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.
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(60804
+ ,21863
+ ,30811
+ ,57907
+ ,20403
+ ,29877
+ ,54355
+ ,18792
+ ,28303
+ ,52536
+ ,17931
+ ,27605
+ ,49081
+ ,16475
+ ,26074
+ ,48877
+ ,16205
+ ,26112
+ ,64599
+ ,25134
+ ,32350
+ ,75314
+ ,31896
+ ,35804
+ ,71209
+ ,26537
+ ,36574
+ ,65210
+ ,22801
+ ,34486
+ ,59829
+ ,20200
+ ,32158
+ ,57656
+ ,19666
+ ,30965
+ ,57428
+ ,19809
+ ,30505
+ ,55315
+ ,18799
+ ,29629
+ ,52790
+ ,17884
+ ,28169
+ ,51050
+ ,17512
+ ,26972
+ ,48519
+ ,16327
+ ,25752
+ ,48354
+ ,16880
+ ,25027
+ ,65333
+ ,26537
+ ,31530
+ ,73990
+ ,31867
+ ,34705
+ ,72755
+ ,29427
+ ,35223
+ ,67424
+ ,25800
+ ,33471
+ ,59214
+ ,22041
+ ,29239
+ ,57427
+ ,21759
+ ,27954
+ ,56681
+ ,21333
+ ,27727
+ ,55437
+ ,20462
+ ,27314
+ ,53600
+ ,19594
+ ,26576
+ ,51641
+ ,18564
+ ,25775
+ ,49478
+ ,17640
+ ,24669
+ ,50124
+ ,18614
+ ,24480
+ ,71313
+ ,32562
+ ,30834
+ ,76208
+ ,35640
+ ,33218
+ ,74387
+ ,31865
+ ,33783
+ ,69520
+ ,28117
+ ,32546
+ ,64735
+ ,25508
+ ,30661
+ ,63413
+ ,25006
+ ,30070
+ ,62553
+ ,24452
+ ,29722
+ ,60109
+ ,22643
+ ,29075
+ ,57764
+ ,21474
+ ,28136
+ ,55667
+ ,20500
+ ,27315
+ ,53103
+ ,19505
+ ,26125
+ ,55301
+ ,21769
+ ,26057
+ ,76795
+ ,36062
+ ,32601
+ ,80928
+ ,38633
+ ,34214
+ ,79213
+ ,34629
+ ,35232
+ ,72759
+ ,30184
+ ,33565
+ ,67802
+ ,27271
+ ,31931
+ ,66940
+ ,26841
+ ,31779
+ ,66396
+ ,26482
+ ,31626
+ ,67539
+ ,25538
+ ,31230
+ ,67776
+ ,23789
+ ,29574
+ ,68014
+ ,22386
+ ,28312
+ ,68251
+ ,21087
+ ,27186
+ ,68488
+ ,22891
+ ,27397
+ ,68725
+ ,36192
+ ,33387
+ ,68962
+ ,38922
+ ,34996
+ ,69200
+ ,34669
+ ,36251
+ ,69437
+ ,30197
+ ,34284
+ ,68212
+ ,27001
+ ,32349
+ ,65444
+ ,25891
+ ,30991
+ ,63181
+ ,24879
+ ,29916
+ ,61198
+ ,23662
+ ,29067
+ ,59010
+ ,22741
+ ,27978
+ ,56388
+ ,21615
+ ,26719
+ ,53723
+ ,20305
+ ,25544
+ ,55340
+ ,21877
+ ,25703
+ ,75352
+ ,35369
+ ,31703
+ ,79817
+ ,37941
+ ,33733
+ ,78289
+ ,33480
+ ,35121
+ ,71892
+ ,29757
+ ,32714
+ ,66448
+ ,26323
+ ,31111
+ ,64167
+ ,25359
+ ,29977
+ ,61250
+ ,22207
+ ,30375
+ ,59580
+ ,21763
+ ,29323
+ ,56417
+ ,19944
+ ,28193
+ ,54662
+ ,19662
+ ,27222
+ ,53349
+ ,18624
+ ,26904
+ ,55385
+ ,19902
+ ,27952
+ ,73546
+ ,31726
+ ,33512
+ ,77683
+ ,32860
+ ,36215
+ ,74995
+ ,28894
+ ,36856
+ ,67282
+ ,22949
+ ,35341
+ ,60742
+ ,19758
+ ,32624
+ ,57283
+ ,18420
+ ,30885
+ ,57314
+ ,18245
+ ,31108
+ ,54704
+ ,16761
+ ,30267
+ ,51578
+ ,15341
+ ,28645
+ ,49962
+ ,14271
+ ,28474
+ ,46252
+ ,13418
+ ,25805
+ ,47234
+ ,15218
+ ,24756
+ ,64708
+ ,26485
+ ,30437
+ ,68753
+ ,27457
+ ,33177
+ ,62970
+ ,21402
+ ,33069
+ ,57474
+ ,17879
+ ,31342
+ ,52494
+ ,15607
+ ,28912
+ ,51831
+ ,15626
+ ,28373
+ ,51663
+ ,15303
+ ,28599
+ ,49637
+ ,14296
+ ,27884
+ ,46679
+ ,13686
+ ,25727
+ ,45557
+ ,12948
+ ,25393
+ ,41630
+ ,11609
+ ,23147
+ ,44417
+ ,14602
+ ,23164
+ ,60070
+ ,23629
+ ,29286
+ ,63157
+ ,24680
+ ,31008)
+ ,dim=c(3
+ ,104)
+ ,dimnames=list(c('Totale'
+ ,'Vlaamse'
+ ,'Waalse')
+ ,1:104))
> y <- array(NA,dim=c(3,104),dimnames=list(c('Totale','Vlaamse','Waalse'),1:104))
> 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
Totale Vlaamse Waalse M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 60804 21863 30811 1 0 0 0 0 0 0 0 0 0 0 1
2 57907 20403 29877 0 1 0 0 0 0 0 0 0 0 0 2
3 54355 18792 28303 0 0 1 0 0 0 0 0 0 0 0 3
4 52536 17931 27605 0 0 0 1 0 0 0 0 0 0 0 4
5 49081 16475 26074 0 0 0 0 1 0 0 0 0 0 0 5
6 48877 16205 26112 0 0 0 0 0 1 0 0 0 0 0 6
7 64599 25134 32350 0 0 0 0 0 0 1 0 0 0 0 7
8 75314 31896 35804 0 0 0 0 0 0 0 1 0 0 0 8
9 71209 26537 36574 0 0 0 0 0 0 0 0 1 0 0 9
10 65210 22801 34486 0 0 0 0 0 0 0 0 0 1 0 10
11 59829 20200 32158 0 0 0 0 0 0 0 0 0 0 1 11
12 57656 19666 30965 0 0 0 0 0 0 0 0 0 0 0 12
13 57428 19809 30505 1 0 0 0 0 0 0 0 0 0 0 13
14 55315 18799 29629 0 1 0 0 0 0 0 0 0 0 0 14
15 52790 17884 28169 0 0 1 0 0 0 0 0 0 0 0 15
16 51050 17512 26972 0 0 0 1 0 0 0 0 0 0 0 16
17 48519 16327 25752 0 0 0 0 1 0 0 0 0 0 0 17
18 48354 16880 25027 0 0 0 0 0 1 0 0 0 0 0 18
19 65333 26537 31530 0 0 0 0 0 0 1 0 0 0 0 19
20 73990 31867 34705 0 0 0 0 0 0 0 1 0 0 0 20
21 72755 29427 35223 0 0 0 0 0 0 0 0 1 0 0 21
22 67424 25800 33471 0 0 0 0 0 0 0 0 0 1 0 22
23 59214 22041 29239 0 0 0 0 0 0 0 0 0 0 1 23
24 57427 21759 27954 0 0 0 0 0 0 0 0 0 0 0 24
25 56681 21333 27727 1 0 0 0 0 0 0 0 0 0 0 25
26 55437 20462 27314 0 1 0 0 0 0 0 0 0 0 0 26
27 53600 19594 26576 0 0 1 0 0 0 0 0 0 0 0 27
28 51641 18564 25775 0 0 0 1 0 0 0 0 0 0 0 28
29 49478 17640 24669 0 0 0 0 1 0 0 0 0 0 0 29
30 50124 18614 24480 0 0 0 0 0 1 0 0 0 0 0 30
31 71313 32562 30834 0 0 0 0 0 0 1 0 0 0 0 31
32 76208 35640 33218 0 0 0 0 0 0 0 1 0 0 0 32
33 74387 31865 33783 0 0 0 0 0 0 0 0 1 0 0 33
34 69520 28117 32546 0 0 0 0 0 0 0 0 0 1 0 34
35 64735 25508 30661 0 0 0 0 0 0 0 0 0 0 1 35
36 63413 25006 30070 0 0 0 0 0 0 0 0 0 0 0 36
37 62553 24452 29722 1 0 0 0 0 0 0 0 0 0 0 37
38 60109 22643 29075 0 1 0 0 0 0 0 0 0 0 0 38
39 57764 21474 28136 0 0 1 0 0 0 0 0 0 0 0 39
40 55667 20500 27315 0 0 0 1 0 0 0 0 0 0 0 40
41 53103 19505 26125 0 0 0 0 1 0 0 0 0 0 0 41
42 55301 21769 26057 0 0 0 0 0 1 0 0 0 0 0 42
43 76795 36062 32601 0 0 0 0 0 0 1 0 0 0 0 43
44 80928 38633 34214 0 0 0 0 0 0 0 1 0 0 0 44
45 79213 34629 35232 0 0 0 0 0 0 0 0 1 0 0 45
46 72759 30184 33565 0 0 0 0 0 0 0 0 0 1 0 46
47 67802 27271 31931 0 0 0 0 0 0 0 0 0 0 1 47
48 66940 26841 31779 0 0 0 0 0 0 0 0 0 0 0 48
49 66396 26482 31626 1 0 0 0 0 0 0 0 0 0 0 49
50 67539 25538 31230 0 1 0 0 0 0 0 0 0 0 0 50
51 67776 23789 29574 0 0 1 0 0 0 0 0 0 0 0 51
52 68014 22386 28312 0 0 0 1 0 0 0 0 0 0 0 52
53 68251 21087 27186 0 0 0 0 1 0 0 0 0 0 0 53
54 68488 22891 27397 0 0 0 0 0 1 0 0 0 0 0 54
55 68725 36192 33387 0 0 0 0 0 0 1 0 0 0 0 55
56 68962 38922 34996 0 0 0 0 0 0 0 1 0 0 0 56
57 69200 34669 36251 0 0 0 0 0 0 0 0 1 0 0 57
58 69437 30197 34284 0 0 0 0 0 0 0 0 0 1 0 58
59 68212 27001 32349 0 0 0 0 0 0 0 0 0 0 1 59
60 65444 25891 30991 0 0 0 0 0 0 0 0 0 0 0 60
61 63181 24879 29916 1 0 0 0 0 0 0 0 0 0 0 61
62 61198 23662 29067 0 1 0 0 0 0 0 0 0 0 0 62
63 59010 22741 27978 0 0 1 0 0 0 0 0 0 0 0 63
64 56388 21615 26719 0 0 0 1 0 0 0 0 0 0 0 64
65 53723 20305 25544 0 0 0 0 1 0 0 0 0 0 0 65
66 55340 21877 25703 0 0 0 0 0 1 0 0 0 0 0 66
67 75352 35369 31703 0 0 0 0 0 0 1 0 0 0 0 67
68 79817 37941 33733 0 0 0 0 0 0 0 1 0 0 0 68
69 78289 33480 35121 0 0 0 0 0 0 0 0 1 0 0 69
70 71892 29757 32714 0 0 0 0 0 0 0 0 0 1 0 70
71 66448 26323 31111 0 0 0 0 0 0 0 0 0 0 1 71
72 64167 25359 29977 0 0 0 0 0 0 0 0 0 0 0 72
73 61250 22207 30375 1 0 0 0 0 0 0 0 0 0 0 73
74 59580 21763 29323 0 1 0 0 0 0 0 0 0 0 0 74
75 56417 19944 28193 0 0 1 0 0 0 0 0 0 0 0 75
76 54662 19662 27222 0 0 0 1 0 0 0 0 0 0 0 76
77 53349 18624 26904 0 0 0 0 1 0 0 0 0 0 0 77
78 55385 19902 27952 0 0 0 0 0 1 0 0 0 0 0 78
79 73546 31726 33512 0 0 0 0 0 0 1 0 0 0 0 79
80 77683 32860 36215 0 0 0 0 0 0 0 1 0 0 0 80
81 74995 28894 36856 0 0 0 0 0 0 0 0 1 0 0 81
82 67282 22949 35341 0 0 0 0 0 0 0 0 0 1 0 82
83 60742 19758 32624 0 0 0 0 0 0 0 0 0 0 1 83
84 57283 18420 30885 0 0 0 0 0 0 0 0 0 0 0 84
85 57314 18245 31108 1 0 0 0 0 0 0 0 0 0 0 85
86 54704 16761 30267 0 1 0 0 0 0 0 0 0 0 0 86
87 51578 15341 28645 0 0 1 0 0 0 0 0 0 0 0 87
88 49962 14271 28474 0 0 0 1 0 0 0 0 0 0 0 88
89 46252 13418 25805 0 0 0 0 1 0 0 0 0 0 0 89
90 47234 15218 24756 0 0 0 0 0 1 0 0 0 0 0 90
91 64708 26485 30437 0 0 0 0 0 0 1 0 0 0 0 91
92 68753 27457 33177 0 0 0 0 0 0 0 1 0 0 0 92
93 62970 21402 33069 0 0 0 0 0 0 0 0 1 0 0 93
94 57474 17879 31342 0 0 0 0 0 0 0 0 0 1 0 94
95 52494 15607 28912 0 0 0 0 0 0 0 0 0 0 1 95
96 51831 15626 28373 0 0 0 0 0 0 0 0 0 0 0 96
97 51663 15303 28599 1 0 0 0 0 0 0 0 0 0 0 97
98 49637 14296 27884 0 1 0 0 0 0 0 0 0 0 0 98
99 46679 13686 25727 0 0 1 0 0 0 0 0 0 0 0 99
100 45557 12948 25393 0 0 0 1 0 0 0 0 0 0 0 100
101 41630 11609 23147 0 0 0 0 1 0 0 0 0 0 0 101
102 44417 14602 23164 0 0 0 0 0 1 0 0 0 0 0 102
103 60070 23629 29286 0 0 0 0 0 0 1 0 0 0 0 103
104 63157 24680 31008 0 0 0 0 0 0 0 1 0 0 0 104
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Vlaamse Waalse M1 M2 M3
-1050.428 1.056 1.244 66.221 428.310 1044.760
M4 M5 M6 M7 M8 M9
1385.866 1881.557 1552.968 -2145.396 -3262.495 -2239.857
M10 M11 t
-881.972 2.298 9.496
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-11913.54 -887.38 22.51 927.57 10817.87
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.050e+03 7.295e+03 -0.144 0.8858
Vlaamse 1.056e+00 8.576e-02 12.318 < 2e-16 ***
Waalse 1.244e+00 2.556e-01 4.868 4.86e-06 ***
M1 6.622e+01 1.380e+03 0.048 0.9618
M2 4.283e+02 1.395e+03 0.307 0.7596
M3 1.045e+03 1.473e+03 0.709 0.4799
M4 1.386e+03 1.550e+03 0.894 0.3737
M5 1.882e+03 1.722e+03 1.093 0.2775
M6 1.553e+03 1.737e+03 0.894 0.3737
M7 -2.145e+03 1.522e+03 -1.410 0.1620
M8 -3.262e+03 1.744e+03 -1.871 0.0646 .
M9 -2.240e+03 1.853e+03 -1.209 0.2300
M10 -8.820e+02 1.616e+03 -0.546 0.5865
M11 2.298e+00 1.437e+03 0.002 0.9987
t 9.496e+00 9.754e+00 0.974 0.3329
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2836 on 89 degrees of freedom
Multiple R-squared: 0.9193, Adjusted R-squared: 0.9066
F-statistic: 72.42 on 14 and 89 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,] 7.025380e-06 1.405076e-05 9.999930e-01
[2,] 3.263402e-07 6.526804e-07 9.999997e-01
[3,] 2.819752e-08 5.639504e-08 1.000000e+00
[4,] 5.326417e-08 1.065283e-07 9.999999e-01
[5,] 2.569327e-09 5.138653e-09 1.000000e+00
[6,] 1.774702e-10 3.549405e-10 1.000000e+00
[7,] 1.066947e-11 2.133894e-11 1.000000e+00
[8,] 4.286570e-13 8.573139e-13 1.000000e+00
[9,] 1.793966e-13 3.587933e-13 1.000000e+00
[10,] 9.144049e-14 1.828810e-13 1.000000e+00
[11,] 7.128457e-14 1.425691e-13 1.000000e+00
[12,] 4.415480e-14 8.830961e-14 1.000000e+00
[13,] 4.084102e-15 8.168205e-15 1.000000e+00
[14,] 8.184224e-16 1.636845e-15 1.000000e+00
[15,] 8.427676e-16 1.685535e-15 1.000000e+00
[16,] 6.964461e-17 1.392892e-16 1.000000e+00
[17,] 9.038471e-18 1.807694e-17 1.000000e+00
[18,] 1.353963e-18 2.707926e-18 1.000000e+00
[19,] 2.106264e-19 4.212527e-19 1.000000e+00
[20,] 2.146991e-20 4.293983e-20 1.000000e+00
[21,] 5.435769e-21 1.087154e-20 1.000000e+00
[22,] 9.288636e-22 1.857727e-21 1.000000e+00
[23,] 1.130478e-22 2.260955e-22 1.000000e+00
[24,] 1.354563e-23 2.709126e-23 1.000000e+00
[25,] 2.382399e-24 4.764799e-24 1.000000e+00
[26,] 1.891944e-24 3.783887e-24 1.000000e+00
[27,] 2.123986e-25 4.247972e-25 1.000000e+00
[28,] 1.841668e-26 3.683336e-26 1.000000e+00
[29,] 1.534922e-27 3.069845e-27 1.000000e+00
[30,] 1.702529e-28 3.405058e-28 1.000000e+00
[31,] 1.796417e-29 3.592833e-29 1.000000e+00
[32,] 2.682758e-30 5.365516e-30 1.000000e+00
[33,] 2.488180e-25 4.976359e-25 1.000000e+00
[34,] 2.543205e-14 5.086410e-14 1.000000e+00
[35,] 8.492491e-08 1.698498e-07 9.999999e-01
[36,] 2.087938e-03 4.175877e-03 9.979121e-01
[37,] 1.265529e-01 2.531057e-01 8.734471e-01
[38,] 6.822596e-01 6.354809e-01 3.177404e-01
[39,] 9.998970e-01 2.060559e-04 1.030279e-04
[40,] 1.000000e+00 3.247525e-16 1.623762e-16
[41,] 1.000000e+00 2.240011e-32 1.120006e-32
[42,] 1.000000e+00 2.603400e-31 1.301700e-31
[43,] 1.000000e+00 2.403148e-30 1.201574e-30
[44,] 1.000000e+00 1.361368e-29 6.806840e-30
[45,] 1.000000e+00 2.549954e-28 1.274977e-28
[46,] 1.000000e+00 4.207380e-27 2.103690e-27
[47,] 1.000000e+00 7.214949e-26 3.607475e-26
[48,] 1.000000e+00 1.187998e-24 5.939990e-25
[49,] 1.000000e+00 1.940940e-23 9.704698e-24
[50,] 1.000000e+00 1.679101e-22 8.395505e-23
[51,] 1.000000e+00 8.177216e-26 4.088608e-26
[52,] 1.000000e+00 1.767859e-24 8.839293e-25
[53,] 1.000000e+00 1.978881e-23 9.894403e-24
[54,] 1.000000e+00 3.273864e-22 1.636932e-22
[55,] 1.000000e+00 7.119847e-21 3.559924e-21
[56,] 1.000000e+00 1.782791e-19 8.913956e-20
[57,] 1.000000e+00 3.949140e-18 1.974570e-18
[58,] 1.000000e+00 7.337003e-17 3.668502e-17
[59,] 1.000000e+00 1.997743e-16 9.988716e-17
[60,] 1.000000e+00 4.360182e-15 2.180091e-15
[61,] 1.000000e+00 9.702818e-14 4.851409e-14
[62,] 1.000000e+00 2.200625e-12 1.100312e-12
[63,] 1.000000e+00 4.792908e-11 2.396454e-11
[64,] 1.000000e+00 1.015824e-09 5.079120e-10
[65,] 1.000000e+00 4.485883e-09 2.242942e-09
[66,] 1.000000e+00 2.053044e-08 1.026522e-08
[67,] 9.999998e-01 4.684117e-07 2.342058e-07
[68,] 9.999943e-01 1.134362e-05 5.671812e-06
[69,] 9.998879e-01 2.241239e-04 1.120620e-04
> postscript(file="/var/www/html/rcomp/tmp/1t1sf1229089308.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/280ku1229089308.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/30iyt1229089308.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4p35o1229089308.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5tw3e1229089308.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 = 104
Frequency = 1
1 2 3 4 5 6
350.45453 -213.75252 -731.59033 -1123.22782 -1640.55087 -1287.49185
7 8 9 10 11 12
929.82084 1311.69171 878.12905 56.26350 -574.47939 -706.35554
13 14 15 16 17 18
-588.87151 -916.63667 -1284.58702 -1493.03570 -1759.56290 -1287.73377
19 20 21 22 23 24
1087.80507 1271.60666 937.77665 250.74981 383.08861 485.44207
25 26 27 28 29 30
396.17648 214.55937 -413.26445 -638.22264 -954.30721 -783.06585
31 32 33 34 35 36
1454.61860 1239.60396 1671.66149 935.76759 358.35215 294.73797
37 38 39 40 41 42
377.23059 277.67529 -290.09889 -687.33676 -1224.91138 -1015.02157
43 44 45 46 47 48
926.81431 1444.59907 1661.01849 609.42049 -131.09676 -356.92309
49 50 51 52 53 54
-407.03211 1854.32229 5373.28835 8312.90295 10817.86808 9205.62803
55 56 57 58 59 60
-8372.32283 -11913.53711 -9775.90718 -3734.75929 -69.83574 17.07451
61 62 63 64 65 66
84.86135 72.19111 -413.97146 -630.72535 -955.17973 -877.63193
67 68 69 70 71 72
1105.19480 1435.14486 1861.05447 1024.31423 308.64048 449.63697
73 74 75 76 77 78
291.70508 27.94675 -433.51795 -1033.20740 -1359.18599 -1658.02277
79 80 81 82 83 84
783.35223 1467.21464 1139.50436 224.48033 -458.01363 -347.24144
85 86 87 88 89 90
-484.50830 -852.05933 -1085.96335 -1709.42930 -1703.03633 -998.51918
91 92 93 94 95 96
1193.76495 1910.74136 1626.76267 633.76336 183.34427 163.62856
97 98 99 100 101 102
-20.01611 -464.24629 -720.29491 -997.71799 -1221.13366 -1298.14110
103 104
890.95204 1832.93486
> postscript(file="/var/www/html/rcomp/tmp/6rju71229089308.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 = 104
Frequency = 1
lag(myerror, k = 1) myerror
0 350.45453 NA
1 -213.75252 350.45453
2 -731.59033 -213.75252
3 -1123.22782 -731.59033
4 -1640.55087 -1123.22782
5 -1287.49185 -1640.55087
6 929.82084 -1287.49185
7 1311.69171 929.82084
8 878.12905 1311.69171
9 56.26350 878.12905
10 -574.47939 56.26350
11 -706.35554 -574.47939
12 -588.87151 -706.35554
13 -916.63667 -588.87151
14 -1284.58702 -916.63667
15 -1493.03570 -1284.58702
16 -1759.56290 -1493.03570
17 -1287.73377 -1759.56290
18 1087.80507 -1287.73377
19 1271.60666 1087.80507
20 937.77665 1271.60666
21 250.74981 937.77665
22 383.08861 250.74981
23 485.44207 383.08861
24 396.17648 485.44207
25 214.55937 396.17648
26 -413.26445 214.55937
27 -638.22264 -413.26445
28 -954.30721 -638.22264
29 -783.06585 -954.30721
30 1454.61860 -783.06585
31 1239.60396 1454.61860
32 1671.66149 1239.60396
33 935.76759 1671.66149
34 358.35215 935.76759
35 294.73797 358.35215
36 377.23059 294.73797
37 277.67529 377.23059
38 -290.09889 277.67529
39 -687.33676 -290.09889
40 -1224.91138 -687.33676
41 -1015.02157 -1224.91138
42 926.81431 -1015.02157
43 1444.59907 926.81431
44 1661.01849 1444.59907
45 609.42049 1661.01849
46 -131.09676 609.42049
47 -356.92309 -131.09676
48 -407.03211 -356.92309
49 1854.32229 -407.03211
50 5373.28835 1854.32229
51 8312.90295 5373.28835
52 10817.86808 8312.90295
53 9205.62803 10817.86808
54 -8372.32283 9205.62803
55 -11913.53711 -8372.32283
56 -9775.90718 -11913.53711
57 -3734.75929 -9775.90718
58 -69.83574 -3734.75929
59 17.07451 -69.83574
60 84.86135 17.07451
61 72.19111 84.86135
62 -413.97146 72.19111
63 -630.72535 -413.97146
64 -955.17973 -630.72535
65 -877.63193 -955.17973
66 1105.19480 -877.63193
67 1435.14486 1105.19480
68 1861.05447 1435.14486
69 1024.31423 1861.05447
70 308.64048 1024.31423
71 449.63697 308.64048
72 291.70508 449.63697
73 27.94675 291.70508
74 -433.51795 27.94675
75 -1033.20740 -433.51795
76 -1359.18599 -1033.20740
77 -1658.02277 -1359.18599
78 783.35223 -1658.02277
79 1467.21464 783.35223
80 1139.50436 1467.21464
81 224.48033 1139.50436
82 -458.01363 224.48033
83 -347.24144 -458.01363
84 -484.50830 -347.24144
85 -852.05933 -484.50830
86 -1085.96335 -852.05933
87 -1709.42930 -1085.96335
88 -1703.03633 -1709.42930
89 -998.51918 -1703.03633
90 1193.76495 -998.51918
91 1910.74136 1193.76495
92 1626.76267 1910.74136
93 633.76336 1626.76267
94 183.34427 633.76336
95 163.62856 183.34427
96 -20.01611 163.62856
97 -464.24629 -20.01611
98 -720.29491 -464.24629
99 -997.71799 -720.29491
100 -1221.13366 -997.71799
101 -1298.14110 -1221.13366
102 890.95204 -1298.14110
103 1832.93486 890.95204
104 NA 1832.93486
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -213.75252 350.45453
[2,] -731.59033 -213.75252
[3,] -1123.22782 -731.59033
[4,] -1640.55087 -1123.22782
[5,] -1287.49185 -1640.55087
[6,] 929.82084 -1287.49185
[7,] 1311.69171 929.82084
[8,] 878.12905 1311.69171
[9,] 56.26350 878.12905
[10,] -574.47939 56.26350
[11,] -706.35554 -574.47939
[12,] -588.87151 -706.35554
[13,] -916.63667 -588.87151
[14,] -1284.58702 -916.63667
[15,] -1493.03570 -1284.58702
[16,] -1759.56290 -1493.03570
[17,] -1287.73377 -1759.56290
[18,] 1087.80507 -1287.73377
[19,] 1271.60666 1087.80507
[20,] 937.77665 1271.60666
[21,] 250.74981 937.77665
[22,] 383.08861 250.74981
[23,] 485.44207 383.08861
[24,] 396.17648 485.44207
[25,] 214.55937 396.17648
[26,] -413.26445 214.55937
[27,] -638.22264 -413.26445
[28,] -954.30721 -638.22264
[29,] -783.06585 -954.30721
[30,] 1454.61860 -783.06585
[31,] 1239.60396 1454.61860
[32,] 1671.66149 1239.60396
[33,] 935.76759 1671.66149
[34,] 358.35215 935.76759
[35,] 294.73797 358.35215
[36,] 377.23059 294.73797
[37,] 277.67529 377.23059
[38,] -290.09889 277.67529
[39,] -687.33676 -290.09889
[40,] -1224.91138 -687.33676
[41,] -1015.02157 -1224.91138
[42,] 926.81431 -1015.02157
[43,] 1444.59907 926.81431
[44,] 1661.01849 1444.59907
[45,] 609.42049 1661.01849
[46,] -131.09676 609.42049
[47,] -356.92309 -131.09676
[48,] -407.03211 -356.92309
[49,] 1854.32229 -407.03211
[50,] 5373.28835 1854.32229
[51,] 8312.90295 5373.28835
[52,] 10817.86808 8312.90295
[53,] 9205.62803 10817.86808
[54,] -8372.32283 9205.62803
[55,] -11913.53711 -8372.32283
[56,] -9775.90718 -11913.53711
[57,] -3734.75929 -9775.90718
[58,] -69.83574 -3734.75929
[59,] 17.07451 -69.83574
[60,] 84.86135 17.07451
[61,] 72.19111 84.86135
[62,] -413.97146 72.19111
[63,] -630.72535 -413.97146
[64,] -955.17973 -630.72535
[65,] -877.63193 -955.17973
[66,] 1105.19480 -877.63193
[67,] 1435.14486 1105.19480
[68,] 1861.05447 1435.14486
[69,] 1024.31423 1861.05447
[70,] 308.64048 1024.31423
[71,] 449.63697 308.64048
[72,] 291.70508 449.63697
[73,] 27.94675 291.70508
[74,] -433.51795 27.94675
[75,] -1033.20740 -433.51795
[76,] -1359.18599 -1033.20740
[77,] -1658.02277 -1359.18599
[78,] 783.35223 -1658.02277
[79,] 1467.21464 783.35223
[80,] 1139.50436 1467.21464
[81,] 224.48033 1139.50436
[82,] -458.01363 224.48033
[83,] -347.24144 -458.01363
[84,] -484.50830 -347.24144
[85,] -852.05933 -484.50830
[86,] -1085.96335 -852.05933
[87,] -1709.42930 -1085.96335
[88,] -1703.03633 -1709.42930
[89,] -998.51918 -1703.03633
[90,] 1193.76495 -998.51918
[91,] 1910.74136 1193.76495
[92,] 1626.76267 1910.74136
[93,] 633.76336 1626.76267
[94,] 183.34427 633.76336
[95,] 163.62856 183.34427
[96,] -20.01611 163.62856
[97,] -464.24629 -20.01611
[98,] -720.29491 -464.24629
[99,] -997.71799 -720.29491
[100,] -1221.13366 -997.71799
[101,] -1298.14110 -1221.13366
[102,] 890.95204 -1298.14110
[103,] 1832.93486 890.95204
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -213.75252 350.45453
2 -731.59033 -213.75252
3 -1123.22782 -731.59033
4 -1640.55087 -1123.22782
5 -1287.49185 -1640.55087
6 929.82084 -1287.49185
7 1311.69171 929.82084
8 878.12905 1311.69171
9 56.26350 878.12905
10 -574.47939 56.26350
11 -706.35554 -574.47939
12 -588.87151 -706.35554
13 -916.63667 -588.87151
14 -1284.58702 -916.63667
15 -1493.03570 -1284.58702
16 -1759.56290 -1493.03570
17 -1287.73377 -1759.56290
18 1087.80507 -1287.73377
19 1271.60666 1087.80507
20 937.77665 1271.60666
21 250.74981 937.77665
22 383.08861 250.74981
23 485.44207 383.08861
24 396.17648 485.44207
25 214.55937 396.17648
26 -413.26445 214.55937
27 -638.22264 -413.26445
28 -954.30721 -638.22264
29 -783.06585 -954.30721
30 1454.61860 -783.06585
31 1239.60396 1454.61860
32 1671.66149 1239.60396
33 935.76759 1671.66149
34 358.35215 935.76759
35 294.73797 358.35215
36 377.23059 294.73797
37 277.67529 377.23059
38 -290.09889 277.67529
39 -687.33676 -290.09889
40 -1224.91138 -687.33676
41 -1015.02157 -1224.91138
42 926.81431 -1015.02157
43 1444.59907 926.81431
44 1661.01849 1444.59907
45 609.42049 1661.01849
46 -131.09676 609.42049
47 -356.92309 -131.09676
48 -407.03211 -356.92309
49 1854.32229 -407.03211
50 5373.28835 1854.32229
51 8312.90295 5373.28835
52 10817.86808 8312.90295
53 9205.62803 10817.86808
54 -8372.32283 9205.62803
55 -11913.53711 -8372.32283
56 -9775.90718 -11913.53711
57 -3734.75929 -9775.90718
58 -69.83574 -3734.75929
59 17.07451 -69.83574
60 84.86135 17.07451
61 72.19111 84.86135
62 -413.97146 72.19111
63 -630.72535 -413.97146
64 -955.17973 -630.72535
65 -877.63193 -955.17973
66 1105.19480 -877.63193
67 1435.14486 1105.19480
68 1861.05447 1435.14486
69 1024.31423 1861.05447
70 308.64048 1024.31423
71 449.63697 308.64048
72 291.70508 449.63697
73 27.94675 291.70508
74 -433.51795 27.94675
75 -1033.20740 -433.51795
76 -1359.18599 -1033.20740
77 -1658.02277 -1359.18599
78 783.35223 -1658.02277
79 1467.21464 783.35223
80 1139.50436 1467.21464
81 224.48033 1139.50436
82 -458.01363 224.48033
83 -347.24144 -458.01363
84 -484.50830 -347.24144
85 -852.05933 -484.50830
86 -1085.96335 -852.05933
87 -1709.42930 -1085.96335
88 -1703.03633 -1709.42930
89 -998.51918 -1703.03633
90 1193.76495 -998.51918
91 1910.74136 1193.76495
92 1626.76267 1910.74136
93 633.76336 1626.76267
94 183.34427 633.76336
95 163.62856 183.34427
96 -20.01611 163.62856
97 -464.24629 -20.01611
98 -720.29491 -464.24629
99 -997.71799 -720.29491
100 -1221.13366 -997.71799
101 -1298.14110 -1221.13366
102 890.95204 -1298.14110
103 1832.93486 890.95204
> 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/7exum1229089308.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/83lvi1229089308.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9o2jr1229089308.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10m29p1229089308.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11zusi1229089308.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/12agay1229089308.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/13fvlq1229089309.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/142mrr1229089309.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/1594gr1229089309.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/16wpaw1229089309.tab")
+ }
>
> system("convert tmp/1t1sf1229089308.ps tmp/1t1sf1229089308.png")
> system("convert tmp/280ku1229089308.ps tmp/280ku1229089308.png")
> system("convert tmp/30iyt1229089308.ps tmp/30iyt1229089308.png")
> system("convert tmp/4p35o1229089308.ps tmp/4p35o1229089308.png")
> system("convert tmp/5tw3e1229089308.ps tmp/5tw3e1229089308.png")
> system("convert tmp/6rju71229089308.ps tmp/6rju71229089308.png")
> system("convert tmp/7exum1229089308.ps tmp/7exum1229089308.png")
> system("convert tmp/83lvi1229089308.ps tmp/83lvi1229089308.png")
> system("convert tmp/9o2jr1229089308.ps tmp/9o2jr1229089308.png")
> system("convert tmp/10m29p1229089308.ps tmp/10m29p1229089308.png")
>
>
> proc.time()
user system elapsed
3.124 1.605 4.079