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(1149822
+ ,1086979
+ ,1276674
+ ,1522522
+ ,1742117
+ ,1737275
+ ,1979900
+ ,2061036
+ ,1867943
+ ,1707752
+ ,1298756
+ ,1281814
+ ,1281151
+ ,1164976
+ ,1454329
+ ,1645288
+ ,1817743
+ ,1895785
+ ,2236311
+ ,2295951
+ ,2087315
+ ,1980891
+ ,1465446
+ ,1445026
+ ,1488120
+ ,1338333
+ ,1715789
+ ,1806090
+ ,2083316
+ ,2092278
+ ,2430800
+ ,2424894
+ ,2299016
+ ,2130688
+ ,1652221
+ ,1608162
+ ,1647074
+ ,1479691
+ ,1884978
+ ,2007898
+ ,2208954
+ ,2217164
+ ,2534291
+ ,2560312
+ ,2429069
+ ,2315077
+ ,1799608
+ ,1772590
+ ,1744799
+ ,1659093
+ ,2099821
+ ,2135736
+ ,2427894
+ ,2468882
+ ,2703217
+ ,2766841
+ ,2655236
+ ,2550373
+ ,2052097
+ ,1998055
+ ,1920748
+ ,1876694
+ ,2380930
+ ,2467402
+ ,2770771
+ ,2781340
+ ,3143926
+ ,3172235
+ ,2952540
+ ,2920877
+ ,2384552
+ ,2248987
+ ,2208616
+ ,2178756
+ ,2632870
+ ,2706905
+ ,3029745
+ ,3015402
+ ,3391414
+ ,3507805
+ ,3177852
+ ,3142961
+ ,2545815
+ ,2414007
+ ,2372578
+ ,2332664
+ ,2825328
+ ,2901478
+ ,3263955
+ ,3226738
+ ,3610786
+ ,3709274
+ ,3467185
+ ,3449646
+ ,2802951
+ ,2462530
+ ,2490645
+ ,2561520
+ ,3067554
+ ,3226951
+ ,3546493
+ ,3492787
+ ,3952263
+ ,3932072
+ ,3720284
+ ,3651555
+ ,2914972
+ ,2713514
+ ,2703997
+ ,2591373
+ ,3163748
+ ,3355137
+ ,3613702
+ ,3686773
+ ,4098716
+ ,4063517
+ ,3551489
+ ,3226663
+ ,2656842
+ ,2597484
+ ,2572399
+ ,2596631
+ ,3165225
+ ,3303145
+ ,3698247
+ ,3668631
+ ,4130433
+ ,4131400
+ ,3864358
+ ,3721110
+ ,2892532
+ ,2843451
+ ,2747502
+ ,2668775
+ ,3018602
+ ,3013392
+ ,3393657
+ ,3544233
+ ,4075832
+ ,4032923
+ ,3734509
+ ,3761285
+ ,2970090
+ ,2847849
+ ,2741680
+ ,2830639
+ ,3257673
+ ,3480085
+ ,3843271
+ ,3796961
+ ,4337767
+ ,4243630
+ ,3927202
+ ,3915296
+ ,3087396
+ ,2963792
+ ,2955792
+ ,2829925
+ ,3281195
+ ,3548011
+ ,4059648
+ ,3941175
+ ,4528594
+ ,4433151
+ ,4145737
+ ,4077132
+ ,3198519
+ ,3078660
+ ,3028202
+ ,2858642
+ ,3398954
+ ,3808883
+ ,4175961
+ ,4227542
+ ,4744616
+ ,4608012
+ ,4295049
+ ,4201144
+ ,3353276
+ ,3286851
+ ,3169889
+ ,3051720
+ ,3695426
+ ,3905501
+ ,4296458
+ ,4246247
+ ,4921849
+ ,4821446
+ ,4425064
+ ,4379099
+ ,3472889
+ ,3359160
+ ,3200944
+ ,3153170
+ ,3741498
+ ,3918719
+ ,4403449
+ ,4400407
+ ,4847473
+ ,4716136
+ ,4297440
+ ,4272253
+ ,3271834
+ ,3168388
+ ,2911748
+ ,2720999
+ ,3199918
+ ,3672623
+ ,3892013
+ ,3850845
+ ,4532467
+ ,4484739
+ ,4014972
+ ,3983758
+ ,3158459
+ ,3100569
+ ,2935404
+ ,2855719
+ ,3465611
+ ,3006985
+ ,4095110
+ ,4104793
+ ,4730788
+ ,4642726
+ ,4246919
+ ,4308117)
+ ,dim=c(1
+ ,226)
+ ,dimnames=list(c('Passagiers')
+ ,1:226))
> y <- array(NA,dim=c(1,226),dimnames=list(c('Passagiers'),1:226))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
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
Passagiers M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 1149822 1 0 0 0 0 0 0 0 0 0 0
2 1086979 0 1 0 0 0 0 0 0 0 0 0
3 1276674 0 0 1 0 0 0 0 0 0 0 0
4 1522522 0 0 0 1 0 0 0 0 0 0 0
5 1742117 0 0 0 0 1 0 0 0 0 0 0
6 1737275 0 0 0 0 0 1 0 0 0 0 0
7 1979900 0 0 0 0 0 0 1 0 0 0 0
8 2061036 0 0 0 0 0 0 0 1 0 0 0
9 1867943 0 0 0 0 0 0 0 0 1 0 0
10 1707752 0 0 0 0 0 0 0 0 0 1 0
11 1298756 0 0 0 0 0 0 0 0 0 0 1
12 1281814 0 0 0 0 0 0 0 0 0 0 0
13 1281151 1 0 0 0 0 0 0 0 0 0 0
14 1164976 0 1 0 0 0 0 0 0 0 0 0
15 1454329 0 0 1 0 0 0 0 0 0 0 0
16 1645288 0 0 0 1 0 0 0 0 0 0 0
17 1817743 0 0 0 0 1 0 0 0 0 0 0
18 1895785 0 0 0 0 0 1 0 0 0 0 0
19 2236311 0 0 0 0 0 0 1 0 0 0 0
20 2295951 0 0 0 0 0 0 0 1 0 0 0
21 2087315 0 0 0 0 0 0 0 0 1 0 0
22 1980891 0 0 0 0 0 0 0 0 0 1 0
23 1465446 0 0 0 0 0 0 0 0 0 0 1
24 1445026 0 0 0 0 0 0 0 0 0 0 0
25 1488120 1 0 0 0 0 0 0 0 0 0 0
26 1338333 0 1 0 0 0 0 0 0 0 0 0
27 1715789 0 0 1 0 0 0 0 0 0 0 0
28 1806090 0 0 0 1 0 0 0 0 0 0 0
29 2083316 0 0 0 0 1 0 0 0 0 0 0
30 2092278 0 0 0 0 0 1 0 0 0 0 0
31 2430800 0 0 0 0 0 0 1 0 0 0 0
32 2424894 0 0 0 0 0 0 0 1 0 0 0
33 2299016 0 0 0 0 0 0 0 0 1 0 0
34 2130688 0 0 0 0 0 0 0 0 0 1 0
35 1652221 0 0 0 0 0 0 0 0 0 0 1
36 1608162 0 0 0 0 0 0 0 0 0 0 0
37 1647074 1 0 0 0 0 0 0 0 0 0 0
38 1479691 0 1 0 0 0 0 0 0 0 0 0
39 1884978 0 0 1 0 0 0 0 0 0 0 0
40 2007898 0 0 0 1 0 0 0 0 0 0 0
41 2208954 0 0 0 0 1 0 0 0 0 0 0
42 2217164 0 0 0 0 0 1 0 0 0 0 0
43 2534291 0 0 0 0 0 0 1 0 0 0 0
44 2560312 0 0 0 0 0 0 0 1 0 0 0
45 2429069 0 0 0 0 0 0 0 0 1 0 0
46 2315077 0 0 0 0 0 0 0 0 0 1 0
47 1799608 0 0 0 0 0 0 0 0 0 0 1
48 1772590 0 0 0 0 0 0 0 0 0 0 0
49 1744799 1 0 0 0 0 0 0 0 0 0 0
50 1659093 0 1 0 0 0 0 0 0 0 0 0
51 2099821 0 0 1 0 0 0 0 0 0 0 0
52 2135736 0 0 0 1 0 0 0 0 0 0 0
53 2427894 0 0 0 0 1 0 0 0 0 0 0
54 2468882 0 0 0 0 0 1 0 0 0 0 0
55 2703217 0 0 0 0 0 0 1 0 0 0 0
56 2766841 0 0 0 0 0 0 0 1 0 0 0
57 2655236 0 0 0 0 0 0 0 0 1 0 0
58 2550373 0 0 0 0 0 0 0 0 0 1 0
59 2052097 0 0 0 0 0 0 0 0 0 0 1
60 1998055 0 0 0 0 0 0 0 0 0 0 0
61 1920748 1 0 0 0 0 0 0 0 0 0 0
62 1876694 0 1 0 0 0 0 0 0 0 0 0
63 2380930 0 0 1 0 0 0 0 0 0 0 0
64 2467402 0 0 0 1 0 0 0 0 0 0 0
65 2770771 0 0 0 0 1 0 0 0 0 0 0
66 2781340 0 0 0 0 0 1 0 0 0 0 0
67 3143926 0 0 0 0 0 0 1 0 0 0 0
68 3172235 0 0 0 0 0 0 0 1 0 0 0
69 2952540 0 0 0 0 0 0 0 0 1 0 0
70 2920877 0 0 0 0 0 0 0 0 0 1 0
71 2384552 0 0 0 0 0 0 0 0 0 0 1
72 2248987 0 0 0 0 0 0 0 0 0 0 0
73 2208616 1 0 0 0 0 0 0 0 0 0 0
74 2178756 0 1 0 0 0 0 0 0 0 0 0
75 2632870 0 0 1 0 0 0 0 0 0 0 0
76 2706905 0 0 0 1 0 0 0 0 0 0 0
77 3029745 0 0 0 0 1 0 0 0 0 0 0
78 3015402 0 0 0 0 0 1 0 0 0 0 0
79 3391414 0 0 0 0 0 0 1 0 0 0 0
80 3507805 0 0 0 0 0 0 0 1 0 0 0
81 3177852 0 0 0 0 0 0 0 0 1 0 0
82 3142961 0 0 0 0 0 0 0 0 0 1 0
83 2545815 0 0 0 0 0 0 0 0 0 0 1
84 2414007 0 0 0 0 0 0 0 0 0 0 0
85 2372578 1 0 0 0 0 0 0 0 0 0 0
86 2332664 0 1 0 0 0 0 0 0 0 0 0
87 2825328 0 0 1 0 0 0 0 0 0 0 0
88 2901478 0 0 0 1 0 0 0 0 0 0 0
89 3263955 0 0 0 0 1 0 0 0 0 0 0
90 3226738 0 0 0 0 0 1 0 0 0 0 0
91 3610786 0 0 0 0 0 0 1 0 0 0 0
92 3709274 0 0 0 0 0 0 0 1 0 0 0
93 3467185 0 0 0 0 0 0 0 0 1 0 0
94 3449646 0 0 0 0 0 0 0 0 0 1 0
95 2802951 0 0 0 0 0 0 0 0 0 0 1
96 2462530 0 0 0 0 0 0 0 0 0 0 0
97 2490645 1 0 0 0 0 0 0 0 0 0 0
98 2561520 0 1 0 0 0 0 0 0 0 0 0
99 3067554 0 0 1 0 0 0 0 0 0 0 0
100 3226951 0 0 0 1 0 0 0 0 0 0 0
101 3546493 0 0 0 0 1 0 0 0 0 0 0
102 3492787 0 0 0 0 0 1 0 0 0 0 0
103 3952263 0 0 0 0 0 0 1 0 0 0 0
104 3932072 0 0 0 0 0 0 0 1 0 0 0
105 3720284 0 0 0 0 0 0 0 0 1 0 0
106 3651555 0 0 0 0 0 0 0 0 0 1 0
107 2914972 0 0 0 0 0 0 0 0 0 0 1
108 2713514 0 0 0 0 0 0 0 0 0 0 0
109 2703997 1 0 0 0 0 0 0 0 0 0 0
110 2591373 0 1 0 0 0 0 0 0 0 0 0
111 3163748 0 0 1 0 0 0 0 0 0 0 0
112 3355137 0 0 0 1 0 0 0 0 0 0 0
113 3613702 0 0 0 0 1 0 0 0 0 0 0
114 3686773 0 0 0 0 0 1 0 0 0 0 0
115 4098716 0 0 0 0 0 0 1 0 0 0 0
116 4063517 0 0 0 0 0 0 0 1 0 0 0
117 3551489 0 0 0 0 0 0 0 0 1 0 0
118 3226663 0 0 0 0 0 0 0 0 0 1 0
119 2656842 0 0 0 0 0 0 0 0 0 0 1
120 2597484 0 0 0 0 0 0 0 0 0 0 0
121 2572399 1 0 0 0 0 0 0 0 0 0 0
122 2596631 0 1 0 0 0 0 0 0 0 0 0
123 3165225 0 0 1 0 0 0 0 0 0 0 0
124 3303145 0 0 0 1 0 0 0 0 0 0 0
125 3698247 0 0 0 0 1 0 0 0 0 0 0
126 3668631 0 0 0 0 0 1 0 0 0 0 0
127 4130433 0 0 0 0 0 0 1 0 0 0 0
128 4131400 0 0 0 0 0 0 0 1 0 0 0
129 3864358 0 0 0 0 0 0 0 0 1 0 0
130 3721110 0 0 0 0 0 0 0 0 0 1 0
131 2892532 0 0 0 0 0 0 0 0 0 0 1
132 2843451 0 0 0 0 0 0 0 0 0 0 0
133 2747502 1 0 0 0 0 0 0 0 0 0 0
134 2668775 0 1 0 0 0 0 0 0 0 0 0
135 3018602 0 0 1 0 0 0 0 0 0 0 0
136 3013392 0 0 0 1 0 0 0 0 0 0 0
137 3393657 0 0 0 0 1 0 0 0 0 0 0
138 3544233 0 0 0 0 0 1 0 0 0 0 0
139 4075832 0 0 0 0 0 0 1 0 0 0 0
140 4032923 0 0 0 0 0 0 0 1 0 0 0
141 3734509 0 0 0 0 0 0 0 0 1 0 0
142 3761285 0 0 0 0 0 0 0 0 0 1 0
143 2970090 0 0 0 0 0 0 0 0 0 0 1
144 2847849 0 0 0 0 0 0 0 0 0 0 0
145 2741680 1 0 0 0 0 0 0 0 0 0 0
146 2830639 0 1 0 0 0 0 0 0 0 0 0
147 3257673 0 0 1 0 0 0 0 0 0 0 0
148 3480085 0 0 0 1 0 0 0 0 0 0 0
149 3843271 0 0 0 0 1 0 0 0 0 0 0
150 3796961 0 0 0 0 0 1 0 0 0 0 0
151 4337767 0 0 0 0 0 0 1 0 0 0 0
152 4243630 0 0 0 0 0 0 0 1 0 0 0
153 3927202 0 0 0 0 0 0 0 0 1 0 0
154 3915296 0 0 0 0 0 0 0 0 0 1 0
155 3087396 0 0 0 0 0 0 0 0 0 0 1
156 2963792 0 0 0 0 0 0 0 0 0 0 0
157 2955792 1 0 0 0 0 0 0 0 0 0 0
158 2829925 0 1 0 0 0 0 0 0 0 0 0
159 3281195 0 0 1 0 0 0 0 0 0 0 0
160 3548011 0 0 0 1 0 0 0 0 0 0 0
161 4059648 0 0 0 0 1 0 0 0 0 0 0
162 3941175 0 0 0 0 0 1 0 0 0 0 0
163 4528594 0 0 0 0 0 0 1 0 0 0 0
164 4433151 0 0 0 0 0 0 0 1 0 0 0
165 4145737 0 0 0 0 0 0 0 0 1 0 0
166 4077132 0 0 0 0 0 0 0 0 0 1 0
167 3198519 0 0 0 0 0 0 0 0 0 0 1
168 3078660 0 0 0 0 0 0 0 0 0 0 0
169 3028202 1 0 0 0 0 0 0 0 0 0 0
170 2858642 0 1 0 0 0 0 0 0 0 0 0
171 3398954 0 0 1 0 0 0 0 0 0 0 0
172 3808883 0 0 0 1 0 0 0 0 0 0 0
173 4175961 0 0 0 0 1 0 0 0 0 0 0
174 4227542 0 0 0 0 0 1 0 0 0 0 0
175 4744616 0 0 0 0 0 0 1 0 0 0 0
176 4608012 0 0 0 0 0 0 0 1 0 0 0
177 4295049 0 0 0 0 0 0 0 0 1 0 0
178 4201144 0 0 0 0 0 0 0 0 0 1 0
179 3353276 0 0 0 0 0 0 0 0 0 0 1
180 3286851 0 0 0 0 0 0 0 0 0 0 0
181 3169889 1 0 0 0 0 0 0 0 0 0 0
182 3051720 0 1 0 0 0 0 0 0 0 0 0
183 3695426 0 0 1 0 0 0 0 0 0 0 0
184 3905501 0 0 0 1 0 0 0 0 0 0 0
185 4296458 0 0 0 0 1 0 0 0 0 0 0
186 4246247 0 0 0 0 0 1 0 0 0 0 0
187 4921849 0 0 0 0 0 0 1 0 0 0 0
188 4821446 0 0 0 0 0 0 0 1 0 0 0
189 4425064 0 0 0 0 0 0 0 0 1 0 0
190 4379099 0 0 0 0 0 0 0 0 0 1 0
191 3472889 0 0 0 0 0 0 0 0 0 0 1
192 3359160 0 0 0 0 0 0 0 0 0 0 0
193 3200944 1 0 0 0 0 0 0 0 0 0 0
194 3153170 0 1 0 0 0 0 0 0 0 0 0
195 3741498 0 0 1 0 0 0 0 0 0 0 0
196 3918719 0 0 0 1 0 0 0 0 0 0 0
197 4403449 0 0 0 0 1 0 0 0 0 0 0
198 4400407 0 0 0 0 0 1 0 0 0 0 0
199 4847473 0 0 0 0 0 0 1 0 0 0 0
200 4716136 0 0 0 0 0 0 0 1 0 0 0
201 4297440 0 0 0 0 0 0 0 0 1 0 0
202 4272253 0 0 0 0 0 0 0 0 0 1 0
203 3271834 0 0 0 0 0 0 0 0 0 0 1
204 3168388 0 0 0 0 0 0 0 0 0 0 0
205 2911748 1 0 0 0 0 0 0 0 0 0 0
206 2720999 0 1 0 0 0 0 0 0 0 0 0
207 3199918 0 0 1 0 0 0 0 0 0 0 0
208 3672623 0 0 0 1 0 0 0 0 0 0 0
209 3892013 0 0 0 0 1 0 0 0 0 0 0
210 3850845 0 0 0 0 0 1 0 0 0 0 0
211 4532467 0 0 0 0 0 0 1 0 0 0 0
212 4484739 0 0 0 0 0 0 0 1 0 0 0
213 4014972 0 0 0 0 0 0 0 0 1 0 0
214 3983758 0 0 0 0 0 0 0 0 0 1 0
215 3158459 0 0 0 0 0 0 0 0 0 0 1
216 3100569 0 0 0 0 0 0 0 0 0 0 0
217 2935404 1 0 0 0 0 0 0 0 0 0 0
218 2855719 0 1 0 0 0 0 0 0 0 0 0
219 3465611 0 0 1 0 0 0 0 0 0 0 0
220 3006985 0 0 0 1 0 0 0 0 0 0 0
221 4095110 0 0 0 0 1 0 0 0 0 0 0
222 4104793 0 0 0 0 0 1 0 0 0 0 0
223 4730788 0 0 0 0 0 0 1 0 0 0 0
224 4642726 0 0 0 0 0 0 0 1 0 0 0
225 4246919 0 0 0 0 0 0 0 0 1 0 0
226 4308117 0 0 0 0 0 0 0 0 0 1 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
2510605 -127915 -203431 264454 406908 771632
M6 M7 M8 M9 M10 M11
773356 1222629 1205611 918826 841799 99298
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1753334 -645533 273442 587847 1188615
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2510605 187597 13.383 < 2e-16 ***
M1 -127915 261788 -0.489 0.625611
M2 -203431 261788 -0.777 0.437968
M3 264454 261788 1.010 0.313548
M4 406908 261788 1.554 0.121581
M5 771632 261788 2.948 0.003558 **
M6 773356 261788 2.954 0.003486 **
M7 1222629 261788 4.670 5.31e-06 ***
M8 1205611 261788 4.605 7.06e-06 ***
M9 918826 261788 3.510 0.000547 ***
M10 841799 261788 3.216 0.001503 **
M11 99298 265302 0.374 0.708565
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 795900 on 214 degrees of freedom
Multiple R-squared: 0.2818, Adjusted R-squared: 0.2448
F-statistic: 7.632 on 11 and 214 DF, p-value: 4.525e-11
> 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,] 3.214083e-03 6.428166e-03 9.967859e-01
[2,] 5.809041e-04 1.161808e-03 9.994191e-01
[3,] 8.331929e-05 1.666386e-04 9.999167e-01
[4,] 2.243204e-05 4.486408e-05 9.999776e-01
[5,] 1.623655e-05 3.247310e-05 9.999838e-01
[6,] 7.840177e-06 1.568035e-05 9.999922e-01
[7,] 3.231941e-06 6.463881e-06 9.999968e-01
[8,] 1.988558e-06 3.977115e-06 9.999980e-01
[9,] 6.001827e-07 1.200365e-06 9.999994e-01
[10,] 1.790638e-07 3.581276e-07 9.999998e-01
[11,] 1.426043e-07 2.852086e-07 9.999999e-01
[12,] 6.725163e-08 1.345033e-07 9.999999e-01
[13,] 9.878401e-08 1.975680e-07 9.999999e-01
[14,] 5.076104e-08 1.015221e-07 9.999999e-01
[15,] 4.593648e-08 9.187296e-08 1.000000e+00
[16,] 3.396187e-08 6.792375e-08 1.000000e+00
[17,] 3.557132e-08 7.114264e-08 1.000000e+00
[18,] 2.397682e-08 4.795364e-08 1.000000e+00
[19,] 2.337348e-08 4.674696e-08 1.000000e+00
[20,] 1.960041e-08 3.920082e-08 1.000000e+00
[21,] 1.375068e-08 2.750137e-08 1.000000e+00
[22,] 8.529488e-09 1.705898e-08 1.000000e+00
[23,] 9.325757e-09 1.865151e-08 1.000000e+00
[24,] 7.532296e-09 1.506459e-08 1.000000e+00
[25,] 1.274877e-08 2.549754e-08 1.000000e+00
[26,] 1.520801e-08 3.041601e-08 1.000000e+00
[27,] 1.810971e-08 3.621942e-08 1.000000e+00
[28,] 2.006737e-08 4.013475e-08 1.000000e+00
[29,] 2.694039e-08 5.388079e-08 1.000000e+00
[30,] 3.343482e-08 6.686964e-08 1.000000e+00
[31,] 4.546146e-08 9.092292e-08 1.000000e+00
[32,] 7.546451e-08 1.509290e-07 9.999999e-01
[33,] 8.534401e-08 1.706880e-07 9.999999e-01
[34,] 9.248516e-08 1.849703e-07 9.999999e-01
[35,] 1.135619e-07 2.271238e-07 9.999999e-01
[36,] 1.671090e-07 3.342181e-07 9.999998e-01
[37,] 4.659487e-07 9.318975e-07 9.999995e-01
[38,] 7.511504e-07 1.502301e-06 9.999992e-01
[39,] 1.818809e-06 3.637618e-06 9.999982e-01
[40,] 4.465044e-06 8.930087e-06 9.999955e-01
[41,] 1.092361e-05 2.184723e-05 9.999891e-01
[42,] 2.648293e-05 5.296585e-05 9.999735e-01
[43,] 6.106614e-05 1.221323e-04 9.999389e-01
[44,] 1.605087e-04 3.210174e-04 9.998395e-01
[45,] 2.928074e-04 5.856149e-04 9.997072e-01
[46,] 4.613611e-04 9.227223e-04 9.995386e-01
[47,] 7.105676e-04 1.421135e-03 9.992894e-01
[48,] 1.274923e-03 2.549846e-03 9.987251e-01
[49,] 3.431741e-03 6.863482e-03 9.965683e-01
[50,] 7.497808e-03 1.499562e-02 9.925022e-01
[51,] 1.908956e-02 3.817912e-02 9.809104e-01
[52,] 4.110794e-02 8.221588e-02 9.588921e-01
[53,] 9.805965e-02 1.961193e-01 9.019403e-01
[54,] 1.871768e-01 3.743536e-01 8.128232e-01
[55,] 2.812117e-01 5.624234e-01 7.187883e-01
[56,] 4.180307e-01 8.360615e-01 5.819693e-01
[57,] 5.099440e-01 9.801120e-01 4.900560e-01
[58,] 5.752703e-01 8.494595e-01 4.247297e-01
[59,] 6.444059e-01 7.111882e-01 3.555941e-01
[60,] 7.200108e-01 5.599784e-01 2.799892e-01
[61,] 8.059817e-01 3.880366e-01 1.940183e-01
[62,] 8.699026e-01 2.601947e-01 1.300974e-01
[63,] 9.298651e-01 1.402698e-01 7.013491e-02
[64,] 9.640367e-01 7.192658e-02 3.596329e-02
[65,] 9.875765e-01 2.484709e-02 1.242354e-02
[66,] 9.958895e-01 8.220923e-03 4.110462e-03
[67,] 9.983494e-01 3.301251e-03 1.650626e-03
[68,] 9.994456e-01 1.108806e-03 5.544029e-04
[69,] 9.996925e-01 6.149387e-04 3.074693e-04
[70,] 9.998106e-01 3.788744e-04 1.894372e-04
[71,] 9.998873e-01 2.253412e-04 1.126706e-04
[72,] 9.999368e-01 1.264368e-04 6.321839e-05
[73,] 9.999724e-01 5.513636e-05 2.756818e-05
[74,] 9.999888e-01 2.248931e-05 1.124466e-05
[75,] 9.999969e-01 6.180172e-06 3.090086e-06
[76,] 9.999992e-01 1.676072e-06 8.380362e-07
[77,] 9.999999e-01 2.212851e-07 1.106425e-07
[78,] 1.000000e+00 4.103727e-08 2.051863e-08
[79,] 1.000000e+00 1.147582e-08 5.737910e-09
[80,] 1.000000e+00 2.971852e-09 1.485926e-09
[81,] 1.000000e+00 1.684531e-09 8.422656e-10
[82,] 1.000000e+00 9.087036e-10 4.543518e-10
[83,] 1.000000e+00 5.557957e-10 2.778979e-10
[84,] 1.000000e+00 3.432257e-10 1.716129e-10
[85,] 1.000000e+00 1.678597e-10 8.392983e-11
[86,] 1.000000e+00 7.691574e-11 3.845787e-11
[87,] 1.000000e+00 2.508871e-11 1.254436e-11
[88,] 1.000000e+00 8.385973e-12 4.192987e-12
[89,] 1.000000e+00 1.562592e-12 7.812962e-13
[90,] 1.000000e+00 4.281726e-13 2.140863e-13
[91,] 1.000000e+00 1.963627e-13 9.818136e-14
[92,] 1.000000e+00 8.827314e-14 4.413657e-14
[93,] 1.000000e+00 7.849687e-14 3.924844e-14
[94,] 1.000000e+00 6.735944e-14 3.367972e-14
[95,] 1.000000e+00 6.265986e-14 3.132993e-14
[96,] 1.000000e+00 5.948980e-14 2.974490e-14
[97,] 1.000000e+00 4.878102e-14 2.439051e-14
[98,] 1.000000e+00 3.810941e-14 1.905470e-14
[99,] 1.000000e+00 2.072955e-14 1.036477e-14
[100,] 1.000000e+00 1.267350e-14 6.336751e-15
[101,] 1.000000e+00 4.576843e-15 2.288421e-15
[102,] 1.000000e+00 2.282835e-15 1.141417e-15
[103,] 1.000000e+00 9.444218e-16 4.722109e-16
[104,] 1.000000e+00 7.581875e-17 3.790938e-17
[105,] 1.000000e+00 4.219033e-17 2.109517e-17
[106,] 1.000000e+00 2.601070e-17 1.300535e-17
[107,] 1.000000e+00 2.241141e-17 1.120571e-17
[108,] 1.000000e+00 2.578348e-17 1.289174e-17
[109,] 1.000000e+00 2.928625e-17 1.464312e-17
[110,] 1.000000e+00 3.153731e-17 1.576865e-17
[111,] 1.000000e+00 2.342379e-17 1.171190e-17
[112,] 1.000000e+00 1.721352e-17 8.606761e-18
[113,] 1.000000e+00 6.757537e-18 3.378768e-18
[114,] 1.000000e+00 4.272832e-18 2.136416e-18
[115,] 1.000000e+00 4.031171e-18 2.015586e-18
[116,] 1.000000e+00 2.575432e-18 1.287716e-18
[117,] 1.000000e+00 2.891128e-18 1.445564e-18
[118,] 1.000000e+00 3.707121e-18 1.853560e-18
[119,] 1.000000e+00 5.181904e-18 2.590952e-18
[120,] 1.000000e+00 7.642861e-18 3.821431e-18
[121,] 1.000000e+00 6.144454e-18 3.072227e-18
[122,] 1.000000e+00 1.633241e-18 8.166207e-19
[123,] 1.000000e+00 1.340887e-19 6.704436e-20
[124,] 1.000000e+00 3.739110e-20 1.869555e-20
[125,] 1.000000e+00 5.110163e-21 2.555082e-21
[126,] 1.000000e+00 1.066917e-21 5.334585e-22
[127,] 1.000000e+00 3.956411e-22 1.978205e-22
[128,] 1.000000e+00 1.929767e-22 9.648836e-23
[129,] 1.000000e+00 2.360012e-22 1.180006e-22
[130,] 1.000000e+00 2.549660e-22 1.274830e-22
[131,] 1.000000e+00 3.087366e-22 1.543683e-22
[132,] 1.000000e+00 7.178739e-22 3.589369e-22
[133,] 1.000000e+00 1.194721e-21 5.973607e-22
[134,] 1.000000e+00 2.150044e-21 1.075022e-21
[135,] 1.000000e+00 1.893131e-21 9.465657e-22
[136,] 1.000000e+00 1.544191e-21 7.720956e-22
[137,] 1.000000e+00 7.630151e-22 3.815076e-22
[138,] 1.000000e+00 4.265003e-22 2.132502e-22
[139,] 1.000000e+00 3.986726e-22 1.993363e-22
[140,] 1.000000e+00 4.031788e-22 2.015894e-22
[141,] 1.000000e+00 7.788433e-22 3.894216e-22
[142,] 1.000000e+00 1.315692e-21 6.578458e-22
[143,] 1.000000e+00 3.542267e-21 1.771134e-21
[144,] 1.000000e+00 9.855999e-21 4.927999e-21
[145,] 1.000000e+00 1.793904e-20 8.969522e-21
[146,] 1.000000e+00 4.431720e-20 2.215860e-20
[147,] 1.000000e+00 9.642709e-20 4.821355e-20
[148,] 1.000000e+00 1.556513e-19 7.782566e-20
[149,] 1.000000e+00 2.210497e-19 1.105248e-19
[150,] 1.000000e+00 3.545729e-19 1.772864e-19
[151,] 1.000000e+00 8.802965e-19 4.401482e-19
[152,] 1.000000e+00 1.936163e-18 9.680814e-19
[153,] 1.000000e+00 5.451713e-18 2.725856e-18
[154,] 1.000000e+00 1.414410e-17 7.072051e-18
[155,] 1.000000e+00 4.451456e-17 2.225728e-17
[156,] 1.000000e+00 1.363863e-16 6.819316e-17
[157,] 1.000000e+00 3.698735e-16 1.849367e-16
[158,] 1.000000e+00 7.611990e-16 3.805995e-16
[159,] 1.000000e+00 2.095811e-15 1.047906e-15
[160,] 1.000000e+00 5.384598e-15 2.692299e-15
[161,] 1.000000e+00 1.384283e-14 6.921414e-15
[162,] 1.000000e+00 3.749373e-14 1.874687e-14
[163,] 1.000000e+00 1.056556e-13 5.282779e-14
[164,] 1.000000e+00 3.008445e-13 1.504223e-13
[165,] 1.000000e+00 9.105924e-13 4.552962e-13
[166,] 1.000000e+00 2.649763e-12 1.324881e-12
[167,] 1.000000e+00 6.829055e-12 3.414527e-12
[168,] 1.000000e+00 1.829602e-11 9.148012e-12
[169,] 1.000000e+00 3.765338e-11 1.882669e-11
[170,] 1.000000e+00 4.243095e-11 2.121548e-11
[171,] 1.000000e+00 1.012545e-10 5.062726e-11
[172,] 1.000000e+00 2.671433e-10 1.335716e-10
[173,] 1.000000e+00 5.324575e-10 2.662287e-10
[174,] 1.000000e+00 1.149212e-09 5.746059e-10
[175,] 1.000000e+00 2.382048e-09 1.191024e-09
[176,] 1.000000e+00 5.617023e-09 2.808511e-09
[177,] 1.000000e+00 1.223102e-08 6.115511e-09
[178,] 1.000000e+00 2.930468e-08 1.465234e-08
[179,] 1.000000e+00 6.152553e-08 3.076276e-08
[180,] 1.000000e+00 9.490521e-08 4.745260e-08
[181,] 9.999999e-01 1.166662e-07 5.833312e-08
[182,] 1.000000e+00 4.298443e-08 2.149222e-08
[183,] 1.000000e+00 4.185640e-08 2.092820e-08
[184,] 1.000000e+00 3.296786e-08 1.648393e-08
[185,] 1.000000e+00 8.720282e-08 4.360141e-08
[186,] 9.999999e-01 2.975909e-07 1.487954e-07
[187,] 9.999995e-01 9.915675e-07 4.957837e-07
[188,] 9.999982e-01 3.638443e-06 1.819222e-06
[189,] 9.999929e-01 1.423704e-05 7.118518e-06
[190,] 9.999716e-01 5.680862e-05 2.840431e-05
[191,] 9.998880e-01 2.239683e-04 1.119842e-04
[192,] 9.996090e-01 7.820031e-04 3.910015e-04
[193,] 9.989366e-01 2.126838e-03 1.063419e-03
[194,] 9.996695e-01 6.609298e-04 3.304649e-04
[195,] 9.987985e-01 2.402908e-03 1.201454e-03
[196,] 9.963536e-01 7.292796e-03 3.646398e-03
[197,] 9.860260e-01 2.794808e-02 1.397404e-02
> postscript(file="/var/www/html/rcomp/tmp/1yoy21291992438.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2yoy21291992438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/39gxn1291992438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/49gxn1291992438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/59gxn1291992438.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 = 226
Frequency = 1
1 2 3 4 5 6
-1232868.00 -1220194.63 -1498385.11 -1394991.21 -1540120.05 -1546685.95
7 8 9 10 11 12
-1753333.84 -1655179.79 -1561487.47 -1644652.05 -1311147.06 -1228790.94
13 14 15 16 17 18
-1101539.00 -1142197.63 -1320730.11 -1272225.21 -1464494.05 -1388175.95
19 20 21 22 23 24
-1496922.84 -1420264.79 -1342115.47 -1371513.05 -1144457.06 -1065578.94
25 26 27 28 29 30
-894570.00 -968840.63 -1059270.11 -1111423.21 -1198921.05 -1191682.95
31 32 33 34 35 36
-1302433.84 -1291321.79 -1130414.47 -1221716.05 -957682.06 -902442.94
37 38 39 40 41 42
-735616.00 -827482.63 -890081.11 -909615.21 -1073283.05 -1066796.95
43 44 45 46 47 48
-1198942.84 -1155903.79 -1000361.47 -1037327.05 -810295.06 -738014.94
49 50 51 52 53 54
-637891.00 -648080.63 -675238.11 -781777.21 -854343.05 -815078.95
55 56 57 58 59 60
-1030016.84 -949374.79 -774194.47 -802031.05 -557806.06 -512549.94
61 62 63 64 65 66
-461942.00 -430479.63 -394129.11 -450111.21 -511466.05 -502620.95
67 68 69 70 71 72
-589307.84 -543980.79 -476890.47 -431527.05 -225351.06 -261617.94
73 74 75 76 77 78
-174074.00 -128417.63 -142189.11 -210608.21 -252492.05 -268558.95
79 80 81 82 83 84
-341819.84 -208410.79 -251578.47 -209443.05 -64088.06 -96597.94
85 86 87 88 89 90
-10112.00 25490.37 50268.89 -16035.21 -18282.05 -57222.95
91 92 93 94 95 96
-122447.84 -6941.79 37754.53 97241.95 193047.94 -48074.94
97 98 99 100 101 102
107955.00 254346.37 292494.89 309437.79 264255.95 208826.05
103 104 105 106 107 108
219029.16 215856.21 290853.53 299150.95 305068.94 202909.06
109 110 111 112 113 114
321307.00 284199.37 388688.89 437623.79 331464.95 402812.05
115 116 117 118 119 120
365482.16 347301.21 122058.53 -125741.05 46938.94 86879.06
121 122 123 124 125 126
189709.00 289457.37 390165.89 385631.79 416009.95 384670.05
127 128 129 130 131 132
397199.16 415184.21 434927.53 368705.95 282628.94 332846.06
133 134 135 136 137 138
364812.00 361601.37 243542.89 95878.79 111419.95 260272.05
139 140 141 142 143 144
342598.16 316707.21 305078.53 408880.95 360186.94 337244.06
145 146 147 148 149 150
358990.00 523465.37 482613.89 562571.79 561033.95 513000.05
151 152 153 154 155 156
604533.16 527414.21 497771.53 562891.95 477492.94 453187.06
157 158 159 160 161 162
573102.00 522751.37 506135.89 630497.79 777410.95 657214.05
163 164 165 166 167 168
795360.16 716935.21 716306.53 724727.95 588615.94 568055.06
169 170 171 172 173 174
645512.00 551468.37 623894.89 891369.79 893723.95 943581.05
175 176 177 178 179 180
1011382.16 891796.21 865618.53 848739.95 743372.94 776246.06
181 182 183 184 185 186
787199.00 744546.37 920366.89 987987.79 1014220.95 962286.05
187 188 189 190 191 192
1188615.16 1105230.21 995633.53 1026694.95 862985.94 848555.06
193 194 195 196 197 198
818254.00 845996.37 966438.89 1001205.79 1121211.95 1116446.05
199 200 201 202 203 204
1114239.16 999920.21 868009.53 919848.95 661930.94 657783.06
205 206 207 208 209 210
529058.00 413825.37 424858.89 755109.79 609775.95 566884.05
211 212 213 214 215 216
799233.16 768523.21 585541.53 631353.95 548555.94 589964.06
217 218 219 220 221 222
552714.00 548545.37 690551.89 89471.79 812872.95 820832.05
223 224 225 226
997554.16 926510.21 817488.53 955712.95
> postscript(file="/var/www/html/rcomp/tmp/617wq1291992438.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 = 226
Frequency = 1
lag(myerror, k = 1) myerror
0 -1232868.00 NA
1 -1220194.63 -1232868.00
2 -1498385.11 -1220194.63
3 -1394991.21 -1498385.11
4 -1540120.05 -1394991.21
5 -1546685.95 -1540120.05
6 -1753333.84 -1546685.95
7 -1655179.79 -1753333.84
8 -1561487.47 -1655179.79
9 -1644652.05 -1561487.47
10 -1311147.06 -1644652.05
11 -1228790.94 -1311147.06
12 -1101539.00 -1228790.94
13 -1142197.63 -1101539.00
14 -1320730.11 -1142197.63
15 -1272225.21 -1320730.11
16 -1464494.05 -1272225.21
17 -1388175.95 -1464494.05
18 -1496922.84 -1388175.95
19 -1420264.79 -1496922.84
20 -1342115.47 -1420264.79
21 -1371513.05 -1342115.47
22 -1144457.06 -1371513.05
23 -1065578.94 -1144457.06
24 -894570.00 -1065578.94
25 -968840.63 -894570.00
26 -1059270.11 -968840.63
27 -1111423.21 -1059270.11
28 -1198921.05 -1111423.21
29 -1191682.95 -1198921.05
30 -1302433.84 -1191682.95
31 -1291321.79 -1302433.84
32 -1130414.47 -1291321.79
33 -1221716.05 -1130414.47
34 -957682.06 -1221716.05
35 -902442.94 -957682.06
36 -735616.00 -902442.94
37 -827482.63 -735616.00
38 -890081.11 -827482.63
39 -909615.21 -890081.11
40 -1073283.05 -909615.21
41 -1066796.95 -1073283.05
42 -1198942.84 -1066796.95
43 -1155903.79 -1198942.84
44 -1000361.47 -1155903.79
45 -1037327.05 -1000361.47
46 -810295.06 -1037327.05
47 -738014.94 -810295.06
48 -637891.00 -738014.94
49 -648080.63 -637891.00
50 -675238.11 -648080.63
51 -781777.21 -675238.11
52 -854343.05 -781777.21
53 -815078.95 -854343.05
54 -1030016.84 -815078.95
55 -949374.79 -1030016.84
56 -774194.47 -949374.79
57 -802031.05 -774194.47
58 -557806.06 -802031.05
59 -512549.94 -557806.06
60 -461942.00 -512549.94
61 -430479.63 -461942.00
62 -394129.11 -430479.63
63 -450111.21 -394129.11
64 -511466.05 -450111.21
65 -502620.95 -511466.05
66 -589307.84 -502620.95
67 -543980.79 -589307.84
68 -476890.47 -543980.79
69 -431527.05 -476890.47
70 -225351.06 -431527.05
71 -261617.94 -225351.06
72 -174074.00 -261617.94
73 -128417.63 -174074.00
74 -142189.11 -128417.63
75 -210608.21 -142189.11
76 -252492.05 -210608.21
77 -268558.95 -252492.05
78 -341819.84 -268558.95
79 -208410.79 -341819.84
80 -251578.47 -208410.79
81 -209443.05 -251578.47
82 -64088.06 -209443.05
83 -96597.94 -64088.06
84 -10112.00 -96597.94
85 25490.37 -10112.00
86 50268.89 25490.37
87 -16035.21 50268.89
88 -18282.05 -16035.21
89 -57222.95 -18282.05
90 -122447.84 -57222.95
91 -6941.79 -122447.84
92 37754.53 -6941.79
93 97241.95 37754.53
94 193047.94 97241.95
95 -48074.94 193047.94
96 107955.00 -48074.94
97 254346.37 107955.00
98 292494.89 254346.37
99 309437.79 292494.89
100 264255.95 309437.79
101 208826.05 264255.95
102 219029.16 208826.05
103 215856.21 219029.16
104 290853.53 215856.21
105 299150.95 290853.53
106 305068.94 299150.95
107 202909.06 305068.94
108 321307.00 202909.06
109 284199.37 321307.00
110 388688.89 284199.37
111 437623.79 388688.89
112 331464.95 437623.79
113 402812.05 331464.95
114 365482.16 402812.05
115 347301.21 365482.16
116 122058.53 347301.21
117 -125741.05 122058.53
118 46938.94 -125741.05
119 86879.06 46938.94
120 189709.00 86879.06
121 289457.37 189709.00
122 390165.89 289457.37
123 385631.79 390165.89
124 416009.95 385631.79
125 384670.05 416009.95
126 397199.16 384670.05
127 415184.21 397199.16
128 434927.53 415184.21
129 368705.95 434927.53
130 282628.94 368705.95
131 332846.06 282628.94
132 364812.00 332846.06
133 361601.37 364812.00
134 243542.89 361601.37
135 95878.79 243542.89
136 111419.95 95878.79
137 260272.05 111419.95
138 342598.16 260272.05
139 316707.21 342598.16
140 305078.53 316707.21
141 408880.95 305078.53
142 360186.94 408880.95
143 337244.06 360186.94
144 358990.00 337244.06
145 523465.37 358990.00
146 482613.89 523465.37
147 562571.79 482613.89
148 561033.95 562571.79
149 513000.05 561033.95
150 604533.16 513000.05
151 527414.21 604533.16
152 497771.53 527414.21
153 562891.95 497771.53
154 477492.94 562891.95
155 453187.06 477492.94
156 573102.00 453187.06
157 522751.37 573102.00
158 506135.89 522751.37
159 630497.79 506135.89
160 777410.95 630497.79
161 657214.05 777410.95
162 795360.16 657214.05
163 716935.21 795360.16
164 716306.53 716935.21
165 724727.95 716306.53
166 588615.94 724727.95
167 568055.06 588615.94
168 645512.00 568055.06
169 551468.37 645512.00
170 623894.89 551468.37
171 891369.79 623894.89
172 893723.95 891369.79
173 943581.05 893723.95
174 1011382.16 943581.05
175 891796.21 1011382.16
176 865618.53 891796.21
177 848739.95 865618.53
178 743372.94 848739.95
179 776246.06 743372.94
180 787199.00 776246.06
181 744546.37 787199.00
182 920366.89 744546.37
183 987987.79 920366.89
184 1014220.95 987987.79
185 962286.05 1014220.95
186 1188615.16 962286.05
187 1105230.21 1188615.16
188 995633.53 1105230.21
189 1026694.95 995633.53
190 862985.94 1026694.95
191 848555.06 862985.94
192 818254.00 848555.06
193 845996.37 818254.00
194 966438.89 845996.37
195 1001205.79 966438.89
196 1121211.95 1001205.79
197 1116446.05 1121211.95
198 1114239.16 1116446.05
199 999920.21 1114239.16
200 868009.53 999920.21
201 919848.95 868009.53
202 661930.94 919848.95
203 657783.06 661930.94
204 529058.00 657783.06
205 413825.37 529058.00
206 424858.89 413825.37
207 755109.79 424858.89
208 609775.95 755109.79
209 566884.05 609775.95
210 799233.16 566884.05
211 768523.21 799233.16
212 585541.53 768523.21
213 631353.95 585541.53
214 548555.94 631353.95
215 589964.06 548555.94
216 552714.00 589964.06
217 548545.37 552714.00
218 690551.89 548545.37
219 89471.79 690551.89
220 812872.95 89471.79
221 820832.05 812872.95
222 997554.16 820832.05
223 926510.21 997554.16
224 817488.53 926510.21
225 955712.95 817488.53
226 NA 955712.95
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1220194.63 -1232868.00
[2,] -1498385.11 -1220194.63
[3,] -1394991.21 -1498385.11
[4,] -1540120.05 -1394991.21
[5,] -1546685.95 -1540120.05
[6,] -1753333.84 -1546685.95
[7,] -1655179.79 -1753333.84
[8,] -1561487.47 -1655179.79
[9,] -1644652.05 -1561487.47
[10,] -1311147.06 -1644652.05
[11,] -1228790.94 -1311147.06
[12,] -1101539.00 -1228790.94
[13,] -1142197.63 -1101539.00
[14,] -1320730.11 -1142197.63
[15,] -1272225.21 -1320730.11
[16,] -1464494.05 -1272225.21
[17,] -1388175.95 -1464494.05
[18,] -1496922.84 -1388175.95
[19,] -1420264.79 -1496922.84
[20,] -1342115.47 -1420264.79
[21,] -1371513.05 -1342115.47
[22,] -1144457.06 -1371513.05
[23,] -1065578.94 -1144457.06
[24,] -894570.00 -1065578.94
[25,] -968840.63 -894570.00
[26,] -1059270.11 -968840.63
[27,] -1111423.21 -1059270.11
[28,] -1198921.05 -1111423.21
[29,] -1191682.95 -1198921.05
[30,] -1302433.84 -1191682.95
[31,] -1291321.79 -1302433.84
[32,] -1130414.47 -1291321.79
[33,] -1221716.05 -1130414.47
[34,] -957682.06 -1221716.05
[35,] -902442.94 -957682.06
[36,] -735616.00 -902442.94
[37,] -827482.63 -735616.00
[38,] -890081.11 -827482.63
[39,] -909615.21 -890081.11
[40,] -1073283.05 -909615.21
[41,] -1066796.95 -1073283.05
[42,] -1198942.84 -1066796.95
[43,] -1155903.79 -1198942.84
[44,] -1000361.47 -1155903.79
[45,] -1037327.05 -1000361.47
[46,] -810295.06 -1037327.05
[47,] -738014.94 -810295.06
[48,] -637891.00 -738014.94
[49,] -648080.63 -637891.00
[50,] -675238.11 -648080.63
[51,] -781777.21 -675238.11
[52,] -854343.05 -781777.21
[53,] -815078.95 -854343.05
[54,] -1030016.84 -815078.95
[55,] -949374.79 -1030016.84
[56,] -774194.47 -949374.79
[57,] -802031.05 -774194.47
[58,] -557806.06 -802031.05
[59,] -512549.94 -557806.06
[60,] -461942.00 -512549.94
[61,] -430479.63 -461942.00
[62,] -394129.11 -430479.63
[63,] -450111.21 -394129.11
[64,] -511466.05 -450111.21
[65,] -502620.95 -511466.05
[66,] -589307.84 -502620.95
[67,] -543980.79 -589307.84
[68,] -476890.47 -543980.79
[69,] -431527.05 -476890.47
[70,] -225351.06 -431527.05
[71,] -261617.94 -225351.06
[72,] -174074.00 -261617.94
[73,] -128417.63 -174074.00
[74,] -142189.11 -128417.63
[75,] -210608.21 -142189.11
[76,] -252492.05 -210608.21
[77,] -268558.95 -252492.05
[78,] -341819.84 -268558.95
[79,] -208410.79 -341819.84
[80,] -251578.47 -208410.79
[81,] -209443.05 -251578.47
[82,] -64088.06 -209443.05
[83,] -96597.94 -64088.06
[84,] -10112.00 -96597.94
[85,] 25490.37 -10112.00
[86,] 50268.89 25490.37
[87,] -16035.21 50268.89
[88,] -18282.05 -16035.21
[89,] -57222.95 -18282.05
[90,] -122447.84 -57222.95
[91,] -6941.79 -122447.84
[92,] 37754.53 -6941.79
[93,] 97241.95 37754.53
[94,] 193047.94 97241.95
[95,] -48074.94 193047.94
[96,] 107955.00 -48074.94
[97,] 254346.37 107955.00
[98,] 292494.89 254346.37
[99,] 309437.79 292494.89
[100,] 264255.95 309437.79
[101,] 208826.05 264255.95
[102,] 219029.16 208826.05
[103,] 215856.21 219029.16
[104,] 290853.53 215856.21
[105,] 299150.95 290853.53
[106,] 305068.94 299150.95
[107,] 202909.06 305068.94
[108,] 321307.00 202909.06
[109,] 284199.37 321307.00
[110,] 388688.89 284199.37
[111,] 437623.79 388688.89
[112,] 331464.95 437623.79
[113,] 402812.05 331464.95
[114,] 365482.16 402812.05
[115,] 347301.21 365482.16
[116,] 122058.53 347301.21
[117,] -125741.05 122058.53
[118,] 46938.94 -125741.05
[119,] 86879.06 46938.94
[120,] 189709.00 86879.06
[121,] 289457.37 189709.00
[122,] 390165.89 289457.37
[123,] 385631.79 390165.89
[124,] 416009.95 385631.79
[125,] 384670.05 416009.95
[126,] 397199.16 384670.05
[127,] 415184.21 397199.16
[128,] 434927.53 415184.21
[129,] 368705.95 434927.53
[130,] 282628.94 368705.95
[131,] 332846.06 282628.94
[132,] 364812.00 332846.06
[133,] 361601.37 364812.00
[134,] 243542.89 361601.37
[135,] 95878.79 243542.89
[136,] 111419.95 95878.79
[137,] 260272.05 111419.95
[138,] 342598.16 260272.05
[139,] 316707.21 342598.16
[140,] 305078.53 316707.21
[141,] 408880.95 305078.53
[142,] 360186.94 408880.95
[143,] 337244.06 360186.94
[144,] 358990.00 337244.06
[145,] 523465.37 358990.00
[146,] 482613.89 523465.37
[147,] 562571.79 482613.89
[148,] 561033.95 562571.79
[149,] 513000.05 561033.95
[150,] 604533.16 513000.05
[151,] 527414.21 604533.16
[152,] 497771.53 527414.21
[153,] 562891.95 497771.53
[154,] 477492.94 562891.95
[155,] 453187.06 477492.94
[156,] 573102.00 453187.06
[157,] 522751.37 573102.00
[158,] 506135.89 522751.37
[159,] 630497.79 506135.89
[160,] 777410.95 630497.79
[161,] 657214.05 777410.95
[162,] 795360.16 657214.05
[163,] 716935.21 795360.16
[164,] 716306.53 716935.21
[165,] 724727.95 716306.53
[166,] 588615.94 724727.95
[167,] 568055.06 588615.94
[168,] 645512.00 568055.06
[169,] 551468.37 645512.00
[170,] 623894.89 551468.37
[171,] 891369.79 623894.89
[172,] 893723.95 891369.79
[173,] 943581.05 893723.95
[174,] 1011382.16 943581.05
[175,] 891796.21 1011382.16
[176,] 865618.53 891796.21
[177,] 848739.95 865618.53
[178,] 743372.94 848739.95
[179,] 776246.06 743372.94
[180,] 787199.00 776246.06
[181,] 744546.37 787199.00
[182,] 920366.89 744546.37
[183,] 987987.79 920366.89
[184,] 1014220.95 987987.79
[185,] 962286.05 1014220.95
[186,] 1188615.16 962286.05
[187,] 1105230.21 1188615.16
[188,] 995633.53 1105230.21
[189,] 1026694.95 995633.53
[190,] 862985.94 1026694.95
[191,] 848555.06 862985.94
[192,] 818254.00 848555.06
[193,] 845996.37 818254.00
[194,] 966438.89 845996.37
[195,] 1001205.79 966438.89
[196,] 1121211.95 1001205.79
[197,] 1116446.05 1121211.95
[198,] 1114239.16 1116446.05
[199,] 999920.21 1114239.16
[200,] 868009.53 999920.21
[201,] 919848.95 868009.53
[202,] 661930.94 919848.95
[203,] 657783.06 661930.94
[204,] 529058.00 657783.06
[205,] 413825.37 529058.00
[206,] 424858.89 413825.37
[207,] 755109.79 424858.89
[208,] 609775.95 755109.79
[209,] 566884.05 609775.95
[210,] 799233.16 566884.05
[211,] 768523.21 799233.16
[212,] 585541.53 768523.21
[213,] 631353.95 585541.53
[214,] 548555.94 631353.95
[215,] 589964.06 548555.94
[216,] 552714.00 589964.06
[217,] 548545.37 552714.00
[218,] 690551.89 548545.37
[219,] 89471.79 690551.89
[220,] 812872.95 89471.79
[221,] 820832.05 812872.95
[222,] 997554.16 820832.05
[223,] 926510.21 997554.16
[224,] 817488.53 926510.21
[225,] 955712.95 817488.53
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1220194.63 -1232868.00
2 -1498385.11 -1220194.63
3 -1394991.21 -1498385.11
4 -1540120.05 -1394991.21
5 -1546685.95 -1540120.05
6 -1753333.84 -1546685.95
7 -1655179.79 -1753333.84
8 -1561487.47 -1655179.79
9 -1644652.05 -1561487.47
10 -1311147.06 -1644652.05
11 -1228790.94 -1311147.06
12 -1101539.00 -1228790.94
13 -1142197.63 -1101539.00
14 -1320730.11 -1142197.63
15 -1272225.21 -1320730.11
16 -1464494.05 -1272225.21
17 -1388175.95 -1464494.05
18 -1496922.84 -1388175.95
19 -1420264.79 -1496922.84
20 -1342115.47 -1420264.79
21 -1371513.05 -1342115.47
22 -1144457.06 -1371513.05
23 -1065578.94 -1144457.06
24 -894570.00 -1065578.94
25 -968840.63 -894570.00
26 -1059270.11 -968840.63
27 -1111423.21 -1059270.11
28 -1198921.05 -1111423.21
29 -1191682.95 -1198921.05
30 -1302433.84 -1191682.95
31 -1291321.79 -1302433.84
32 -1130414.47 -1291321.79
33 -1221716.05 -1130414.47
34 -957682.06 -1221716.05
35 -902442.94 -957682.06
36 -735616.00 -902442.94
37 -827482.63 -735616.00
38 -890081.11 -827482.63
39 -909615.21 -890081.11
40 -1073283.05 -909615.21
41 -1066796.95 -1073283.05
42 -1198942.84 -1066796.95
43 -1155903.79 -1198942.84
44 -1000361.47 -1155903.79
45 -1037327.05 -1000361.47
46 -810295.06 -1037327.05
47 -738014.94 -810295.06
48 -637891.00 -738014.94
49 -648080.63 -637891.00
50 -675238.11 -648080.63
51 -781777.21 -675238.11
52 -854343.05 -781777.21
53 -815078.95 -854343.05
54 -1030016.84 -815078.95
55 -949374.79 -1030016.84
56 -774194.47 -949374.79
57 -802031.05 -774194.47
58 -557806.06 -802031.05
59 -512549.94 -557806.06
60 -461942.00 -512549.94
61 -430479.63 -461942.00
62 -394129.11 -430479.63
63 -450111.21 -394129.11
64 -511466.05 -450111.21
65 -502620.95 -511466.05
66 -589307.84 -502620.95
67 -543980.79 -589307.84
68 -476890.47 -543980.79
69 -431527.05 -476890.47
70 -225351.06 -431527.05
71 -261617.94 -225351.06
72 -174074.00 -261617.94
73 -128417.63 -174074.00
74 -142189.11 -128417.63
75 -210608.21 -142189.11
76 -252492.05 -210608.21
77 -268558.95 -252492.05
78 -341819.84 -268558.95
79 -208410.79 -341819.84
80 -251578.47 -208410.79
81 -209443.05 -251578.47
82 -64088.06 -209443.05
83 -96597.94 -64088.06
84 -10112.00 -96597.94
85 25490.37 -10112.00
86 50268.89 25490.37
87 -16035.21 50268.89
88 -18282.05 -16035.21
89 -57222.95 -18282.05
90 -122447.84 -57222.95
91 -6941.79 -122447.84
92 37754.53 -6941.79
93 97241.95 37754.53
94 193047.94 97241.95
95 -48074.94 193047.94
96 107955.00 -48074.94
97 254346.37 107955.00
98 292494.89 254346.37
99 309437.79 292494.89
100 264255.95 309437.79
101 208826.05 264255.95
102 219029.16 208826.05
103 215856.21 219029.16
104 290853.53 215856.21
105 299150.95 290853.53
106 305068.94 299150.95
107 202909.06 305068.94
108 321307.00 202909.06
109 284199.37 321307.00
110 388688.89 284199.37
111 437623.79 388688.89
112 331464.95 437623.79
113 402812.05 331464.95
114 365482.16 402812.05
115 347301.21 365482.16
116 122058.53 347301.21
117 -125741.05 122058.53
118 46938.94 -125741.05
119 86879.06 46938.94
120 189709.00 86879.06
121 289457.37 189709.00
122 390165.89 289457.37
123 385631.79 390165.89
124 416009.95 385631.79
125 384670.05 416009.95
126 397199.16 384670.05
127 415184.21 397199.16
128 434927.53 415184.21
129 368705.95 434927.53
130 282628.94 368705.95
131 332846.06 282628.94
132 364812.00 332846.06
133 361601.37 364812.00
134 243542.89 361601.37
135 95878.79 243542.89
136 111419.95 95878.79
137 260272.05 111419.95
138 342598.16 260272.05
139 316707.21 342598.16
140 305078.53 316707.21
141 408880.95 305078.53
142 360186.94 408880.95
143 337244.06 360186.94
144 358990.00 337244.06
145 523465.37 358990.00
146 482613.89 523465.37
147 562571.79 482613.89
148 561033.95 562571.79
149 513000.05 561033.95
150 604533.16 513000.05
151 527414.21 604533.16
152 497771.53 527414.21
153 562891.95 497771.53
154 477492.94 562891.95
155 453187.06 477492.94
156 573102.00 453187.06
157 522751.37 573102.00
158 506135.89 522751.37
159 630497.79 506135.89
160 777410.95 630497.79
161 657214.05 777410.95
162 795360.16 657214.05
163 716935.21 795360.16
164 716306.53 716935.21
165 724727.95 716306.53
166 588615.94 724727.95
167 568055.06 588615.94
168 645512.00 568055.06
169 551468.37 645512.00
170 623894.89 551468.37
171 891369.79 623894.89
172 893723.95 891369.79
173 943581.05 893723.95
174 1011382.16 943581.05
175 891796.21 1011382.16
176 865618.53 891796.21
177 848739.95 865618.53
178 743372.94 848739.95
179 776246.06 743372.94
180 787199.00 776246.06
181 744546.37 787199.00
182 920366.89 744546.37
183 987987.79 920366.89
184 1014220.95 987987.79
185 962286.05 1014220.95
186 1188615.16 962286.05
187 1105230.21 1188615.16
188 995633.53 1105230.21
189 1026694.95 995633.53
190 862985.94 1026694.95
191 848555.06 862985.94
192 818254.00 848555.06
193 845996.37 818254.00
194 966438.89 845996.37
195 1001205.79 966438.89
196 1121211.95 1001205.79
197 1116446.05 1121211.95
198 1114239.16 1116446.05
199 999920.21 1114239.16
200 868009.53 999920.21
201 919848.95 868009.53
202 661930.94 919848.95
203 657783.06 661930.94
204 529058.00 657783.06
205 413825.37 529058.00
206 424858.89 413825.37
207 755109.79 424858.89
208 609775.95 755109.79
209 566884.05 609775.95
210 799233.16 566884.05
211 768523.21 799233.16
212 585541.53 768523.21
213 631353.95 585541.53
214 548555.94 631353.95
215 589964.06 548555.94
216 552714.00 589964.06
217 548545.37 552714.00
218 690551.89 548545.37
219 89471.79 690551.89
220 812872.95 89471.79
221 820832.05 812872.95
222 997554.16 820832.05
223 926510.21 997554.16
224 817488.53 926510.21
225 955712.95 817488.53
> 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/7cget1291992438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8cget1291992438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9cget1291992438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/105qve1291992438.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11qqb21291992438.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/12cqsq1291992438.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/1380pz1291992438.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/14b1om1291992438.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/15ej5a1291992438.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/1602ly1291992438.tab")
+ }
>
> try(system("convert tmp/1yoy21291992438.ps tmp/1yoy21291992438.png",intern=TRUE))
character(0)
> try(system("convert tmp/2yoy21291992438.ps tmp/2yoy21291992438.png",intern=TRUE))
character(0)
> try(system("convert tmp/39gxn1291992438.ps tmp/39gxn1291992438.png",intern=TRUE))
character(0)
> try(system("convert tmp/49gxn1291992438.ps tmp/49gxn1291992438.png",intern=TRUE))
character(0)
> try(system("convert tmp/59gxn1291992438.ps tmp/59gxn1291992438.png",intern=TRUE))
character(0)
> try(system("convert tmp/617wq1291992438.ps tmp/617wq1291992438.png",intern=TRUE))
character(0)
> try(system("convert tmp/7cget1291992438.ps tmp/7cget1291992438.png",intern=TRUE))
character(0)
> try(system("convert tmp/8cget1291992438.ps tmp/8cget1291992438.png",intern=TRUE))
character(0)
> try(system("convert tmp/9cget1291992438.ps tmp/9cget1291992438.png",intern=TRUE))
character(0)
> try(system("convert tmp/105qve1291992438.ps tmp/105qve1291992438.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.566 1.897 13.273