R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(2.462
+ ,9.939
+ ,9.321
+ ,9.769
+ ,3.695
+ ,9.336
+ ,9.939
+ ,9.321
+ ,4.831
+ ,10.195
+ ,9.336
+ ,9.939
+ ,5.134
+ ,9.464
+ ,10.195
+ ,9.336
+ ,6.250
+ ,10.010
+ ,9.464
+ ,10.195
+ ,5.760
+ ,10.213
+ ,10.010
+ ,9.464
+ ,6.249
+ ,9.563
+ ,10.213
+ ,10.010
+ ,2.917
+ ,9.890
+ ,9.563
+ ,10.213
+ ,1.741
+ ,9.305
+ ,9.890
+ ,9.563
+ ,2.359
+ ,9.391
+ ,9.305
+ ,9.890
+ ,1.511
+ ,9.928
+ ,9.391
+ ,9.305
+ ,2.059
+ ,8.686
+ ,9.928
+ ,9.391
+ ,2.635
+ ,9.843
+ ,8.686
+ ,9.928
+ ,2.867
+ ,9.627
+ ,9.843
+ ,8.686
+ ,4.403
+ ,10.074
+ ,9.627
+ ,9.843
+ ,5.720
+ ,9.503
+ ,10.074
+ ,9.627
+ ,4.502
+ ,10.119
+ ,9.503
+ ,10.074
+ ,5.749
+ ,10.000
+ ,10.119
+ ,9.503
+ ,5.627
+ ,9.313
+ ,10.000
+ ,10.119
+ ,2.846
+ ,9.866
+ ,9.313
+ ,10.000
+ ,1.762
+ ,9.172
+ ,9.866
+ ,9.313
+ ,2.429
+ ,9.241
+ ,9.172
+ ,9.866
+ ,1.169
+ ,9.659
+ ,9.241
+ ,9.172
+ ,2.154
+ ,8.904
+ ,9.659
+ ,9.241
+ ,2.249
+ ,9.755
+ ,8.904
+ ,9.659
+ ,2.687
+ ,9.080
+ ,9.755
+ ,8.904
+ ,4.359
+ ,9.435
+ ,9.080
+ ,9.755
+ ,5.382
+ ,8.971
+ ,9.435
+ ,9.080
+ ,4.459
+ ,10.063
+ ,8.971
+ ,9.435
+ ,6.398
+ ,9.793
+ ,10.063
+ ,8.971
+ ,4.596
+ ,9.454
+ ,9.793
+ ,10.063
+ ,3.024
+ ,9.759
+ ,9.454
+ ,9.793
+ ,1.887
+ ,8.820
+ ,9.759
+ ,9.454
+ ,2.070
+ ,9.403
+ ,8.820
+ ,9.759
+ ,1.351
+ ,9.676
+ ,9.403
+ ,8.820
+ ,2.218
+ ,8.642
+ ,9.676
+ ,9.403
+ ,2.461
+ ,9.402
+ ,8.642
+ ,9.676
+ ,3.028
+ ,9.610
+ ,9.402
+ ,8.642
+ ,4.784
+ ,9.294
+ ,9.610
+ ,9.402
+ ,4.975
+ ,9.448
+ ,9.294
+ ,9.610
+ ,4.607
+ ,10.319
+ ,9.448
+ ,9.294
+ ,6.249
+ ,9.548
+ ,10.319
+ ,9.448
+ ,4.809
+ ,9.801
+ ,9.548
+ ,10.319
+ ,3.157
+ ,9.596
+ ,9.801
+ ,9.548
+ ,1.910
+ ,8.923
+ ,9.596
+ ,9.801
+ ,2.228
+ ,9.746
+ ,8.923
+ ,9.596
+ ,1.594
+ ,9.829
+ ,9.746
+ ,8.923
+ ,2.467
+ ,9.125
+ ,9.829
+ ,9.746
+ ,2.222
+ ,9.782
+ ,9.125
+ ,9.829
+ ,3.607
+ ,9.441
+ ,9.782
+ ,9.125
+ ,4.685
+ ,9.162
+ ,9.441
+ ,9.782
+ ,4.962
+ ,9.915
+ ,9.162
+ ,9.441
+ ,5.770
+ ,10.444
+ ,9.915
+ ,9.162
+ ,5.480
+ ,10.209
+ ,10.444
+ ,9.915
+ ,5.000
+ ,9.985
+ ,10.209
+ ,10.444
+ ,3.228
+ ,9.842
+ ,9.985
+ ,10.209
+ ,1.993
+ ,9.429
+ ,9.842
+ ,9.985
+ ,2.288
+ ,10.132
+ ,9.429
+ ,9.842
+ ,1.580
+ ,9.849
+ ,10.132
+ ,9.429
+ ,2.111
+ ,9.172
+ ,9.849
+ ,10.132
+ ,2.192
+ ,10.313
+ ,9.172
+ ,9.849
+ ,3.601
+ ,9.819
+ ,10.313
+ ,9.172
+ ,4.665
+ ,9.955
+ ,9.819
+ ,10.313
+ ,4.876
+ ,10.048
+ ,9.955
+ ,9.819
+ ,5.813
+ ,10.082
+ ,10.048
+ ,9.955
+ ,5.589
+ ,10.541
+ ,10.082
+ ,10.048
+ ,5.331
+ ,10.208
+ ,10.541
+ ,10.082
+ ,3.075
+ ,10.233
+ ,10.208
+ ,10.541
+ ,2.002
+ ,9.439
+ ,10.233
+ ,10.208
+ ,2.306
+ ,9.963
+ ,9.439
+ ,10.233
+ ,1.507
+ ,10.158
+ ,9.963
+ ,9.439
+ ,1.992
+ ,9.225
+ ,10.158
+ ,9.963
+ ,2.487
+ ,10.474
+ ,9.225
+ ,10.158
+ ,3.490
+ ,9.757
+ ,10.474
+ ,9.225
+ ,4.647
+ ,10.490
+ ,9.757
+ ,10.474
+ ,5.594
+ ,10.281
+ ,10.490
+ ,9.757
+ ,5.611
+ ,10.444
+ ,10.281
+ ,10.490
+ ,5.788
+ ,10.640
+ ,10.444
+ ,10.281
+ ,6.204
+ ,10.695
+ ,10.640
+ ,10.444
+ ,3.013
+ ,10.786
+ ,10.695
+ ,10.640
+ ,1.931
+ ,9.832
+ ,10.786
+ ,10.695
+ ,2.549
+ ,9.747
+ ,9.832
+ ,10.786
+ ,1.504
+ ,10.411
+ ,9.747
+ ,9.832
+ ,2.090
+ ,9.511
+ ,10.411
+ ,9.747
+ ,2.702
+ ,10.402
+ ,9.511
+ ,10.411
+ ,2.939
+ ,9.701
+ ,10.402
+ ,9.511
+ ,4.500
+ ,10.540
+ ,9.701
+ ,10.402
+ ,6.208
+ ,10.112
+ ,10.540
+ ,9.701
+ ,6.415
+ ,10.915
+ ,10.112
+ ,10.540
+ ,5.657
+ ,11.183
+ ,10.915
+ ,10.112
+ ,5.964
+ ,10.384
+ ,11.183
+ ,10.915
+ ,3.163
+ ,10.834
+ ,10.384
+ ,11.183
+ ,1.997
+ ,9.886
+ ,10.834
+ ,10.384
+ ,2.422
+ ,10.216
+ ,9.886
+ ,10.834)
+ ,dim=c(4
+ ,94)
+ ,dimnames=list(c('huwelijk'
+ ,'geboortes'
+ ,'geboortes-1'
+ ,'geboortes-2')
+ ,1:94))
> y <- array(NA,dim=c(4,94),dimnames=list(c('huwelijk','geboortes','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 = '2'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> 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 huwelijk geboortes-1 geboortes-2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10
1 9.939 2.462 9.321 9.769 1 0 0 0 0 0 0 0 0 0
2 9.336 3.695 9.939 9.321 0 1 0 0 0 0 0 0 0 0
3 10.195 4.831 9.336 9.939 0 0 1 0 0 0 0 0 0 0
4 9.464 5.134 10.195 9.336 0 0 0 1 0 0 0 0 0 0
5 10.010 6.250 9.464 10.195 0 0 0 0 1 0 0 0 0 0
6 10.213 5.760 10.010 9.464 0 0 0 0 0 1 0 0 0 0
7 9.563 6.249 10.213 10.010 0 0 0 0 0 0 1 0 0 0
8 9.890 2.917 9.563 10.213 0 0 0 0 0 0 0 1 0 0
9 9.305 1.741 9.890 9.563 0 0 0 0 0 0 0 0 1 0
10 9.391 2.359 9.305 9.890 0 0 0 0 0 0 0 0 0 1
11 9.928 1.511 9.391 9.305 0 0 0 0 0 0 0 0 0 0
12 8.686 2.059 9.928 9.391 0 0 0 0 0 0 0 0 0 0
13 9.843 2.635 8.686 9.928 1 0 0 0 0 0 0 0 0 0
14 9.627 2.867 9.843 8.686 0 1 0 0 0 0 0 0 0 0
15 10.074 4.403 9.627 9.843 0 0 1 0 0 0 0 0 0 0
16 9.503 5.720 10.074 9.627 0 0 0 1 0 0 0 0 0 0
17 10.119 4.502 9.503 10.074 0 0 0 0 1 0 0 0 0 0
18 10.000 5.749 10.119 9.503 0 0 0 0 0 1 0 0 0 0
19 9.313 5.627 10.000 10.119 0 0 0 0 0 0 1 0 0 0
20 9.866 2.846 9.313 10.000 0 0 0 0 0 0 0 1 0 0
21 9.172 1.762 9.866 9.313 0 0 0 0 0 0 0 0 1 0
22 9.241 2.429 9.172 9.866 0 0 0 0 0 0 0 0 0 1
23 9.659 1.169 9.241 9.172 0 0 0 0 0 0 0 0 0 0
24 8.904 2.154 9.659 9.241 0 0 0 0 0 0 0 0 0 0
25 9.755 2.249 8.904 9.659 1 0 0 0 0 0 0 0 0 0
26 9.080 2.687 9.755 8.904 0 1 0 0 0 0 0 0 0 0
27 9.435 4.359 9.080 9.755 0 0 1 0 0 0 0 0 0 0
28 8.971 5.382 9.435 9.080 0 0 0 1 0 0 0 0 0 0
29 10.063 4.459 8.971 9.435 0 0 0 0 1 0 0 0 0 0
30 9.793 6.398 10.063 8.971 0 0 0 0 0 1 0 0 0 0
31 9.454 4.596 9.793 10.063 0 0 0 0 0 0 1 0 0 0
32 9.759 3.024 9.454 9.793 0 0 0 0 0 0 0 1 0 0
33 8.820 1.887 9.759 9.454 0 0 0 0 0 0 0 0 1 0
34 9.403 2.070 8.820 9.759 0 0 0 0 0 0 0 0 0 1
35 9.676 1.351 9.403 8.820 0 0 0 0 0 0 0 0 0 0
36 8.642 2.218 9.676 9.403 0 0 0 0 0 0 0 0 0 0
37 9.402 2.461 8.642 9.676 1 0 0 0 0 0 0 0 0 0
38 9.610 3.028 9.402 8.642 0 1 0 0 0 0 0 0 0 0
39 9.294 4.784 9.610 9.402 0 0 1 0 0 0 0 0 0 0
40 9.448 4.975 9.294 9.610 0 0 0 1 0 0 0 0 0 0
41 10.319 4.607 9.448 9.294 0 0 0 0 1 0 0 0 0 0
42 9.548 6.249 10.319 9.448 0 0 0 0 0 1 0 0 0 0
43 9.801 4.809 9.548 10.319 0 0 0 0 0 0 1 0 0 0
44 9.596 3.157 9.801 9.548 0 0 0 0 0 0 0 1 0 0
45 8.923 1.910 9.596 9.801 0 0 0 0 0 0 0 0 1 0
46 9.746 2.228 8.923 9.596 0 0 0 0 0 0 0 0 0 1
47 9.829 1.594 9.746 8.923 0 0 0 0 0 0 0 0 0 0
48 9.125 2.467 9.829 9.746 0 0 0 0 0 0 0 0 0 0
49 9.782 2.222 9.125 9.829 1 0 0 0 0 0 0 0 0 0
50 9.441 3.607 9.782 9.125 0 1 0 0 0 0 0 0 0 0
51 9.162 4.685 9.441 9.782 0 0 1 0 0 0 0 0 0 0
52 9.915 4.962 9.162 9.441 0 0 0 1 0 0 0 0 0 0
53 10.444 5.770 9.915 9.162 0 0 0 0 1 0 0 0 0 0
54 10.209 5.480 10.444 9.915 0 0 0 0 0 1 0 0 0 0
55 9.985 5.000 10.209 10.444 0 0 0 0 0 0 1 0 0 0
56 9.842 3.228 9.985 10.209 0 0 0 0 0 0 0 1 0 0
57 9.429 1.993 9.842 9.985 0 0 0 0 0 0 0 0 1 0
58 10.132 2.288 9.429 9.842 0 0 0 0 0 0 0 0 0 1
59 9.849 1.580 10.132 9.429 0 0 0 0 0 0 0 0 0 0
60 9.172 2.111 9.849 10.132 0 0 0 0 0 0 0 0 0 0
61 10.313 2.192 9.172 9.849 1 0 0 0 0 0 0 0 0 0
62 9.819 3.601 10.313 9.172 0 1 0 0 0 0 0 0 0 0
63 9.955 4.665 9.819 10.313 0 0 1 0 0 0 0 0 0 0
64 10.048 4.876 9.955 9.819 0 0 0 1 0 0 0 0 0 0
65 10.082 5.813 10.048 9.955 0 0 0 0 1 0 0 0 0 0
66 10.541 5.589 10.082 10.048 0 0 0 0 0 1 0 0 0 0
67 10.208 5.331 10.541 10.082 0 0 0 0 0 0 1 0 0 0
68 10.233 3.075 10.208 10.541 0 0 0 0 0 0 0 1 0 0
69 9.439 2.002 10.233 10.208 0 0 0 0 0 0 0 0 1 0
70 9.963 2.306 9.439 10.233 0 0 0 0 0 0 0 0 0 1
71 10.158 1.507 9.963 9.439 0 0 0 0 0 0 0 0 0 0
72 9.225 1.992 10.158 9.963 0 0 0 0 0 0 0 0 0 0
73 10.474 2.487 9.225 10.158 1 0 0 0 0 0 0 0 0 0
74 9.757 3.490 10.474 9.225 0 1 0 0 0 0 0 0 0 0
75 10.490 4.647 9.757 10.474 0 0 1 0 0 0 0 0 0 0
76 10.281 5.594 10.490 9.757 0 0 0 1 0 0 0 0 0 0
77 10.444 5.611 10.281 10.490 0 0 0 0 1 0 0 0 0 0
78 10.640 5.788 10.444 10.281 0 0 0 0 0 1 0 0 0 0
79 10.695 6.204 10.640 10.444 0 0 0 0 0 0 1 0 0 0
80 10.786 3.013 10.695 10.640 0 0 0 0 0 0 0 1 0 0
81 9.832 1.931 10.786 10.695 0 0 0 0 0 0 0 0 1 0
82 9.747 2.549 9.832 10.786 0 0 0 0 0 0 0 0 0 1
83 10.411 1.504 9.747 9.832 0 0 0 0 0 0 0 0 0 0
84 9.511 2.090 10.411 9.747 0 0 0 0 0 0 0 0 0 0
85 10.402 2.702 9.511 10.411 1 0 0 0 0 0 0 0 0 0
86 9.701 2.939 10.402 9.511 0 1 0 0 0 0 0 0 0 0
87 10.540 4.500 9.701 10.402 0 0 1 0 0 0 0 0 0 0
88 10.112 6.208 10.540 9.701 0 0 0 1 0 0 0 0 0 0
89 10.915 6.415 10.112 10.540 0 0 0 0 1 0 0 0 0 0
90 11.183 5.657 10.915 10.112 0 0 0 0 0 1 0 0 0 0
91 10.384 5.964 11.183 10.915 0 0 0 0 0 0 1 0 0 0
92 10.834 3.163 10.384 11.183 0 0 0 0 0 0 0 1 0 0
93 9.886 1.997 10.834 10.384 0 0 0 0 0 0 0 0 1 0
94 10.216 2.422 9.886 10.834 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) huwelijk `geboortes-1` `geboortes-2` M1
3.63649 -0.11289 0.26368 0.28804 1.16088
M2 M3 M4 M5 M6
0.80478 1.15406 1.09394 1.62511 1.52928
M7 M8 M9 M10 M11
0.98422 0.98083 0.14776 0.71742 1.00091
t
0.00508
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.665715 -0.139046 -0.006872 0.160798 0.610058
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.636491 1.159936 3.135 0.002422 **
huwelijk -0.112893 0.086241 -1.309 0.194366
`geboortes-1` 0.263684 0.113501 2.323 0.022777 *
`geboortes-2` 0.288035 0.103306 2.788 0.006656 **
M1 1.160878 0.179015 6.485 7.39e-09 ***
M2 0.804780 0.173408 4.641 1.38e-05 ***
M3 1.154064 0.273383 4.221 6.51e-05 ***
M4 1.093942 0.308809 3.542 0.000673 ***
M5 1.625108 0.324640 5.006 3.37e-06 ***
M6 1.529283 0.331643 4.611 1.54e-05 ***
M7 0.984223 0.310683 3.168 0.002192 **
M8 0.980830 0.169087 5.801 1.34e-07 ***
M9 0.147756 0.141153 1.047 0.298435
M10 0.717424 0.167258 4.289 5.09e-05 ***
M11 1.000905 0.153908 6.503 6.83e-09 ***
t 0.005080 0.001519 3.344 0.001271 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.2629 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/freestat/rcomp/tmp/1b6ql1290948670.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2b6ql1290948670.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3mgpo1290948670.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4mgpo1290948670.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5mgpo1290948670.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 = 94
Frequency = 1
1 2 3 4 5 6
0.142881936 -0.003820038 0.610057756 -0.084511899 -0.003438908 0.301571139
7 8 9 10 11 12
0.035961299 0.098039513 0.309270237 -0.049642739 0.248887644 -0.101790744
13 14 15 16 17 18
0.127097591 0.340964712 0.330703005 -0.092225554 -0.128162874 -0.013601740
19 20 21 22 23 24
-0.320445398 0.132340361 0.196022049 -0.210713676 -0.041816605 0.180114047
25 26 27 28 29 30
-0.045436655 -0.326899711 -0.204638466 -0.397290360 0.074360779 -0.040289480
31 32 33 34 35 36
-0.286081469 0.006923025 -0.215221397 -0.026561953 -0.006554596 -0.186761349
37 38 39 40 41 42
-0.371271110 0.349186054 -0.396691028 -0.142673230 0.200948673 -0.567962513
43 44 45 46 47 48
0.014873898 -0.222947939 -0.227548905 0.293109275 -0.007188936 0.124253045
49 50 51 52 53 54
-0.250637181 -0.054726072 -0.665714509 0.345387184 0.311167156 -0.222206117
55 56 57 58 59 60
-0.050818993 -0.268797876 0.109000361 0.420646106 -0.297253338 -0.046348249
61 62 63 64 65 66
0.197866027 0.108086792 -0.188547683 0.089743851 -0.370416585 0.118287730
67 68 69 70 71 72
0.165318184 -0.110455797 -0.108271919 0.077463333 -0.015768525 -0.100538883
73 74 75 76 77 78
0.228235036 -0.085119393 0.253438753 0.219632137 -0.307714261 0.016231528
79 80 81 82 83 84
0.559543849 0.217659312 -0.070333676 -0.434971095 0.119694356 0.131072133
85 86 87 88 89 90
-0.028735644 -0.327672342 0.261392172 0.061937870 0.223256020 0.407969454
91 92 93 94
-0.118351371 0.147239402 0.007083251 -0.069329252
> postscript(file="/var/www/html/freestat/rcomp/tmp/6ep691290948670.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 = 94
Frequency = 1
lag(myerror, k = 1) myerror
0 0.142881936 NA
1 -0.003820038 0.142881936
2 0.610057756 -0.003820038
3 -0.084511899 0.610057756
4 -0.003438908 -0.084511899
5 0.301571139 -0.003438908
6 0.035961299 0.301571139
7 0.098039513 0.035961299
8 0.309270237 0.098039513
9 -0.049642739 0.309270237
10 0.248887644 -0.049642739
11 -0.101790744 0.248887644
12 0.127097591 -0.101790744
13 0.340964712 0.127097591
14 0.330703005 0.340964712
15 -0.092225554 0.330703005
16 -0.128162874 -0.092225554
17 -0.013601740 -0.128162874
18 -0.320445398 -0.013601740
19 0.132340361 -0.320445398
20 0.196022049 0.132340361
21 -0.210713676 0.196022049
22 -0.041816605 -0.210713676
23 0.180114047 -0.041816605
24 -0.045436655 0.180114047
25 -0.326899711 -0.045436655
26 -0.204638466 -0.326899711
27 -0.397290360 -0.204638466
28 0.074360779 -0.397290360
29 -0.040289480 0.074360779
30 -0.286081469 -0.040289480
31 0.006923025 -0.286081469
32 -0.215221397 0.006923025
33 -0.026561953 -0.215221397
34 -0.006554596 -0.026561953
35 -0.186761349 -0.006554596
36 -0.371271110 -0.186761349
37 0.349186054 -0.371271110
38 -0.396691028 0.349186054
39 -0.142673230 -0.396691028
40 0.200948673 -0.142673230
41 -0.567962513 0.200948673
42 0.014873898 -0.567962513
43 -0.222947939 0.014873898
44 -0.227548905 -0.222947939
45 0.293109275 -0.227548905
46 -0.007188936 0.293109275
47 0.124253045 -0.007188936
48 -0.250637181 0.124253045
49 -0.054726072 -0.250637181
50 -0.665714509 -0.054726072
51 0.345387184 -0.665714509
52 0.311167156 0.345387184
53 -0.222206117 0.311167156
54 -0.050818993 -0.222206117
55 -0.268797876 -0.050818993
56 0.109000361 -0.268797876
57 0.420646106 0.109000361
58 -0.297253338 0.420646106
59 -0.046348249 -0.297253338
60 0.197866027 -0.046348249
61 0.108086792 0.197866027
62 -0.188547683 0.108086792
63 0.089743851 -0.188547683
64 -0.370416585 0.089743851
65 0.118287730 -0.370416585
66 0.165318184 0.118287730
67 -0.110455797 0.165318184
68 -0.108271919 -0.110455797
69 0.077463333 -0.108271919
70 -0.015768525 0.077463333
71 -0.100538883 -0.015768525
72 0.228235036 -0.100538883
73 -0.085119393 0.228235036
74 0.253438753 -0.085119393
75 0.219632137 0.253438753
76 -0.307714261 0.219632137
77 0.016231528 -0.307714261
78 0.559543849 0.016231528
79 0.217659312 0.559543849
80 -0.070333676 0.217659312
81 -0.434971095 -0.070333676
82 0.119694356 -0.434971095
83 0.131072133 0.119694356
84 -0.028735644 0.131072133
85 -0.327672342 -0.028735644
86 0.261392172 -0.327672342
87 0.061937870 0.261392172
88 0.223256020 0.061937870
89 0.407969454 0.223256020
90 -0.118351371 0.407969454
91 0.147239402 -0.118351371
92 0.007083251 0.147239402
93 -0.069329252 0.007083251
94 NA -0.069329252
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.003820038 0.142881936
[2,] 0.610057756 -0.003820038
[3,] -0.084511899 0.610057756
[4,] -0.003438908 -0.084511899
[5,] 0.301571139 -0.003438908
[6,] 0.035961299 0.301571139
[7,] 0.098039513 0.035961299
[8,] 0.309270237 0.098039513
[9,] -0.049642739 0.309270237
[10,] 0.248887644 -0.049642739
[11,] -0.101790744 0.248887644
[12,] 0.127097591 -0.101790744
[13,] 0.340964712 0.127097591
[14,] 0.330703005 0.340964712
[15,] -0.092225554 0.330703005
[16,] -0.128162874 -0.092225554
[17,] -0.013601740 -0.128162874
[18,] -0.320445398 -0.013601740
[19,] 0.132340361 -0.320445398
[20,] 0.196022049 0.132340361
[21,] -0.210713676 0.196022049
[22,] -0.041816605 -0.210713676
[23,] 0.180114047 -0.041816605
[24,] -0.045436655 0.180114047
[25,] -0.326899711 -0.045436655
[26,] -0.204638466 -0.326899711
[27,] -0.397290360 -0.204638466
[28,] 0.074360779 -0.397290360
[29,] -0.040289480 0.074360779
[30,] -0.286081469 -0.040289480
[31,] 0.006923025 -0.286081469
[32,] -0.215221397 0.006923025
[33,] -0.026561953 -0.215221397
[34,] -0.006554596 -0.026561953
[35,] -0.186761349 -0.006554596
[36,] -0.371271110 -0.186761349
[37,] 0.349186054 -0.371271110
[38,] -0.396691028 0.349186054
[39,] -0.142673230 -0.396691028
[40,] 0.200948673 -0.142673230
[41,] -0.567962513 0.200948673
[42,] 0.014873898 -0.567962513
[43,] -0.222947939 0.014873898
[44,] -0.227548905 -0.222947939
[45,] 0.293109275 -0.227548905
[46,] -0.007188936 0.293109275
[47,] 0.124253045 -0.007188936
[48,] -0.250637181 0.124253045
[49,] -0.054726072 -0.250637181
[50,] -0.665714509 -0.054726072
[51,] 0.345387184 -0.665714509
[52,] 0.311167156 0.345387184
[53,] -0.222206117 0.311167156
[54,] -0.050818993 -0.222206117
[55,] -0.268797876 -0.050818993
[56,] 0.109000361 -0.268797876
[57,] 0.420646106 0.109000361
[58,] -0.297253338 0.420646106
[59,] -0.046348249 -0.297253338
[60,] 0.197866027 -0.046348249
[61,] 0.108086792 0.197866027
[62,] -0.188547683 0.108086792
[63,] 0.089743851 -0.188547683
[64,] -0.370416585 0.089743851
[65,] 0.118287730 -0.370416585
[66,] 0.165318184 0.118287730
[67,] -0.110455797 0.165318184
[68,] -0.108271919 -0.110455797
[69,] 0.077463333 -0.108271919
[70,] -0.015768525 0.077463333
[71,] -0.100538883 -0.015768525
[72,] 0.228235036 -0.100538883
[73,] -0.085119393 0.228235036
[74,] 0.253438753 -0.085119393
[75,] 0.219632137 0.253438753
[76,] -0.307714261 0.219632137
[77,] 0.016231528 -0.307714261
[78,] 0.559543849 0.016231528
[79,] 0.217659312 0.559543849
[80,] -0.070333676 0.217659312
[81,] -0.434971095 -0.070333676
[82,] 0.119694356 -0.434971095
[83,] 0.131072133 0.119694356
[84,] -0.028735644 0.131072133
[85,] -0.327672342 -0.028735644
[86,] 0.261392172 -0.327672342
[87,] 0.061937870 0.261392172
[88,] 0.223256020 0.061937870
[89,] 0.407969454 0.223256020
[90,] -0.118351371 0.407969454
[91,] 0.147239402 -0.118351371
[92,] 0.007083251 0.147239402
[93,] -0.069329252 0.007083251
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.003820038 0.142881936
2 0.610057756 -0.003820038
3 -0.084511899 0.610057756
4 -0.003438908 -0.084511899
5 0.301571139 -0.003438908
6 0.035961299 0.301571139
7 0.098039513 0.035961299
8 0.309270237 0.098039513
9 -0.049642739 0.309270237
10 0.248887644 -0.049642739
11 -0.101790744 0.248887644
12 0.127097591 -0.101790744
13 0.340964712 0.127097591
14 0.330703005 0.340964712
15 -0.092225554 0.330703005
16 -0.128162874 -0.092225554
17 -0.013601740 -0.128162874
18 -0.320445398 -0.013601740
19 0.132340361 -0.320445398
20 0.196022049 0.132340361
21 -0.210713676 0.196022049
22 -0.041816605 -0.210713676
23 0.180114047 -0.041816605
24 -0.045436655 0.180114047
25 -0.326899711 -0.045436655
26 -0.204638466 -0.326899711
27 -0.397290360 -0.204638466
28 0.074360779 -0.397290360
29 -0.040289480 0.074360779
30 -0.286081469 -0.040289480
31 0.006923025 -0.286081469
32 -0.215221397 0.006923025
33 -0.026561953 -0.215221397
34 -0.006554596 -0.026561953
35 -0.186761349 -0.006554596
36 -0.371271110 -0.186761349
37 0.349186054 -0.371271110
38 -0.396691028 0.349186054
39 -0.142673230 -0.396691028
40 0.200948673 -0.142673230
41 -0.567962513 0.200948673
42 0.014873898 -0.567962513
43 -0.222947939 0.014873898
44 -0.227548905 -0.222947939
45 0.293109275 -0.227548905
46 -0.007188936 0.293109275
47 0.124253045 -0.007188936
48 -0.250637181 0.124253045
49 -0.054726072 -0.250637181
50 -0.665714509 -0.054726072
51 0.345387184 -0.665714509
52 0.311167156 0.345387184
53 -0.222206117 0.311167156
54 -0.050818993 -0.222206117
55 -0.268797876 -0.050818993
56 0.109000361 -0.268797876
57 0.420646106 0.109000361
58 -0.297253338 0.420646106
59 -0.046348249 -0.297253338
60 0.197866027 -0.046348249
61 0.108086792 0.197866027
62 -0.188547683 0.108086792
63 0.089743851 -0.188547683
64 -0.370416585 0.089743851
65 0.118287730 -0.370416585
66 0.165318184 0.118287730
67 -0.110455797 0.165318184
68 -0.108271919 -0.110455797
69 0.077463333 -0.108271919
70 -0.015768525 0.077463333
71 -0.100538883 -0.015768525
72 0.228235036 -0.100538883
73 -0.085119393 0.228235036
74 0.253438753 -0.085119393
75 0.219632137 0.253438753
76 -0.307714261 0.219632137
77 0.016231528 -0.307714261
78 0.559543849 0.016231528
79 0.217659312 0.559543849
80 -0.070333676 0.217659312
81 -0.434971095 -0.070333676
82 0.119694356 -0.434971095
83 0.131072133 0.119694356
84 -0.028735644 0.131072133
85 -0.327672342 -0.028735644
86 0.261392172 -0.327672342
87 0.061937870 0.261392172
88 0.223256020 0.061937870
89 0.407969454 0.223256020
90 -0.118351371 0.407969454
91 0.147239402 -0.118351371
92 0.007083251 0.147239402
93 -0.069329252 0.007083251
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/7pgoc1290948670.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8pgoc1290948670.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9pgoc1290948670.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/100pnx1290948670.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/113ql31290948670.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/12682q1290948670.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/1320hz1290948670.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/146jy51290948670.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/freestat/rcomp/tmp/15r1xt1290948670.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/freestat/rcomp/tmp/16v2dg1290948670.tab")
+ }
>
> try(system("convert tmp/1b6ql1290948670.ps tmp/1b6ql1290948670.png",intern=TRUE))
character(0)
> try(system("convert tmp/2b6ql1290948670.ps tmp/2b6ql1290948670.png",intern=TRUE))
character(0)
> try(system("convert tmp/3mgpo1290948670.ps tmp/3mgpo1290948670.png",intern=TRUE))
character(0)
> try(system("convert tmp/4mgpo1290948670.ps tmp/4mgpo1290948670.png",intern=TRUE))
character(0)
> try(system("convert tmp/5mgpo1290948670.ps tmp/5mgpo1290948670.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ep691290948670.ps tmp/6ep691290948670.png",intern=TRUE))
character(0)
> try(system("convert tmp/7pgoc1290948670.ps tmp/7pgoc1290948670.png",intern=TRUE))
character(0)
> try(system("convert tmp/8pgoc1290948670.ps tmp/8pgoc1290948670.png",intern=TRUE))
character(0)
> try(system("convert tmp/9pgoc1290948670.ps tmp/9pgoc1290948670.png",intern=TRUE))
character(0)
> try(system("convert tmp/100pnx1290948670.ps tmp/100pnx1290948670.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.426 2.564 4.845