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(9939
+ ,2462
+ ,9321
+ ,9769
+ ,9336
+ ,3695
+ ,9939
+ ,9321
+ ,10195
+ ,4831
+ ,9336
+ ,9939
+ ,9464
+ ,5134
+ ,10195
+ ,9336
+ ,10010
+ ,6250
+ ,9464
+ ,10195
+ ,10213
+ ,5760
+ ,10010
+ ,9464
+ ,9563
+ ,6249
+ ,10213
+ ,10010
+ ,9890
+ ,2917
+ ,9563
+ ,10213
+ ,9305
+ ,1741
+ ,9890
+ ,9563
+ ,9391
+ ,2359
+ ,9305
+ ,9890
+ ,9928
+ ,1511
+ ,9391
+ ,9305
+ ,8686
+ ,2059
+ ,9928
+ ,9391
+ ,9843
+ ,2635
+ ,8686
+ ,9928
+ ,9627
+ ,2867
+ ,9843
+ ,8686
+ ,10074
+ ,4403
+ ,9627
+ ,9843
+ ,9503
+ ,5720
+ ,10074
+ ,9627
+ ,10119
+ ,4502
+ ,9503
+ ,10074
+ ,10000
+ ,5749
+ ,10119
+ ,9503
+ ,9313
+ ,5627
+ ,10000
+ ,10119
+ ,9866
+ ,2846
+ ,9313
+ ,10000
+ ,9172
+ ,1762
+ ,9866
+ ,9313
+ ,9241
+ ,2429
+ ,9172
+ ,9866
+ ,9659
+ ,1169
+ ,9241
+ ,9172
+ ,8904
+ ,2154
+ ,9659
+ ,9241
+ ,9755
+ ,2249
+ ,8904
+ ,9659
+ ,9080
+ ,2687
+ ,9755
+ ,8904
+ ,9435
+ ,4359
+ ,9080
+ ,9755
+ ,8971
+ ,5382
+ ,9435
+ ,9080
+ ,10063
+ ,4459
+ ,8971
+ ,9435
+ ,9793
+ ,6398
+ ,10063
+ ,8971
+ ,9454
+ ,4596
+ ,9793
+ ,10063
+ ,9759
+ ,3024
+ ,9454
+ ,9793
+ ,8820
+ ,1887
+ ,9759
+ ,9454
+ ,9403
+ ,2070
+ ,8820
+ ,9759
+ ,9676
+ ,1351
+ ,9403
+ ,8820
+ ,8642
+ ,2218
+ ,9676
+ ,9403
+ ,9402
+ ,2461
+ ,8642
+ ,9676
+ ,9610
+ ,3028
+ ,9402
+ ,8642
+ ,9294
+ ,4784
+ ,9610
+ ,9402
+ ,9448
+ ,4975
+ ,9294
+ ,9610
+ ,10319
+ ,4607
+ ,9448
+ ,9294
+ ,9548
+ ,6249
+ ,10319
+ ,9448
+ ,9801
+ ,4809
+ ,9548
+ ,10319
+ ,9596
+ ,3157
+ ,9801
+ ,9548
+ ,8923
+ ,1910
+ ,9596
+ ,9801
+ ,9746
+ ,2228
+ ,8923
+ ,9596
+ ,9829
+ ,1594
+ ,9746
+ ,8923
+ ,9125
+ ,2467
+ ,9829
+ ,9746
+ ,9782
+ ,2222
+ ,9125
+ ,9829
+ ,9441
+ ,3607
+ ,9782
+ ,9125
+ ,9162
+ ,4685
+ ,9441
+ ,9782
+ ,9915
+ ,4962
+ ,9162
+ ,9441
+ ,10444
+ ,5770
+ ,9915
+ ,9162
+ ,10209
+ ,5480
+ ,10444
+ ,9915
+ ,9985
+ ,5000
+ ,10209
+ ,10444
+ ,9842
+ ,3228
+ ,9985
+ ,10209
+ ,9429
+ ,1993
+ ,9842
+ ,9985
+ ,10132
+ ,2288
+ ,9429
+ ,9842
+ ,9849
+ ,1580
+ ,10132
+ ,9429
+ ,9172
+ ,2111
+ ,9849
+ ,10132
+ ,10313
+ ,2192
+ ,9172
+ ,9849
+ ,9819
+ ,3601
+ ,10313
+ ,9172
+ ,9955
+ ,4665
+ ,9819
+ ,10313
+ ,10048
+ ,4876
+ ,9955
+ ,9819
+ ,10082
+ ,5813
+ ,10048
+ ,9955
+ ,10541
+ ,5589
+ ,10082
+ ,10048
+ ,10208
+ ,5331
+ ,10541
+ ,10082
+ ,10233
+ ,3075
+ ,10208
+ ,10541
+ ,9439
+ ,2002
+ ,10233
+ ,10208
+ ,9963
+ ,2306
+ ,9439
+ ,10233
+ ,10158
+ ,1507
+ ,9963
+ ,9439
+ ,9225
+ ,1992
+ ,10158
+ ,9963
+ ,10474
+ ,2487
+ ,9225
+ ,10158
+ ,9757
+ ,3490
+ ,10474
+ ,9225
+ ,10490
+ ,4647
+ ,9757
+ ,10474
+ ,10281
+ ,5594
+ ,10490
+ ,9757
+ ,10444
+ ,5611
+ ,10281
+ ,10490
+ ,10640
+ ,5788
+ ,10444
+ ,10281
+ ,10695
+ ,6204
+ ,10640
+ ,10444
+ ,10786
+ ,3013
+ ,10695
+ ,10640
+ ,9832
+ ,1931
+ ,10786
+ ,10695
+ ,9747
+ ,2549
+ ,9832
+ ,10786
+ ,10411
+ ,1504
+ ,9747
+ ,9832
+ ,9511
+ ,2090
+ ,10411
+ ,9747
+ ,10402
+ ,2702
+ ,9511
+ ,10411
+ ,9701
+ ,2939
+ ,10402
+ ,9511
+ ,10540
+ ,4500
+ ,9701
+ ,10402
+ ,10112
+ ,6208
+ ,10540
+ ,9701
+ ,10915
+ ,6415
+ ,10112
+ ,10540
+ ,11183
+ ,5657
+ ,10915
+ ,10112
+ ,10384
+ ,5964
+ ,11183
+ ,10915
+ ,10834
+ ,3163
+ ,10384
+ ,11183
+ ,9886
+ ,1997
+ ,10834
+ ,10384
+ ,10216
+ ,2422
+ ,9886
+ ,10834)
+ ,dim=c(4
+ ,94)
+ ,dimnames=list(c('geboortes'
+ ,'huwelijken'
+ ,'geboortes-1'
+ ,'geboortes-2')
+ ,1:94))
> y <- array(NA,dim=c(4,94),dimnames=list(c('geboortes','huwelijken','geboortes-1','geboortes-2'),1:94))
> 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
geboortes huwelijken geboortes-1 geboortes-2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10
1 9939 2462 9321 9769 1 0 0 0 0 0 0 0 0 0
2 9336 3695 9939 9321 0 1 0 0 0 0 0 0 0 0
3 10195 4831 9336 9939 0 0 1 0 0 0 0 0 0 0
4 9464 5134 10195 9336 0 0 0 1 0 0 0 0 0 0
5 10010 6250 9464 10195 0 0 0 0 1 0 0 0 0 0
6 10213 5760 10010 9464 0 0 0 0 0 1 0 0 0 0
7 9563 6249 10213 10010 0 0 0 0 0 0 1 0 0 0
8 9890 2917 9563 10213 0 0 0 0 0 0 0 1 0 0
9 9305 1741 9890 9563 0 0 0 0 0 0 0 0 1 0
10 9391 2359 9305 9890 0 0 0 0 0 0 0 0 0 1
11 9928 1511 9391 9305 0 0 0 0 0 0 0 0 0 0
12 8686 2059 9928 9391 0 0 0 0 0 0 0 0 0 0
13 9843 2635 8686 9928 1 0 0 0 0 0 0 0 0 0
14 9627 2867 9843 8686 0 1 0 0 0 0 0 0 0 0
15 10074 4403 9627 9843 0 0 1 0 0 0 0 0 0 0
16 9503 5720 10074 9627 0 0 0 1 0 0 0 0 0 0
17 10119 4502 9503 10074 0 0 0 0 1 0 0 0 0 0
18 10000 5749 10119 9503 0 0 0 0 0 1 0 0 0 0
19 9313 5627 10000 10119 0 0 0 0 0 0 1 0 0 0
20 9866 2846 9313 10000 0 0 0 0 0 0 0 1 0 0
21 9172 1762 9866 9313 0 0 0 0 0 0 0 0 1 0
22 9241 2429 9172 9866 0 0 0 0 0 0 0 0 0 1
23 9659 1169 9241 9172 0 0 0 0 0 0 0 0 0 0
24 8904 2154 9659 9241 0 0 0 0 0 0 0 0 0 0
25 9755 2249 8904 9659 1 0 0 0 0 0 0 0 0 0
26 9080 2687 9755 8904 0 1 0 0 0 0 0 0 0 0
27 9435 4359 9080 9755 0 0 1 0 0 0 0 0 0 0
28 8971 5382 9435 9080 0 0 0 1 0 0 0 0 0 0
29 10063 4459 8971 9435 0 0 0 0 1 0 0 0 0 0
30 9793 6398 10063 8971 0 0 0 0 0 1 0 0 0 0
31 9454 4596 9793 10063 0 0 0 0 0 0 1 0 0 0
32 9759 3024 9454 9793 0 0 0 0 0 0 0 1 0 0
33 8820 1887 9759 9454 0 0 0 0 0 0 0 0 1 0
34 9403 2070 8820 9759 0 0 0 0 0 0 0 0 0 1
35 9676 1351 9403 8820 0 0 0 0 0 0 0 0 0 0
36 8642 2218 9676 9403 0 0 0 0 0 0 0 0 0 0
37 9402 2461 8642 9676 1 0 0 0 0 0 0 0 0 0
38 9610 3028 9402 8642 0 1 0 0 0 0 0 0 0 0
39 9294 4784 9610 9402 0 0 1 0 0 0 0 0 0 0
40 9448 4975 9294 9610 0 0 0 1 0 0 0 0 0 0
41 10319 4607 9448 9294 0 0 0 0 1 0 0 0 0 0
42 9548 6249 10319 9448 0 0 0 0 0 1 0 0 0 0
43 9801 4809 9548 10319 0 0 0 0 0 0 1 0 0 0
44 9596 3157 9801 9548 0 0 0 0 0 0 0 1 0 0
45 8923 1910 9596 9801 0 0 0 0 0 0 0 0 1 0
46 9746 2228 8923 9596 0 0 0 0 0 0 0 0 0 1
47 9829 1594 9746 8923 0 0 0 0 0 0 0 0 0 0
48 9125 2467 9829 9746 0 0 0 0 0 0 0 0 0 0
49 9782 2222 9125 9829 1 0 0 0 0 0 0 0 0 0
50 9441 3607 9782 9125 0 1 0 0 0 0 0 0 0 0
51 9162 4685 9441 9782 0 0 1 0 0 0 0 0 0 0
52 9915 4962 9162 9441 0 0 0 1 0 0 0 0 0 0
53 10444 5770 9915 9162 0 0 0 0 1 0 0 0 0 0
54 10209 5480 10444 9915 0 0 0 0 0 1 0 0 0 0
55 9985 5000 10209 10444 0 0 0 0 0 0 1 0 0 0
56 9842 3228 9985 10209 0 0 0 0 0 0 0 1 0 0
57 9429 1993 9842 9985 0 0 0 0 0 0 0 0 1 0
58 10132 2288 9429 9842 0 0 0 0 0 0 0 0 0 1
59 9849 1580 10132 9429 0 0 0 0 0 0 0 0 0 0
60 9172 2111 9849 10132 0 0 0 0 0 0 0 0 0 0
61 10313 2192 9172 9849 1 0 0 0 0 0 0 0 0 0
62 9819 3601 10313 9172 0 1 0 0 0 0 0 0 0 0
63 9955 4665 9819 10313 0 0 1 0 0 0 0 0 0 0
64 10048 4876 9955 9819 0 0 0 1 0 0 0 0 0 0
65 10082 5813 10048 9955 0 0 0 0 1 0 0 0 0 0
66 10541 5589 10082 10048 0 0 0 0 0 1 0 0 0 0
67 10208 5331 10541 10082 0 0 0 0 0 0 1 0 0 0
68 10233 3075 10208 10541 0 0 0 0 0 0 0 1 0 0
69 9439 2002 10233 10208 0 0 0 0 0 0 0 0 1 0
70 9963 2306 9439 10233 0 0 0 0 0 0 0 0 0 1
71 10158 1507 9963 9439 0 0 0 0 0 0 0 0 0 0
72 9225 1992 10158 9963 0 0 0 0 0 0 0 0 0 0
73 10474 2487 9225 10158 1 0 0 0 0 0 0 0 0 0
74 9757 3490 10474 9225 0 1 0 0 0 0 0 0 0 0
75 10490 4647 9757 10474 0 0 1 0 0 0 0 0 0 0
76 10281 5594 10490 9757 0 0 0 1 0 0 0 0 0 0
77 10444 5611 10281 10490 0 0 0 0 1 0 0 0 0 0
78 10640 5788 10444 10281 0 0 0 0 0 1 0 0 0 0
79 10695 6204 10640 10444 0 0 0 0 0 0 1 0 0 0
80 10786 3013 10695 10640 0 0 0 0 0 0 0 1 0 0
81 9832 1931 10786 10695 0 0 0 0 0 0 0 0 1 0
82 9747 2549 9832 10786 0 0 0 0 0 0 0 0 0 1
83 10411 1504 9747 9832 0 0 0 0 0 0 0 0 0 0
84 9511 2090 10411 9747 0 0 0 0 0 0 0 0 0 0
85 10402 2702 9511 10411 1 0 0 0 0 0 0 0 0 0
86 9701 2939 10402 9511 0 1 0 0 0 0 0 0 0 0
87 10540 4500 9701 10402 0 0 1 0 0 0 0 0 0 0
88 10112 6208 10540 9701 0 0 0 1 0 0 0 0 0 0
89 10915 6415 10112 10540 0 0 0 0 1 0 0 0 0 0
90 11183 5657 10915 10112 0 0 0 0 0 1 0 0 0 0
91 10384 5964 11183 10915 0 0 0 0 0 0 1 0 0 0
92 10834 3163 10384 11183 0 0 0 0 0 0 0 1 0 0
93 9886 1997 10834 10384 0 0 0 0 0 0 0 0 1 0
94 10216 2422 9886 10834 0 0 0 0 0 0 0 0 0 1
M11 t
1 0 1
2 0 2
3 0 3
4 0 4
5 0 5
6 0 6
7 0 7
8 0 8
9 0 9
10 0 10
11 1 11
12 0 12
13 0 13
14 0 14
15 0 15
16 0 16
17 0 17
18 0 18
19 0 19
20 0 20
21 0 21
22 0 22
23 1 23
24 0 24
25 0 25
26 0 26
27 0 27
28 0 28
29 0 29
30 0 30
31 0 31
32 0 32
33 0 33
34 0 34
35 1 35
36 0 36
37 0 37
38 0 38
39 0 39
40 0 40
41 0 41
42 0 42
43 0 43
44 0 44
45 0 45
46 0 46
47 1 47
48 0 48
49 0 49
50 0 50
51 0 51
52 0 52
53 0 53
54 0 54
55 0 55
56 0 56
57 0 57
58 0 58
59 1 59
60 0 60
61 0 61
62 0 62
63 0 63
64 0 64
65 0 65
66 0 66
67 0 67
68 0 68
69 0 69
70 0 70
71 1 71
72 0 72
73 0 73
74 0 74
75 0 75
76 0 76
77 0 77
78 0 78
79 0 79
80 0 80
81 0 81
82 0 82
83 1 83
84 0 84
85 0 85
86 0 86
87 0 87
88 0 88
89 0 89
90 0 90
91 0 91
92 0 92
93 0 93
94 0 94
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) huwelijken `geboortes-1` `geboortes-2` M1
3636.4907 -0.1129 0.2637 0.2880 1160.8781
M2 M3 M4 M5 M6
804.7805 1154.0644 1093.9421 1625.1079 1529.2834
M7 M8 M9 M10 M11
984.2230 980.8298 147.7561 717.4243 1000.9052
t
5.0797
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-665.715 -139.046 -6.872 160.798 610.058
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3636.49072 1159.93565 3.135 0.002422 **
huwelijken -0.11289 0.08624 -1.309 0.194366
`geboortes-1` 0.26368 0.11350 2.323 0.022777 *
`geboortes-2` 0.28804 0.10331 2.788 0.006656 **
M1 1160.87809 179.01480 6.485 7.39e-09 ***
M2 804.78050 173.40809 4.641 1.38e-05 ***
M3 1154.06440 273.38315 4.221 6.51e-05 ***
M4 1093.94206 308.80929 3.542 0.000673 ***
M5 1625.10788 324.63993 5.006 3.37e-06 ***
M6 1529.28340 331.64297 4.611 1.54e-05 ***
M7 984.22302 310.68344 3.168 0.002192 **
M8 980.82980 169.08708 5.801 1.34e-07 ***
M9 147.75608 141.15335 1.047 0.298435
M10 717.42434 167.25797 4.289 5.09e-05 ***
M11 1000.90518 153.90816 6.503 6.83e-09 ***
t 5.07968 1.51901 3.344 0.001271 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 262.9 on 78 degrees of freedom
Multiple R-squared: 0.7821, Adjusted R-squared: 0.7401
F-statistic: 18.66 on 15 and 78 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,] 0.20118263 0.40236527 0.79881737
[2,] 0.10477399 0.20954799 0.89522601
[3,] 0.07067286 0.14134573 0.92932714
[4,] 0.03407870 0.06815740 0.96592130
[5,] 0.03695076 0.07390152 0.96304924
[6,] 0.04639208 0.09278416 0.95360792
[7,] 0.02967776 0.05935552 0.97032224
[8,] 0.04523780 0.09047561 0.95476220
[9,] 0.25113397 0.50226794 0.74886603
[10,] 0.25320227 0.50640453 0.74679773
[11,] 0.20582747 0.41165494 0.79417253
[12,] 0.16155453 0.32310906 0.83844547
[13,] 0.13829494 0.27658987 0.86170506
[14,] 0.10326471 0.20652942 0.89673529
[15,] 0.07557841 0.15115683 0.92442159
[16,] 0.09413043 0.18826086 0.90586957
[17,] 0.06699254 0.13398509 0.93300746
[18,] 0.04819686 0.09639372 0.95180314
[19,] 0.03791808 0.07583616 0.96208192
[20,] 0.14332107 0.28664213 0.85667893
[21,] 0.15404148 0.30808296 0.84595852
[22,] 0.16888860 0.33777720 0.83111140
[23,] 0.24409699 0.48819397 0.75590301
[24,] 0.26481029 0.52962058 0.73518971
[25,] 0.32993928 0.65987856 0.67006072
[26,] 0.33359351 0.66718701 0.66640649
[27,] 0.30611115 0.61222230 0.69388885
[28,] 0.43435304 0.86870607 0.56564696
[29,] 0.41836568 0.83673135 0.58163432
[30,] 0.51420135 0.97159731 0.48579865
[31,] 0.46046593 0.92093186 0.53953407
[32,] 0.40783131 0.81566262 0.59216869
[33,] 0.79173253 0.41653494 0.20826747
[34,] 0.84327030 0.31345940 0.15672970
[35,] 0.87686327 0.24627345 0.12313673
[36,] 0.85261189 0.29477621 0.14738811
[37,] 0.82954346 0.34091308 0.17045654
[38,] 0.88657633 0.22684735 0.11342367
[39,] 0.86033235 0.27933531 0.13966765
[40,] 0.93399823 0.13200354 0.06600177
[41,] 0.90925220 0.18149560 0.09074780
[42,] 0.87633145 0.24733711 0.12366855
[43,] 0.86423681 0.27152639 0.13576319
[44,] 0.89839135 0.20321731 0.10160865
[45,] 0.87032022 0.25935957 0.12967978
[46,] 0.85224130 0.29551740 0.14775870
[47,] 0.87946570 0.24106861 0.12053430
[48,] 0.83610760 0.32778480 0.16389240
[49,] 0.79984813 0.40030374 0.20015187
[50,] 0.83872709 0.32254583 0.16127291
[51,] 0.84815085 0.30369831 0.15184915
[52,] 0.77380667 0.45238665 0.22619333
[53,] 0.71243413 0.57513173 0.28756587
[54,] 0.59773378 0.80453245 0.40226622
[55,] 0.48749745 0.97499490 0.51250255
[56,] 0.35628780 0.71257561 0.64371220
[57,] 0.27725919 0.55451838 0.72274081
> postscript(file="/var/www/html/rcomp/tmp/1ri7j1291545234.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ri7j1291545234.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/rcomp/tmp/3ri7j1291545234.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4jr6m1291545234.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5jr6m1291545234.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 = 94
Frequency = 1
1 2 3 4 5 6
142.881936 -3.820038 610.057756 -84.511899 -3.438908 301.571139
7 8 9 10 11 12
35.961299 98.039513 309.270237 -49.642739 248.887644 -101.790744
13 14 15 16 17 18
127.097591 340.964712 330.703005 -92.225554 -128.162874 -13.601740
19 20 21 22 23 24
-320.445398 132.340361 196.022049 -210.713676 -41.816605 180.114047
25 26 27 28 29 30
-45.436655 -326.899711 -204.638466 -397.290360 74.360779 -40.289480
31 32 33 34 35 36
-286.081469 6.923025 -215.221397 -26.561953 -6.554596 -186.761349
37 38 39 40 41 42
-371.271110 349.186054 -396.691028 -142.673230 200.948673 -567.962513
43 44 45 46 47 48
14.873898 -222.947939 -227.548905 293.109275 -7.188936 124.253045
49 50 51 52 53 54
-250.637181 -54.726072 -665.714509 345.387184 311.167156 -222.206117
55 56 57 58 59 60
-50.818993 -268.797876 109.000361 420.646106 -297.253338 -46.348249
61 62 63 64 65 66
197.866027 108.086792 -188.547683 89.743851 -370.416585 118.287730
67 68 69 70 71 72
165.318184 -110.455797 -108.271919 77.463333 -15.768525 -100.538883
73 74 75 76 77 78
228.235036 -85.119393 253.438753 219.632137 -307.714261 16.231528
79 80 81 82 83 84
559.543849 217.659312 -70.333676 -434.971095 119.694356 131.072133
85 86 87 88 89 90
-28.735644 -327.672342 261.392172 61.937870 223.256020 407.969454
91 92 93 94
-118.351371 147.239402 7.083251 -69.329252
> postscript(file="/var/www/html/rcomp/tmp/6jr6m1291545234.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 = 94
Frequency = 1
lag(myerror, k = 1) myerror
0 142.881936 NA
1 -3.820038 142.881936
2 610.057756 -3.820038
3 -84.511899 610.057756
4 -3.438908 -84.511899
5 301.571139 -3.438908
6 35.961299 301.571139
7 98.039513 35.961299
8 309.270237 98.039513
9 -49.642739 309.270237
10 248.887644 -49.642739
11 -101.790744 248.887644
12 127.097591 -101.790744
13 340.964712 127.097591
14 330.703005 340.964712
15 -92.225554 330.703005
16 -128.162874 -92.225554
17 -13.601740 -128.162874
18 -320.445398 -13.601740
19 132.340361 -320.445398
20 196.022049 132.340361
21 -210.713676 196.022049
22 -41.816605 -210.713676
23 180.114047 -41.816605
24 -45.436655 180.114047
25 -326.899711 -45.436655
26 -204.638466 -326.899711
27 -397.290360 -204.638466
28 74.360779 -397.290360
29 -40.289480 74.360779
30 -286.081469 -40.289480
31 6.923025 -286.081469
32 -215.221397 6.923025
33 -26.561953 -215.221397
34 -6.554596 -26.561953
35 -186.761349 -6.554596
36 -371.271110 -186.761349
37 349.186054 -371.271110
38 -396.691028 349.186054
39 -142.673230 -396.691028
40 200.948673 -142.673230
41 -567.962513 200.948673
42 14.873898 -567.962513
43 -222.947939 14.873898
44 -227.548905 -222.947939
45 293.109275 -227.548905
46 -7.188936 293.109275
47 124.253045 -7.188936
48 -250.637181 124.253045
49 -54.726072 -250.637181
50 -665.714509 -54.726072
51 345.387184 -665.714509
52 311.167156 345.387184
53 -222.206117 311.167156
54 -50.818993 -222.206117
55 -268.797876 -50.818993
56 109.000361 -268.797876
57 420.646106 109.000361
58 -297.253338 420.646106
59 -46.348249 -297.253338
60 197.866027 -46.348249
61 108.086792 197.866027
62 -188.547683 108.086792
63 89.743851 -188.547683
64 -370.416585 89.743851
65 118.287730 -370.416585
66 165.318184 118.287730
67 -110.455797 165.318184
68 -108.271919 -110.455797
69 77.463333 -108.271919
70 -15.768525 77.463333
71 -100.538883 -15.768525
72 228.235036 -100.538883
73 -85.119393 228.235036
74 253.438753 -85.119393
75 219.632137 253.438753
76 -307.714261 219.632137
77 16.231528 -307.714261
78 559.543849 16.231528
79 217.659312 559.543849
80 -70.333676 217.659312
81 -434.971095 -70.333676
82 119.694356 -434.971095
83 131.072133 119.694356
84 -28.735644 131.072133
85 -327.672342 -28.735644
86 261.392172 -327.672342
87 61.937870 261.392172
88 223.256020 61.937870
89 407.969454 223.256020
90 -118.351371 407.969454
91 147.239402 -118.351371
92 7.083251 147.239402
93 -69.329252 7.083251
94 NA -69.329252
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.820038 142.881936
[2,] 610.057756 -3.820038
[3,] -84.511899 610.057756
[4,] -3.438908 -84.511899
[5,] 301.571139 -3.438908
[6,] 35.961299 301.571139
[7,] 98.039513 35.961299
[8,] 309.270237 98.039513
[9,] -49.642739 309.270237
[10,] 248.887644 -49.642739
[11,] -101.790744 248.887644
[12,] 127.097591 -101.790744
[13,] 340.964712 127.097591
[14,] 330.703005 340.964712
[15,] -92.225554 330.703005
[16,] -128.162874 -92.225554
[17,] -13.601740 -128.162874
[18,] -320.445398 -13.601740
[19,] 132.340361 -320.445398
[20,] 196.022049 132.340361
[21,] -210.713676 196.022049
[22,] -41.816605 -210.713676
[23,] 180.114047 -41.816605
[24,] -45.436655 180.114047
[25,] -326.899711 -45.436655
[26,] -204.638466 -326.899711
[27,] -397.290360 -204.638466
[28,] 74.360779 -397.290360
[29,] -40.289480 74.360779
[30,] -286.081469 -40.289480
[31,] 6.923025 -286.081469
[32,] -215.221397 6.923025
[33,] -26.561953 -215.221397
[34,] -6.554596 -26.561953
[35,] -186.761349 -6.554596
[36,] -371.271110 -186.761349
[37,] 349.186054 -371.271110
[38,] -396.691028 349.186054
[39,] -142.673230 -396.691028
[40,] 200.948673 -142.673230
[41,] -567.962513 200.948673
[42,] 14.873898 -567.962513
[43,] -222.947939 14.873898
[44,] -227.548905 -222.947939
[45,] 293.109275 -227.548905
[46,] -7.188936 293.109275
[47,] 124.253045 -7.188936
[48,] -250.637181 124.253045
[49,] -54.726072 -250.637181
[50,] -665.714509 -54.726072
[51,] 345.387184 -665.714509
[52,] 311.167156 345.387184
[53,] -222.206117 311.167156
[54,] -50.818993 -222.206117
[55,] -268.797876 -50.818993
[56,] 109.000361 -268.797876
[57,] 420.646106 109.000361
[58,] -297.253338 420.646106
[59,] -46.348249 -297.253338
[60,] 197.866027 -46.348249
[61,] 108.086792 197.866027
[62,] -188.547683 108.086792
[63,] 89.743851 -188.547683
[64,] -370.416585 89.743851
[65,] 118.287730 -370.416585
[66,] 165.318184 118.287730
[67,] -110.455797 165.318184
[68,] -108.271919 -110.455797
[69,] 77.463333 -108.271919
[70,] -15.768525 77.463333
[71,] -100.538883 -15.768525
[72,] 228.235036 -100.538883
[73,] -85.119393 228.235036
[74,] 253.438753 -85.119393
[75,] 219.632137 253.438753
[76,] -307.714261 219.632137
[77,] 16.231528 -307.714261
[78,] 559.543849 16.231528
[79,] 217.659312 559.543849
[80,] -70.333676 217.659312
[81,] -434.971095 -70.333676
[82,] 119.694356 -434.971095
[83,] 131.072133 119.694356
[84,] -28.735644 131.072133
[85,] -327.672342 -28.735644
[86,] 261.392172 -327.672342
[87,] 61.937870 261.392172
[88,] 223.256020 61.937870
[89,] 407.969454 223.256020
[90,] -118.351371 407.969454
[91,] 147.239402 -118.351371
[92,] 7.083251 147.239402
[93,] -69.329252 7.083251
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.820038 142.881936
2 610.057756 -3.820038
3 -84.511899 610.057756
4 -3.438908 -84.511899
5 301.571139 -3.438908
6 35.961299 301.571139
7 98.039513 35.961299
8 309.270237 98.039513
9 -49.642739 309.270237
10 248.887644 -49.642739
11 -101.790744 248.887644
12 127.097591 -101.790744
13 340.964712 127.097591
14 330.703005 340.964712
15 -92.225554 330.703005
16 -128.162874 -92.225554
17 -13.601740 -128.162874
18 -320.445398 -13.601740
19 132.340361 -320.445398
20 196.022049 132.340361
21 -210.713676 196.022049
22 -41.816605 -210.713676
23 180.114047 -41.816605
24 -45.436655 180.114047
25 -326.899711 -45.436655
26 -204.638466 -326.899711
27 -397.290360 -204.638466
28 74.360779 -397.290360
29 -40.289480 74.360779
30 -286.081469 -40.289480
31 6.923025 -286.081469
32 -215.221397 6.923025
33 -26.561953 -215.221397
34 -6.554596 -26.561953
35 -186.761349 -6.554596
36 -371.271110 -186.761349
37 349.186054 -371.271110
38 -396.691028 349.186054
39 -142.673230 -396.691028
40 200.948673 -142.673230
41 -567.962513 200.948673
42 14.873898 -567.962513
43 -222.947939 14.873898
44 -227.548905 -222.947939
45 293.109275 -227.548905
46 -7.188936 293.109275
47 124.253045 -7.188936
48 -250.637181 124.253045
49 -54.726072 -250.637181
50 -665.714509 -54.726072
51 345.387184 -665.714509
52 311.167156 345.387184
53 -222.206117 311.167156
54 -50.818993 -222.206117
55 -268.797876 -50.818993
56 109.000361 -268.797876
57 420.646106 109.000361
58 -297.253338 420.646106
59 -46.348249 -297.253338
60 197.866027 -46.348249
61 108.086792 197.866027
62 -188.547683 108.086792
63 89.743851 -188.547683
64 -370.416585 89.743851
65 118.287730 -370.416585
66 165.318184 118.287730
67 -110.455797 165.318184
68 -108.271919 -110.455797
69 77.463333 -108.271919
70 -15.768525 77.463333
71 -100.538883 -15.768525
72 228.235036 -100.538883
73 -85.119393 228.235036
74 253.438753 -85.119393
75 219.632137 253.438753
76 -307.714261 219.632137
77 16.231528 -307.714261
78 559.543849 16.231528
79 217.659312 559.543849
80 -70.333676 217.659312
81 -434.971095 -70.333676
82 119.694356 -434.971095
83 131.072133 119.694356
84 -28.735644 131.072133
85 -327.672342 -28.735644
86 261.392172 -327.672342
87 61.937870 261.392172
88 223.256020 61.937870
89 407.969454 223.256020
90 -118.351371 407.969454
91 147.239402 -118.351371
92 7.083251 147.239402
93 -69.329252 7.083251
> 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/7c05p1291545234.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8c05p1291545234.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9mr591291545234.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10mr591291545234.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11qs4g1291545234.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/12tb231291545234.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/13iuzx1291545234.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/14blyi1291545234.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/15e3fo1291545234.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/16sdcx1291545234.tab")
+ }
>
> try(system("convert tmp/1ri7j1291545234.ps tmp/1ri7j1291545234.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ri7j1291545234.ps tmp/2ri7j1291545234.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ri7j1291545234.ps tmp/3ri7j1291545234.png",intern=TRUE))
character(0)
> try(system("convert tmp/4jr6m1291545234.ps tmp/4jr6m1291545234.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jr6m1291545234.ps tmp/5jr6m1291545234.png",intern=TRUE))
character(0)
> try(system("convert tmp/6jr6m1291545234.ps tmp/6jr6m1291545234.png",intern=TRUE))
character(0)
> try(system("convert tmp/7c05p1291545234.ps tmp/7c05p1291545234.png",intern=TRUE))
character(0)
> try(system("convert tmp/8c05p1291545234.ps tmp/8c05p1291545234.png",intern=TRUE))
character(0)
> try(system("convert tmp/9mr591291545234.ps tmp/9mr591291545234.png",intern=TRUE))
character(0)
> try(system("convert tmp/10mr591291545234.ps tmp/10mr591291545234.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.023 1.679 7.898