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.
R is a collaborative project with many contributors.
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
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1.39,1.08,1.34,1.12,1.33,1.12,1.3,1.16,1.28,1.16,1.29,1.16,1.29,1.16,1.28,1.15,1.27,1.17,1.26,1.16,1.29,1.19,1.36,1.13,1.33,1.14,1.35,1.13,1.31,1.16,1.3,1.17,1.32,1.14,1.33,1.14,1.36,1.11,1.35,1.12,1.4,1.08,1.41,1.07,1.4,1.09,1.4,1.08,1.4,1.08,1.41,1.08,1.4,1.09,1.39,1.08,1.41,1.07,1.42,1.07,1.43,1.07,1.42,1.08,1.42,1.07,1.43,1.06,1.43,1.06,1.43,1.06,1.46,1.04,1.47,1.03,1.47,1.03,1.46,1.04,1.47,1.03,1.49,1.02,1.5,1.01,1.47,1.03,1.48,1.02,1.49,1.01,1.49,1.02,1.5,1.01,1.48,1.02,1.46,1.03,1.43,1.04,1.44,1.04,1.43,1.03),dim=c(2,53),dimnames=list(c('eu/us','us/ch'),1:53))
> y <- array(NA,dim=c(2,53),dimnames=list(c('eu/us','us/ch'),1:53))
> 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)
> 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
eu/us us/ch
1 1.39 1.08
2 1.34 1.12
3 1.33 1.12
4 1.30 1.16
5 1.28 1.16
6 1.29 1.16
7 1.29 1.16
8 1.28 1.15
9 1.27 1.17
10 1.26 1.16
11 1.29 1.19
12 1.36 1.13
13 1.33 1.14
14 1.35 1.13
15 1.31 1.16
16 1.30 1.17
17 1.32 1.14
18 1.33 1.14
19 1.36 1.11
20 1.35 1.12
21 1.40 1.08
22 1.41 1.07
23 1.40 1.09
24 1.40 1.08
25 1.40 1.08
26 1.41 1.08
27 1.40 1.09
28 1.39 1.08
29 1.41 1.07
30 1.42 1.07
31 1.43 1.07
32 1.42 1.08
33 1.42 1.07
34 1.43 1.06
35 1.43 1.06
36 1.43 1.06
37 1.46 1.04
38 1.47 1.03
39 1.47 1.03
40 1.46 1.04
41 1.47 1.03
42 1.49 1.02
43 1.50 1.01
44 1.47 1.03
45 1.48 1.02
46 1.49 1.01
47 1.49 1.02
48 1.50 1.01
49 1.48 1.02
50 1.46 1.03
51 1.43 1.04
52 1.44 1.04
53 1.43 1.03
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `us/ch`
2.817 -1.311
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.036956 -0.006502 0.002380 0.007274 0.032834
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.81747 0.03914 71.98 <2e-16 ***
`us/ch` -1.31118 0.03603 -36.39 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.01368 on 51 degrees of freedom
Multiple R-squared: 0.9629, Adjusted R-squared: 0.9622
F-statistic: 1324 on 1 and 51 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/rcomp/tmp/140ix1290500082.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/240ix1290500082.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/340ix1290500082.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4x9001290500082.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5x9001290500082.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 53
Frequency = 1
1 2 3 4 5
-1.139659e-02 -8.949284e-03 -1.894928e-02 3.498023e-03 -1.650198e-02
6 7 8 9 10
-6.501977e-03 -6.501977e-03 -2.961380e-02 -1.339015e-02 -3.650198e-02
11 12 13 14 15
3.283350e-02 2.416254e-02 7.274370e-03 1.416254e-02 1.349802e-02
16 17 18 19 20
1.660985e-02 -2.725630e-03 7.274370e-03 -2.061111e-03 1.050716e-03
21 22 23 24 25
-1.396591e-03 -4.508418e-03 1.171524e-02 -1.396591e-03 -1.396591e-03
26 27 28 29 30
8.603409e-03 1.171524e-02 -1.139659e-02 -4.508418e-03 5.491582e-03
31 32 33 34 35
1.549158e-02 1.860341e-02 5.491582e-03 2.379755e-03 2.379755e-03
36 37 38 39 40
2.379755e-03 6.156102e-03 3.044275e-03 3.044275e-03 6.156102e-03
41 42 43 44 45
3.044275e-03 9.932448e-03 6.820622e-03 3.044275e-03 -6.755165e-05
46 47 48 49 50
-3.179378e-03 9.932448e-03 6.820622e-03 -6.755165e-05 -6.955725e-03
51 52 53
-2.384390e-02 -1.384390e-02 -3.695572e-02
> postscript(file="/var/www/html/rcomp/tmp/6x9001290500082.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 = 53
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.139659e-02 NA
1 -8.949284e-03 -1.139659e-02
2 -1.894928e-02 -8.949284e-03
3 3.498023e-03 -1.894928e-02
4 -1.650198e-02 3.498023e-03
5 -6.501977e-03 -1.650198e-02
6 -6.501977e-03 -6.501977e-03
7 -2.961380e-02 -6.501977e-03
8 -1.339015e-02 -2.961380e-02
9 -3.650198e-02 -1.339015e-02
10 3.283350e-02 -3.650198e-02
11 2.416254e-02 3.283350e-02
12 7.274370e-03 2.416254e-02
13 1.416254e-02 7.274370e-03
14 1.349802e-02 1.416254e-02
15 1.660985e-02 1.349802e-02
16 -2.725630e-03 1.660985e-02
17 7.274370e-03 -2.725630e-03
18 -2.061111e-03 7.274370e-03
19 1.050716e-03 -2.061111e-03
20 -1.396591e-03 1.050716e-03
21 -4.508418e-03 -1.396591e-03
22 1.171524e-02 -4.508418e-03
23 -1.396591e-03 1.171524e-02
24 -1.396591e-03 -1.396591e-03
25 8.603409e-03 -1.396591e-03
26 1.171524e-02 8.603409e-03
27 -1.139659e-02 1.171524e-02
28 -4.508418e-03 -1.139659e-02
29 5.491582e-03 -4.508418e-03
30 1.549158e-02 5.491582e-03
31 1.860341e-02 1.549158e-02
32 5.491582e-03 1.860341e-02
33 2.379755e-03 5.491582e-03
34 2.379755e-03 2.379755e-03
35 2.379755e-03 2.379755e-03
36 6.156102e-03 2.379755e-03
37 3.044275e-03 6.156102e-03
38 3.044275e-03 3.044275e-03
39 6.156102e-03 3.044275e-03
40 3.044275e-03 6.156102e-03
41 9.932448e-03 3.044275e-03
42 6.820622e-03 9.932448e-03
43 3.044275e-03 6.820622e-03
44 -6.755165e-05 3.044275e-03
45 -3.179378e-03 -6.755165e-05
46 9.932448e-03 -3.179378e-03
47 6.820622e-03 9.932448e-03
48 -6.755165e-05 6.820622e-03
49 -6.955725e-03 -6.755165e-05
50 -2.384390e-02 -6.955725e-03
51 -1.384390e-02 -2.384390e-02
52 -3.695572e-02 -1.384390e-02
53 NA -3.695572e-02
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -8.949284e-03 -1.139659e-02
[2,] -1.894928e-02 -8.949284e-03
[3,] 3.498023e-03 -1.894928e-02
[4,] -1.650198e-02 3.498023e-03
[5,] -6.501977e-03 -1.650198e-02
[6,] -6.501977e-03 -6.501977e-03
[7,] -2.961380e-02 -6.501977e-03
[8,] -1.339015e-02 -2.961380e-02
[9,] -3.650198e-02 -1.339015e-02
[10,] 3.283350e-02 -3.650198e-02
[11,] 2.416254e-02 3.283350e-02
[12,] 7.274370e-03 2.416254e-02
[13,] 1.416254e-02 7.274370e-03
[14,] 1.349802e-02 1.416254e-02
[15,] 1.660985e-02 1.349802e-02
[16,] -2.725630e-03 1.660985e-02
[17,] 7.274370e-03 -2.725630e-03
[18,] -2.061111e-03 7.274370e-03
[19,] 1.050716e-03 -2.061111e-03
[20,] -1.396591e-03 1.050716e-03
[21,] -4.508418e-03 -1.396591e-03
[22,] 1.171524e-02 -4.508418e-03
[23,] -1.396591e-03 1.171524e-02
[24,] -1.396591e-03 -1.396591e-03
[25,] 8.603409e-03 -1.396591e-03
[26,] 1.171524e-02 8.603409e-03
[27,] -1.139659e-02 1.171524e-02
[28,] -4.508418e-03 -1.139659e-02
[29,] 5.491582e-03 -4.508418e-03
[30,] 1.549158e-02 5.491582e-03
[31,] 1.860341e-02 1.549158e-02
[32,] 5.491582e-03 1.860341e-02
[33,] 2.379755e-03 5.491582e-03
[34,] 2.379755e-03 2.379755e-03
[35,] 2.379755e-03 2.379755e-03
[36,] 6.156102e-03 2.379755e-03
[37,] 3.044275e-03 6.156102e-03
[38,] 3.044275e-03 3.044275e-03
[39,] 6.156102e-03 3.044275e-03
[40,] 3.044275e-03 6.156102e-03
[41,] 9.932448e-03 3.044275e-03
[42,] 6.820622e-03 9.932448e-03
[43,] 3.044275e-03 6.820622e-03
[44,] -6.755165e-05 3.044275e-03
[45,] -3.179378e-03 -6.755165e-05
[46,] 9.932448e-03 -3.179378e-03
[47,] 6.820622e-03 9.932448e-03
[48,] -6.755165e-05 6.820622e-03
[49,] -6.955725e-03 -6.755165e-05
[50,] -2.384390e-02 -6.955725e-03
[51,] -1.384390e-02 -2.384390e-02
[52,] -3.695572e-02 -1.384390e-02
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -8.949284e-03 -1.139659e-02
2 -1.894928e-02 -8.949284e-03
3 3.498023e-03 -1.894928e-02
4 -1.650198e-02 3.498023e-03
5 -6.501977e-03 -1.650198e-02
6 -6.501977e-03 -6.501977e-03
7 -2.961380e-02 -6.501977e-03
8 -1.339015e-02 -2.961380e-02
9 -3.650198e-02 -1.339015e-02
10 3.283350e-02 -3.650198e-02
11 2.416254e-02 3.283350e-02
12 7.274370e-03 2.416254e-02
13 1.416254e-02 7.274370e-03
14 1.349802e-02 1.416254e-02
15 1.660985e-02 1.349802e-02
16 -2.725630e-03 1.660985e-02
17 7.274370e-03 -2.725630e-03
18 -2.061111e-03 7.274370e-03
19 1.050716e-03 -2.061111e-03
20 -1.396591e-03 1.050716e-03
21 -4.508418e-03 -1.396591e-03
22 1.171524e-02 -4.508418e-03
23 -1.396591e-03 1.171524e-02
24 -1.396591e-03 -1.396591e-03
25 8.603409e-03 -1.396591e-03
26 1.171524e-02 8.603409e-03
27 -1.139659e-02 1.171524e-02
28 -4.508418e-03 -1.139659e-02
29 5.491582e-03 -4.508418e-03
30 1.549158e-02 5.491582e-03
31 1.860341e-02 1.549158e-02
32 5.491582e-03 1.860341e-02
33 2.379755e-03 5.491582e-03
34 2.379755e-03 2.379755e-03
35 2.379755e-03 2.379755e-03
36 6.156102e-03 2.379755e-03
37 3.044275e-03 6.156102e-03
38 3.044275e-03 3.044275e-03
39 6.156102e-03 3.044275e-03
40 3.044275e-03 6.156102e-03
41 9.932448e-03 3.044275e-03
42 6.820622e-03 9.932448e-03
43 3.044275e-03 6.820622e-03
44 -6.755165e-05 3.044275e-03
45 -3.179378e-03 -6.755165e-05
46 9.932448e-03 -3.179378e-03
47 6.820622e-03 9.932448e-03
48 -6.755165e-05 6.820622e-03
49 -6.955725e-03 -6.755165e-05
50 -2.384390e-02 -6.955725e-03
51 -1.384390e-02 -2.384390e-02
52 -3.695572e-02 -1.384390e-02
> 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/780h31290500082.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8i9gn1290500082.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9i9gn1290500082.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/104sft1290500082.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/11cw261290500082.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/123lt81290500082.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/137law1290500082.tab")
>
> try(system("convert tmp/140ix1290500082.ps tmp/140ix1290500082.png",intern=TRUE))
character(0)
> try(system("convert tmp/240ix1290500082.ps tmp/240ix1290500082.png",intern=TRUE))
character(0)
> try(system("convert tmp/340ix1290500082.ps tmp/340ix1290500082.png",intern=TRUE))
character(0)
> try(system("convert tmp/4x9001290500082.ps tmp/4x9001290500082.png",intern=TRUE))
character(0)
> try(system("convert tmp/5x9001290500082.ps tmp/5x9001290500082.png",intern=TRUE))
character(0)
> try(system("convert tmp/6x9001290500082.ps tmp/6x9001290500082.png",intern=TRUE))
character(0)
> try(system("convert tmp/780h31290500082.ps tmp/780h31290500082.png",intern=TRUE))
character(0)
> try(system("convert tmp/8i9gn1290500082.ps tmp/8i9gn1290500082.png",intern=TRUE))
character(0)
> try(system("convert tmp/9i9gn1290500082.ps tmp/9i9gn1290500082.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
1.869 1.423 6.100