R version 2.12.0 (2010-10-15)
Copyright (C) 2010 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.
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(31514
+ ,-9
+ ,0
+ ,8.3
+ ,1.2
+ ,27071
+ ,-13
+ ,4
+ ,8.2
+ ,1.7
+ ,29462
+ ,-18
+ ,5
+ ,8
+ ,1.8
+ ,26105
+ ,-11
+ ,-7
+ ,7.9
+ ,1.5
+ ,22397
+ ,-9
+ ,-2
+ ,7.6
+ ,1
+ ,23843
+ ,-10
+ ,1
+ ,7.6
+ ,1.6
+ ,21705
+ ,-13
+ ,3
+ ,8.3
+ ,1.5
+ ,18089
+ ,-11
+ ,-2
+ ,8.4
+ ,1.8
+ ,20764
+ ,-5
+ ,-6
+ ,8.4
+ ,1.8
+ ,25316
+ ,-15
+ ,10
+ ,8.4
+ ,1.6
+ ,17704
+ ,-6
+ ,-9
+ ,8.4
+ ,1.9
+ ,15548
+ ,-6
+ ,0
+ ,8.6
+ ,1.7
+ ,28029
+ ,-3
+ ,-3
+ ,8.9
+ ,1.6
+ ,29383
+ ,-1
+ ,-2
+ ,8.8
+ ,1.3
+ ,36438
+ ,-3
+ ,2
+ ,8.3
+ ,1.1
+ ,32034
+ ,-4
+ ,1
+ ,7.5
+ ,1.9
+ ,22679
+ ,-6
+ ,2
+ ,7.2
+ ,2.6
+ ,24319
+ ,0
+ ,-6
+ ,7.4
+ ,2.3
+ ,18004
+ ,-4
+ ,4
+ ,8.8
+ ,2.4
+ ,17537
+ ,-2
+ ,-2
+ ,9.3
+ ,2.2
+ ,20366
+ ,-2
+ ,0
+ ,9.3
+ ,2
+ ,22782
+ ,-6
+ ,4
+ ,8.7
+ ,2.9
+ ,19169
+ ,-7
+ ,1
+ ,8.2
+ ,2.6
+ ,13807
+ ,-6
+ ,-1
+ ,8.3
+ ,2.3
+ ,29743
+ ,-6
+ ,0
+ ,8.5
+ ,2.3
+ ,25591
+ ,-3
+ ,-3
+ ,8.6
+ ,2.6
+ ,29096
+ ,-2
+ ,-1
+ ,8.5
+ ,3.1
+ ,26482
+ ,-5
+ ,3
+ ,8.2
+ ,2.8
+ ,22405
+ ,-11
+ ,6
+ ,8.1
+ ,2.5
+ ,27044
+ ,-11
+ ,0
+ ,7.9
+ ,2.9
+ ,17970
+ ,-11
+ ,0
+ ,8.6
+ ,3.1
+ ,18730
+ ,-10
+ ,-1
+ ,8.7
+ ,3.1
+ ,19684
+ ,-14
+ ,4
+ ,8.7
+ ,3.2
+ ,19785
+ ,-8
+ ,-6
+ ,8.5
+ ,2.5
+ ,18479
+ ,-9
+ ,1
+ ,8.4
+ ,2.6
+ ,10698
+ ,-5
+ ,-4
+ ,8.5
+ ,2.9
+ ,31956
+ ,-1
+ ,-4
+ ,8.7
+ ,2.6
+ ,29506
+ ,-2
+ ,1
+ ,8.7
+ ,2.4
+ ,34506
+ ,-5
+ ,3
+ ,8.6
+ ,1.7
+ ,27165
+ ,-4
+ ,-1
+ ,8.5
+ ,2
+ ,26736
+ ,-6
+ ,2
+ ,8.3
+ ,2.2
+ ,23691
+ ,-2
+ ,-4
+ ,8
+ ,1.9
+ ,18157
+ ,-2
+ ,0
+ ,8.2
+ ,1.6
+ ,17328
+ ,-2
+ ,0
+ ,8.1
+ ,1.6
+ ,18205
+ ,-2
+ ,0
+ ,8.1
+ ,1.2
+ ,20995
+ ,2
+ ,-4
+ ,8
+ ,1.2
+ ,17382
+ ,1
+ ,1
+ ,7.9
+ ,1.5
+ ,9367
+ ,-8
+ ,9
+ ,7.9
+ ,1.6
+ ,31124
+ ,-1
+ ,-7
+ ,8
+ ,1.7
+ ,26551
+ ,1
+ ,-2
+ ,8
+ ,1.8
+ ,30651
+ ,-1
+ ,2
+ ,7.9
+ ,1.8
+ ,25859
+ ,2
+ ,-3
+ ,8
+ ,1.8
+ ,25100
+ ,2
+ ,0
+ ,7.7
+ ,1.3
+ ,25778
+ ,1
+ ,1
+ ,7.2
+ ,1.3
+ ,20418
+ ,-1
+ ,2
+ ,7.5
+ ,1.4
+ ,18688
+ ,-2
+ ,1
+ ,7.3
+ ,1.1
+ ,20424
+ ,-2
+ ,0
+ ,7
+ ,1.5
+ ,24776
+ ,-1
+ ,-1
+ ,7
+ ,2.2
+ ,19814
+ ,-8
+ ,7
+ ,7
+ ,2.9
+ ,12738
+ ,-4
+ ,-4
+ ,7.2
+ ,3.1
+ ,31566
+ ,-6
+ ,2
+ ,7.3
+ ,3.5
+ ,30111
+ ,-3
+ ,-3
+ ,7.1
+ ,3.6
+ ,30019
+ ,-3
+ ,0
+ ,6.8
+ ,4.4
+ ,31934
+ ,-7
+ ,4
+ ,6.4
+ ,4.2
+ ,25826
+ ,-9
+ ,2
+ ,6.1
+ ,5.2
+ ,26835
+ ,-11
+ ,2
+ ,6.5
+ ,5.8
+ ,20205
+ ,-13
+ ,2
+ ,7.7
+ ,5.9
+ ,17789
+ ,-11
+ ,-2
+ ,7.9
+ ,5.4
+ ,20520
+ ,-9
+ ,-2
+ ,7.5
+ ,5.5
+ ,22518
+ ,-17
+ ,8
+ ,6.9
+ ,4.7
+ ,15572
+ ,-22
+ ,5
+ ,6.6
+ ,3.1
+ ,11509
+ ,-25
+ ,3
+ ,6.9
+ ,2.6
+ ,25447
+ ,-20
+ ,-5
+ ,7.7
+ ,2.3
+ ,24090
+ ,-24
+ ,4
+ ,8
+ ,1.9
+ ,27786
+ ,-24
+ ,0
+ ,8
+ ,0.6
+ ,26195
+ ,-22
+ ,-2
+ ,7.7
+ ,0.6
+ ,20516
+ ,-19
+ ,-3
+ ,7.3
+ ,-0.4
+ ,22759
+ ,-18
+ ,-1
+ ,7.4
+ ,-1.1
+ ,19028
+ ,-17
+ ,-1
+ ,8.1
+ ,-1.7
+ ,16971
+ ,-11
+ ,-6
+ ,8.3
+ ,-0.8
+ ,20036
+ ,-11
+ ,0
+ ,8.1
+ ,-1.2
+ ,22485
+ ,-12
+ ,1
+ ,7.9
+ ,-1
+ ,18730
+ ,-10
+ ,-2
+ ,7.9
+ ,-0.1
+ ,14538
+ ,-15
+ ,5
+ ,8.3
+ ,0.3)
+ ,dim=c(5
+ ,84)
+ ,dimnames=list(c('Inschrijvingen'
+ ,'Consumentenvertrouwen'
+ ,'Evolutie_consumentenvertrouwen'
+ ,'Totaal_Werkloosheid'
+ ,'Algemene_index')
+ ,1:84))
> y <- array(NA,dim=c(5,84),dimnames=list(c('Inschrijvingen','Consumentenvertrouwen','Evolutie_consumentenvertrouwen','Totaal_Werkloosheid','Algemene_index'),1:84))
> 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 = '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
Inschrijvingen Consumentenvertrouwen Evolutie_consumentenvertrouwen
1 31514 -9 0
2 27071 -13 4
3 29462 -18 5
4 26105 -11 -7
5 22397 -9 -2
6 23843 -10 1
7 21705 -13 3
8 18089 -11 -2
9 20764 -5 -6
10 25316 -15 10
11 17704 -6 -9
12 15548 -6 0
13 28029 -3 -3
14 29383 -1 -2
15 36438 -3 2
16 32034 -4 1
17 22679 -6 2
18 24319 0 -6
19 18004 -4 4
20 17537 -2 -2
21 20366 -2 0
22 22782 -6 4
23 19169 -7 1
24 13807 -6 -1
25 29743 -6 0
26 25591 -3 -3
27 29096 -2 -1
28 26482 -5 3
29 22405 -11 6
30 27044 -11 0
31 17970 -11 0
32 18730 -10 -1
33 19684 -14 4
34 19785 -8 -6
35 18479 -9 1
36 10698 -5 -4
37 31956 -1 -4
38 29506 -2 1
39 34506 -5 3
40 27165 -4 -1
41 26736 -6 2
42 23691 -2 -4
43 18157 -2 0
44 17328 -2 0
45 18205 -2 0
46 20995 2 -4
47 17382 1 1
48 9367 -8 9
49 31124 -1 -7
50 26551 1 -2
51 30651 -1 2
52 25859 2 -3
53 25100 2 0
54 25778 1 1
55 20418 -1 2
56 18688 -2 1
57 20424 -2 0
58 24776 -1 -1
59 19814 -8 7
60 12738 -4 -4
61 31566 -6 2
62 30111 -3 -3
63 30019 -3 0
64 31934 -7 4
65 25826 -9 2
66 26835 -11 2
67 20205 -13 2
68 17789 -11 -2
69 20520 -9 -2
70 22518 -17 8
71 15572 -22 5
72 11509 -25 3
73 25447 -20 -5
74 24090 -24 4
75 27786 -24 0
76 26195 -22 -2
77 20516 -19 -3
78 22759 -18 -1
79 19028 -17 -1
80 16971 -11 -6
81 20036 -11 0
82 22485 -12 1
83 18730 -10 -2
84 14538 -15 5
Totaal_Werkloosheid Algemene_index M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 8.3 1.2 1 0 0 0 0 0 0 0 0 0 0
2 8.2 1.7 0 1 0 0 0 0 0 0 0 0 0
3 8.0 1.8 0 0 1 0 0 0 0 0 0 0 0
4 7.9 1.5 0 0 0 1 0 0 0 0 0 0 0
5 7.6 1.0 0 0 0 0 1 0 0 0 0 0 0
6 7.6 1.6 0 0 0 0 0 1 0 0 0 0 0
7 8.3 1.5 0 0 0 0 0 0 1 0 0 0 0
8 8.4 1.8 0 0 0 0 0 0 0 1 0 0 0
9 8.4 1.8 0 0 0 0 0 0 0 0 1 0 0
10 8.4 1.6 0 0 0 0 0 0 0 0 0 1 0
11 8.4 1.9 0 0 0 0 0 0 0 0 0 0 1
12 8.6 1.7 0 0 0 0 0 0 0 0 0 0 0
13 8.9 1.6 1 0 0 0 0 0 0 0 0 0 0
14 8.8 1.3 0 1 0 0 0 0 0 0 0 0 0
15 8.3 1.1 0 0 1 0 0 0 0 0 0 0 0
16 7.5 1.9 0 0 0 1 0 0 0 0 0 0 0
17 7.2 2.6 0 0 0 0 1 0 0 0 0 0 0
18 7.4 2.3 0 0 0 0 0 1 0 0 0 0 0
19 8.8 2.4 0 0 0 0 0 0 1 0 0 0 0
20 9.3 2.2 0 0 0 0 0 0 0 1 0 0 0
21 9.3 2.0 0 0 0 0 0 0 0 0 1 0 0
22 8.7 2.9 0 0 0 0 0 0 0 0 0 1 0
23 8.2 2.6 0 0 0 0 0 0 0 0 0 0 1
24 8.3 2.3 0 0 0 0 0 0 0 0 0 0 0
25 8.5 2.3 1 0 0 0 0 0 0 0 0 0 0
26 8.6 2.6 0 1 0 0 0 0 0 0 0 0 0
27 8.5 3.1 0 0 1 0 0 0 0 0 0 0 0
28 8.2 2.8 0 0 0 1 0 0 0 0 0 0 0
29 8.1 2.5 0 0 0 0 1 0 0 0 0 0 0
30 7.9 2.9 0 0 0 0 0 1 0 0 0 0 0
31 8.6 3.1 0 0 0 0 0 0 1 0 0 0 0
32 8.7 3.1 0 0 0 0 0 0 0 1 0 0 0
33 8.7 3.2 0 0 0 0 0 0 0 0 1 0 0
34 8.5 2.5 0 0 0 0 0 0 0 0 0 1 0
35 8.4 2.6 0 0 0 0 0 0 0 0 0 0 1
36 8.5 2.9 0 0 0 0 0 0 0 0 0 0 0
37 8.7 2.6 1 0 0 0 0 0 0 0 0 0 0
38 8.7 2.4 0 1 0 0 0 0 0 0 0 0 0
39 8.6 1.7 0 0 1 0 0 0 0 0 0 0 0
40 8.5 2.0 0 0 0 1 0 0 0 0 0 0 0
41 8.3 2.2 0 0 0 0 1 0 0 0 0 0 0
42 8.0 1.9 0 0 0 0 0 1 0 0 0 0 0
43 8.2 1.6 0 0 0 0 0 0 1 0 0 0 0
44 8.1 1.6 0 0 0 0 0 0 0 1 0 0 0
45 8.1 1.2 0 0 0 0 0 0 0 0 1 0 0
46 8.0 1.2 0 0 0 0 0 0 0 0 0 1 0
47 7.9 1.5 0 0 0 0 0 0 0 0 0 0 1
48 7.9 1.6 0 0 0 0 0 0 0 0 0 0 0
49 8.0 1.7 1 0 0 0 0 0 0 0 0 0 0
50 8.0 1.8 0 1 0 0 0 0 0 0 0 0 0
51 7.9 1.8 0 0 1 0 0 0 0 0 0 0 0
52 8.0 1.8 0 0 0 1 0 0 0 0 0 0 0
53 7.7 1.3 0 0 0 0 1 0 0 0 0 0 0
54 7.2 1.3 0 0 0 0 0 1 0 0 0 0 0
55 7.5 1.4 0 0 0 0 0 0 1 0 0 0 0
56 7.3 1.1 0 0 0 0 0 0 0 1 0 0 0
57 7.0 1.5 0 0 0 0 0 0 0 0 1 0 0
58 7.0 2.2 0 0 0 0 0 0 0 0 0 1 0
59 7.0 2.9 0 0 0 0 0 0 0 0 0 0 1
60 7.2 3.1 0 0 0 0 0 0 0 0 0 0 0
61 7.3 3.5 1 0 0 0 0 0 0 0 0 0 0
62 7.1 3.6 0 1 0 0 0 0 0 0 0 0 0
63 6.8 4.4 0 0 1 0 0 0 0 0 0 0 0
64 6.4 4.2 0 0 0 1 0 0 0 0 0 0 0
65 6.1 5.2 0 0 0 0 1 0 0 0 0 0 0
66 6.5 5.8 0 0 0 0 0 1 0 0 0 0 0
67 7.7 5.9 0 0 0 0 0 0 1 0 0 0 0
68 7.9 5.4 0 0 0 0 0 0 0 1 0 0 0
69 7.5 5.5 0 0 0 0 0 0 0 0 1 0 0
70 6.9 4.7 0 0 0 0 0 0 0 0 0 1 0
71 6.6 3.1 0 0 0 0 0 0 0 0 0 0 1
72 6.9 2.6 0 0 0 0 0 0 0 0 0 0 0
73 7.7 2.3 1 0 0 0 0 0 0 0 0 0 0
74 8.0 1.9 0 1 0 0 0 0 0 0 0 0 0
75 8.0 0.6 0 0 1 0 0 0 0 0 0 0 0
76 7.7 0.6 0 0 0 1 0 0 0 0 0 0 0
77 7.3 -0.4 0 0 0 0 1 0 0 0 0 0 0
78 7.4 -1.1 0 0 0 0 0 1 0 0 0 0 0
79 8.1 -1.7 0 0 0 0 0 0 1 0 0 0 0
80 8.3 -0.8 0 0 0 0 0 0 0 1 0 0 0
81 8.1 -1.2 0 0 0 0 0 0 0 0 1 0 0
82 7.9 -1.0 0 0 0 0 0 0 0 0 0 1 0
83 7.9 -0.1 0 0 0 0 0 0 0 0 0 0 1
84 8.3 0.3 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Consumentenvertrouwen
15316.89 114.50
Evolutie_consumentenvertrouwen Totaal_Werkloosheid
165.69 -244.27
Algemene_index M1
80.52 17577.39
M2 M3
14741.72 18266.44
M4 M5
15324.49 10791.10
M6 M7
12224.07 6632.16
M8 M9
5502.96 7345.22
M10 M11
9767.73 5439.17
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4724.2 -1376.6 -99.5 1310.3 4805.6
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 15316.89 3262.83 4.694 1.34e-05 ***
Consumentenvertrouwen 114.50 33.61 3.407 0.00111 **
Evolutie_consumentenvertrouwen 165.69 64.83 2.556 0.01283 *
Totaal_Werkloosheid -244.27 375.12 -0.651 0.51714
Algemene_index 80.52 152.77 0.527 0.59986
M1 17577.39 1032.41 17.026 < 2e-16 ***
M2 14741.72 1014.78 14.527 < 2e-16 ***
M3 18266.44 1007.97 18.122 < 2e-16 ***
M4 15324.49 1018.30 15.049 < 2e-16 ***
M5 10791.10 1024.90 10.529 6.37e-16 ***
M6 12224.07 1039.11 11.764 < 2e-16 ***
M7 6632.16 1008.91 6.574 8.25e-09 ***
M8 5502.96 1025.57 5.366 1.05e-06 ***
M9 7345.22 1014.88 7.238 5.29e-10 ***
M10 9767.73 1008.58 9.685 1.99e-14 ***
M11 5439.17 1009.30 5.389 9.58e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1881 on 68 degrees of freedom
Multiple R-squared: 0.9111, Adjusted R-squared: 0.8914
F-statistic: 46.43 on 15 and 68 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,] 0.163851061 0.327702121 0.836148939
[2,] 0.193343765 0.386687530 0.806656235
[3,] 0.128648286 0.257296573 0.871351714
[4,] 0.092753383 0.185506766 0.907246617
[5,] 0.047505001 0.095010002 0.952494999
[6,] 0.027363003 0.054726006 0.972636997
[7,] 0.033432314 0.066864627 0.966567686
[8,] 0.019486987 0.038973975 0.980513013
[9,] 0.010284170 0.020568340 0.989715830
[10,] 0.005357645 0.010715290 0.994642355
[11,] 0.052912347 0.105824695 0.947087653
[12,] 0.596251450 0.807497101 0.403748550
[13,] 0.547805839 0.904388323 0.452194161
[14,] 0.550665286 0.898669428 0.449334714
[15,] 0.467721879 0.935443758 0.532278121
[16,] 0.404841254 0.809682507 0.595158746
[17,] 0.331727806 0.663455613 0.668272194
[18,] 0.294705279 0.589410559 0.705294721
[19,] 0.381562246 0.763124492 0.618437754
[20,] 0.372721943 0.745443887 0.627278057
[21,] 0.529229668 0.941540664 0.470770332
[22,] 0.453218427 0.906436853 0.546781573
[23,] 0.706007248 0.587985505 0.293992752
[24,] 0.659064342 0.681871316 0.340935658
[25,] 0.672032064 0.655935872 0.327967936
[26,] 0.663915199 0.672169602 0.336084801
[27,] 0.701101444 0.597797112 0.298898556
[28,] 0.692621376 0.614757247 0.307378624
[29,] 0.676133637 0.647732727 0.323866363
[30,] 0.911294018 0.177411964 0.088705982
[31,] 0.909190602 0.181618795 0.090809398
[32,] 0.891246093 0.217507814 0.108753907
[33,] 0.849401053 0.301197894 0.150598947
[34,] 0.966983985 0.066032029 0.033016015
[35,] 0.958121369 0.083757263 0.041878631
[36,] 0.963534516 0.072930968 0.036465484
[37,] 0.971091914 0.057816172 0.028908086
[38,] 0.960747780 0.078504440 0.039252220
[39,] 0.956014051 0.087971898 0.043985949
[40,] 0.936313954 0.127372092 0.063686046
[41,] 0.904141430 0.191717141 0.095858570
[42,] 0.937536002 0.124927995 0.062463998
[43,] 0.901226127 0.197547745 0.098773873
[44,] 0.897539463 0.204921075 0.102460537
[45,] 0.995806151 0.008387697 0.004193849
[46,] 0.997221925 0.005556149 0.002778075
[47,] 0.989120005 0.021759990 0.010879995
> postscript(file="/var/www/rcomp/tmp/1u2wl1292677520.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2ntdo1292677520.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3ntdo1292677520.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4ntdo1292677520.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5glur1292677520.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 = 84
Frequency = 1
1 2 3 4 5 6
1581.03721 -295.75365 -1079.56656 -308.06592 -573.17288 -991.03416
7 8 9 10 11 12
2654.02704 766.97073 1575.47876 2214.97711 1025.05550 2881.93734
13 14 15 16 17 18
-1979.53936 1815.15835 4805.63268 3363.95006 -1523.99722 -605.41125
19 20 21 22 23 24
-2193.52022 -627.91455 43.54307 -386.77150 842.39528 1185.03872
25 26 27 28 29 30
-573.18855 -1735.67457 -2265.97524 -2306.41877 -1660.37229 2458.76467
31 32 33 34 35 36
-868.44756 1096.37695 -170.39721 -1514.46882 430.25263 -1540.83938
37 38 39 40 41 42
1754.77638 1442.57698 2961.90960 -937.44594 2833.90541 -1157.02719
43 44 45 46 47 48
-1688.88997 -1413.11138 -2346.16074 -1798.33292 -1845.32697 -4724.24322
49 50 51 52 53 54
1321.34151 -1481.52007 -1364.44305 -2705.09822 539.18744 -389.10600
55 56 57 58 59 60
-28.66356 -373.95901 -420.01123 1504.30109 290.45372 51.00684
61 62 63 64 65 66
528.67630 2337.40308 -1914.09991 2656.47964 1488.45910 1342.88984
67 68 69 70 71 72
818.86729 54.96038 608.93956 -638.64734 -2130.94166 33.66725
73 74 75 76 77 78
-2633.10348 -2082.19011 -1143.45752 236.59916 -1104.00956 -659.07591
79 80 81 82 83 84
1306.62696 496.67688 708.60778 618.94239 1388.11150 2113.43246
> postscript(file="/var/www/rcomp/tmp/6glur1292677520.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 = 84
Frequency = 1
lag(myerror, k = 1) myerror
0 1581.03721 NA
1 -295.75365 1581.03721
2 -1079.56656 -295.75365
3 -308.06592 -1079.56656
4 -573.17288 -308.06592
5 -991.03416 -573.17288
6 2654.02704 -991.03416
7 766.97073 2654.02704
8 1575.47876 766.97073
9 2214.97711 1575.47876
10 1025.05550 2214.97711
11 2881.93734 1025.05550
12 -1979.53936 2881.93734
13 1815.15835 -1979.53936
14 4805.63268 1815.15835
15 3363.95006 4805.63268
16 -1523.99722 3363.95006
17 -605.41125 -1523.99722
18 -2193.52022 -605.41125
19 -627.91455 -2193.52022
20 43.54307 -627.91455
21 -386.77150 43.54307
22 842.39528 -386.77150
23 1185.03872 842.39528
24 -573.18855 1185.03872
25 -1735.67457 -573.18855
26 -2265.97524 -1735.67457
27 -2306.41877 -2265.97524
28 -1660.37229 -2306.41877
29 2458.76467 -1660.37229
30 -868.44756 2458.76467
31 1096.37695 -868.44756
32 -170.39721 1096.37695
33 -1514.46882 -170.39721
34 430.25263 -1514.46882
35 -1540.83938 430.25263
36 1754.77638 -1540.83938
37 1442.57698 1754.77638
38 2961.90960 1442.57698
39 -937.44594 2961.90960
40 2833.90541 -937.44594
41 -1157.02719 2833.90541
42 -1688.88997 -1157.02719
43 -1413.11138 -1688.88997
44 -2346.16074 -1413.11138
45 -1798.33292 -2346.16074
46 -1845.32697 -1798.33292
47 -4724.24322 -1845.32697
48 1321.34151 -4724.24322
49 -1481.52007 1321.34151
50 -1364.44305 -1481.52007
51 -2705.09822 -1364.44305
52 539.18744 -2705.09822
53 -389.10600 539.18744
54 -28.66356 -389.10600
55 -373.95901 -28.66356
56 -420.01123 -373.95901
57 1504.30109 -420.01123
58 290.45372 1504.30109
59 51.00684 290.45372
60 528.67630 51.00684
61 2337.40308 528.67630
62 -1914.09991 2337.40308
63 2656.47964 -1914.09991
64 1488.45910 2656.47964
65 1342.88984 1488.45910
66 818.86729 1342.88984
67 54.96038 818.86729
68 608.93956 54.96038
69 -638.64734 608.93956
70 -2130.94166 -638.64734
71 33.66725 -2130.94166
72 -2633.10348 33.66725
73 -2082.19011 -2633.10348
74 -1143.45752 -2082.19011
75 236.59916 -1143.45752
76 -1104.00956 236.59916
77 -659.07591 -1104.00956
78 1306.62696 -659.07591
79 496.67688 1306.62696
80 708.60778 496.67688
81 618.94239 708.60778
82 1388.11150 618.94239
83 2113.43246 1388.11150
84 NA 2113.43246
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -295.75365 1581.03721
[2,] -1079.56656 -295.75365
[3,] -308.06592 -1079.56656
[4,] -573.17288 -308.06592
[5,] -991.03416 -573.17288
[6,] 2654.02704 -991.03416
[7,] 766.97073 2654.02704
[8,] 1575.47876 766.97073
[9,] 2214.97711 1575.47876
[10,] 1025.05550 2214.97711
[11,] 2881.93734 1025.05550
[12,] -1979.53936 2881.93734
[13,] 1815.15835 -1979.53936
[14,] 4805.63268 1815.15835
[15,] 3363.95006 4805.63268
[16,] -1523.99722 3363.95006
[17,] -605.41125 -1523.99722
[18,] -2193.52022 -605.41125
[19,] -627.91455 -2193.52022
[20,] 43.54307 -627.91455
[21,] -386.77150 43.54307
[22,] 842.39528 -386.77150
[23,] 1185.03872 842.39528
[24,] -573.18855 1185.03872
[25,] -1735.67457 -573.18855
[26,] -2265.97524 -1735.67457
[27,] -2306.41877 -2265.97524
[28,] -1660.37229 -2306.41877
[29,] 2458.76467 -1660.37229
[30,] -868.44756 2458.76467
[31,] 1096.37695 -868.44756
[32,] -170.39721 1096.37695
[33,] -1514.46882 -170.39721
[34,] 430.25263 -1514.46882
[35,] -1540.83938 430.25263
[36,] 1754.77638 -1540.83938
[37,] 1442.57698 1754.77638
[38,] 2961.90960 1442.57698
[39,] -937.44594 2961.90960
[40,] 2833.90541 -937.44594
[41,] -1157.02719 2833.90541
[42,] -1688.88997 -1157.02719
[43,] -1413.11138 -1688.88997
[44,] -2346.16074 -1413.11138
[45,] -1798.33292 -2346.16074
[46,] -1845.32697 -1798.33292
[47,] -4724.24322 -1845.32697
[48,] 1321.34151 -4724.24322
[49,] -1481.52007 1321.34151
[50,] -1364.44305 -1481.52007
[51,] -2705.09822 -1364.44305
[52,] 539.18744 -2705.09822
[53,] -389.10600 539.18744
[54,] -28.66356 -389.10600
[55,] -373.95901 -28.66356
[56,] -420.01123 -373.95901
[57,] 1504.30109 -420.01123
[58,] 290.45372 1504.30109
[59,] 51.00684 290.45372
[60,] 528.67630 51.00684
[61,] 2337.40308 528.67630
[62,] -1914.09991 2337.40308
[63,] 2656.47964 -1914.09991
[64,] 1488.45910 2656.47964
[65,] 1342.88984 1488.45910
[66,] 818.86729 1342.88984
[67,] 54.96038 818.86729
[68,] 608.93956 54.96038
[69,] -638.64734 608.93956
[70,] -2130.94166 -638.64734
[71,] 33.66725 -2130.94166
[72,] -2633.10348 33.66725
[73,] -2082.19011 -2633.10348
[74,] -1143.45752 -2082.19011
[75,] 236.59916 -1143.45752
[76,] -1104.00956 236.59916
[77,] -659.07591 -1104.00956
[78,] 1306.62696 -659.07591
[79,] 496.67688 1306.62696
[80,] 708.60778 496.67688
[81,] 618.94239 708.60778
[82,] 1388.11150 618.94239
[83,] 2113.43246 1388.11150
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -295.75365 1581.03721
2 -1079.56656 -295.75365
3 -308.06592 -1079.56656
4 -573.17288 -308.06592
5 -991.03416 -573.17288
6 2654.02704 -991.03416
7 766.97073 2654.02704
8 1575.47876 766.97073
9 2214.97711 1575.47876
10 1025.05550 2214.97711
11 2881.93734 1025.05550
12 -1979.53936 2881.93734
13 1815.15835 -1979.53936
14 4805.63268 1815.15835
15 3363.95006 4805.63268
16 -1523.99722 3363.95006
17 -605.41125 -1523.99722
18 -2193.52022 -605.41125
19 -627.91455 -2193.52022
20 43.54307 -627.91455
21 -386.77150 43.54307
22 842.39528 -386.77150
23 1185.03872 842.39528
24 -573.18855 1185.03872
25 -1735.67457 -573.18855
26 -2265.97524 -1735.67457
27 -2306.41877 -2265.97524
28 -1660.37229 -2306.41877
29 2458.76467 -1660.37229
30 -868.44756 2458.76467
31 1096.37695 -868.44756
32 -170.39721 1096.37695
33 -1514.46882 -170.39721
34 430.25263 -1514.46882
35 -1540.83938 430.25263
36 1754.77638 -1540.83938
37 1442.57698 1754.77638
38 2961.90960 1442.57698
39 -937.44594 2961.90960
40 2833.90541 -937.44594
41 -1157.02719 2833.90541
42 -1688.88997 -1157.02719
43 -1413.11138 -1688.88997
44 -2346.16074 -1413.11138
45 -1798.33292 -2346.16074
46 -1845.32697 -1798.33292
47 -4724.24322 -1845.32697
48 1321.34151 -4724.24322
49 -1481.52007 1321.34151
50 -1364.44305 -1481.52007
51 -2705.09822 -1364.44305
52 539.18744 -2705.09822
53 -389.10600 539.18744
54 -28.66356 -389.10600
55 -373.95901 -28.66356
56 -420.01123 -373.95901
57 1504.30109 -420.01123
58 290.45372 1504.30109
59 51.00684 290.45372
60 528.67630 51.00684
61 2337.40308 528.67630
62 -1914.09991 2337.40308
63 2656.47964 -1914.09991
64 1488.45910 2656.47964
65 1342.88984 1488.45910
66 818.86729 1342.88984
67 54.96038 818.86729
68 608.93956 54.96038
69 -638.64734 608.93956
70 -2130.94166 -638.64734
71 33.66725 -2130.94166
72 -2633.10348 33.66725
73 -2082.19011 -2633.10348
74 -1143.45752 -2082.19011
75 236.59916 -1143.45752
76 -1104.00956 236.59916
77 -659.07591 -1104.00956
78 1306.62696 -659.07591
79 496.67688 1306.62696
80 708.60778 496.67688
81 618.94239 708.60778
82 1388.11150 618.94239
83 2113.43246 1388.11150
> 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/rcomp/tmp/7qcuc1292677520.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8qcuc1292677520.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9j3tf1292677520.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10j3tf1292677520.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/1154931292677520.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/rcomp/tmp/1284q91292677520.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/rcomp/tmp/13mwn01292677520.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/rcomp/tmp/14ipoi1292677521.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/rcomp/tmp/15l7no1292677521.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/rcomp/tmp/16zz3x1292677521.tab")
+ }
>
> try(system("convert tmp/1u2wl1292677520.ps tmp/1u2wl1292677520.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ntdo1292677520.ps tmp/2ntdo1292677520.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ntdo1292677520.ps tmp/3ntdo1292677520.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ntdo1292677520.ps tmp/4ntdo1292677520.png",intern=TRUE))
character(0)
> try(system("convert tmp/5glur1292677520.ps tmp/5glur1292677520.png",intern=TRUE))
character(0)
> try(system("convert tmp/6glur1292677520.ps tmp/6glur1292677520.png",intern=TRUE))
character(0)
> try(system("convert tmp/7qcuc1292677520.ps tmp/7qcuc1292677520.png",intern=TRUE))
character(0)
> try(system("convert tmp/8qcuc1292677520.ps tmp/8qcuc1292677520.png",intern=TRUE))
character(0)
> try(system("convert tmp/9j3tf1292677520.ps tmp/9j3tf1292677520.png",intern=TRUE))
character(0)
> try(system("convert tmp/10j3tf1292677520.ps tmp/10j3tf1292677520.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.400 1.650 5.077