R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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(455626
+ ,0
+ ,454724
+ ,461251
+ ,470390
+ ,474605
+ ,516847
+ ,0
+ ,455626
+ ,454724
+ ,461251
+ ,470390
+ ,525192
+ ,0
+ ,516847
+ ,455626
+ ,454724
+ ,461251
+ ,522975
+ ,0
+ ,525192
+ ,516847
+ ,455626
+ ,454724
+ ,518585
+ ,0
+ ,522975
+ ,525192
+ ,516847
+ ,455626
+ ,509239
+ ,0
+ ,518585
+ ,522975
+ ,525192
+ ,516847
+ ,512238
+ ,0
+ ,509239
+ ,518585
+ ,522975
+ ,525192
+ ,519164
+ ,0
+ ,512238
+ ,509239
+ ,518585
+ ,522975
+ ,517009
+ ,0
+ ,519164
+ ,512238
+ ,509239
+ ,518585
+ ,509933
+ ,0
+ ,517009
+ ,519164
+ ,512238
+ ,509239
+ ,509127
+ ,0
+ ,509933
+ ,517009
+ ,519164
+ ,512238
+ ,500875
+ ,0
+ ,509127
+ ,509933
+ ,517009
+ ,519164
+ ,506971
+ ,0
+ ,500875
+ ,509127
+ ,509933
+ ,517009
+ ,569323
+ ,0
+ ,506971
+ ,500875
+ ,509127
+ ,509933
+ ,579714
+ ,0
+ ,569323
+ ,506971
+ ,500875
+ ,509127
+ ,577992
+ ,0
+ ,579714
+ ,569323
+ ,506971
+ ,500875
+ ,565644
+ ,0
+ ,577992
+ ,579714
+ ,569323
+ ,506971
+ ,547344
+ ,0
+ ,565644
+ ,577992
+ ,579714
+ ,569323
+ ,554788
+ ,0
+ ,547344
+ ,565644
+ ,577992
+ ,579714
+ ,562325
+ ,0
+ ,554788
+ ,547344
+ ,565644
+ ,577992
+ ,560854
+ ,0
+ ,562325
+ ,554788
+ ,547344
+ ,565644
+ ,555332
+ ,0
+ ,560854
+ ,562325
+ ,554788
+ ,547344
+ ,543599
+ ,0
+ ,555332
+ ,560854
+ ,562325
+ ,554788
+ ,536662
+ ,0
+ ,543599
+ ,555332
+ ,560854
+ ,562325
+ ,542722
+ ,0
+ ,536662
+ ,543599
+ ,555332
+ ,560854
+ ,593530
+ ,0
+ ,542722
+ ,536662
+ ,543599
+ ,555332
+ ,610763
+ ,0
+ ,593530
+ ,542722
+ ,536662
+ ,543599
+ ,612613
+ ,0
+ ,610763
+ ,593530
+ ,542722
+ ,536662
+ ,611324
+ ,0
+ ,612613
+ ,610763
+ ,593530
+ ,542722
+ ,594167
+ ,0
+ ,611324
+ ,612613
+ ,610763
+ ,593530
+ ,595454
+ ,0
+ ,594167
+ ,611324
+ ,612613
+ ,610763
+ ,590865
+ ,0
+ ,595454
+ ,594167
+ ,611324
+ ,612613
+ ,589379
+ ,0
+ ,590865
+ ,595454
+ ,594167
+ ,611324
+ ,584428
+ ,0
+ ,589379
+ ,590865
+ ,595454
+ ,594167
+ ,573100
+ ,0
+ ,584428
+ ,589379
+ ,590865
+ ,595454
+ ,567456
+ ,0
+ ,573100
+ ,584428
+ ,589379
+ ,590865
+ ,569028
+ ,0
+ ,567456
+ ,573100
+ ,584428
+ ,589379
+ ,620735
+ ,0
+ ,569028
+ ,567456
+ ,573100
+ ,584428
+ ,628884
+ ,0
+ ,620735
+ ,569028
+ ,567456
+ ,573100
+ ,628232
+ ,0
+ ,628884
+ ,620735
+ ,569028
+ ,567456
+ ,612117
+ ,0
+ ,628232
+ ,628884
+ ,620735
+ ,569028
+ ,595404
+ ,0
+ ,612117
+ ,628232
+ ,628884
+ ,620735
+ ,597141
+ ,0
+ ,595404
+ ,612117
+ ,628232
+ ,628884
+ ,593408
+ ,0
+ ,597141
+ ,595404
+ ,612117
+ ,628232
+ ,590072
+ ,0
+ ,593408
+ ,597141
+ ,595404
+ ,612117
+ ,579799
+ ,0
+ ,590072
+ ,593408
+ ,597141
+ ,595404
+ ,574205
+ ,0
+ ,579799
+ ,590072
+ ,593408
+ ,597141
+ ,572775
+ ,0
+ ,574205
+ ,579799
+ ,590072
+ ,593408
+ ,572942
+ ,0
+ ,572775
+ ,574205
+ ,579799
+ ,590072
+ ,619567
+ ,0
+ ,572942
+ ,572775
+ ,574205
+ ,579799
+ ,625809
+ ,0
+ ,619567
+ ,572942
+ ,572775
+ ,574205
+ ,619916
+ ,0
+ ,625809
+ ,619567
+ ,572942
+ ,572775
+ ,587625
+ ,0
+ ,619916
+ ,625809
+ ,619567
+ ,572942
+ ,565724
+ ,0
+ ,587625
+ ,619916
+ ,625809
+ ,619567
+ ,557274
+ ,0
+ ,565724
+ ,587625
+ ,619916
+ ,625809
+ ,560576
+ ,0
+ ,557274
+ ,565724
+ ,587625
+ ,619916
+ ,548854
+ ,0
+ ,560576
+ ,557274
+ ,565724
+ ,587625
+ ,531673
+ ,0
+ ,548854
+ ,560576
+ ,557274
+ ,565724
+ ,525919
+ ,0
+ ,531673
+ ,548854
+ ,560576
+ ,557274
+ ,511038
+ ,0
+ ,525919
+ ,531673
+ ,548854
+ ,560576
+ ,498662
+ ,0
+ ,511038
+ ,525919
+ ,531673
+ ,548854
+ ,555362
+ ,0
+ ,498662
+ ,511038
+ ,525919
+ ,531673
+ ,564591
+ ,0
+ ,555362
+ ,498662
+ ,511038
+ ,525919
+ ,541667
+ ,0
+ ,564591
+ ,555362
+ ,498662
+ ,511038
+ ,527070
+ ,0
+ ,541667
+ ,564591
+ ,555362
+ ,498662
+ ,509846
+ ,0
+ ,527070
+ ,541667
+ ,564591
+ ,555362
+ ,514258
+ ,0
+ ,509846
+ ,527070
+ ,541667
+ ,564591
+ ,516922
+ ,0
+ ,514258
+ ,509846
+ ,527070
+ ,541667
+ ,507561
+ ,0
+ ,516922
+ ,514258
+ ,509846
+ ,527070
+ ,492622
+ ,0
+ ,507561
+ ,516922
+ ,514258
+ ,509846
+ ,490243
+ ,0
+ ,492622
+ ,507561
+ ,516922
+ ,514258
+ ,469357
+ ,0
+ ,490243
+ ,492622
+ ,507561
+ ,516922
+ ,477580
+ ,0
+ ,469357
+ ,490243
+ ,492622
+ ,507561
+ ,528379
+ ,0
+ ,477580
+ ,469357
+ ,490243
+ ,492622
+ ,533590
+ ,0
+ ,528379
+ ,477580
+ ,469357
+ ,490243
+ ,517945
+ ,1
+ ,533590
+ ,528379
+ ,477580
+ ,469357
+ ,506174
+ ,1
+ ,517945
+ ,533590
+ ,528379
+ ,477580
+ ,501866
+ ,1
+ ,506174
+ ,517945
+ ,533590
+ ,528379
+ ,516441
+ ,1
+ ,501866
+ ,506174
+ ,517945
+ ,533590
+ ,528222
+ ,1
+ ,516441
+ ,501866
+ ,506174
+ ,517945
+ ,532638
+ ,1
+ ,528222
+ ,516441
+ ,501866
+ ,506174)
+ ,dim=c(6
+ ,81)
+ ,dimnames=list(c('Werkzoekend'
+ ,'Crisis'
+ ,'y-1'
+ ,'y-2'
+ ,'y-3'
+ ,'y-4')
+ ,1:81))
> y <- array(NA,dim=c(6,81),dimnames=list(c('Werkzoekend','Crisis','y-1','y-2','y-3','y-4'),1:81))
> 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
Werkzoekend Crisis y-1 y-2 y-3 y-4 M1 M2 M3 M4 M5 M6 M7 M8 M9
1 455626 0 454724 461251 470390 474605 1 0 0 0 0 0 0 0 0
2 516847 0 455626 454724 461251 470390 0 1 0 0 0 0 0 0 0
3 525192 0 516847 455626 454724 461251 0 0 1 0 0 0 0 0 0
4 522975 0 525192 516847 455626 454724 0 0 0 1 0 0 0 0 0
5 518585 0 522975 525192 516847 455626 0 0 0 0 1 0 0 0 0
6 509239 0 518585 522975 525192 516847 0 0 0 0 0 1 0 0 0
7 512238 0 509239 518585 522975 525192 0 0 0 0 0 0 1 0 0
8 519164 0 512238 509239 518585 522975 0 0 0 0 0 0 0 1 0
9 517009 0 519164 512238 509239 518585 0 0 0 0 0 0 0 0 1
10 509933 0 517009 519164 512238 509239 0 0 0 0 0 0 0 0 0
11 509127 0 509933 517009 519164 512238 0 0 0 0 0 0 0 0 0
12 500875 0 509127 509933 517009 519164 0 0 0 0 0 0 0 0 0
13 506971 0 500875 509127 509933 517009 1 0 0 0 0 0 0 0 0
14 569323 0 506971 500875 509127 509933 0 1 0 0 0 0 0 0 0
15 579714 0 569323 506971 500875 509127 0 0 1 0 0 0 0 0 0
16 577992 0 579714 569323 506971 500875 0 0 0 1 0 0 0 0 0
17 565644 0 577992 579714 569323 506971 0 0 0 0 1 0 0 0 0
18 547344 0 565644 577992 579714 569323 0 0 0 0 0 1 0 0 0
19 554788 0 547344 565644 577992 579714 0 0 0 0 0 0 1 0 0
20 562325 0 554788 547344 565644 577992 0 0 0 0 0 0 0 1 0
21 560854 0 562325 554788 547344 565644 0 0 0 0 0 0 0 0 1
22 555332 0 560854 562325 554788 547344 0 0 0 0 0 0 0 0 0
23 543599 0 555332 560854 562325 554788 0 0 0 0 0 0 0 0 0
24 536662 0 543599 555332 560854 562325 0 0 0 0 0 0 0 0 0
25 542722 0 536662 543599 555332 560854 1 0 0 0 0 0 0 0 0
26 593530 0 542722 536662 543599 555332 0 1 0 0 0 0 0 0 0
27 610763 0 593530 542722 536662 543599 0 0 1 0 0 0 0 0 0
28 612613 0 610763 593530 542722 536662 0 0 0 1 0 0 0 0 0
29 611324 0 612613 610763 593530 542722 0 0 0 0 1 0 0 0 0
30 594167 0 611324 612613 610763 593530 0 0 0 0 0 1 0 0 0
31 595454 0 594167 611324 612613 610763 0 0 0 0 0 0 1 0 0
32 590865 0 595454 594167 611324 612613 0 0 0 0 0 0 0 1 0
33 589379 0 590865 595454 594167 611324 0 0 0 0 0 0 0 0 1
34 584428 0 589379 590865 595454 594167 0 0 0 0 0 0 0 0 0
35 573100 0 584428 589379 590865 595454 0 0 0 0 0 0 0 0 0
36 567456 0 573100 584428 589379 590865 0 0 0 0 0 0 0 0 0
37 569028 0 567456 573100 584428 589379 1 0 0 0 0 0 0 0 0
38 620735 0 569028 567456 573100 584428 0 1 0 0 0 0 0 0 0
39 628884 0 620735 569028 567456 573100 0 0 1 0 0 0 0 0 0
40 628232 0 628884 620735 569028 567456 0 0 0 1 0 0 0 0 0
41 612117 0 628232 628884 620735 569028 0 0 0 0 1 0 0 0 0
42 595404 0 612117 628232 628884 620735 0 0 0 0 0 1 0 0 0
43 597141 0 595404 612117 628232 628884 0 0 0 0 0 0 1 0 0
44 593408 0 597141 595404 612117 628232 0 0 0 0 0 0 0 1 0
45 590072 0 593408 597141 595404 612117 0 0 0 0 0 0 0 0 1
46 579799 0 590072 593408 597141 595404 0 0 0 0 0 0 0 0 0
47 574205 0 579799 590072 593408 597141 0 0 0 0 0 0 0 0 0
48 572775 0 574205 579799 590072 593408 0 0 0 0 0 0 0 0 0
49 572942 0 572775 574205 579799 590072 1 0 0 0 0 0 0 0 0
50 619567 0 572942 572775 574205 579799 0 1 0 0 0 0 0 0 0
51 625809 0 619567 572942 572775 574205 0 0 1 0 0 0 0 0 0
52 619916 0 625809 619567 572942 572775 0 0 0 1 0 0 0 0 0
53 587625 0 619916 625809 619567 572942 0 0 0 0 1 0 0 0 0
54 565724 0 587625 619916 625809 619567 0 0 0 0 0 1 0 0 0
55 557274 0 565724 587625 619916 625809 0 0 0 0 0 0 1 0 0
56 560576 0 557274 565724 587625 619916 0 0 0 0 0 0 0 1 0
57 548854 0 560576 557274 565724 587625 0 0 0 0 0 0 0 0 1
58 531673 0 548854 560576 557274 565724 0 0 0 0 0 0 0 0 0
59 525919 0 531673 548854 560576 557274 0 0 0 0 0 0 0 0 0
60 511038 0 525919 531673 548854 560576 0 0 0 0 0 0 0 0 0
61 498662 0 511038 525919 531673 548854 1 0 0 0 0 0 0 0 0
62 555362 0 498662 511038 525919 531673 0 1 0 0 0 0 0 0 0
63 564591 0 555362 498662 511038 525919 0 0 1 0 0 0 0 0 0
64 541667 0 564591 555362 498662 511038 0 0 0 1 0 0 0 0 0
65 527070 0 541667 564591 555362 498662 0 0 0 0 1 0 0 0 0
66 509846 0 527070 541667 564591 555362 0 0 0 0 0 1 0 0 0
67 514258 0 509846 527070 541667 564591 0 0 0 0 0 0 1 0 0
68 516922 0 514258 509846 527070 541667 0 0 0 0 0 0 0 1 0
69 507561 0 516922 514258 509846 527070 0 0 0 0 0 0 0 0 1
70 492622 0 507561 516922 514258 509846 0 0 0 0 0 0 0 0 0
71 490243 0 492622 507561 516922 514258 0 0 0 0 0 0 0 0 0
72 469357 0 490243 492622 507561 516922 0 0 0 0 0 0 0 0 0
73 477580 0 469357 490243 492622 507561 1 0 0 0 0 0 0 0 0
74 528379 0 477580 469357 490243 492622 0 1 0 0 0 0 0 0 0
75 533590 0 528379 477580 469357 490243 0 0 1 0 0 0 0 0 0
76 517945 1 533590 528379 477580 469357 0 0 0 1 0 0 0 0 0
77 506174 1 517945 533590 528379 477580 0 0 0 0 1 0 0 0 0
78 501866 1 506174 517945 533590 528379 0 0 0 0 0 1 0 0 0
79 516441 1 501866 506174 517945 533590 0 0 0 0 0 0 1 0 0
80 528222 1 516441 501866 506174 517945 0 0 0 0 0 0 0 1 0
81 532638 1 528222 516441 501866 506174 0 0 0 0 0 0 0 0 1
M10 M11 t
1 0 0 1
2 0 0 2
3 0 0 3
4 0 0 4
5 0 0 5
6 0 0 6
7 0 0 7
8 0 0 8
9 0 0 9
10 1 0 10
11 0 1 11
12 0 0 12
13 0 0 13
14 0 0 14
15 0 0 15
16 0 0 16
17 0 0 17
18 0 0 18
19 0 0 19
20 0 0 20
21 0 0 21
22 1 0 22
23 0 1 23
24 0 0 24
25 0 0 25
26 0 0 26
27 0 0 27
28 0 0 28
29 0 0 29
30 0 0 30
31 0 0 31
32 0 0 32
33 0 0 33
34 1 0 34
35 0 1 35
36 0 0 36
37 0 0 37
38 0 0 38
39 0 0 39
40 0 0 40
41 0 0 41
42 0 0 42
43 0 0 43
44 0 0 44
45 0 0 45
46 1 0 46
47 0 1 47
48 0 0 48
49 0 0 49
50 0 0 50
51 0 0 51
52 0 0 52
53 0 0 53
54 0 0 54
55 0 0 55
56 0 0 56
57 0 0 57
58 1 0 58
59 0 1 59
60 0 0 60
61 0 0 61
62 0 0 62
63 0 0 63
64 0 0 64
65 0 0 65
66 0 0 66
67 0 0 67
68 0 0 68
69 0 0 69
70 1 0 70
71 0 1 71
72 0 0 72
73 0 0 73
74 0 0 74
75 0 0 75
76 0 0 76
77 0 0 77
78 0 0 78
79 0 0 79
80 0 0 80
81 0 0 81
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Crisis `y-1` `y-2` `y-3` `y-4`
4.527e+03 9.593e+03 1.015e+00 1.853e-02 1.831e-02 -6.760e-02
M1 M2 M3 M4 M5 M6
1.054e+04 6.309e+04 1.703e+04 -2.024e+03 -9.391e+03 -7.193e+03
M7 M8 M9 M10 M11 t
1.256e+04 1.266e+04 5.038e+03 -1.352e+03 2.791e+03 -1.102e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-14973.7 -2813.7 654.4 2983.1 12204.8
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.527e+03 1.056e+04 0.429 0.669609
Crisis 9.593e+03 3.599e+03 2.665 0.009760 **
`y-1` 1.015e+00 1.239e-01 8.194 1.64e-11 ***
`y-2` 1.853e-02 1.773e-01 0.105 0.917081
`y-3` 1.831e-02 1.762e-01 0.104 0.917550
`y-4` -6.760e-02 1.297e-01 -0.521 0.603990
M1 1.054e+04 3.433e+03 3.070 0.003156 **
M2 6.309e+04 3.463e+03 18.222 < 2e-16 ***
M3 1.703e+04 8.209e+03 2.075 0.042103 *
M4 -2.024e+03 8.547e+03 -0.237 0.813605
M5 -9.391e+03 8.525e+03 -1.102 0.274815
M6 -7.193e+03 3.923e+03 -1.834 0.071421 .
M7 1.256e+04 3.633e+03 3.456 0.000986 ***
M8 1.266e+04 3.800e+03 3.333 0.001443 **
M9 5.038e+03 4.067e+03 1.239 0.220093
M10 -1.352e+03 3.813e+03 -0.354 0.724165
M11 2.791e+03 3.631e+03 0.769 0.444961
t -1.102e+02 4.309e+01 -2.557 0.012978 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5950 on 63 degrees of freedom
Multiple R-squared: 0.9838, Adjusted R-squared: 0.9794
F-statistic: 225 on 17 and 63 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,] 0.203762360 0.407524719 0.7962376
[2,] 0.124875466 0.249750932 0.8751245
[3,] 0.303055483 0.606110966 0.6969445
[4,] 0.192697494 0.385394988 0.8073025
[5,] 0.113102661 0.226205322 0.8868973
[6,] 0.211431209 0.422862418 0.7885688
[7,] 0.159597496 0.319194991 0.8404025
[8,] 0.110639472 0.221278944 0.8893605
[9,] 0.140311103 0.280622206 0.8596889
[10,] 0.105097014 0.210194028 0.8949030
[11,] 0.077485235 0.154970471 0.9225148
[12,] 0.148347768 0.296695537 0.8516522
[13,] 0.101123257 0.202246514 0.8988767
[14,] 0.069640910 0.139281820 0.9303591
[15,] 0.092548434 0.185096867 0.9074516
[16,] 0.060400757 0.120801514 0.9395992
[17,] 0.042872337 0.085744673 0.9571277
[18,] 0.041296942 0.082593884 0.9587031
[19,] 0.031564558 0.063129115 0.9684354
[20,] 0.031575233 0.063150466 0.9684248
[21,] 0.038390612 0.076781224 0.9616094
[22,] 0.023693192 0.047386385 0.9763068
[23,] 0.014256338 0.028512675 0.9857437
[24,] 0.013614666 0.027229332 0.9863853
[25,] 0.008018916 0.016037832 0.9919811
[26,] 0.004907541 0.009815081 0.9950925
[27,] 0.003408283 0.006816566 0.9965917
[28,] 0.010834121 0.021668242 0.9891659
[29,] 0.008750353 0.017500706 0.9912496
[30,] 0.006999002 0.013998005 0.9930010
[31,] 0.003767353 0.007534706 0.9962326
[32,] 0.178466513 0.356933027 0.8215335
[33,] 0.349268066 0.698536133 0.6507319
[34,] 0.282021932 0.564043865 0.7179781
[35,] 0.330957693 0.661915386 0.6690423
[36,] 0.277517417 0.555034835 0.7224826
[37,] 0.199539551 0.399079101 0.8004604
[38,] 0.127966921 0.255933841 0.8720331
[39,] 0.094143826 0.188287652 0.9058562
[40,] 0.065732875 0.131465749 0.9342671
> postscript(file="/var/www/html/rcomp/tmp/11dn81259317184.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2mh2d1259317184.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3fu741259317184.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4k5j01259317184.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xf6w1259317184.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 = 81
Frequency = 1
1 2 3 4 5 6
-5861.0654 2001.4651 -6122.2676 765.6808 4888.3145 1936.1244
7 8 9 10 11 12
-4533.1706 -544.2848 -2172.8674 -1377.5706 1079.9708 -2813.7122
13 14 15 16 17 18
1227.2873 4635.8880 -2090.9167 2983.0564 -1062.1431 -4862.7409
19 20 21 22 23 24
2476.1883 2910.4113 889.4441 1846.5905 -7923.2466 586.7735
25 26 27 28 29 30
3477.5614 -4340.4962 6727.4622 8733.6323 12204.7775 -2647.3744
31 32 33 34 35 36
-2433.1757 -7859.0789 3251.1702 5209.2588 -4928.8861 3633.1077
37 38 39 40 41 42
704.7829 -1652.6278 -494.1165 8381.4438 -585.9153 324.8638
43 44 45 46 47 48
244.9486 -4687.4465 2685.4150 1204.7959 2250.4400 9397.9325
49 50 51 52 53 54
654.4002 -5902.0870 -1156.8824 4817.6706 -14973.6892 -3047.0104
55 56 57 58 59 60
-7782.3358 4696.1312 -4265.8590 -4438.8614 2794.9192 -2589.0606
61 62 63 64 65 66
-10662.9338 5369.4030 3345.4461 -11608.4718 2489.4461 2079.2000
67 68 69 70 71 72
5645.6314 2871.7093 -2209.6957 -2444.2132 6726.8027 -8215.0410
73 74 75 76 77 78
10459.9674 -111.5450 -208.7251 -14073.0121 -2960.7905 6216.9375
79 80 81
6381.9138 2612.5585 1822.3928
> postscript(file="/var/www/html/rcomp/tmp/6fhs11259317184.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 = 81
Frequency = 1
lag(myerror, k = 1) myerror
0 -5861.0654 NA
1 2001.4651 -5861.0654
2 -6122.2676 2001.4651
3 765.6808 -6122.2676
4 4888.3145 765.6808
5 1936.1244 4888.3145
6 -4533.1706 1936.1244
7 -544.2848 -4533.1706
8 -2172.8674 -544.2848
9 -1377.5706 -2172.8674
10 1079.9708 -1377.5706
11 -2813.7122 1079.9708
12 1227.2873 -2813.7122
13 4635.8880 1227.2873
14 -2090.9167 4635.8880
15 2983.0564 -2090.9167
16 -1062.1431 2983.0564
17 -4862.7409 -1062.1431
18 2476.1883 -4862.7409
19 2910.4113 2476.1883
20 889.4441 2910.4113
21 1846.5905 889.4441
22 -7923.2466 1846.5905
23 586.7735 -7923.2466
24 3477.5614 586.7735
25 -4340.4962 3477.5614
26 6727.4622 -4340.4962
27 8733.6323 6727.4622
28 12204.7775 8733.6323
29 -2647.3744 12204.7775
30 -2433.1757 -2647.3744
31 -7859.0789 -2433.1757
32 3251.1702 -7859.0789
33 5209.2588 3251.1702
34 -4928.8861 5209.2588
35 3633.1077 -4928.8861
36 704.7829 3633.1077
37 -1652.6278 704.7829
38 -494.1165 -1652.6278
39 8381.4438 -494.1165
40 -585.9153 8381.4438
41 324.8638 -585.9153
42 244.9486 324.8638
43 -4687.4465 244.9486
44 2685.4150 -4687.4465
45 1204.7959 2685.4150
46 2250.4400 1204.7959
47 9397.9325 2250.4400
48 654.4002 9397.9325
49 -5902.0870 654.4002
50 -1156.8824 -5902.0870
51 4817.6706 -1156.8824
52 -14973.6892 4817.6706
53 -3047.0104 -14973.6892
54 -7782.3358 -3047.0104
55 4696.1312 -7782.3358
56 -4265.8590 4696.1312
57 -4438.8614 -4265.8590
58 2794.9192 -4438.8614
59 -2589.0606 2794.9192
60 -10662.9338 -2589.0606
61 5369.4030 -10662.9338
62 3345.4461 5369.4030
63 -11608.4718 3345.4461
64 2489.4461 -11608.4718
65 2079.2000 2489.4461
66 5645.6314 2079.2000
67 2871.7093 5645.6314
68 -2209.6957 2871.7093
69 -2444.2132 -2209.6957
70 6726.8027 -2444.2132
71 -8215.0410 6726.8027
72 10459.9674 -8215.0410
73 -111.5450 10459.9674
74 -208.7251 -111.5450
75 -14073.0121 -208.7251
76 -2960.7905 -14073.0121
77 6216.9375 -2960.7905
78 6381.9138 6216.9375
79 2612.5585 6381.9138
80 1822.3928 2612.5585
81 NA 1822.3928
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2001.4651 -5861.0654
[2,] -6122.2676 2001.4651
[3,] 765.6808 -6122.2676
[4,] 4888.3145 765.6808
[5,] 1936.1244 4888.3145
[6,] -4533.1706 1936.1244
[7,] -544.2848 -4533.1706
[8,] -2172.8674 -544.2848
[9,] -1377.5706 -2172.8674
[10,] 1079.9708 -1377.5706
[11,] -2813.7122 1079.9708
[12,] 1227.2873 -2813.7122
[13,] 4635.8880 1227.2873
[14,] -2090.9167 4635.8880
[15,] 2983.0564 -2090.9167
[16,] -1062.1431 2983.0564
[17,] -4862.7409 -1062.1431
[18,] 2476.1883 -4862.7409
[19,] 2910.4113 2476.1883
[20,] 889.4441 2910.4113
[21,] 1846.5905 889.4441
[22,] -7923.2466 1846.5905
[23,] 586.7735 -7923.2466
[24,] 3477.5614 586.7735
[25,] -4340.4962 3477.5614
[26,] 6727.4622 -4340.4962
[27,] 8733.6323 6727.4622
[28,] 12204.7775 8733.6323
[29,] -2647.3744 12204.7775
[30,] -2433.1757 -2647.3744
[31,] -7859.0789 -2433.1757
[32,] 3251.1702 -7859.0789
[33,] 5209.2588 3251.1702
[34,] -4928.8861 5209.2588
[35,] 3633.1077 -4928.8861
[36,] 704.7829 3633.1077
[37,] -1652.6278 704.7829
[38,] -494.1165 -1652.6278
[39,] 8381.4438 -494.1165
[40,] -585.9153 8381.4438
[41,] 324.8638 -585.9153
[42,] 244.9486 324.8638
[43,] -4687.4465 244.9486
[44,] 2685.4150 -4687.4465
[45,] 1204.7959 2685.4150
[46,] 2250.4400 1204.7959
[47,] 9397.9325 2250.4400
[48,] 654.4002 9397.9325
[49,] -5902.0870 654.4002
[50,] -1156.8824 -5902.0870
[51,] 4817.6706 -1156.8824
[52,] -14973.6892 4817.6706
[53,] -3047.0104 -14973.6892
[54,] -7782.3358 -3047.0104
[55,] 4696.1312 -7782.3358
[56,] -4265.8590 4696.1312
[57,] -4438.8614 -4265.8590
[58,] 2794.9192 -4438.8614
[59,] -2589.0606 2794.9192
[60,] -10662.9338 -2589.0606
[61,] 5369.4030 -10662.9338
[62,] 3345.4461 5369.4030
[63,] -11608.4718 3345.4461
[64,] 2489.4461 -11608.4718
[65,] 2079.2000 2489.4461
[66,] 5645.6314 2079.2000
[67,] 2871.7093 5645.6314
[68,] -2209.6957 2871.7093
[69,] -2444.2132 -2209.6957
[70,] 6726.8027 -2444.2132
[71,] -8215.0410 6726.8027
[72,] 10459.9674 -8215.0410
[73,] -111.5450 10459.9674
[74,] -208.7251 -111.5450
[75,] -14073.0121 -208.7251
[76,] -2960.7905 -14073.0121
[77,] 6216.9375 -2960.7905
[78,] 6381.9138 6216.9375
[79,] 2612.5585 6381.9138
[80,] 1822.3928 2612.5585
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2001.4651 -5861.0654
2 -6122.2676 2001.4651
3 765.6808 -6122.2676
4 4888.3145 765.6808
5 1936.1244 4888.3145
6 -4533.1706 1936.1244
7 -544.2848 -4533.1706
8 -2172.8674 -544.2848
9 -1377.5706 -2172.8674
10 1079.9708 -1377.5706
11 -2813.7122 1079.9708
12 1227.2873 -2813.7122
13 4635.8880 1227.2873
14 -2090.9167 4635.8880
15 2983.0564 -2090.9167
16 -1062.1431 2983.0564
17 -4862.7409 -1062.1431
18 2476.1883 -4862.7409
19 2910.4113 2476.1883
20 889.4441 2910.4113
21 1846.5905 889.4441
22 -7923.2466 1846.5905
23 586.7735 -7923.2466
24 3477.5614 586.7735
25 -4340.4962 3477.5614
26 6727.4622 -4340.4962
27 8733.6323 6727.4622
28 12204.7775 8733.6323
29 -2647.3744 12204.7775
30 -2433.1757 -2647.3744
31 -7859.0789 -2433.1757
32 3251.1702 -7859.0789
33 5209.2588 3251.1702
34 -4928.8861 5209.2588
35 3633.1077 -4928.8861
36 704.7829 3633.1077
37 -1652.6278 704.7829
38 -494.1165 -1652.6278
39 8381.4438 -494.1165
40 -585.9153 8381.4438
41 324.8638 -585.9153
42 244.9486 324.8638
43 -4687.4465 244.9486
44 2685.4150 -4687.4465
45 1204.7959 2685.4150
46 2250.4400 1204.7959
47 9397.9325 2250.4400
48 654.4002 9397.9325
49 -5902.0870 654.4002
50 -1156.8824 -5902.0870
51 4817.6706 -1156.8824
52 -14973.6892 4817.6706
53 -3047.0104 -14973.6892
54 -7782.3358 -3047.0104
55 4696.1312 -7782.3358
56 -4265.8590 4696.1312
57 -4438.8614 -4265.8590
58 2794.9192 -4438.8614
59 -2589.0606 2794.9192
60 -10662.9338 -2589.0606
61 5369.4030 -10662.9338
62 3345.4461 5369.4030
63 -11608.4718 3345.4461
64 2489.4461 -11608.4718
65 2079.2000 2489.4461
66 5645.6314 2079.2000
67 2871.7093 5645.6314
68 -2209.6957 2871.7093
69 -2444.2132 -2209.6957
70 6726.8027 -2444.2132
71 -8215.0410 6726.8027
72 10459.9674 -8215.0410
73 -111.5450 10459.9674
74 -208.7251 -111.5450
75 -14073.0121 -208.7251
76 -2960.7905 -14073.0121
77 6216.9375 -2960.7905
78 6381.9138 6216.9375
79 2612.5585 6381.9138
80 1822.3928 2612.5585
> 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/7ty6p1259317184.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8f2lj1259317184.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9v28e1259317184.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10trka1259317184.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11d3uz1259317184.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/12kof81259317184.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/13eupj1259317184.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/1449kf1259317184.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/154u7d1259317184.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/161k9v1259317184.tab")
+ }
>
> system("convert tmp/11dn81259317184.ps tmp/11dn81259317184.png")
> system("convert tmp/2mh2d1259317184.ps tmp/2mh2d1259317184.png")
> system("convert tmp/3fu741259317184.ps tmp/3fu741259317184.png")
> system("convert tmp/4k5j01259317184.ps tmp/4k5j01259317184.png")
> system("convert tmp/5xf6w1259317184.ps tmp/5xf6w1259317184.png")
> system("convert tmp/6fhs11259317184.ps tmp/6fhs11259317184.png")
> system("convert tmp/7ty6p1259317184.ps tmp/7ty6p1259317184.png")
> system("convert tmp/8f2lj1259317184.ps tmp/8f2lj1259317184.png")
> system("convert tmp/9v28e1259317184.ps tmp/9v28e1259317184.png")
> system("convert tmp/10trka1259317184.ps tmp/10trka1259317184.png")
>
>
> proc.time()
user system elapsed
2.703 1.595 3.209