R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
Natural language support but running in an English locale
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 = '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)
> 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
us/ch eu/us
1 1.08 1.39
2 1.12 1.34
3 1.12 1.33
4 1.16 1.30
5 1.16 1.28
6 1.16 1.29
7 1.16 1.29
8 1.15 1.28
9 1.17 1.27
10 1.16 1.26
11 1.19 1.29
12 1.13 1.36
13 1.14 1.33
14 1.13 1.35
15 1.16 1.31
16 1.17 1.30
17 1.14 1.32
18 1.14 1.33
19 1.11 1.36
20 1.12 1.35
21 1.08 1.40
22 1.07 1.41
23 1.09 1.40
24 1.08 1.40
25 1.08 1.40
26 1.08 1.41
27 1.09 1.40
28 1.08 1.39
29 1.07 1.41
30 1.07 1.42
31 1.07 1.43
32 1.08 1.42
33 1.07 1.42
34 1.06 1.43
35 1.06 1.43
36 1.06 1.43
37 1.04 1.46
38 1.03 1.47
39 1.03 1.47
40 1.04 1.46
41 1.03 1.47
42 1.02 1.49
43 1.01 1.50
44 1.03 1.47
45 1.02 1.48
46 1.01 1.49
47 1.02 1.49
48 1.01 1.50
49 1.02 1.48
50 1.03 1.46
51 1.04 1.43
52 1.04 1.44
53 1.03 1.43
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `eu/us`
2.1094 -0.7344
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.0291829 -0.0038707 0.0001927 0.0048805 0.0280026
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.10936 0.02818 74.85 <2e-16 ***
`eu/us` -0.73439 0.02018 -36.39 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.01024 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/freestat/rcomp/tmp/1v6kn1290348729.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/freestat/rcomp/tmp/26xjq1290348729.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/36xjq1290348729.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4z7it1290348729.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5z7it1290348729.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-8.558440e-03 -5.277900e-03 -1.262179e-02 5.346532e-03 -9.341252e-03
6 7 8 9 10
-1.997360e-03 -1.997360e-03 -1.934125e-02 -6.685144e-03 -2.402904e-02
11 12 13 14 15
2.800264e-02 1.940988e-02 7.378208e-03 1.206599e-02 1.269042e-02
16 17 18 19 20
1.534653e-02 3.431588e-05 7.378208e-03 -5.901159e-04 2.065992e-03
21 22 23 24 25
-1.214548e-03 -3.870656e-03 8.785452e-03 -1.214548e-03 -1.214548e-03
26 27 28 29 30
6.129344e-03 8.785452e-03 -8.558440e-03 -3.870656e-03 3.473237e-03
31 32 33 34 35
1.081713e-02 1.347324e-02 3.473237e-03 8.171286e-04 8.171286e-04
36 37 38 39 40
8.171286e-04 2.848805e-03 1.926969e-04 1.926969e-04 2.848805e-03
41 42 43 44 45
1.926969e-04 4.880481e-03 2.224373e-03 1.926969e-04 -2.463411e-03
46 47 48 49 50
-5.119519e-03 4.880481e-03 2.224373e-03 -2.463411e-03 -7.151195e-03
51 52 53
-1.918287e-02 -1.183898e-02 -2.918287e-02
> postscript(file="/var/www/html/freestat/rcomp/tmp/6z7it1290348729.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 -8.558440e-03 NA
1 -5.277900e-03 -8.558440e-03
2 -1.262179e-02 -5.277900e-03
3 5.346532e-03 -1.262179e-02
4 -9.341252e-03 5.346532e-03
5 -1.997360e-03 -9.341252e-03
6 -1.997360e-03 -1.997360e-03
7 -1.934125e-02 -1.997360e-03
8 -6.685144e-03 -1.934125e-02
9 -2.402904e-02 -6.685144e-03
10 2.800264e-02 -2.402904e-02
11 1.940988e-02 2.800264e-02
12 7.378208e-03 1.940988e-02
13 1.206599e-02 7.378208e-03
14 1.269042e-02 1.206599e-02
15 1.534653e-02 1.269042e-02
16 3.431588e-05 1.534653e-02
17 7.378208e-03 3.431588e-05
18 -5.901159e-04 7.378208e-03
19 2.065992e-03 -5.901159e-04
20 -1.214548e-03 2.065992e-03
21 -3.870656e-03 -1.214548e-03
22 8.785452e-03 -3.870656e-03
23 -1.214548e-03 8.785452e-03
24 -1.214548e-03 -1.214548e-03
25 6.129344e-03 -1.214548e-03
26 8.785452e-03 6.129344e-03
27 -8.558440e-03 8.785452e-03
28 -3.870656e-03 -8.558440e-03
29 3.473237e-03 -3.870656e-03
30 1.081713e-02 3.473237e-03
31 1.347324e-02 1.081713e-02
32 3.473237e-03 1.347324e-02
33 8.171286e-04 3.473237e-03
34 8.171286e-04 8.171286e-04
35 8.171286e-04 8.171286e-04
36 2.848805e-03 8.171286e-04
37 1.926969e-04 2.848805e-03
38 1.926969e-04 1.926969e-04
39 2.848805e-03 1.926969e-04
40 1.926969e-04 2.848805e-03
41 4.880481e-03 1.926969e-04
42 2.224373e-03 4.880481e-03
43 1.926969e-04 2.224373e-03
44 -2.463411e-03 1.926969e-04
45 -5.119519e-03 -2.463411e-03
46 4.880481e-03 -5.119519e-03
47 2.224373e-03 4.880481e-03
48 -2.463411e-03 2.224373e-03
49 -7.151195e-03 -2.463411e-03
50 -1.918287e-02 -7.151195e-03
51 -1.183898e-02 -1.918287e-02
52 -2.918287e-02 -1.183898e-02
53 NA -2.918287e-02
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -5.277900e-03 -8.558440e-03
[2,] -1.262179e-02 -5.277900e-03
[3,] 5.346532e-03 -1.262179e-02
[4,] -9.341252e-03 5.346532e-03
[5,] -1.997360e-03 -9.341252e-03
[6,] -1.997360e-03 -1.997360e-03
[7,] -1.934125e-02 -1.997360e-03
[8,] -6.685144e-03 -1.934125e-02
[9,] -2.402904e-02 -6.685144e-03
[10,] 2.800264e-02 -2.402904e-02
[11,] 1.940988e-02 2.800264e-02
[12,] 7.378208e-03 1.940988e-02
[13,] 1.206599e-02 7.378208e-03
[14,] 1.269042e-02 1.206599e-02
[15,] 1.534653e-02 1.269042e-02
[16,] 3.431588e-05 1.534653e-02
[17,] 7.378208e-03 3.431588e-05
[18,] -5.901159e-04 7.378208e-03
[19,] 2.065992e-03 -5.901159e-04
[20,] -1.214548e-03 2.065992e-03
[21,] -3.870656e-03 -1.214548e-03
[22,] 8.785452e-03 -3.870656e-03
[23,] -1.214548e-03 8.785452e-03
[24,] -1.214548e-03 -1.214548e-03
[25,] 6.129344e-03 -1.214548e-03
[26,] 8.785452e-03 6.129344e-03
[27,] -8.558440e-03 8.785452e-03
[28,] -3.870656e-03 -8.558440e-03
[29,] 3.473237e-03 -3.870656e-03
[30,] 1.081713e-02 3.473237e-03
[31,] 1.347324e-02 1.081713e-02
[32,] 3.473237e-03 1.347324e-02
[33,] 8.171286e-04 3.473237e-03
[34,] 8.171286e-04 8.171286e-04
[35,] 8.171286e-04 8.171286e-04
[36,] 2.848805e-03 8.171286e-04
[37,] 1.926969e-04 2.848805e-03
[38,] 1.926969e-04 1.926969e-04
[39,] 2.848805e-03 1.926969e-04
[40,] 1.926969e-04 2.848805e-03
[41,] 4.880481e-03 1.926969e-04
[42,] 2.224373e-03 4.880481e-03
[43,] 1.926969e-04 2.224373e-03
[44,] -2.463411e-03 1.926969e-04
[45,] -5.119519e-03 -2.463411e-03
[46,] 4.880481e-03 -5.119519e-03
[47,] 2.224373e-03 4.880481e-03
[48,] -2.463411e-03 2.224373e-03
[49,] -7.151195e-03 -2.463411e-03
[50,] -1.918287e-02 -7.151195e-03
[51,] -1.183898e-02 -1.918287e-02
[52,] -2.918287e-02 -1.183898e-02
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -5.277900e-03 -8.558440e-03
2 -1.262179e-02 -5.277900e-03
3 5.346532e-03 -1.262179e-02
4 -9.341252e-03 5.346532e-03
5 -1.997360e-03 -9.341252e-03
6 -1.997360e-03 -1.997360e-03
7 -1.934125e-02 -1.997360e-03
8 -6.685144e-03 -1.934125e-02
9 -2.402904e-02 -6.685144e-03
10 2.800264e-02 -2.402904e-02
11 1.940988e-02 2.800264e-02
12 7.378208e-03 1.940988e-02
13 1.206599e-02 7.378208e-03
14 1.269042e-02 1.206599e-02
15 1.534653e-02 1.269042e-02
16 3.431588e-05 1.534653e-02
17 7.378208e-03 3.431588e-05
18 -5.901159e-04 7.378208e-03
19 2.065992e-03 -5.901159e-04
20 -1.214548e-03 2.065992e-03
21 -3.870656e-03 -1.214548e-03
22 8.785452e-03 -3.870656e-03
23 -1.214548e-03 8.785452e-03
24 -1.214548e-03 -1.214548e-03
25 6.129344e-03 -1.214548e-03
26 8.785452e-03 6.129344e-03
27 -8.558440e-03 8.785452e-03
28 -3.870656e-03 -8.558440e-03
29 3.473237e-03 -3.870656e-03
30 1.081713e-02 3.473237e-03
31 1.347324e-02 1.081713e-02
32 3.473237e-03 1.347324e-02
33 8.171286e-04 3.473237e-03
34 8.171286e-04 8.171286e-04
35 8.171286e-04 8.171286e-04
36 2.848805e-03 8.171286e-04
37 1.926969e-04 2.848805e-03
38 1.926969e-04 1.926969e-04
39 2.848805e-03 1.926969e-04
40 1.926969e-04 2.848805e-03
41 4.880481e-03 1.926969e-04
42 2.224373e-03 4.880481e-03
43 1.926969e-04 2.224373e-03
44 -2.463411e-03 1.926969e-04
45 -5.119519e-03 -2.463411e-03
46 4.880481e-03 -5.119519e-03
47 2.224373e-03 4.880481e-03
48 -2.463411e-03 2.224373e-03
49 -7.151195e-03 -2.463411e-03
50 -1.918287e-02 -7.151195e-03
51 -1.183898e-02 -1.918287e-02
52 -2.918287e-02 -1.183898e-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/freestat/rcomp/tmp/7rghw1290348729.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8rghw1290348729.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9rghw1290348729.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/106pf51290348729.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/freestat/rcomp/tmp/11gze71290348729.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/freestat/rcomp/tmp/125it11290348729.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/freestat/rcomp/tmp/138ia71290348729.tab")
>
> try(system("convert tmp/1v6kn1290348729.ps tmp/1v6kn1290348729.png",intern=TRUE))
character(0)
> try(system("convert tmp/26xjq1290348729.ps tmp/26xjq1290348729.png",intern=TRUE))
character(0)
> try(system("convert tmp/36xjq1290348729.ps tmp/36xjq1290348729.png",intern=TRUE))
character(0)
> try(system("convert tmp/4z7it1290348729.ps tmp/4z7it1290348729.png",intern=TRUE))
character(0)
> try(system("convert tmp/5z7it1290348729.ps tmp/5z7it1290348729.png",intern=TRUE))
character(0)
> try(system("convert tmp/6z7it1290348729.ps tmp/6z7it1290348729.png",intern=TRUE))
character(0)
> try(system("convert tmp/7rghw1290348729.ps tmp/7rghw1290348729.png",intern=TRUE))
character(0)
> try(system("convert tmp/8rghw1290348729.ps tmp/8rghw1290348729.png",intern=TRUE))
character(0)
> try(system("convert tmp/9rghw1290348729.ps tmp/9rghw1290348729.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.036 2.250 3.914