R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(112.285
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+ ,613
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+ ,721
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+ ,17
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+ ,1.182
+ ,20.156
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+ ,528
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+ ,14
+ ,7
+ ,6
+ ,4
+ ,8
+ ,20.154
+ ,642
+ ,18.475
+ ,61
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+ ,12
+ ,16
+ ,10
+ ,36.944
+ ,947
+ ,12.645
+ ,71
+ ,37
+ ,24
+ ,20
+ ,15
+ ,8.019
+ ,819
+ ,11.017
+ ,44
+ ,35
+ ,16
+ ,12
+ ,15
+ ,30.884
+ ,757
+ ,37.623
+ ,60
+ ,51
+ ,72
+ ,15
+ ,28
+ ,19.540
+ ,894
+ ,35.873
+ ,64
+ ,39
+ ,27
+ ,16
+ ,17)
+ ,dim=c(8
+ ,289)
+ ,dimnames=list(c('y'
+ ,'x1'
+ ,'x2'
+ ,'x3'
+ ,'x4'
+ ,'x5'
+ ,'x6'
+ ,'x7')
+ ,1:289))
> y <- array(NA,dim=c(8,289),dimnames=list(c('y','x1','x2','x3','x4','x5','x6','x7'),1:289))
> 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 = 'Do not include Seasonal 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
> 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
y x1 x2 x3 x4 x5 x6 x7
1 112.285 1.418 146.283 115 94 144 30 79
2 84.786 869.000 98.364 109 103 103 28 58
3 83.123 1.530 86.146 146 93 98 38 60
4 101.193 2.172 96.933 116 103 135 30 108
5 38.361 901.000 79.234 68 51 61 22 49
6 68.504 463.000 42.551 101 70 39 26 0
7 119.182 3.201 195.663 96 91 150 25 121
8 22.807 371.000 6.853 67 22 5 18 1
9 17.140 1.192 21.529 44 38 28 11 20
10 116.174 1.583 95.757 100 93 84 26 43
11 57.635 1.439 85.584 93 60 80 25 69
12 66.198 1.764 143.983 140 123 130 38 78
13 71.701 1.495 75.851 166 148 82 44 86
14 57.793 1.373 59.238 99 90 60 30 44
15 80.444 2.187 93.163 139 124 131 40 104
16 53.855 1.491 96.037 130 70 84 34 63
17 97.668 4.041 151.511 181 168 140 47 158
18 133.824 1.706 136.368 116 115 151 30 102
19 101.481 2.152 112.642 116 71 91 31 77
20 99.645 1.036 94.728 88 66 138 23 82
21 114.789 1.882 105.499 139 134 150 36 115
22 99.052 1.929 121.527 135 117 124 36 101
23 67.654 2.242 127.766 108 108 119 30 80
24 65.553 1.220 98.958 89 84 73 25 50
25 97.500 1.289 77.900 156 156 110 39 83
26 69.112 2.515 85.646 129 120 123 34 123
27 82.753 2.147 98.579 118 114 90 31 73
28 85.323 2.352 130.767 118 94 116 31 81
29 72.654 1.638 131.741 125 120 113 33 105
30 30.727 1.222 53.907 95 81 56 25 47
31 77.873 1.812 178.812 126 110 115 33 105
32 117.478 1.677 146.761 135 133 119 35 94
33 74.007 1.579 82.036 154 122 129 42 44
34 90.183 1.731 163.253 165 158 127 43 114
35 61.542 807.000 27.032 113 109 27 30 38
36 101.494 2.452 171.975 127 124 175 33 107
37 27.570 829.000 65.990 52 39 35 13 30
38 55.813 1.940 86.572 121 92 64 32 71
39 79.215 2.662 159.676 136 126 96 36 84
40 1.423 186.000 1.929 0 0 0 0 0
41 55.461 1.499 85.371 108 70 84 28 59
42 31.081 865.000 58.391 46 37 41 14 33
43 22.996 1.793 31.580 54 38 47 17 42
44 83.122 2.527 136.815 124 120 126 32 96
45 70.106 2.747 120.642 115 93 105 30 106
46 60.578 1.324 69.107 128 95 80 35 56
47 39.992 2.702 50.495 80 77 70 20 57
48 79.892 1.383 108.016 97 90 73 28 59
49 49.810 1.179 46.341 104 80 57 28 39
50 71.570 2.099 78.348 59 31 40 39 34
51 100.708 4.308 79.336 125 110 68 34 76
52 33.032 918.000 56.968 82 66 21 26 20
53 82.875 1.831 93.176 149 138 127 39 91
54 139.077 3.373 161.632 149 133 154 39 115
55 71.595 1.713 87.850 122 113 116 33 85
56 72.260 1.438 127.969 118 100 102 28 76
57 5.950 496.000 15.049 12 7 7 4 8
58 115.762 2.253 155.135 144 140 148 39 79
59 32.551 744.000 25.109 67 61 21 18 21
60 31.701 1.161 45.824 52 41 35 14 30
61 80.670 2.352 102.996 108 96 112 29 76
62 143.558 2.144 160.604 166 164 137 44 101
63 117.105 4.691 158.051 80 78 135 21 94
64 23.789 1.112 44.547 60 49 26 16 27
65 120.733 2.694 162.647 107 102 230 28 92
66 105.195 1.973 174.141 127 124 181 35 123
67 73.107 1.769 60.622 107 99 71 28 75
68 132.068 3.148 179.566 146 129 147 38 128
69 149.193 2.474 184.301 84 62 190 23 105
70 46.821 2.084 75.661 141 73 64 36 55
71 87.011 1.954 96.144 123 114 105 32 56
72 95.260 1.226 129.847 111 99 107 29 41
73 55.183 1.389 117.286 98 70 94 25 72
74 106.671 1.496 71.180 105 104 116 27 67
75 73.511 2.269 109.377 135 116 106 36 75
76 92.945 1.833 85.298 107 91 143 28 114
77 78.664 1.268 73.631 85 74 81 23 118
78 70.054 1.943 86.767 155 138 89 40 77
79 22.618 893.000 23.824 88 67 26 23 22
80 74.011 1.762 93.487 155 151 84 40 66
81 83.737 1.403 82.981 104 72 113 28 69
82 69.094 1.425 73.815 132 120 120 34 105
83 93.133 1.857 94.552 127 115 110 33 116
84 95.536 1.840 132.190 108 105 134 28 88
85 225.920 1.502 128.754 129 104 54 34 73
86 62.133 1.441 66.363 116 108 96 30 99
87 61.370 1.420 67.808 122 98 78 33 62
88 43.836 1.416 61.724 85 69 51 22 53
89 106.117 2.970 131.722 147 111 121 38 118
90 38.692 1.317 68.580 99 99 38 26 30
91 84.651 1.644 106.175 87 71 145 35 100
92 56.622 870.000 55.792 28 27 59 8 49
93 15.986 1.654 25.157 90 69 27 24 24
94 95.364 1.054 76.669 109 107 91 29 67
95 26.706 937.000 57.283 78 73 48 20 46
96 89.691 3.004 105.805 111 107 68 29 57
97 67.267 2.008 129.484 158 93 58 45 75
98 126.846 2.547 72.413 141 129 150 37 135
99 41.140 1.885 87.831 122 69 74 33 68
100 102.860 1.626 96.971 124 118 181 33 124
101 51.715 1.468 71.299 93 73 65 25 33
102 55.801 2.445 77.494 124 119 97 32 98
103 111.813 1.964 120.336 112 104 121 29 58
104 120.293 1.381 93.913 108 107 99 28 68
105 138.599 1.369 136.048 99 99 152 28 81
106 161.647 1.659 181.248 117 90 188 31 131
107 115.929 2.888 146.123 199 197 138 52 110
108 24.266 1.290 32.036 78 36 40 21 37
109 162.901 2.845 186.646 91 85 254 24 130
110 109.825 1.982 102.255 158 139 87 41 93
111 129.838 1.904 168.237 126 106 178 33 118
112 37.510 1.391 64.219 122 50 51 32 39
113 43.750 602.000 19.630 71 64 49 19 13
114 40.652 1.743 76.825 75 31 73 20 74
115 87.771 1.559 115.338 115 63 176 31 81
116 85.872 2.014 109.427 119 92 94 31 109
117 89.275 2.143 118.168 124 106 120 32 151
118 44.418 2.146 84.845 72 63 66 18 51
119 192.565 874.000 153.197 91 69 56 23 28
120 35.232 1.590 29.877 45 41 39 17 40
121 40.909 1.590 63.506 78 56 66 20 56
122 13.294 1.210 22.445 39 25 27 12 27
123 32.387 2.072 47.695 68 65 65 17 37
124 140.867 1.281 68.370 119 93 58 30 83
125 120.662 1.401 146.304 117 114 98 31 54
126 21.233 834.000 38.233 39 38 25 10 27
127 44.332 1.105 42.071 50 44 26 13 28
128 61.056 1.272 50.517 88 87 77 22 59
129 101.338 1.944 103.950 155 110 130 42 133
130 1.168 391.000 5.841 0 0 11 1 12
131 13.497 761.000 2.341 36 27 2 9 0
132 65.567 1.605 84.396 123 83 101 32 106
133 25.162 530.000 24.610 32 30 31 11 23
134 32.334 1.988 35.753 99 80 36 25 44
135 40.735 1.386 55.515 136 98 120 36 71
136 91.413 2.395 209.056 117 82 195 31 116
137 855.000 387.000 6.622 0 0 4 0 4
138 97.068 1.742 115.814 88 60 89 24 62
139 44.339 620.000 11.609 39 28 24 13 12
140 14.116 449.000 13.155 25 9 39 8 18
141 10.288 800.000 18.274 52 33 14 13 14
142 65.622 1.684 72.875 75 59 78 19 60
143 16.563 1.050 10.112 71 49 15 18 7
144 76.643 2.699 142.775 124 115 106 33 98
145 110.681 1.606 68.847 151 140 83 40 64
146 29.011 1.502 17.659 71 49 24 22 29
147 92.696 1.204 20.112 145 120 37 38 32
148 94.785 1.138 61.023 87 66 77 24 25
149 8.773 568.000 13.983 27 21 16 8 16
150 83.209 1.459 65.176 131 124 56 35 48
151 93.815 2.158 132.432 162 152 132 43 100
152 86.687 1.111 112.494 165 139 144 43 46
153 34.553 1.421 45.109 54 38 40 14 45
154 105.547 2.833 170.875 159 144 153 41 129
155 103.487 1.955 180.759 147 120 143 38 130
156 213.688 2.922 214.921 170 160 220 45 136
157 71.220 1.002 100.226 119 114 79 31 59
158 23.517 1.060 32.043 49 39 50 13 25
159 56.926 956.000 54.454 104 78 39 28 32
160 91.721 2.186 78.876 120 119 95 31 63
161 115.168 3.604 170.745 150 141 169 40 95
162 111.194 1.035 6.940 112 101 12 30 14
163 51.009 1.417 49.025 59 56 63 16 36
164 135.777 3.261 122.037 136 133 134 37 113
165 51.513 1.587 53.782 107 83 69 30 47
166 74.163 1.424 127.748 130 116 119 35 92
167 51.633 1.701 86.839 115 90 119 32 70
168 75.345 1.249 44.830 107 36 75 27 19
169 33.416 946.000 77.395 75 50 63 20 50
170 83.305 1.926 89.324 71 61 55 18 41
171 98.952 3.352 103.300 120 97 103 31 91
172 102.372 1.641 112.283 116 98 197 31 111
173 37.238 2.035 10.901 79 78 16 21 41
174 103.772 2.312 120.691 150 117 140 39 120
175 123.969 1.369 58.106 156 148 89 41 135
176 27.142 1.577 57.140 51 41 40 13 27
177 135.400 2.201 122.422 118 105 125 32 87
178 21.399 961.000 25.899 71 55 21 18 25
179 130.115 1.900 139.296 144 132 167 39 131
180 24.874 1.254 52.678 47 44 32 14 45
181 34.988 1.335 23.853 28 21 36 7 29
182 45.549 1.597 17.306 68 50 13 17 58
183 6.023 207.000 7.953 0 0 5 0 4
184 64.466 1.645 89.455 110 73 96 30 47
185 54.990 2.429 147.866 147 86 151 37 109
186 1.644 151.000 4.245 0 0 6 0 7
187 6.179 474.000 21.509 15 13 13 5 12
188 3.926 141.000 7.670 4 4 3 1 0
189 32.755 1.639 66.675 64 57 57 16 37
190 34.777 872.000 14.336 111 48 23 32 37
191 73.224 1.318 53.608 85 46 61 24 46
192 27.114 1.018 30.059 68 48 21 17 15
193 20.760 1.383 29.668 40 32 43 11 42
194 37.636 1.314 22.097 80 68 20 24 7
195 65.461 1.335 96.841 88 87 82 22 54
196 30.080 1.403 41.907 48 43 90 12 54
197 24.094 910.000 27.080 76 67 25 19 14
198 69.008 616.000 35.885 51 46 60 13 16
199 54.968 1.407 41.247 67 46 61 17 33
200 46.090 771.000 28.313 59 56 85 15 32
201 27.507 766.000 36.845 61 48 43 16 21
202 10.672 473.000 16.548 76 44 25 24 15
203 34.029 1.376 36.134 60 60 41 15 38
204 46.300 1.232 55.764 68 65 26 17 22
205 24.760 1.521 28.910 71 55 38 18 28
206 18.779 572.000 13.339 76 38 12 20 10
207 21.280 1.059 25.319 62 52 29 16 31
208 40.662 1.544 66.956 61 60 49 16 32
209 28.987 1.230 47.487 67 54 46 18 32
210 22.827 1.206 52.785 88 86 41 22 43
211 18.513 1.205 44.683 30 24 31 8 27
212 30.594 1.255 35.619 64 52 41 17 37
213 24.006 613.000 21.920 68 49 26 18 20
214 27.913 721.000 45.608 64 61 23 16 32
215 42.744 1.109 7.721 91 61 14 23 0
216 12.934 740.000 20.634 88 81 16 22 5
217 22.574 1.126 29.788 52 43 25 13 26
218 41.385 728.000 31.931 49 40 21 13 10
219 18.653 689.000 37.754 62 40 32 16 27
220 18.472 592.000 32.505 61 56 9 16 11
221 30.976 995.000 40.557 76 68 35 20 29
222 63.339 1.613 94.238 88 79 42 22 25
223 25.568 2.048 44.197 66 47 68 17 55
224 33.747 705.000 43.228 71 57 32 18 23
225 4.154 301.000 4.103 68 41 6 17 5
226 19.474 1.803 44.144 48 29 68 12 43
227 35.130 799.000 32.868 25 3 33 7 23
228 39.067 861.000 27.640 68 60 84 17 34
229 13.310 1.186 14.063 41 30 46 14 36
230 65.892 1.451 28.990 90 79 30 23 35
231 4.143 628.000 4.694 66 47 0 17 0
232 28.579 1.161 42.648 54 40 36 14 37
233 51.776 1.463 64.329 59 48 47 15 28
234 21.152 742.000 21.928 60 36 20 17 16
235 38.084 979.000 25.836 77 42 50 21 26
236 27.717 675.000 22.779 68 49 30 18 38
237 32.928 1.241 40.820 72 57 30 18 23
238 11.342 676.000 27.530 67 12 34 17 22
239 19.499 1.049 32.378 64 40 33 17 30
240 16.380 620.000 10.824 63 43 34 16 16
241 36.874 1.081 39.613 59 33 37 15 18
242 48.259 1.688 60.865 84 77 83 21 28
243 16.734 736.000 19.787 64 43 32 16 32
244 28.207 617.000 20.107 56 45 30 14 21
245 30.143 812.000 36.605 54 47 43 15 23
246 41.369 1.051 40.961 67 43 41 17 29
247 45.833 1.656 48.231 58 45 51 15 50
248 29.156 705.000 39.725 59 50 19 15 12
249 35.944 945.000 21.455 40 35 37 10 21
250 36.278 554.000 23.430 22 7 33 6 18
251 45.588 1.597 62.991 83 71 41 22 27
252 45.097 982.000 49.363 81 67 54 21 41
253 3.895 222.000 9.604 2 0 14 1 13
254 28.394 1.212 24.552 72 62 25 18 12
255 18.632 1.143 31.493 61 54 25 17 21
256 2.325 435.000 3.439 15 4 8 4 8
257 25.139 532.000 19.555 32 25 26 10 26
258 27.975 882.000 21.228 62 40 20 16 27
259 14.483 608.000 23.177 58 38 11 16 13
260 13.127 459.000 22.094 36 19 14 9 16
261 5.839 578.000 2.342 59 17 3 16 2
262 24.069 826.000 38.798 68 67 40 17 42
263 3.738 509.000 3.255 21 14 5 7 5
264 18.625 717.000 24.261 55 30 38 15 37
265 36.341 637.000 18.511 54 54 32 14 17
266 24.548 857.000 40.798 55 35 41 14 38
267 21.792 830.000 28.893 72 59 46 18 37
268 26.263 652.000 21.425 41 24 47 12 29
269 23.686 707.000 50.276 61 58 37 16 32
270 49.303 954.000 37.643 67 42 51 21 35
271 25.659 1.461 30.377 76 46 49 19 17
272 28.904 672.000 27.126 64 61 21 16 20
273 2.781 778.000 13.000 3 3 1 1 7
274 29.236 1.141 42.097 63 52 44 16 46
275 19.546 680.000 24.451 40 25 26 10 24
276 22.818 1.090 14.335 69 40 21 19 40
277 32.689 616.000 5.084 48 32 4 12 3
278 5.752 285.000 9.927 8 4 10 2 10
279 22.197 1.145 43.527 52 49 43 14 37
280 20.055 733.000 27.184 66 63 34 17 17
281 25.272 888.000 21.610 76 67 32 19 28
282 82.206 849.000 20.484 43 32 20 14 19
283 32.073 1.182 20.156 39 23 34 11 29
284 5.444 528.000 6.012 14 7 6 4 8
285 20.154 642.000 18.475 61 54 12 16 10
286 36.944 947.000 12.645 71 37 24 20 15
287 8.019 819.000 11.017 44 35 16 12 15
288 30.884 757.000 37.623 60 51 72 15 28
289 19.540 894.000 35.873 64 39 27 16 17
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x1 x2 x3 x4 x5
21.358591 -0.004701 0.374478 -0.402221 0.395489 0.157090
x6 x7
0.435028 0.014957
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-39.52 -17.09 -8.01 6.77 832.29
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 21.358591 9.944442 2.148 0.0326 *
x1 -0.004701 0.011082 -0.424 0.6717
x2 0.374478 0.149855 2.499 0.0130 *
x3 -0.402221 0.522142 -0.770 0.4418
x4 0.395489 0.251243 1.574 0.1166
x5 0.157090 0.166204 0.945 0.3454
x6 0.435028 1.721527 0.253 0.8007
x7 0.014957 0.208353 0.072 0.9428
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 54.46 on 281 degrees of freedom
Multiple R-squared: 0.2427, Adjusted R-squared: 0.2238
F-statistic: 12.86 on 7 and 281 DF, p-value: 2.431e-14
> 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,] 3.182569e-02 6.365138e-02 9.681743e-01
[2,] 8.621660e-02 1.724332e-01 9.137834e-01
[3,] 3.574186e-02 7.148371e-02 9.642581e-01
[4,] 1.859117e-02 3.718233e-02 9.814088e-01
[5,] 7.036883e-03 1.407377e-02 9.929631e-01
[6,] 2.820021e-03 5.640042e-03 9.971800e-01
[7,] 9.614013e-04 1.922803e-03 9.990386e-01
[8,] 4.334141e-04 8.668282e-04 9.995666e-01
[9,] 5.028172e-04 1.005634e-03 9.994972e-01
[10,] 1.762342e-04 3.524685e-04 9.998238e-01
[11,] 6.083901e-05 1.216780e-04 9.999392e-01
[12,] 2.032046e-05 4.064092e-05 9.999797e-01
[13,] 1.487363e-05 2.974726e-05 9.999851e-01
[14,] 4.827736e-06 9.655471e-06 9.999952e-01
[15,] 1.551430e-06 3.102861e-06 9.999984e-01
[16,] 6.372419e-07 1.274484e-06 9.999994e-01
[17,] 1.951099e-07 3.902197e-07 9.999998e-01
[18,] 6.545075e-08 1.309015e-07 9.999999e-01
[19,] 2.687821e-08 5.375642e-08 1.000000e+00
[20,] 1.827634e-08 3.655268e-08 1.000000e+00
[21,] 6.959802e-09 1.391960e-08 1.000000e+00
[22,] 3.570342e-09 7.140683e-09 1.000000e+00
[23,] 2.796239e-09 5.592479e-09 1.000000e+00
[24,] 1.031071e-09 2.062143e-09 1.000000e+00
[25,] 5.050138e-10 1.010028e-09 1.000000e+00
[26,] 3.646054e-10 7.292107e-10 1.000000e+00
[27,] 2.476017e-10 4.952033e-10 1.000000e+00
[28,] 7.583905e-11 1.516781e-10 1.000000e+00
[29,] 2.355613e-11 4.711226e-11 1.000000e+00
[30,] 1.018602e-11 2.037204e-11 1.000000e+00
[31,] 3.803223e-12 7.606447e-12 1.000000e+00
[32,] 1.145705e-12 2.291409e-12 1.000000e+00
[33,] 3.372210e-13 6.744420e-13 1.000000e+00
[34,] 1.310675e-13 2.621351e-13 1.000000e+00
[35,] 3.891230e-14 7.782461e-14 1.000000e+00
[36,] 1.076884e-14 2.153768e-14 1.000000e+00
[37,] 5.515915e-15 1.103183e-14 1.000000e+00
[38,] 3.758746e-15 7.517493e-15 1.000000e+00
[39,] 1.037584e-15 2.075169e-15 1.000000e+00
[40,] 2.269110e-15 4.538220e-15 1.000000e+00
[41,] 6.125679e-15 1.225136e-14 1.000000e+00
[42,] 2.002660e-15 4.005319e-15 1.000000e+00
[43,] 6.904189e-16 1.380838e-15 1.000000e+00
[44,] 6.337181e-16 1.267436e-15 1.000000e+00
[45,] 2.325129e-16 4.650258e-16 1.000000e+00
[46,] 7.501494e-17 1.500299e-16 1.000000e+00
[47,] 2.316724e-17 4.633449e-17 1.000000e+00
[48,] 6.645081e-18 1.329016e-17 1.000000e+00
[49,] 1.910925e-18 3.821849e-18 1.000000e+00
[50,] 5.409548e-19 1.081910e-18 1.000000e+00
[51,] 1.501987e-19 3.003973e-19 1.000000e+00
[52,] 1.519609e-19 3.039219e-19 1.000000e+00
[53,] 9.524839e-20 1.904968e-19 1.000000e+00
[54,] 2.946257e-20 5.892514e-20 1.000000e+00
[55,] 1.431746e-20 2.863492e-20 1.000000e+00
[56,] 6.315592e-21 1.263118e-20 1.000000e+00
[57,] 2.484868e-21 4.969735e-21 1.000000e+00
[58,] 1.348504e-21 2.697007e-21 1.000000e+00
[59,] 1.743248e-21 3.486496e-21 1.000000e+00
[60,] 5.722455e-22 1.144491e-21 1.000000e+00
[61,] 1.619487e-22 3.238974e-22 1.000000e+00
[62,] 4.558208e-23 9.116417e-23 1.000000e+00
[63,] 2.066485e-23 4.132971e-23 1.000000e+00
[64,] 1.753456e-23 3.506912e-23 1.000000e+00
[65,] 6.240580e-24 1.248116e-23 1.000000e+00
[66,] 1.862960e-24 3.725920e-24 1.000000e+00
[67,] 1.050780e-24 2.101560e-24 1.000000e+00
[68,] 3.141883e-25 6.283766e-25 1.000000e+00
[69,] 9.424607e-26 1.884921e-25 1.000000e+00
[70,] 2.684356e-26 5.368713e-26 1.000000e+00
[71,] 7.884183e-27 1.576837e-26 1.000000e+00
[72,] 2.765098e-27 5.530197e-27 1.000000e+00
[73,] 9.306306e-28 1.861261e-27 1.000000e+00
[74,] 2.463938e-28 4.927875e-28 1.000000e+00
[75,] 4.428527e-18 8.857055e-18 1.000000e+00
[76,] 1.695187e-18 3.390373e-18 1.000000e+00
[77,] 6.339791e-19 1.267958e-18 1.000000e+00
[78,] 2.458963e-19 4.917925e-19 1.000000e+00
[79,] 9.457247e-20 1.891449e-19 1.000000e+00
[80,] 4.575375e-20 9.150750e-20 1.000000e+00
[81,] 1.705097e-20 3.410193e-20 1.000000e+00
[82,] 7.885048e-21 1.577010e-20 1.000000e+00
[83,] 3.675921e-21 7.351841e-21 1.000000e+00
[84,] 2.156031e-21 4.312063e-21 1.000000e+00
[85,] 1.042245e-21 2.084490e-21 1.000000e+00
[86,] 4.136297e-22 8.272594e-22 1.000000e+00
[87,] 1.838862e-22 3.677725e-22 1.000000e+00
[88,] 2.334441e-22 4.668882e-22 1.000000e+00
[89,] 1.291386e-22 2.582771e-22 1.000000e+00
[90,] 4.509211e-23 9.018422e-23 1.000000e+00
[91,] 1.607497e-23 3.214994e-23 1.000000e+00
[92,] 8.030188e-24 1.606038e-23 1.000000e+00
[93,] 3.873973e-24 7.747945e-24 1.000000e+00
[94,] 5.060604e-24 1.012121e-23 1.000000e+00
[95,] 4.035923e-24 8.071846e-24 1.000000e+00
[96,] 3.876865e-24 7.753731e-24 1.000000e+00
[97,] 1.379857e-24 2.759715e-24 1.000000e+00
[98,] 4.977218e-25 9.954437e-25 1.000000e+00
[99,] 2.054018e-25 4.108035e-25 1.000000e+00
[100,] 1.223564e-25 2.447128e-25 1.000000e+00
[101,] 4.259226e-26 8.518451e-26 1.000000e+00
[102,] 1.494854e-26 2.989709e-26 1.000000e+00
[103,] 5.378971e-27 1.075794e-26 1.000000e+00
[104,] 2.031520e-27 4.063040e-27 1.000000e+00
[105,] 7.348968e-28 1.469794e-27 1.000000e+00
[106,] 2.480429e-28 4.960858e-28 1.000000e+00
[107,] 8.136167e-29 1.627233e-28 1.000000e+00
[108,] 3.433726e-29 6.867451e-29 1.000000e+00
[109,] 7.789212e-26 1.557842e-25 1.000000e+00
[110,] 2.878530e-26 5.757059e-26 1.000000e+00
[111,] 1.078298e-26 2.156596e-26 1.000000e+00
[112,] 4.047193e-27 8.094386e-27 1.000000e+00
[113,] 1.644281e-27 3.288561e-27 1.000000e+00
[114,] 1.012924e-25 2.025847e-25 1.000000e+00
[115,] 4.392877e-26 8.785754e-26 1.000000e+00
[116,] 1.831330e-26 3.662659e-26 1.000000e+00
[117,] 7.058405e-27 1.411681e-26 1.000000e+00
[118,] 2.578875e-27 5.157750e-27 1.000000e+00
[119,] 1.022358e-27 2.044715e-27 1.000000e+00
[120,] 3.953023e-28 7.906045e-28 1.000000e+00
[121,] 1.372142e-28 2.744285e-28 1.000000e+00
[122,] 4.819186e-29 9.638373e-29 1.000000e+00
[123,] 1.710178e-29 3.420356e-29 1.000000e+00
[124,] 5.953402e-30 1.190680e-29 1.000000e+00
[125,] 3.005480e-30 6.010960e-30 1.000000e+00
[126,] 5.666954e-30 1.133391e-29 1.000000e+00
[127,] 1.000000e+00 4.372628e-55 2.186314e-55
[128,] 1.000000e+00 4.243595e-55 2.121798e-55
[129,] 1.000000e+00 1.097001e-54 5.485007e-55
[130,] 1.000000e+00 4.158439e-54 2.079219e-54
[131,] 1.000000e+00 1.617027e-53 8.085136e-54
[132,] 1.000000e+00 5.258037e-53 2.629018e-53
[133,] 1.000000e+00 1.936105e-52 9.680527e-53
[134,] 1.000000e+00 4.392632e-52 2.196316e-52
[135,] 1.000000e+00 1.068906e-51 5.344528e-52
[136,] 1.000000e+00 3.474860e-51 1.737430e-51
[137,] 1.000000e+00 3.701850e-51 1.850925e-51
[138,] 1.000000e+00 1.772092e-51 8.860461e-52
[139,] 1.000000e+00 6.230826e-51 3.115413e-51
[140,] 1.000000e+00 2.579966e-50 1.289983e-50
[141,] 1.000000e+00 4.110366e-50 2.055183e-50
[142,] 1.000000e+00 7.482054e-50 3.741027e-50
[143,] 1.000000e+00 3.004228e-49 1.502114e-49
[144,] 1.000000e+00 6.980502e-49 3.490251e-49
[145,] 1.000000e+00 2.294758e-48 1.147379e-48
[146,] 1.000000e+00 1.312126e-50 6.560629e-51
[147,] 1.000000e+00 5.062111e-50 2.531055e-50
[148,] 1.000000e+00 1.772816e-49 8.864081e-50
[149,] 1.000000e+00 7.290640e-49 3.645320e-49
[150,] 1.000000e+00 2.843096e-48 1.421548e-48
[151,] 1.000000e+00 1.161796e-47 5.808978e-48
[152,] 1.000000e+00 1.138108e-50 5.690542e-51
[153,] 1.000000e+00 4.829829e-50 2.414914e-50
[154,] 1.000000e+00 3.909188e-50 1.954594e-50
[155,] 1.000000e+00 1.521981e-49 7.609906e-50
[156,] 1.000000e+00 2.202774e-49 1.101387e-49
[157,] 1.000000e+00 9.320690e-50 4.660345e-50
[158,] 1.000000e+00 9.051706e-51 4.525853e-51
[159,] 1.000000e+00 2.184129e-50 1.092064e-50
[160,] 1.000000e+00 7.895898e-51 3.947949e-51
[161,] 1.000000e+00 1.734051e-50 8.670255e-51
[162,] 1.000000e+00 8.306099e-50 4.153050e-50
[163,] 1.000000e+00 4.146586e-49 2.073293e-49
[164,] 1.000000e+00 2.028918e-48 1.014459e-48
[165,] 1.000000e+00 3.329685e-49 1.664842e-49
[166,] 1.000000e+00 1.314853e-48 6.574265e-49
[167,] 1.000000e+00 2.596405e-50 1.298202e-50
[168,] 1.000000e+00 1.295467e-49 6.477335e-50
[169,] 1.000000e+00 5.276085e-50 2.638043e-50
[170,] 1.000000e+00 1.904353e-49 9.521765e-50
[171,] 1.000000e+00 4.938652e-49 2.469326e-49
[172,] 1.000000e+00 7.082186e-50 3.541093e-50
[173,] 1.000000e+00 3.472492e-49 1.736246e-49
[174,] 1.000000e+00 1.834804e-48 9.174022e-49
[175,] 1.000000e+00 4.440668e-49 2.220334e-49
[176,] 1.000000e+00 2.212210e-48 1.106105e-48
[177,] 1.000000e+00 7.601408e-48 3.800704e-48
[178,] 1.000000e+00 3.799333e-47 1.899667e-47
[179,] 1.000000e+00 1.211321e-46 6.056607e-47
[180,] 1.000000e+00 6.363907e-46 3.181954e-46
[181,] 1.000000e+00 2.985623e-46 1.492812e-46
[182,] 1.000000e+00 1.622070e-45 8.110351e-46
[183,] 1.000000e+00 8.338428e-45 4.169214e-45
[184,] 1.000000e+00 4.606731e-44 2.303365e-44
[185,] 1.000000e+00 2.411453e-43 1.205726e-43
[186,] 1.000000e+00 9.667654e-43 4.833827e-43
[187,] 1.000000e+00 4.666054e-42 2.333027e-42
[188,] 1.000000e+00 1.187555e-42 5.937774e-43
[189,] 1.000000e+00 1.647170e-42 8.235849e-43
[190,] 1.000000e+00 6.687556e-42 3.343778e-42
[191,] 1.000000e+00 3.226134e-41 1.613067e-41
[192,] 1.000000e+00 1.037537e-41 5.187687e-42
[193,] 1.000000e+00 4.713034e-41 2.356517e-41
[194,] 1.000000e+00 1.708651e-40 8.543256e-41
[195,] 1.000000e+00 9.324474e-40 4.662237e-40
[196,] 1.000000e+00 4.975682e-39 2.487841e-39
[197,] 1.000000e+00 2.660847e-38 1.330423e-38
[198,] 1.000000e+00 1.357854e-37 6.789272e-38
[199,] 1.000000e+00 5.099043e-37 2.549521e-37
[200,] 1.000000e+00 1.207558e-36 6.037789e-37
[201,] 1.000000e+00 4.916419e-36 2.458210e-36
[202,] 1.000000e+00 2.612987e-35 1.306493e-35
[203,] 1.000000e+00 1.349873e-34 6.749364e-35
[204,] 1.000000e+00 6.880237e-34 3.440119e-34
[205,] 1.000000e+00 6.170720e-34 3.085360e-34
[206,] 1.000000e+00 1.604911e-33 8.024555e-34
[207,] 1.000000e+00 8.461918e-33 4.230959e-33
[208,] 1.000000e+00 2.567885e-32 1.283943e-32
[209,] 1.000000e+00 9.082433e-32 4.541217e-32
[210,] 1.000000e+00 3.029072e-31 1.514536e-31
[211,] 1.000000e+00 1.202747e-30 6.013736e-31
[212,] 1.000000e+00 5.949951e-30 2.974976e-30
[213,] 1.000000e+00 2.356194e-29 1.178097e-29
[214,] 1.000000e+00 1.212759e-28 6.063796e-29
[215,] 1.000000e+00 5.097252e-28 2.548626e-28
[216,] 1.000000e+00 1.690346e-27 8.451731e-28
[217,] 1.000000e+00 4.751977e-27 2.375988e-27
[218,] 1.000000e+00 2.286006e-26 1.143003e-26
[219,] 1.000000e+00 1.550968e-26 7.754840e-27
[220,] 1.000000e+00 1.049145e-27 5.245726e-28
[221,] 1.000000e+00 4.184048e-27 2.092024e-27
[222,] 1.000000e+00 2.302230e-26 1.151115e-26
[223,] 1.000000e+00 6.387096e-26 3.193548e-26
[224,] 1.000000e+00 2.557788e-25 1.278894e-25
[225,] 1.000000e+00 1.398884e-24 6.994422e-25
[226,] 1.000000e+00 7.454191e-24 3.727095e-24
[227,] 1.000000e+00 3.435124e-23 1.717562e-23
[228,] 1.000000e+00 1.280161e-22 6.400803e-23
[229,] 1.000000e+00 4.969233e-22 2.484617e-22
[230,] 1.000000e+00 2.309131e-21 1.154566e-21
[231,] 1.000000e+00 8.896176e-21 4.448088e-21
[232,] 1.000000e+00 4.530990e-20 2.265495e-20
[233,] 1.000000e+00 2.147082e-19 1.073541e-19
[234,] 1.000000e+00 9.037987e-19 4.518994e-19
[235,] 1.000000e+00 3.634049e-18 1.817025e-18
[236,] 1.000000e+00 9.220164e-18 4.610082e-18
[237,] 1.000000e+00 1.540040e-17 7.700201e-18
[238,] 1.000000e+00 7.358818e-17 3.679409e-17
[239,] 1.000000e+00 1.960538e-16 9.802688e-17
[240,] 1.000000e+00 2.333449e-16 1.166725e-16
[241,] 1.000000e+00 9.894217e-16 4.947109e-16
[242,] 1.000000e+00 4.114280e-15 2.057140e-15
[243,] 1.000000e+00 1.973293e-14 9.866463e-15
[244,] 1.000000e+00 7.641565e-14 3.820783e-14
[245,] 1.000000e+00 2.142631e-13 1.071315e-13
[246,] 1.000000e+00 9.898893e-13 4.949446e-13
[247,] 1.000000e+00 4.458281e-12 2.229140e-12
[248,] 1.000000e+00 1.659573e-11 8.297867e-12
[249,] 1.000000e+00 4.757070e-11 2.378535e-11
[250,] 1.000000e+00 2.093234e-10 1.046617e-10
[251,] 1.000000e+00 5.509229e-10 2.754614e-10
[252,] 1.000000e+00 2.465042e-09 1.232521e-09
[253,] 1.000000e+00 2.825552e-09 1.412776e-09
[254,] 1.000000e+00 1.155711e-08 5.778554e-09
[255,] 1.000000e+00 4.013615e-08 2.006807e-08
[256,] 9.999999e-01 1.605961e-07 8.029804e-08
[257,] 9.999997e-01 6.870789e-07 3.435395e-07
[258,] 9.999986e-01 2.700668e-06 1.350334e-06
[259,] 9.999949e-01 1.016478e-05 5.082388e-06
[260,] 9.999927e-01 1.459547e-05 7.297736e-06
[261,] 9.999702e-01 5.955791e-05 2.977896e-05
[262,] 9.999050e-01 1.900206e-04 9.501028e-05
[263,] 9.996905e-01 6.189661e-04 3.094830e-04
[264,] 9.990958e-01 1.808326e-03 9.041628e-04
[265,] 9.969367e-01 6.126563e-03 3.063282e-03
[266,] 9.896271e-01 2.074572e-02 1.037286e-02
[267,] 9.915400e-01 1.692006e-02 8.460032e-03
[268,] 9.690189e-01 6.196229e-02 3.098114e-02
> postscript(file="/var/www/rcomp/tmp/13uli1323983269.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2ukgx1323983269.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3n80u1323983269.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/41pzk1323983269.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5ar3a1323983269.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 = 289
Frequency = 1
1 2 3 4 5 6
8.37937032 4.55602528 18.63231479 13.59426725 -21.13784423 28.89065430
7 8 9 10 11 12
-9.05830189 10.24350555 -19.08894696 37.25616029 -6.56386891 -39.52436443
13 14 15 16 17 18
-3.12768740 -4.65093613 -8.45915684 -7.78462115 -18.85140110 24.28597948
19 20 21 22 23 24
27.59575071 19.20036627 15.90083552 3.57009301 -33.75364954 -13.37196515
25 26 27 28 29 30
12.53841163 -15.83221856 -1.85065163 -7.62760070 -28.88962415 -25.01215907
31 32 33 34 35 36
-37.25392347 7.54269077 -3.56634560 -28.78462584 18.33666477 -25.65954497
37 38 39 40 41 42
-20.71365492 -10.70862505 -29.05380295 -19.78348169 -8.36326753 -17.23253281
43 44 45 46 47 48
-18.89572712 -22.19229186 -18.07324384 -1.37134950 -19.08753379 -3.01908450
49 50 51 52 53 54
-0.42309973 8.59432223 29.82411124 -13.37278655 -6.29149929 21.65953453
55 56 57 58 59 60
-12.12242894 -18.44091114 -19.61333961 -2.52627422 -3.33195807 -14.14901793
61 62 63 64 65 66
-5.12096178 21.80211220 6.16269223 -20.94055763 -8.51039086 -24.82382911
67 68 69 70 71 72
8.48340849 9.64909637 26.67239707 -1.55610603 2.79229613 0.73779065
73 74 75 76 77 78
-25.07571589 28.79613945 -13.80740487 10.35119350 10.16590758 -8.55482536
79 80 81 82 83 84
-8.98507104 -11.30654322 13.70223931 -9.47773128 8.60548913 -7.94971386
85 86 87 88 89 90
142.74292091 -9.73770170 -2.59775173 -12.10509354 13.36871134 -25.40447698
91 92 93 94 95 96
-9.04629030 5.56338608 -20.91547352 18.91116241 -26.12487346 6.90362747
97 98 99 100 101 102
-5.60986575 42.39864917 -18.31594180 3.75936564 -9.38086024 -22.37809290
103 104 105 106 107 108
16.82716266 36.14533384 29.69636125 38.91051723 -3.95034550 -7.92026696
109 110 111 112 113 114
22.36057597 25.86745428 10.16245579 -1.10994538 4.95972318 -12.83620488
115 116 117 118 119 120
2.22258461 5.14154184 -3.40147492 -23.62022645 108.03851912 -9.54276808
121 122 123 124 125 126
-14.90395168 -20.53027340 -23.33806364 81.59170073 16.80813267 -18.54529429
127 128 129 130 131 132
-0.22502208 -0.77521657 19.21986210 -22.88213884 -5.58808502 -2.11332750
133 134 135 136 137 138
-11.91341118 -11.41224223 -21.03583882 -39.44486220 832.29290437 18.66490405
139 140 141 142 143 144
16.55593829 -13.43771715 -14.35227338 2.39799689 -9.69019328 -26.24807054
145 146 147 148 149 150
37.51835580 -3.54923607 51.85292370 36.56042552 -18.82974823 16.35966049
151 152 153 154 155 156
-13.01861389 -7.41456400 -10.04694406 -16.58483870 -14.82419820 60.78909579
157 158 159 160 161 162
-11.66618722 -19.43503350 11.86714158 12.68698984 -10.91491832 77.20045123
163 164 165 166 167 168
-4.51362300 31.99935513 -4.35926922 -23.91143091 -25.23707371 42.19279473
169 170 171 172 173 174
-21.43065618 15.85477197 17.80245642 0.78050221 0.47184287 10.53556082
175 176 177 178 179 180
51.23516732 -23.65142428 39.28474759 -9.83758345 17.15784410 -26.49291354
181 182 183 184 185 186
-1.47400944 14.98861929 -18.18588397 -3.84462205 -38.06223539 -21.64156535
187 188 189 190 191 192
-24.51056672 -20.52129559 -26.83291443 19.72527314 27.08169716 -8.04739773
193 194 195 196 197 198
-20.43728504 -0.39398836 -14.42789627 -24.83077850 -11.45823711 24.10809322
199 200 201 202 203 204
9.45469994 -1.01937175 -12.52529088 -16.08464242 -13.98506314 -6.09980702
205 206 207 208 209 210
-14.83051916 -0.08049259 -17.16246995 -20.09321323 -20.09150690 -33.56379863
211 212 213 214 215 216
-25.75168299 -13.31007986 -6.92104818 -16.56983066 18.77166512 -21.47045740
217 218 219 220 221 222
-15.99627613 6.27708897 -16.87732795 -18.42639597 -11.84922469 -5.69255256
223 224 225 226 227 228
-23.27339608 -7.67154476 -14.60274323 -27.11525113 5.51543759 -6.07206097
229 230 231 232 233 234
-22.53789662 23.39853789 -15.45772153 -15.14353609 -3.24537878 -5.81056765
235 236 237 238 239 240
8.63466641 -4.13782319 -10.18111749 -8.01041307 -17.08507824 -10.32393734
241 242 243 244 245 246
-1.24077408 -15.14318875 -12.30392501 -4.17021514 -11.59809265 0.34922191
247 248 249 250 251 252
-3.33230129 -9.49719505 2.76391272 6.76709034 -10.46233701 -2.27962677
253 254 255 256 257 258
-22.04063594 -9.65071249 -22.97239593 -16.94140254 -6.88097181 1.42576046
259 260 261 262 263 264
-13.27900038 -13.73548141 -4.13306120 -21.38915937 -17.44209399 -11.23859946
265 266 267 268 269 270
0.03728833 -12.87877440 -16.46813636 -6.09140548 -24.83017029 11.00075245
271 272 273 274 275 276
-10.90914255 -8.39443652 -20.46466625 -17.66756158 -10.36391139 -4.13262595
277 278 279 280 281 282
13.08007792 -18.93882399 -27.31824931 -19.39722689 -9.64430770 52.29164798
283 284 285 286 287 288
-0.79776335 -15.62320329 -10.92073183 16.53197151 -17.71721465 -15.29591733
289
-12.18717573
> postscript(file="/var/www/rcomp/tmp/6j2ac1323983269.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 = 289
Frequency = 1
lag(myerror, k = 1) myerror
0 8.37937032 NA
1 4.55602528 8.37937032
2 18.63231479 4.55602528
3 13.59426725 18.63231479
4 -21.13784423 13.59426725
5 28.89065430 -21.13784423
6 -9.05830189 28.89065430
7 10.24350555 -9.05830189
8 -19.08894696 10.24350555
9 37.25616029 -19.08894696
10 -6.56386891 37.25616029
11 -39.52436443 -6.56386891
12 -3.12768740 -39.52436443
13 -4.65093613 -3.12768740
14 -8.45915684 -4.65093613
15 -7.78462115 -8.45915684
16 -18.85140110 -7.78462115
17 24.28597948 -18.85140110
18 27.59575071 24.28597948
19 19.20036627 27.59575071
20 15.90083552 19.20036627
21 3.57009301 15.90083552
22 -33.75364954 3.57009301
23 -13.37196515 -33.75364954
24 12.53841163 -13.37196515
25 -15.83221856 12.53841163
26 -1.85065163 -15.83221856
27 -7.62760070 -1.85065163
28 -28.88962415 -7.62760070
29 -25.01215907 -28.88962415
30 -37.25392347 -25.01215907
31 7.54269077 -37.25392347
32 -3.56634560 7.54269077
33 -28.78462584 -3.56634560
34 18.33666477 -28.78462584
35 -25.65954497 18.33666477
36 -20.71365492 -25.65954497
37 -10.70862505 -20.71365492
38 -29.05380295 -10.70862505
39 -19.78348169 -29.05380295
40 -8.36326753 -19.78348169
41 -17.23253281 -8.36326753
42 -18.89572712 -17.23253281
43 -22.19229186 -18.89572712
44 -18.07324384 -22.19229186
45 -1.37134950 -18.07324384
46 -19.08753379 -1.37134950
47 -3.01908450 -19.08753379
48 -0.42309973 -3.01908450
49 8.59432223 -0.42309973
50 29.82411124 8.59432223
51 -13.37278655 29.82411124
52 -6.29149929 -13.37278655
53 21.65953453 -6.29149929
54 -12.12242894 21.65953453
55 -18.44091114 -12.12242894
56 -19.61333961 -18.44091114
57 -2.52627422 -19.61333961
58 -3.33195807 -2.52627422
59 -14.14901793 -3.33195807
60 -5.12096178 -14.14901793
61 21.80211220 -5.12096178
62 6.16269223 21.80211220
63 -20.94055763 6.16269223
64 -8.51039086 -20.94055763
65 -24.82382911 -8.51039086
66 8.48340849 -24.82382911
67 9.64909637 8.48340849
68 26.67239707 9.64909637
69 -1.55610603 26.67239707
70 2.79229613 -1.55610603
71 0.73779065 2.79229613
72 -25.07571589 0.73779065
73 28.79613945 -25.07571589
74 -13.80740487 28.79613945
75 10.35119350 -13.80740487
76 10.16590758 10.35119350
77 -8.55482536 10.16590758
78 -8.98507104 -8.55482536
79 -11.30654322 -8.98507104
80 13.70223931 -11.30654322
81 -9.47773128 13.70223931
82 8.60548913 -9.47773128
83 -7.94971386 8.60548913
84 142.74292091 -7.94971386
85 -9.73770170 142.74292091
86 -2.59775173 -9.73770170
87 -12.10509354 -2.59775173
88 13.36871134 -12.10509354
89 -25.40447698 13.36871134
90 -9.04629030 -25.40447698
91 5.56338608 -9.04629030
92 -20.91547352 5.56338608
93 18.91116241 -20.91547352
94 -26.12487346 18.91116241
95 6.90362747 -26.12487346
96 -5.60986575 6.90362747
97 42.39864917 -5.60986575
98 -18.31594180 42.39864917
99 3.75936564 -18.31594180
100 -9.38086024 3.75936564
101 -22.37809290 -9.38086024
102 16.82716266 -22.37809290
103 36.14533384 16.82716266
104 29.69636125 36.14533384
105 38.91051723 29.69636125
106 -3.95034550 38.91051723
107 -7.92026696 -3.95034550
108 22.36057597 -7.92026696
109 25.86745428 22.36057597
110 10.16245579 25.86745428
111 -1.10994538 10.16245579
112 4.95972318 -1.10994538
113 -12.83620488 4.95972318
114 2.22258461 -12.83620488
115 5.14154184 2.22258461
116 -3.40147492 5.14154184
117 -23.62022645 -3.40147492
118 108.03851912 -23.62022645
119 -9.54276808 108.03851912
120 -14.90395168 -9.54276808
121 -20.53027340 -14.90395168
122 -23.33806364 -20.53027340
123 81.59170073 -23.33806364
124 16.80813267 81.59170073
125 -18.54529429 16.80813267
126 -0.22502208 -18.54529429
127 -0.77521657 -0.22502208
128 19.21986210 -0.77521657
129 -22.88213884 19.21986210
130 -5.58808502 -22.88213884
131 -2.11332750 -5.58808502
132 -11.91341118 -2.11332750
133 -11.41224223 -11.91341118
134 -21.03583882 -11.41224223
135 -39.44486220 -21.03583882
136 832.29290437 -39.44486220
137 18.66490405 832.29290437
138 16.55593829 18.66490405
139 -13.43771715 16.55593829
140 -14.35227338 -13.43771715
141 2.39799689 -14.35227338
142 -9.69019328 2.39799689
143 -26.24807054 -9.69019328
144 37.51835580 -26.24807054
145 -3.54923607 37.51835580
146 51.85292370 -3.54923607
147 36.56042552 51.85292370
148 -18.82974823 36.56042552
149 16.35966049 -18.82974823
150 -13.01861389 16.35966049
151 -7.41456400 -13.01861389
152 -10.04694406 -7.41456400
153 -16.58483870 -10.04694406
154 -14.82419820 -16.58483870
155 60.78909579 -14.82419820
156 -11.66618722 60.78909579
157 -19.43503350 -11.66618722
158 11.86714158 -19.43503350
159 12.68698984 11.86714158
160 -10.91491832 12.68698984
161 77.20045123 -10.91491832
162 -4.51362300 77.20045123
163 31.99935513 -4.51362300
164 -4.35926922 31.99935513
165 -23.91143091 -4.35926922
166 -25.23707371 -23.91143091
167 42.19279473 -25.23707371
168 -21.43065618 42.19279473
169 15.85477197 -21.43065618
170 17.80245642 15.85477197
171 0.78050221 17.80245642
172 0.47184287 0.78050221
173 10.53556082 0.47184287
174 51.23516732 10.53556082
175 -23.65142428 51.23516732
176 39.28474759 -23.65142428
177 -9.83758345 39.28474759
178 17.15784410 -9.83758345
179 -26.49291354 17.15784410
180 -1.47400944 -26.49291354
181 14.98861929 -1.47400944
182 -18.18588397 14.98861929
183 -3.84462205 -18.18588397
184 -38.06223539 -3.84462205
185 -21.64156535 -38.06223539
186 -24.51056672 -21.64156535
187 -20.52129559 -24.51056672
188 -26.83291443 -20.52129559
189 19.72527314 -26.83291443
190 27.08169716 19.72527314
191 -8.04739773 27.08169716
192 -20.43728504 -8.04739773
193 -0.39398836 -20.43728504
194 -14.42789627 -0.39398836
195 -24.83077850 -14.42789627
196 -11.45823711 -24.83077850
197 24.10809322 -11.45823711
198 9.45469994 24.10809322
199 -1.01937175 9.45469994
200 -12.52529088 -1.01937175
201 -16.08464242 -12.52529088
202 -13.98506314 -16.08464242
203 -6.09980702 -13.98506314
204 -14.83051916 -6.09980702
205 -0.08049259 -14.83051916
206 -17.16246995 -0.08049259
207 -20.09321323 -17.16246995
208 -20.09150690 -20.09321323
209 -33.56379863 -20.09150690
210 -25.75168299 -33.56379863
211 -13.31007986 -25.75168299
212 -6.92104818 -13.31007986
213 -16.56983066 -6.92104818
214 18.77166512 -16.56983066
215 -21.47045740 18.77166512
216 -15.99627613 -21.47045740
217 6.27708897 -15.99627613
218 -16.87732795 6.27708897
219 -18.42639597 -16.87732795
220 -11.84922469 -18.42639597
221 -5.69255256 -11.84922469
222 -23.27339608 -5.69255256
223 -7.67154476 -23.27339608
224 -14.60274323 -7.67154476
225 -27.11525113 -14.60274323
226 5.51543759 -27.11525113
227 -6.07206097 5.51543759
228 -22.53789662 -6.07206097
229 23.39853789 -22.53789662
230 -15.45772153 23.39853789
231 -15.14353609 -15.45772153
232 -3.24537878 -15.14353609
233 -5.81056765 -3.24537878
234 8.63466641 -5.81056765
235 -4.13782319 8.63466641
236 -10.18111749 -4.13782319
237 -8.01041307 -10.18111749
238 -17.08507824 -8.01041307
239 -10.32393734 -17.08507824
240 -1.24077408 -10.32393734
241 -15.14318875 -1.24077408
242 -12.30392501 -15.14318875
243 -4.17021514 -12.30392501
244 -11.59809265 -4.17021514
245 0.34922191 -11.59809265
246 -3.33230129 0.34922191
247 -9.49719505 -3.33230129
248 2.76391272 -9.49719505
249 6.76709034 2.76391272
250 -10.46233701 6.76709034
251 -2.27962677 -10.46233701
252 -22.04063594 -2.27962677
253 -9.65071249 -22.04063594
254 -22.97239593 -9.65071249
255 -16.94140254 -22.97239593
256 -6.88097181 -16.94140254
257 1.42576046 -6.88097181
258 -13.27900038 1.42576046
259 -13.73548141 -13.27900038
260 -4.13306120 -13.73548141
261 -21.38915937 -4.13306120
262 -17.44209399 -21.38915937
263 -11.23859946 -17.44209399
264 0.03728833 -11.23859946
265 -12.87877440 0.03728833
266 -16.46813636 -12.87877440
267 -6.09140548 -16.46813636
268 -24.83017029 -6.09140548
269 11.00075245 -24.83017029
270 -10.90914255 11.00075245
271 -8.39443652 -10.90914255
272 -20.46466625 -8.39443652
273 -17.66756158 -20.46466625
274 -10.36391139 -17.66756158
275 -4.13262595 -10.36391139
276 13.08007792 -4.13262595
277 -18.93882399 13.08007792
278 -27.31824931 -18.93882399
279 -19.39722689 -27.31824931
280 -9.64430770 -19.39722689
281 52.29164798 -9.64430770
282 -0.79776335 52.29164798
283 -15.62320329 -0.79776335
284 -10.92073183 -15.62320329
285 16.53197151 -10.92073183
286 -17.71721465 16.53197151
287 -15.29591733 -17.71721465
288 -12.18717573 -15.29591733
289 NA -12.18717573
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 4.55602528 8.37937032
[2,] 18.63231479 4.55602528
[3,] 13.59426725 18.63231479
[4,] -21.13784423 13.59426725
[5,] 28.89065430 -21.13784423
[6,] -9.05830189 28.89065430
[7,] 10.24350555 -9.05830189
[8,] -19.08894696 10.24350555
[9,] 37.25616029 -19.08894696
[10,] -6.56386891 37.25616029
[11,] -39.52436443 -6.56386891
[12,] -3.12768740 -39.52436443
[13,] -4.65093613 -3.12768740
[14,] -8.45915684 -4.65093613
[15,] -7.78462115 -8.45915684
[16,] -18.85140110 -7.78462115
[17,] 24.28597948 -18.85140110
[18,] 27.59575071 24.28597948
[19,] 19.20036627 27.59575071
[20,] 15.90083552 19.20036627
[21,] 3.57009301 15.90083552
[22,] -33.75364954 3.57009301
[23,] -13.37196515 -33.75364954
[24,] 12.53841163 -13.37196515
[25,] -15.83221856 12.53841163
[26,] -1.85065163 -15.83221856
[27,] -7.62760070 -1.85065163
[28,] -28.88962415 -7.62760070
[29,] -25.01215907 -28.88962415
[30,] -37.25392347 -25.01215907
[31,] 7.54269077 -37.25392347
[32,] -3.56634560 7.54269077
[33,] -28.78462584 -3.56634560
[34,] 18.33666477 -28.78462584
[35,] -25.65954497 18.33666477
[36,] -20.71365492 -25.65954497
[37,] -10.70862505 -20.71365492
[38,] -29.05380295 -10.70862505
[39,] -19.78348169 -29.05380295
[40,] -8.36326753 -19.78348169
[41,] -17.23253281 -8.36326753
[42,] -18.89572712 -17.23253281
[43,] -22.19229186 -18.89572712
[44,] -18.07324384 -22.19229186
[45,] -1.37134950 -18.07324384
[46,] -19.08753379 -1.37134950
[47,] -3.01908450 -19.08753379
[48,] -0.42309973 -3.01908450
[49,] 8.59432223 -0.42309973
[50,] 29.82411124 8.59432223
[51,] -13.37278655 29.82411124
[52,] -6.29149929 -13.37278655
[53,] 21.65953453 -6.29149929
[54,] -12.12242894 21.65953453
[55,] -18.44091114 -12.12242894
[56,] -19.61333961 -18.44091114
[57,] -2.52627422 -19.61333961
[58,] -3.33195807 -2.52627422
[59,] -14.14901793 -3.33195807
[60,] -5.12096178 -14.14901793
[61,] 21.80211220 -5.12096178
[62,] 6.16269223 21.80211220
[63,] -20.94055763 6.16269223
[64,] -8.51039086 -20.94055763
[65,] -24.82382911 -8.51039086
[66,] 8.48340849 -24.82382911
[67,] 9.64909637 8.48340849
[68,] 26.67239707 9.64909637
[69,] -1.55610603 26.67239707
[70,] 2.79229613 -1.55610603
[71,] 0.73779065 2.79229613
[72,] -25.07571589 0.73779065
[73,] 28.79613945 -25.07571589
[74,] -13.80740487 28.79613945
[75,] 10.35119350 -13.80740487
[76,] 10.16590758 10.35119350
[77,] -8.55482536 10.16590758
[78,] -8.98507104 -8.55482536
[79,] -11.30654322 -8.98507104
[80,] 13.70223931 -11.30654322
[81,] -9.47773128 13.70223931
[82,] 8.60548913 -9.47773128
[83,] -7.94971386 8.60548913
[84,] 142.74292091 -7.94971386
[85,] -9.73770170 142.74292091
[86,] -2.59775173 -9.73770170
[87,] -12.10509354 -2.59775173
[88,] 13.36871134 -12.10509354
[89,] -25.40447698 13.36871134
[90,] -9.04629030 -25.40447698
[91,] 5.56338608 -9.04629030
[92,] -20.91547352 5.56338608
[93,] 18.91116241 -20.91547352
[94,] -26.12487346 18.91116241
[95,] 6.90362747 -26.12487346
[96,] -5.60986575 6.90362747
[97,] 42.39864917 -5.60986575
[98,] -18.31594180 42.39864917
[99,] 3.75936564 -18.31594180
[100,] -9.38086024 3.75936564
[101,] -22.37809290 -9.38086024
[102,] 16.82716266 -22.37809290
[103,] 36.14533384 16.82716266
[104,] 29.69636125 36.14533384
[105,] 38.91051723 29.69636125
[106,] -3.95034550 38.91051723
[107,] -7.92026696 -3.95034550
[108,] 22.36057597 -7.92026696
[109,] 25.86745428 22.36057597
[110,] 10.16245579 25.86745428
[111,] -1.10994538 10.16245579
[112,] 4.95972318 -1.10994538
[113,] -12.83620488 4.95972318
[114,] 2.22258461 -12.83620488
[115,] 5.14154184 2.22258461
[116,] -3.40147492 5.14154184
[117,] -23.62022645 -3.40147492
[118,] 108.03851912 -23.62022645
[119,] -9.54276808 108.03851912
[120,] -14.90395168 -9.54276808
[121,] -20.53027340 -14.90395168
[122,] -23.33806364 -20.53027340
[123,] 81.59170073 -23.33806364
[124,] 16.80813267 81.59170073
[125,] -18.54529429 16.80813267
[126,] -0.22502208 -18.54529429
[127,] -0.77521657 -0.22502208
[128,] 19.21986210 -0.77521657
[129,] -22.88213884 19.21986210
[130,] -5.58808502 -22.88213884
[131,] -2.11332750 -5.58808502
[132,] -11.91341118 -2.11332750
[133,] -11.41224223 -11.91341118
[134,] -21.03583882 -11.41224223
[135,] -39.44486220 -21.03583882
[136,] 832.29290437 -39.44486220
[137,] 18.66490405 832.29290437
[138,] 16.55593829 18.66490405
[139,] -13.43771715 16.55593829
[140,] -14.35227338 -13.43771715
[141,] 2.39799689 -14.35227338
[142,] -9.69019328 2.39799689
[143,] -26.24807054 -9.69019328
[144,] 37.51835580 -26.24807054
[145,] -3.54923607 37.51835580
[146,] 51.85292370 -3.54923607
[147,] 36.56042552 51.85292370
[148,] -18.82974823 36.56042552
[149,] 16.35966049 -18.82974823
[150,] -13.01861389 16.35966049
[151,] -7.41456400 -13.01861389
[152,] -10.04694406 -7.41456400
[153,] -16.58483870 -10.04694406
[154,] -14.82419820 -16.58483870
[155,] 60.78909579 -14.82419820
[156,] -11.66618722 60.78909579
[157,] -19.43503350 -11.66618722
[158,] 11.86714158 -19.43503350
[159,] 12.68698984 11.86714158
[160,] -10.91491832 12.68698984
[161,] 77.20045123 -10.91491832
[162,] -4.51362300 77.20045123
[163,] 31.99935513 -4.51362300
[164,] -4.35926922 31.99935513
[165,] -23.91143091 -4.35926922
[166,] -25.23707371 -23.91143091
[167,] 42.19279473 -25.23707371
[168,] -21.43065618 42.19279473
[169,] 15.85477197 -21.43065618
[170,] 17.80245642 15.85477197
[171,] 0.78050221 17.80245642
[172,] 0.47184287 0.78050221
[173,] 10.53556082 0.47184287
[174,] 51.23516732 10.53556082
[175,] -23.65142428 51.23516732
[176,] 39.28474759 -23.65142428
[177,] -9.83758345 39.28474759
[178,] 17.15784410 -9.83758345
[179,] -26.49291354 17.15784410
[180,] -1.47400944 -26.49291354
[181,] 14.98861929 -1.47400944
[182,] -18.18588397 14.98861929
[183,] -3.84462205 -18.18588397
[184,] -38.06223539 -3.84462205
[185,] -21.64156535 -38.06223539
[186,] -24.51056672 -21.64156535
[187,] -20.52129559 -24.51056672
[188,] -26.83291443 -20.52129559
[189,] 19.72527314 -26.83291443
[190,] 27.08169716 19.72527314
[191,] -8.04739773 27.08169716
[192,] -20.43728504 -8.04739773
[193,] -0.39398836 -20.43728504
[194,] -14.42789627 -0.39398836
[195,] -24.83077850 -14.42789627
[196,] -11.45823711 -24.83077850
[197,] 24.10809322 -11.45823711
[198,] 9.45469994 24.10809322
[199,] -1.01937175 9.45469994
[200,] -12.52529088 -1.01937175
[201,] -16.08464242 -12.52529088
[202,] -13.98506314 -16.08464242
[203,] -6.09980702 -13.98506314
[204,] -14.83051916 -6.09980702
[205,] -0.08049259 -14.83051916
[206,] -17.16246995 -0.08049259
[207,] -20.09321323 -17.16246995
[208,] -20.09150690 -20.09321323
[209,] -33.56379863 -20.09150690
[210,] -25.75168299 -33.56379863
[211,] -13.31007986 -25.75168299
[212,] -6.92104818 -13.31007986
[213,] -16.56983066 -6.92104818
[214,] 18.77166512 -16.56983066
[215,] -21.47045740 18.77166512
[216,] -15.99627613 -21.47045740
[217,] 6.27708897 -15.99627613
[218,] -16.87732795 6.27708897
[219,] -18.42639597 -16.87732795
[220,] -11.84922469 -18.42639597
[221,] -5.69255256 -11.84922469
[222,] -23.27339608 -5.69255256
[223,] -7.67154476 -23.27339608
[224,] -14.60274323 -7.67154476
[225,] -27.11525113 -14.60274323
[226,] 5.51543759 -27.11525113
[227,] -6.07206097 5.51543759
[228,] -22.53789662 -6.07206097
[229,] 23.39853789 -22.53789662
[230,] -15.45772153 23.39853789
[231,] -15.14353609 -15.45772153
[232,] -3.24537878 -15.14353609
[233,] -5.81056765 -3.24537878
[234,] 8.63466641 -5.81056765
[235,] -4.13782319 8.63466641
[236,] -10.18111749 -4.13782319
[237,] -8.01041307 -10.18111749
[238,] -17.08507824 -8.01041307
[239,] -10.32393734 -17.08507824
[240,] -1.24077408 -10.32393734
[241,] -15.14318875 -1.24077408
[242,] -12.30392501 -15.14318875
[243,] -4.17021514 -12.30392501
[244,] -11.59809265 -4.17021514
[245,] 0.34922191 -11.59809265
[246,] -3.33230129 0.34922191
[247,] -9.49719505 -3.33230129
[248,] 2.76391272 -9.49719505
[249,] 6.76709034 2.76391272
[250,] -10.46233701 6.76709034
[251,] -2.27962677 -10.46233701
[252,] -22.04063594 -2.27962677
[253,] -9.65071249 -22.04063594
[254,] -22.97239593 -9.65071249
[255,] -16.94140254 -22.97239593
[256,] -6.88097181 -16.94140254
[257,] 1.42576046 -6.88097181
[258,] -13.27900038 1.42576046
[259,] -13.73548141 -13.27900038
[260,] -4.13306120 -13.73548141
[261,] -21.38915937 -4.13306120
[262,] -17.44209399 -21.38915937
[263,] -11.23859946 -17.44209399
[264,] 0.03728833 -11.23859946
[265,] -12.87877440 0.03728833
[266,] -16.46813636 -12.87877440
[267,] -6.09140548 -16.46813636
[268,] -24.83017029 -6.09140548
[269,] 11.00075245 -24.83017029
[270,] -10.90914255 11.00075245
[271,] -8.39443652 -10.90914255
[272,] -20.46466625 -8.39443652
[273,] -17.66756158 -20.46466625
[274,] -10.36391139 -17.66756158
[275,] -4.13262595 -10.36391139
[276,] 13.08007792 -4.13262595
[277,] -18.93882399 13.08007792
[278,] -27.31824931 -18.93882399
[279,] -19.39722689 -27.31824931
[280,] -9.64430770 -19.39722689
[281,] 52.29164798 -9.64430770
[282,] -0.79776335 52.29164798
[283,] -15.62320329 -0.79776335
[284,] -10.92073183 -15.62320329
[285,] 16.53197151 -10.92073183
[286,] -17.71721465 16.53197151
[287,] -15.29591733 -17.71721465
[288,] -12.18717573 -15.29591733
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 4.55602528 8.37937032
2 18.63231479 4.55602528
3 13.59426725 18.63231479
4 -21.13784423 13.59426725
5 28.89065430 -21.13784423
6 -9.05830189 28.89065430
7 10.24350555 -9.05830189
8 -19.08894696 10.24350555
9 37.25616029 -19.08894696
10 -6.56386891 37.25616029
11 -39.52436443 -6.56386891
12 -3.12768740 -39.52436443
13 -4.65093613 -3.12768740
14 -8.45915684 -4.65093613
15 -7.78462115 -8.45915684
16 -18.85140110 -7.78462115
17 24.28597948 -18.85140110
18 27.59575071 24.28597948
19 19.20036627 27.59575071
20 15.90083552 19.20036627
21 3.57009301 15.90083552
22 -33.75364954 3.57009301
23 -13.37196515 -33.75364954
24 12.53841163 -13.37196515
25 -15.83221856 12.53841163
26 -1.85065163 -15.83221856
27 -7.62760070 -1.85065163
28 -28.88962415 -7.62760070
29 -25.01215907 -28.88962415
30 -37.25392347 -25.01215907
31 7.54269077 -37.25392347
32 -3.56634560 7.54269077
33 -28.78462584 -3.56634560
34 18.33666477 -28.78462584
35 -25.65954497 18.33666477
36 -20.71365492 -25.65954497
37 -10.70862505 -20.71365492
38 -29.05380295 -10.70862505
39 -19.78348169 -29.05380295
40 -8.36326753 -19.78348169
41 -17.23253281 -8.36326753
42 -18.89572712 -17.23253281
43 -22.19229186 -18.89572712
44 -18.07324384 -22.19229186
45 -1.37134950 -18.07324384
46 -19.08753379 -1.37134950
47 -3.01908450 -19.08753379
48 -0.42309973 -3.01908450
49 8.59432223 -0.42309973
50 29.82411124 8.59432223
51 -13.37278655 29.82411124
52 -6.29149929 -13.37278655
53 21.65953453 -6.29149929
54 -12.12242894 21.65953453
55 -18.44091114 -12.12242894
56 -19.61333961 -18.44091114
57 -2.52627422 -19.61333961
58 -3.33195807 -2.52627422
59 -14.14901793 -3.33195807
60 -5.12096178 -14.14901793
61 21.80211220 -5.12096178
62 6.16269223 21.80211220
63 -20.94055763 6.16269223
64 -8.51039086 -20.94055763
65 -24.82382911 -8.51039086
66 8.48340849 -24.82382911
67 9.64909637 8.48340849
68 26.67239707 9.64909637
69 -1.55610603 26.67239707
70 2.79229613 -1.55610603
71 0.73779065 2.79229613
72 -25.07571589 0.73779065
73 28.79613945 -25.07571589
74 -13.80740487 28.79613945
75 10.35119350 -13.80740487
76 10.16590758 10.35119350
77 -8.55482536 10.16590758
78 -8.98507104 -8.55482536
79 -11.30654322 -8.98507104
80 13.70223931 -11.30654322
81 -9.47773128 13.70223931
82 8.60548913 -9.47773128
83 -7.94971386 8.60548913
84 142.74292091 -7.94971386
85 -9.73770170 142.74292091
86 -2.59775173 -9.73770170
87 -12.10509354 -2.59775173
88 13.36871134 -12.10509354
89 -25.40447698 13.36871134
90 -9.04629030 -25.40447698
91 5.56338608 -9.04629030
92 -20.91547352 5.56338608
93 18.91116241 -20.91547352
94 -26.12487346 18.91116241
95 6.90362747 -26.12487346
96 -5.60986575 6.90362747
97 42.39864917 -5.60986575
98 -18.31594180 42.39864917
99 3.75936564 -18.31594180
100 -9.38086024 3.75936564
101 -22.37809290 -9.38086024
102 16.82716266 -22.37809290
103 36.14533384 16.82716266
104 29.69636125 36.14533384
105 38.91051723 29.69636125
106 -3.95034550 38.91051723
107 -7.92026696 -3.95034550
108 22.36057597 -7.92026696
109 25.86745428 22.36057597
110 10.16245579 25.86745428
111 -1.10994538 10.16245579
112 4.95972318 -1.10994538
113 -12.83620488 4.95972318
114 2.22258461 -12.83620488
115 5.14154184 2.22258461
116 -3.40147492 5.14154184
117 -23.62022645 -3.40147492
118 108.03851912 -23.62022645
119 -9.54276808 108.03851912
120 -14.90395168 -9.54276808
121 -20.53027340 -14.90395168
122 -23.33806364 -20.53027340
123 81.59170073 -23.33806364
124 16.80813267 81.59170073
125 -18.54529429 16.80813267
126 -0.22502208 -18.54529429
127 -0.77521657 -0.22502208
128 19.21986210 -0.77521657
129 -22.88213884 19.21986210
130 -5.58808502 -22.88213884
131 -2.11332750 -5.58808502
132 -11.91341118 -2.11332750
133 -11.41224223 -11.91341118
134 -21.03583882 -11.41224223
135 -39.44486220 -21.03583882
136 832.29290437 -39.44486220
137 18.66490405 832.29290437
138 16.55593829 18.66490405
139 -13.43771715 16.55593829
140 -14.35227338 -13.43771715
141 2.39799689 -14.35227338
142 -9.69019328 2.39799689
143 -26.24807054 -9.69019328
144 37.51835580 -26.24807054
145 -3.54923607 37.51835580
146 51.85292370 -3.54923607
147 36.56042552 51.85292370
148 -18.82974823 36.56042552
149 16.35966049 -18.82974823
150 -13.01861389 16.35966049
151 -7.41456400 -13.01861389
152 -10.04694406 -7.41456400
153 -16.58483870 -10.04694406
154 -14.82419820 -16.58483870
155 60.78909579 -14.82419820
156 -11.66618722 60.78909579
157 -19.43503350 -11.66618722
158 11.86714158 -19.43503350
159 12.68698984 11.86714158
160 -10.91491832 12.68698984
161 77.20045123 -10.91491832
162 -4.51362300 77.20045123
163 31.99935513 -4.51362300
164 -4.35926922 31.99935513
165 -23.91143091 -4.35926922
166 -25.23707371 -23.91143091
167 42.19279473 -25.23707371
168 -21.43065618 42.19279473
169 15.85477197 -21.43065618
170 17.80245642 15.85477197
171 0.78050221 17.80245642
172 0.47184287 0.78050221
173 10.53556082 0.47184287
174 51.23516732 10.53556082
175 -23.65142428 51.23516732
176 39.28474759 -23.65142428
177 -9.83758345 39.28474759
178 17.15784410 -9.83758345
179 -26.49291354 17.15784410
180 -1.47400944 -26.49291354
181 14.98861929 -1.47400944
182 -18.18588397 14.98861929
183 -3.84462205 -18.18588397
184 -38.06223539 -3.84462205
185 -21.64156535 -38.06223539
186 -24.51056672 -21.64156535
187 -20.52129559 -24.51056672
188 -26.83291443 -20.52129559
189 19.72527314 -26.83291443
190 27.08169716 19.72527314
191 -8.04739773 27.08169716
192 -20.43728504 -8.04739773
193 -0.39398836 -20.43728504
194 -14.42789627 -0.39398836
195 -24.83077850 -14.42789627
196 -11.45823711 -24.83077850
197 24.10809322 -11.45823711
198 9.45469994 24.10809322
199 -1.01937175 9.45469994
200 -12.52529088 -1.01937175
201 -16.08464242 -12.52529088
202 -13.98506314 -16.08464242
203 -6.09980702 -13.98506314
204 -14.83051916 -6.09980702
205 -0.08049259 -14.83051916
206 -17.16246995 -0.08049259
207 -20.09321323 -17.16246995
208 -20.09150690 -20.09321323
209 -33.56379863 -20.09150690
210 -25.75168299 -33.56379863
211 -13.31007986 -25.75168299
212 -6.92104818 -13.31007986
213 -16.56983066 -6.92104818
214 18.77166512 -16.56983066
215 -21.47045740 18.77166512
216 -15.99627613 -21.47045740
217 6.27708897 -15.99627613
218 -16.87732795 6.27708897
219 -18.42639597 -16.87732795
220 -11.84922469 -18.42639597
221 -5.69255256 -11.84922469
222 -23.27339608 -5.69255256
223 -7.67154476 -23.27339608
224 -14.60274323 -7.67154476
225 -27.11525113 -14.60274323
226 5.51543759 -27.11525113
227 -6.07206097 5.51543759
228 -22.53789662 -6.07206097
229 23.39853789 -22.53789662
230 -15.45772153 23.39853789
231 -15.14353609 -15.45772153
232 -3.24537878 -15.14353609
233 -5.81056765 -3.24537878
234 8.63466641 -5.81056765
235 -4.13782319 8.63466641
236 -10.18111749 -4.13782319
237 -8.01041307 -10.18111749
238 -17.08507824 -8.01041307
239 -10.32393734 -17.08507824
240 -1.24077408 -10.32393734
241 -15.14318875 -1.24077408
242 -12.30392501 -15.14318875
243 -4.17021514 -12.30392501
244 -11.59809265 -4.17021514
245 0.34922191 -11.59809265
246 -3.33230129 0.34922191
247 -9.49719505 -3.33230129
248 2.76391272 -9.49719505
249 6.76709034 2.76391272
250 -10.46233701 6.76709034
251 -2.27962677 -10.46233701
252 -22.04063594 -2.27962677
253 -9.65071249 -22.04063594
254 -22.97239593 -9.65071249
255 -16.94140254 -22.97239593
256 -6.88097181 -16.94140254
257 1.42576046 -6.88097181
258 -13.27900038 1.42576046
259 -13.73548141 -13.27900038
260 -4.13306120 -13.73548141
261 -21.38915937 -4.13306120
262 -17.44209399 -21.38915937
263 -11.23859946 -17.44209399
264 0.03728833 -11.23859946
265 -12.87877440 0.03728833
266 -16.46813636 -12.87877440
267 -6.09140548 -16.46813636
268 -24.83017029 -6.09140548
269 11.00075245 -24.83017029
270 -10.90914255 11.00075245
271 -8.39443652 -10.90914255
272 -20.46466625 -8.39443652
273 -17.66756158 -20.46466625
274 -10.36391139 -17.66756158
275 -4.13262595 -10.36391139
276 13.08007792 -4.13262595
277 -18.93882399 13.08007792
278 -27.31824931 -18.93882399
279 -19.39722689 -27.31824931
280 -9.64430770 -19.39722689
281 52.29164798 -9.64430770
282 -0.79776335 52.29164798
283 -15.62320329 -0.79776335
284 -10.92073183 -15.62320329
285 16.53197151 -10.92073183
286 -17.71721465 16.53197151
287 -15.29591733 -17.71721465
288 -12.18717573 -15.29591733
> 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/rcomp/tmp/72p6h1323983269.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8enxi1323983269.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9ii0c1323983269.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/103har1323983269.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11qalr1323983269.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/rcomp/tmp/12zkba1323983269.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/rcomp/tmp/13bfkv1323983269.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/rcomp/tmp/14hu8k1323983269.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/rcomp/tmp/15je1y1323983269.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/rcomp/tmp/161zgj1323983269.tab")
+ }
>
> try(system("convert tmp/13uli1323983269.ps tmp/13uli1323983269.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ukgx1323983269.ps tmp/2ukgx1323983269.png",intern=TRUE))
character(0)
> try(system("convert tmp/3n80u1323983269.ps tmp/3n80u1323983269.png",intern=TRUE))
character(0)
> try(system("convert tmp/41pzk1323983269.ps tmp/41pzk1323983269.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ar3a1323983269.ps tmp/5ar3a1323983269.png",intern=TRUE))
character(0)
> try(system("convert tmp/6j2ac1323983269.ps tmp/6j2ac1323983269.png",intern=TRUE))
character(0)
> try(system("convert tmp/72p6h1323983269.ps tmp/72p6h1323983269.png",intern=TRUE))
character(0)
> try(system("convert tmp/8enxi1323983269.ps tmp/8enxi1323983269.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ii0c1323983269.ps tmp/9ii0c1323983269.png",intern=TRUE))
character(0)
> try(system("convert tmp/103har1323983269.ps tmp/103har1323983269.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
8.240 0.330 8.554