.w/(s * sqrt(1 - hii))) :
Not plotting observations with leverage one:
7, 8, 9, 10, 11, 12
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/102nqm1227787849.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ozem1227787849.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/120mus1227787849.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/1336hr1227787849.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/149wlp1227787849.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/15lz541227787849.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/16u98r1227787849.tab")
+ }
>
> system("convert tmp/1j63z1227787849.ps tmp/1j63z1227787849.png")
> system("convert tmp/2svc61227787849.ps tmp/2svc61227787849.png")
> system("convert tmp/3lbbe1227787849.ps tmp/3lbbe1227787849.png")
> system("convert tmp/4oezi1227787849.ps tmp/4oezi1227787849.png")
> system("convert tmp/5tenz1227787849.ps tmp/5tenz1227787849.png")
> system("convert tmp/6pu5t1227787849.ps tmp/6pu5t1227787849.png")
> system("convert tmp/7t34y1227787849.ps tmp/7t34y1227787849.png")
> system("convert tmp/8d3x21227787849.ps tmp/8d3x21227787849.png")
> system("convert tmp/97f3m1227787849.ps tmp/97f3m1227787849.png")
> system("convert tmp/102nqm1227787849.ps tmp/102nqm1227787849.png")
convert: unable to open image `tmp/102nqm1227787849.ps': No such file or directory.
convert: missing an image filename `tmp/102nqm1227787849.png'.
>
>
> proc.time()
user system elapsed
1.868 1.303 2.342