R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(210907
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+ ,16
+ ,16
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+ ,10205
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+ ,72
+ ,72535
+ ,17
+ ,16
+ ,64
+ ,39
+ ,19540
+ ,6095
+ ,35873
+ ,27
+ ,21)
+ ,dim=c(10
+ ,289)
+ ,dimnames=list(c('TiRFC'
+ ,'NoBC'
+ ,'NoRC'
+ ,'FMPR'
+ ,'FMPR+'
+ ,'Noc'
+ ,'NoR'
+ ,'NoS'
+ ,'NoiH'
+ ,'NoiB')
+ ,1:289))
> y <- array(NA,dim=c(10,289),dimnames=list(c('TiRFC','NoBC','NoRC','FMPR','FMPR+','Noc','NoR','NoS','NoiH','NoiB'),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 = '6'
> #'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
Noc TiRFC NoBC NoRC FMPR FMPR+ NoR NoS NoiH NoiB
1 112285 210907 79 30 115 94 24188 146283 144 145
2 84786 120982 58 28 109 103 18273 98364 103 101
3 83123 176508 60 38 146 93 14130 86146 98 98
4 101193 179321 108 30 116 103 32287 96933 135 132
5 38361 123185 49 22 68 51 8654 79234 61 60
6 68504 52746 0 26 101 70 9245 42551 39 38
7 119182 385534 121 25 96 91 33251 195663 150 144
8 22807 33170 1 18 67 22 1271 6853 5 5
9 17140 101645 20 11 44 38 5279 21529 28 28
10 116174 149061 43 26 100 93 27101 95757 84 84
11 57635 165446 69 25 93 60 16373 85584 80 79
12 66198 237213 78 38 140 123 19716 143983 130 127
13 71701 173326 86 44 166 148 17753 75851 82 78
14 57793 133131 44 30 99 90 9028 59238 60 60
15 80444 258873 104 40 139 124 18653 93163 131 131
16 53855 180083 63 34 130 70 8828 96037 84 84
17 97668 324799 158 47 181 168 29498 151511 140 133
18 133824 230964 102 30 116 115 27563 136368 151 150
19 101481 236785 77 31 116 71 18293 112642 91 91
20 99645 135473 82 23 88 66 22530 94728 138 132
21 114789 202925 115 36 139 134 15977 105499 150 136
22 99052 215147 101 36 135 117 35082 121527 124 124
23 67654 344297 80 30 108 108 16116 127766 119 118
24 65553 153935 50 25 89 84 15849 98958 73 70
25 97500 132943 83 39 156 156 16026 77900 110 107
26 69112 174724 123 34 129 120 26569 85646 123 119
27 82753 174415 73 31 118 114 24785 98579 90 89
28 85323 225548 81 31 118 94 17569 130767 116 112
29 72654 223632 105 33 125 120 23825 131741 113 108
30 30727 124817 47 25 95 81 7869 53907 56 52
31 77873 221698 105 33 126 110 14975 178812 115 112
32 117478 210767 94 35 135 133 37791 146761 119 116
33 74007 170266 44 42 154 122 9605 82036 129 123
34 90183 260561 114 43 165 158 27295 163253 127 125
35 61542 84853 38 30 113 109 2746 27032 27 27
36 101494 294424 107 33 127 124 34461 171975 175 162
37 27570 101011 30 13 52 39 8098 65990 35 32
38 55813 215641 71 32 121 92 4787 86572 64 64
39 79215 325107 84 36 136 126 24919 159676 96 92
40 1423 7176 0 0 0 0 603 1929 0 0
41 55461 167542 59 28 108 70 16329 85371 84 83
42 31081 106408 33 14 46 37 12558 58391 41 41
43 22996 96560 42 17 54 38 7784 31580 47 47
44 83122 265769 96 32 124 120 28522 136815 126 120
45 70106 269651 106 30 115 93 22265 120642 105 105
46 60578 149112 56 35 128 95 14459 69107 80 79
47 39992 175824 57 20 80 77 14526 50495 70 65
48 79892 152871 59 28 97 90 22240 108016 73 70
49 49810 111665 39 28 104 80 11802 46341 57 55
50 71570 116408 34 39 59 31 7623 78348 40 39
51 100708 362301 76 34 125 110 11912 79336 68 67
52 33032 78800 20 26 82 66 7935 56968 21 21
53 82875 183167 91 39 149 138 18220 93176 127 127
54 139077 277965 115 39 149 133 19199 161632 154 152
55 71595 150629 85 33 122 113 19918 87850 116 113
56 72260 168809 76 28 118 100 21884 127969 102 99
57 5950 24188 8 4 12 7 2694 15049 7 7
58 115762 329267 79 39 144 140 15808 155135 148 141
59 32551 65029 21 18 67 61 3597 25109 21 21
60 31701 101097 30 14 52 41 5296 45824 35 35
61 80670 218946 76 29 108 96 25239 102996 112 109
62 143558 244052 101 44 166 164 29801 160604 137 133
63 117105 341570 94 21 80 78 18450 158051 135 123
64 23789 103597 27 16 60 49 7132 44547 26 26
65 120733 233328 92 28 107 102 34861 162647 230 230
66 105195 256462 123 35 127 124 35940 174141 181 166
67 73107 206161 75 28 107 99 16688 60622 71 68
68 132068 311473 128 38 146 129 24683 179566 147 147
69 149193 235800 105 23 84 62 46230 184301 190 179
70 46821 177939 55 36 141 73 10387 75661 64 61
71 87011 207176 56 32 123 114 21436 96144 105 101
72 95260 196553 41 29 111 99 30546 129847 107 108
73 55183 174184 72 25 98 70 19746 117286 94 90
74 106671 143246 67 27 105 104 15977 71180 116 114
75 73511 187559 75 36 135 116 22583 109377 106 103
76 92945 187681 114 28 107 91 17274 85298 143 142
77 78664 119016 118 23 85 74 16469 73631 81 79
78 70054 182192 77 40 155 138 14251 86767 89 88
79 22618 73566 22 23 88 67 3007 23824 26 25
80 74011 194979 66 40 155 151 16851 93487 84 83
81 83737 167488 69 28 104 72 21113 82981 113 113
82 69094 143756 105 34 132 120 17401 73815 120 118
83 93133 275541 116 33 127 115 23958 94552 110 110
84 95536 243199 88 28 108 105 23567 132190 134 129
85 225920 182999 73 34 129 104 13065 128754 54 51
86 62133 135649 99 30 116 108 15358 66363 96 93
87 61370 152299 62 33 122 98 14587 67808 78 76
88 43836 120221 53 22 85 69 12770 61724 51 49
89 106117 346485 118 38 147 111 24021 131722 121 118
90 38692 145790 30 26 99 99 9648 68580 38 38
91 84651 193339 100 35 87 71 20537 106175 145 141
92 56622 80953 49 8 28 27 7905 55792 59 58
93 15986 122774 24 24 90 69 4527 25157 27 27
94 95364 130585 67 29 109 107 30495 76669 91 91
95 26706 112611 46 20 78 73 7117 57283 48 48
96 89691 286468 57 29 111 107 17719 105805 68 63
97 67267 241066 75 45 158 93 27056 129484 58 56
98 126846 148446 135 37 141 129 33473 72413 150 144
99 41140 204713 68 33 122 69 9758 87831 74 73
100 102860 182079 124 33 124 118 21115 96971 181 168
101 51715 140344 33 25 93 73 7236 71299 65 64
102 55801 220516 98 32 124 119 13790 77494 97 97
103 111813 243060 58 29 112 104 32902 120336 121 117
104 120293 162765 68 28 108 107 25131 93913 99 100
105 138599 182613 81 28 99 99 30910 136048 152 149
106 161647 232138 131 31 117 90 35947 181248 188 187
107 115929 265318 110 52 199 197 29848 146123 138 127
108 24266 85574 37 21 78 36 6943 32036 40 37
109 162901 310839 130 24 91 85 42705 186646 254 245
110 109825 225060 93 41 158 139 31808 102255 87 87
111 129838 232317 118 33 126 106 26675 168237 178 177
112 37510 144966 39 32 122 50 8435 64219 51 49
113 43750 43287 13 19 71 64 7409 19630 49 49
114 40652 155754 74 20 75 31 14993 76825 73 73
115 87771 164709 81 31 115 63 36867 115338 176 177
116 85872 201940 109 31 119 92 33835 109427 94 94
117 89275 235454 151 32 124 106 24164 118168 120 117
118 44418 220801 51 18 72 63 12607 84845 66 60
119 192565 99466 28 23 91 69 22609 153197 56 55
120 35232 92661 40 17 45 41 5892 29877 39 39
121 40909 133328 56 20 78 56 17014 63506 66 64
122 13294 61361 27 12 39 25 5394 22445 27 26
123 32387 125930 37 17 68 65 9178 47695 65 64
124 140867 100750 83 30 119 93 6440 68370 58 58
125 120662 224549 54 31 117 114 21916 146304 98 95
126 21233 82316 27 10 39 38 4011 38233 25 25
127 44332 102010 28 13 50 44 5818 42071 26 26
128 61056 101523 59 22 88 87 18647 50517 77 76
129 101338 243511 133 42 155 110 20556 103950 130 129
130 1168 22938 12 1 0 0 238 5841 11 11
131 13497 41566 0 9 36 27 70 2341 2 2
132 65567 152474 106 32 123 83 22392 84396 101 101
133 25162 61857 23 11 32 30 3913 24610 31 28
134 32334 99923 44 25 99 80 12237 35753 36 36
135 40735 132487 71 36 136 98 8388 55515 120 89
136 91413 317394 116 31 117 82 22120 209056 195 193
137 855 21054 4 0 0 0 338 6622 4 4
138 97068 209641 62 24 88 60 11727 115814 89 84
139 44339 22648 12 13 39 28 3704 11609 24 23
140 14116 31414 18 8 25 9 3988 13155 39 39
141 10288 46698 14 13 52 33 3030 18274 14 14
142 65622 131698 60 19 75 59 13520 72875 78 78
143 16563 91735 7 18 71 49 1421 10112 15 14
144 76643 244749 98 33 124 115 20923 142775 106 101
145 110681 184510 64 40 151 140 20237 68847 83 82
146 29011 79863 29 22 71 49 3219 17659 24 24
147 92696 128423 32 38 145 120 3769 20112 37 36
148 94785 97839 25 24 87 66 12252 61023 77 75
149 8773 38214 16 8 27 21 1888 13983 16 16
150 83209 151101 48 35 131 124 14497 65176 56 55
151 93815 272458 100 43 162 152 28864 132432 132 131
152 86687 172494 46 43 165 139 21721 112494 144 131
153 34553 108043 45 14 54 38 4821 45109 40 39
154 105547 328107 129 41 159 144 33644 170875 153 144
155 103487 250579 130 38 147 120 15923 180759 143 139
156 213688 351067 136 45 170 160 42935 214921 220 211
157 71220 158015 59 31 119 114 18864 100226 79 78
158 23517 98866 25 13 49 39 4977 32043 50 50
159 56926 85439 32 28 104 78 7785 54454 39 39
160 91721 229242 63 31 120 119 17939 78876 95 90
161 115168 351619 95 40 150 141 23436 170745 169 166
162 111194 84207 14 30 112 101 325 6940 12 12
163 51009 120445 36 16 59 56 13539 49025 63 57
164 135777 324598 113 37 136 133 34538 122037 134 133
165 51513 131069 47 30 107 83 12198 53782 69 69
166 74163 204271 92 35 130 116 26924 127748 119 119
167 51633 165543 70 32 115 90 12716 86839 119 119
168 75345 141722 19 27 107 36 8172 44830 75 65
169 33416 116048 50 20 75 50 10855 77395 63 61
170 83305 250047 41 18 71 61 11932 89324 55 49
171 98952 299775 91 31 120 97 14300 103300 103 101
172 102372 195838 111 31 116 98 25515 112283 197 196
173 37238 173260 41 21 79 78 2805 10901 16 15
174 103772 254488 120 39 150 117 29402 120691 140 136
175 123969 104389 135 41 156 148 16440 58106 89 89
176 27142 136084 27 13 51 41 11221 57140 40 40
177 135400 199476 87 32 118 105 28732 122422 125 123
178 21399 92499 25 18 71 55 5250 25899 21 21
179 130115 224330 131 39 144 132 28608 139296 167 163
180 24874 135781 45 14 47 44 8092 52678 32 29
181 34988 74408 29 7 28 21 4473 23853 36 35
182 45549 81240 58 17 68 50 1572 17306 13 13
183 6023 14688 4 0 0 0 2065 7953 5 5
184 64466 181633 47 30 110 73 14817 89455 96 96
185 54990 271856 109 37 147 86 16714 147866 151 151
186 1644 7199 7 0 0 0 556 4245 6 6
187 6179 46660 12 5 15 13 2089 21509 13 13
188 3926 17547 0 1 4 4 2658 7670 3 3
189 32755 133368 37 16 64 57 10695 66675 57 56
190 34777 95227 37 32 111 48 1669 14336 23 23
191 73224 152601 46 24 85 46 16267 53608 61 57
192 27114 98146 15 17 68 48 7768 30059 21 14
193 20760 79619 42 11 40 32 7252 29668 43 43
194 37636 59194 7 24 80 68 6387 22097 20 20
195 65461 139942 54 22 88 87 18715 96841 82 72
196 30080 118612 54 12 48 43 7936 41907 90 87
197 24094 72880 14 19 76 67 8643 27080 25 21
198 69008 65475 16 13 51 46 7294 35885 60 56
199 54968 99643 33 17 67 46 4570 41247 61 59
200 46090 71965 32 15 59 56 7185 28313 85 82
201 27507 77272 21 16 61 48 10058 36845 43 43
202 10672 49289 15 24 76 44 2342 16548 25 25
203 34029 135131 38 15 60 60 8509 36134 41 38
204 46300 108446 22 17 68 65 13275 55764 26 25
205 24760 89746 28 18 71 55 6816 28910 38 38
206 18779 44296 10 20 76 38 1930 13339 12 12
207 21280 77648 31 16 62 52 8086 25319 29 29
208 40662 181528 32 16 61 60 10737 66956 49 47
209 28987 134019 32 18 67 54 8033 47487 46 45
210 22827 124064 43 22 88 86 7058 52785 41 40
211 18513 92630 27 8 30 24 6782 44683 31 30
212 30594 121848 37 17 64 52 5401 35619 41 41
213 24006 52915 20 18 68 49 6521 21920 26 25
214 27913 81872 32 16 64 61 10856 45608 23 23
215 42744 58981 0 23 91 61 2154 7721 14 14
216 12934 53515 5 22 88 81 6117 20634 16 16
217 22574 60812 26 13 52 43 5238 29788 25 26
218 41385 56375 10 13 49 40 4820 31931 21 21
219 18653 65490 27 16 62 40 5615 37754 32 27
220 18472 80949 11 16 61 56 4272 32505 9 9
221 30976 76302 29 20 76 68 8702 40557 35 33
222 63339 104011 25 22 88 79 15340 94238 42 42
223 25568 98104 55 17 66 47 8030 44197 68 68
224 33747 67989 23 18 71 57 9526 43228 32 32
225 4154 30989 5 17 68 41 1278 4103 6 6
226 19474 135458 43 12 48 29 4236 44144 68 67
227 35130 73504 23 7 25 3 3023 32868 33 33
228 39067 63123 34 17 68 60 7196 27640 84 77
229 13310 61254 36 14 41 30 3394 14063 46 46
230 65892 74914 35 23 90 79 6371 28990 30 30
231 4143 31774 0 17 66 47 1574 4694 0 0
232 28579 81437 37 14 54 40 9620 42648 36 36
233 51776 87186 28 15 59 48 6978 64329 47 46
234 21152 50090 16 17 60 36 4911 21928 20 18
235 38084 65745 26 21 77 42 8645 25836 50 48
236 27717 56653 38 18 68 49 8987 22779 30 29
237 32928 158399 23 18 72 57 5544 40820 30 28
238 11342 46455 22 17 67 12 3083 27530 34 34
239 19499 73624 30 17 64 40 6909 32378 33 33
240 16380 38395 16 16 63 43 3189 10824 34 34
241 36874 91899 18 15 59 33 6745 39613 37 33
242 48259 139526 28 21 84 77 16724 60865 83 80
243 16734 52164 32 16 64 43 4850 19787 32 32
244 28207 51567 21 14 56 45 7025 20107 30 30
245 30143 70551 23 15 54 47 6047 36605 43 41
246 41369 84856 29 17 67 43 7377 40961 41 41
247 45833 102538 50 15 58 45 9078 48231 51 51
248 29156 86678 12 15 59 50 4605 39725 19 18
249 35944 85709 21 10 40 35 3238 21455 37 34
250 36278 34662 18 6 22 7 8100 23430 33 31
251 45588 150580 27 22 83 71 9653 62991 41 39
252 45097 99611 41 21 81 67 8914 49363 54 54
253 3895 19349 13 1 2 0 786 9604 14 14
254 28394 99373 12 18 72 62 6700 24552 25 24
255 18632 86230 21 17 61 54 5788 31493 25 24
256 2325 30837 8 4 15 4 593 3439 8 8
257 25139 31706 26 10 32 25 4506 19555 26 26
258 27975 89806 27 16 62 40 6382 21228 20 19
259 14483 62088 13 16 58 38 5621 23177 11 11
260 13127 40151 16 9 36 19 3997 22094 14 14
261 5839 27634 2 16 59 17 520 2342 3 1
262 24069 76990 42 17 68 67 8891 38798 40 39
263 3738 37460 5 7 21 14 999 3255 5 5
264 18625 54157 37 15 55 30 7067 24261 38 37
265 36341 49862 17 14 54 54 4639 18511 32 32
266 24548 84337 38 14 55 35 5654 40798 41 38
267 21792 64175 37 18 72 59 6928 28893 46 47
268 26263 59382 29 12 41 24 1514 21425 47 47
269 23686 119308 32 16 61 58 9238 50276 37 37
270 49303 76702 35 21 67 42 8204 37643 51 51
271 25659 103425 17 19 76 46 5926 30377 49 45
272 28904 70344 20 16 64 61 5785 27126 21 21
273 2781 43410 7 1 3 3 4 13 1 1
274 29236 104838 46 16 63 52 5930 42097 44 42
275 19546 62215 24 10 40 25 3710 24451 26 26
276 22818 69304 40 19 69 40 705 14335 21 21
277 32689 53117 3 12 48 32 443 5084 4 4
278 5752 19764 10 2 8 4 2416 9927 10 10
279 22197 86680 37 14 52 49 7747 43527 43 43
280 20055 84105 17 17 66 63 5432 27184 34 34
281 25272 77945 28 19 76 67 4913 21610 32 31
282 82206 89113 19 14 43 32 2650 20484 20 19
283 32073 91005 29 11 39 23 2370 20156 34 34
284 5444 40248 8 4 14 7 775 6012 6 6
285 20154 64187 10 16 61 54 5576 18475 12 11
286 36944 50857 15 20 71 37 1352 12645 24 24
287 8019 56613 15 12 44 35 3080 11017 16 16
288 30884 62792 28 15 60 51 10205 37623 72 72
289 19540 72535 17 16 64 39 6095 35873 27 21
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) TiRFC NoBC NoRC FMPR `FMPR+`
1124.54616 -0.05602 -28.35343 1017.72333 -206.39404 256.64090
NoR NoS NoiH NoiB
0.88675 0.33020 -96.51429 217.44713
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-40867 -11420 -4433 8026 142470
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1124.54616 3113.22699 0.361 0.71821
TiRFC -0.05602 0.03689 -1.518 0.13003
NoBC -28.35343 81.37247 -0.348 0.72777
NoRC 1017.72333 652.70391 1.559 0.12007
FMPR -206.39404 197.96380 -1.043 0.29804
`FMPR+` 256.64090 97.77322 2.625 0.00915 **
NoR 0.88675 0.29605 2.995 0.00299 **
NoS 0.33020 0.07564 4.366 1.79e-05 ***
NoiH -96.51429 413.33327 -0.234 0.81554
NoiB 217.44713 428.38954 0.508 0.61214
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 20620 on 279 degrees of freedom
Multiple R-squared: 0.7478, Adjusted R-squared: 0.7397
F-statistic: 91.93 on 9 and 279 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.296608452 5.932169e-01 7.033915e-01
[2,] 0.293777454 5.875549e-01 7.062225e-01
[3,] 0.184222393 3.684448e-01 8.157776e-01
[4,] 0.103398840 2.067977e-01 8.966012e-01
[5,] 0.058436769 1.168735e-01 9.415632e-01
[6,] 0.117507109 2.350142e-01 8.824929e-01
[7,] 0.095852750 1.917055e-01 9.041473e-01
[8,] 0.142090511 2.841810e-01 8.579095e-01
[9,] 0.297993783 5.959876e-01 7.020062e-01
[10,] 0.270369006 5.407380e-01 7.296310e-01
[11,] 0.234205245 4.684105e-01 7.657948e-01
[12,] 0.175127148 3.502543e-01 8.248729e-01
[13,] 0.138102159 2.762043e-01 8.618978e-01
[14,] 0.140109905 2.802198e-01 8.598901e-01
[15,] 0.102575231 2.051505e-01 8.974248e-01
[16,] 0.073027499 1.460550e-01 9.269725e-01
[17,] 0.062631274 1.252625e-01 9.373687e-01
[18,] 0.059539637 1.190793e-01 9.404604e-01
[19,] 0.046855012 9.371002e-02 9.531450e-01
[20,] 0.032490856 6.498171e-02 9.675091e-01
[21,] 0.037747828 7.549566e-02 9.622522e-01
[22,] 0.032931710 6.586342e-02 9.670683e-01
[23,] 0.061533736 1.230675e-01 9.384663e-01
[24,] 0.071094289 1.421886e-01 9.289057e-01
[25,] 0.063755087 1.275102e-01 9.362449e-01
[26,] 0.049696851 9.939370e-02 9.503031e-01
[27,] 0.039125063 7.825013e-02 9.608749e-01
[28,] 0.033783544 6.756709e-02 9.662165e-01
[29,] 0.031311211 6.262242e-02 9.686888e-01
[30,] 0.023866855 4.773371e-02 9.761331e-01
[31,] 0.017765665 3.553133e-02 9.822343e-01
[32,] 0.016031317 3.206263e-02 9.839687e-01
[33,] 0.012360298 2.472060e-02 9.876397e-01
[34,] 0.008890141 1.778028e-02 9.911099e-01
[35,] 0.007541302 1.508260e-02 9.924587e-01
[36,] 0.006544157 1.308831e-02 9.934558e-01
[37,] 0.004499488 8.998976e-03 9.955005e-01
[38,] 0.007874980 1.574996e-02 9.921250e-01
[39,] 0.044464384 8.892877e-02 9.555356e-01
[40,] 0.037831135 7.566227e-02 9.621689e-01
[41,] 0.031030184 6.206037e-02 9.689698e-01
[42,] 0.061319361 1.226387e-01 9.386806e-01
[43,] 0.054394206 1.087884e-01 9.456058e-01
[44,] 0.045962908 9.192582e-02 9.540371e-01
[45,] 0.035875920 7.175184e-02 9.641241e-01
[46,] 0.029084754 5.816951e-02 9.709152e-01
[47,] 0.022485596 4.497119e-02 9.775144e-01
[48,] 0.016905980 3.381196e-02 9.830940e-01
[49,] 0.013218628 2.643726e-02 9.867814e-01
[50,] 0.016394562 3.278912e-02 9.836054e-01
[51,] 0.028110906 5.622181e-02 9.718891e-01
[52,] 0.022702531 4.540506e-02 9.772975e-01
[53,] 0.023620573 4.724115e-02 9.763794e-01
[54,] 0.025017949 5.003590e-02 9.749821e-01
[55,] 0.021115016 4.223003e-02 9.788850e-01
[56,] 0.022855262 4.571052e-02 9.771447e-01
[57,] 0.025812187 5.162437e-02 9.741878e-01
[58,] 0.021701693 4.340339e-02 9.782983e-01
[59,] 0.016679614 3.335923e-02 9.833204e-01
[60,] 0.013355343 2.671069e-02 9.866447e-01
[61,] 0.013392722 2.678544e-02 9.866073e-01
[62,] 0.019671350 3.934270e-02 9.803286e-01
[63,] 0.018917592 3.783518e-02 9.810824e-01
[64,] 0.016116359 3.223272e-02 9.838836e-01
[65,] 0.017617733 3.523547e-02 9.823823e-01
[66,] 0.014603831 2.920766e-02 9.853962e-01
[67,] 0.011698314 2.339663e-02 9.883017e-01
[68,] 0.009930026 1.986005e-02 9.900700e-01
[69,] 0.007686731 1.537346e-02 9.923133e-01
[70,] 0.006569159 1.313832e-02 9.934308e-01
[71,] 0.005084879 1.016976e-02 9.949151e-01
[72,] 0.003801834 7.603667e-03 9.961982e-01
[73,] 0.990771486 1.845703e-02 9.228514e-03
[74,] 0.988673950 2.265210e-02 1.132605e-02
[75,] 0.985944487 2.811103e-02 1.405551e-02
[76,] 0.982950365 3.409927e-02 1.704963e-02
[77,] 0.979911867 4.017627e-02 2.008813e-02
[78,] 0.979187540 4.162492e-02 2.081246e-02
[79,] 0.975972554 4.805489e-02 2.402745e-02
[80,] 0.974466572 5.106686e-02 2.553343e-02
[81,] 0.972162998 5.567400e-02 2.783700e-02
[82,] 0.968393717 6.321257e-02 3.160628e-02
[83,] 0.968210445 6.357911e-02 3.178956e-02
[84,] 0.964949157 7.010169e-02 3.505084e-02
[85,] 0.971275372 5.744926e-02 2.872463e-02
[86,] 0.975517267 4.896547e-02 2.448273e-02
[87,] 0.975228959 4.954208e-02 2.477104e-02
[88,] 0.970049727 5.990055e-02 2.995027e-02
[89,] 0.963713689 7.257262e-02 3.628631e-02
[90,] 0.961263069 7.747386e-02 3.873693e-02
[91,] 0.955935384 8.812923e-02 4.406462e-02
[92,] 0.965920591 6.815882e-02 3.407941e-02
[93,] 0.968574440 6.285112e-02 3.142556e-02
[94,] 0.974776539 5.044692e-02 2.522346e-02
[95,] 0.974399478 5.120104e-02 2.560052e-02
[96,] 0.969192292 6.161542e-02 3.080771e-02
[97,] 0.974574305 5.085139e-02 2.542570e-02
[98,] 0.970261420 5.947716e-02 2.973858e-02
[99,] 0.965189622 6.962076e-02 3.481038e-02
[100,] 0.959808047 8.038391e-02 4.019195e-02
[101,] 0.952345823 9.530835e-02 4.765418e-02
[102,] 0.945932984 1.081340e-01 5.406702e-02
[103,] 0.943030959 1.139381e-01 5.696904e-02
[104,] 0.934307400 1.313852e-01 6.569260e-02
[105,] 0.922772895 1.544542e-01 7.722711e-02
[106,] 0.911669484 1.766610e-01 8.833052e-02
[107,] 0.999572981 8.540371e-04 4.270186e-04
[108,] 0.999443886 1.112228e-03 5.561141e-04
[109,] 0.999317979 1.364042e-03 6.820211e-04
[110,] 0.999153627 1.692746e-03 8.463728e-04
[111,] 0.998979854 2.040292e-03 1.020146e-03
[112,] 0.999996711 6.578481e-06 3.289240e-06
[113,] 0.999997125 5.750951e-06 2.875475e-06
[114,] 0.999995867 8.266872e-06 4.133436e-06
[115,] 0.999994908 1.018344e-05 5.091718e-06
[116,] 0.999992423 1.515452e-05 7.577260e-06
[117,] 0.999989686 2.062814e-05 1.031407e-05
[118,] 0.999985169 2.966203e-05 1.483102e-05
[119,] 0.999978908 4.218491e-05 2.109245e-05
[120,] 0.999973126 5.374853e-05 2.687427e-05
[121,] 0.999961583 7.683411e-05 3.841706e-05
[122,] 0.999954767 9.046685e-05 4.523342e-05
[123,] 0.999983478 3.304385e-05 1.652192e-05
[124,] 0.999987166 2.566880e-05 1.283440e-05
[125,] 0.999981717 3.656634e-05 1.828317e-05
[126,] 0.999989582 2.083698e-05 1.041849e-05
[127,] 0.999989649 2.070231e-05 1.035115e-05
[128,] 0.999984938 3.012475e-05 1.506237e-05
[129,] 0.999979162 4.167557e-05 2.083778e-05
[130,] 0.999975595 4.880937e-05 2.440469e-05
[131,] 0.999966273 6.745349e-05 3.372675e-05
[132,] 0.999969833 6.033370e-05 3.016685e-05
[133,] 0.999973810 5.237973e-05 2.618987e-05
[134,] 0.999965945 6.810954e-05 3.405477e-05
[135,] 0.999989418 2.116321e-05 1.058160e-05
[136,] 0.999996990 6.020799e-06 3.010400e-06
[137,] 0.999995666 8.667942e-06 4.333971e-06
[138,] 0.999994053 1.189374e-05 5.946868e-06
[139,] 0.999995179 9.641351e-06 4.820675e-06
[140,] 0.999996604 6.792808e-06 3.396404e-06
[141,] 0.999995003 9.994149e-06 4.997074e-06
[142,] 0.999997662 4.675810e-06 2.337905e-06
[143,] 0.999996722 6.555333e-06 3.277667e-06
[144,] 0.999999776 4.483438e-07 2.241719e-07
[145,] 0.999999686 6.288656e-07 3.144328e-07
[146,] 0.999999518 9.638948e-07 4.819474e-07
[147,] 0.999999339 1.322958e-06 6.614791e-07
[148,] 0.999999094 1.812163e-06 9.060817e-07
[149,] 0.999998610 2.779362e-06 1.389681e-06
[150,] 0.999999999 1.538628e-09 7.693138e-10
[151,] 0.999999999 2.518688e-09 1.259344e-09
[152,] 0.999999999 2.732539e-09 1.366269e-09
[153,] 0.999999998 4.313349e-09 2.156674e-09
[154,] 0.999999999 2.581028e-09 1.290514e-09
[155,] 0.999999999 1.960353e-09 9.801766e-10
[156,] 1.000000000 5.514956e-10 2.757478e-10
[157,] 1.000000000 5.987060e-10 2.993530e-10
[158,] 1.000000000 2.010986e-10 1.005493e-10
[159,] 1.000000000 1.005103e-10 5.025515e-11
[160,] 1.000000000 1.817229e-10 9.086147e-11
[161,] 1.000000000 3.005804e-10 1.502902e-10
[162,] 1.000000000 5.023926e-10 2.511963e-10
[163,] 1.000000000 7.720045e-11 3.860023e-11
[164,] 1.000000000 1.149434e-10 5.747170e-11
[165,] 1.000000000 1.053429e-11 5.267147e-12
[166,] 1.000000000 1.939741e-11 9.698703e-12
[167,] 1.000000000 8.194882e-12 4.097441e-12
[168,] 1.000000000 1.035481e-11 5.177405e-12
[169,] 1.000000000 1.216867e-11 6.084334e-12
[170,] 1.000000000 1.545754e-12 7.728772e-13
[171,] 1.000000000 3.104010e-12 1.552005e-12
[172,] 1.000000000 6.106369e-12 3.053185e-12
[173,] 1.000000000 2.196807e-12 1.098403e-12
[174,] 1.000000000 4.411966e-12 2.205983e-12
[175,] 1.000000000 6.688187e-12 3.344093e-12
[176,] 1.000000000 1.289892e-11 6.449462e-12
[177,] 1.000000000 1.717676e-11 8.588380e-12
[178,] 1.000000000 3.214545e-11 1.607272e-11
[179,] 1.000000000 1.383026e-11 6.915132e-12
[180,] 1.000000000 2.771730e-11 1.385865e-11
[181,] 1.000000000 5.314859e-11 2.657430e-11
[182,] 1.000000000 1.051150e-10 5.255749e-11
[183,] 1.000000000 1.980732e-10 9.903661e-11
[184,] 1.000000000 3.122451e-10 1.561226e-10
[185,] 1.000000000 5.360847e-10 2.680423e-10
[186,] 1.000000000 9.873598e-11 4.936799e-11
[187,] 1.000000000 7.141709e-11 3.570855e-11
[188,] 1.000000000 1.085196e-10 5.425981e-11
[189,] 1.000000000 1.906762e-10 9.533808e-11
[190,] 1.000000000 5.083416e-11 2.541708e-11
[191,] 1.000000000 9.556592e-11 4.778296e-11
[192,] 1.000000000 1.468839e-10 7.344195e-11
[193,] 1.000000000 2.847825e-10 1.423913e-10
[194,] 1.000000000 5.544625e-10 2.772312e-10
[195,] 0.999999999 1.053359e-09 5.266796e-10
[196,] 0.999999999 1.921448e-09 9.607238e-10
[197,] 0.999999999 2.604161e-09 1.302081e-09
[198,] 0.999999999 2.379441e-09 1.189720e-09
[199,] 0.999999998 3.719156e-09 1.859578e-09
[200,] 0.999999996 7.051824e-09 3.525912e-09
[201,] 0.999999993 1.347868e-08 6.739342e-09
[202,] 0.999999988 2.461207e-08 1.230604e-08
[203,] 0.999999993 1.473244e-08 7.366219e-09
[204,] 0.999999992 1.637500e-08 8.187500e-09
[205,] 0.999999984 3.170354e-08 1.585177e-08
[206,] 0.999999981 3.809812e-08 1.904906e-08
[207,] 0.999999973 5.471096e-08 2.735548e-08
[208,] 0.999999963 7.414915e-08 3.707458e-08
[209,] 0.999999939 1.212493e-07 6.062463e-08
[210,] 0.999999899 2.021374e-07 1.010687e-07
[211,] 0.999999847 3.066866e-07 1.533433e-07
[212,] 0.999999718 5.636583e-07 2.818291e-07
[213,] 0.999999548 9.044809e-07 4.522404e-07
[214,] 0.999999555 8.909350e-07 4.454675e-07
[215,] 0.999999436 1.127622e-06 5.638109e-07
[216,] 0.999998958 2.084946e-06 1.042473e-06
[217,] 0.999999601 7.988987e-07 3.994494e-07
[218,] 0.999999985 2.985170e-08 1.492585e-08
[219,] 0.999999972 5.543262e-08 2.771631e-08
[220,] 0.999999943 1.142792e-07 5.713961e-08
[221,] 0.999999964 7.260603e-08 3.630302e-08
[222,] 0.999999932 1.358881e-07 6.794406e-08
[223,] 0.999999858 2.841625e-07 1.420812e-07
[224,] 0.999999714 5.712616e-07 2.856308e-07
[225,] 0.999999486 1.027549e-06 5.137746e-07
[226,] 0.999999041 1.918264e-06 9.591318e-07
[227,] 0.999998479 3.041519e-06 1.520760e-06
[228,] 0.999997042 5.916701e-06 2.958350e-06
[229,] 0.999994970 1.006088e-05 5.030441e-06
[230,] 0.999991177 1.764553e-05 8.822764e-06
[231,] 0.999983249 3.350223e-05 1.675111e-05
[232,] 0.999974733 5.053339e-05 2.526670e-05
[233,] 0.999954491 9.101710e-05 4.550855e-05
[234,] 0.999949029 1.019419e-04 5.097097e-05
[235,] 0.999946052 1.078966e-04 5.394828e-05
[236,] 0.999912611 1.747786e-04 8.738932e-05
[237,] 0.999858656 2.826871e-04 1.413436e-04
[238,] 0.999946357 1.072859e-04 5.364293e-05
[239,] 0.999896390 2.072202e-04 1.036101e-04
[240,] 0.999849846 3.003072e-04 1.501536e-04
[241,] 0.999717071 5.658576e-04 2.829288e-04
[242,] 0.999472786 1.054429e-03 5.272144e-04
[243,] 0.999587522 8.249569e-04 4.124785e-04
[244,] 0.999240989 1.518023e-03 7.590113e-04
[245,] 0.998612724 2.774553e-03 1.387276e-03
[246,] 0.998157152 3.685695e-03 1.842848e-03
[247,] 0.997013837 5.972326e-03 2.986163e-03
[248,] 0.995648370 8.703259e-03 4.351630e-03
[249,] 0.993248330 1.350334e-02 6.751670e-03
[250,] 0.988816436 2.236713e-02 1.118356e-02
[251,] 0.992461969 1.507606e-02 7.538031e-03
[252,] 0.987152671 2.569466e-02 1.284733e-02
[253,] 0.980970569 3.805886e-02 1.902943e-02
[254,] 0.968681020 6.263796e-02 3.131898e-02
[255,] 0.955303802 8.939240e-02 4.469620e-02
[256,] 0.955728929 8.854214e-02 4.427107e-02
[257,] 0.930067437 1.398651e-01 6.993256e-02
[258,] 0.899601602 2.007968e-01 1.003984e-01
[259,] 0.857045403 2.859092e-01 1.429546e-01
[260,] 0.824770212 3.504596e-01 1.752298e-01
[261,] 0.752549025 4.949019e-01 2.474510e-01
[262,] 0.642667679 7.146646e-01 3.573323e-01
[263,] 0.547610246 9.047795e-01 4.523898e-01
[264,] 0.383344549 7.666891e-01 6.166555e-01
> postscript(file="/var/wessaorg/rcomp/tmp/1u0o11324586272.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2l7ig1324586272.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3oo8g1324586272.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/43ta01324586272.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/54f5w1324586272.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
6911.28039 -1054.69519 8353.16470 3840.57892 -16913.88879 20007.06243
7 8 9 10 11 12
3173.10341 9437.62518 -4765.63147 29120.71162 -6147.81649 -40867.14985
13 14 15 16 17 18
-15612.15938 -2644.54265 -10218.98471 -10829.60509 -25968.11214 24912.42914
19 20 21 22 23 24
25554.13556 19609.46899 21854.41142 -12191.29734 -18526.51424 -9068.33032
25 26 27 28 29 30
6062.41807 -23357.27782 -8178.65966 -4106.28368 -28754.33433 -19376.85212
31 32 33 34 35 36
-29242.78097 -6775.12034 -8503.06976 -36402.96695 16438.98630 -24980.73727
37 38 39 40 41 42
-12103.50124 -2993.74857 -27782.84162 -471.22485 -11385.98743 -12771.55129
43 44 45 46 47 48
-10450.97084 -22564.91614 -15849.11328 -9286.34319 -10203.77490 -6133.76074
49 50 51 52 53 54
-3741.51483 5210.53265 40234.19060 -17972.81387 -12045.38640 25128.09616
55 56 57 58 59 60
-16132.94262 -20402.92624 -5188.01169 7802.84890 1498.74593 -1007.55246
61 62 63 64 65 66
-7177.72473 11205.54388 30635.59357 -11419.99339 -9735.38855 -27305.49722
67 68 69 70 71 72
11088.84895 11416.75885 19836.53781 -10328.85033 58.88186 -8822.53445
73 74 75 76 77 78
-24059.42665 31708.17854 -21833.77033 15240.83689 14419.17726 -14648.66927
79 80 81 82 83 84
-9661.59218 -17543.40644 8654.15100 -13037.03521 8077.82267 -2287.77636
85 86 87 88 89 90
142470.11982 -9381.90573 -7343.79419 -9043.61539 12151.17326 -20646.22333
91 92 93 94 95 96
-8628.85169 19779.69619 -16724.95949 5614.32473 -20827.16459 14379.87424
97 98 99 100 101 102
-28608.54100 25775.86627 -19088.17857 7369.83693 -3197.93755 -17253.83938
103 104 105 106 107 108
10186.42847 31063.28949 26468.17100 32499.76283 -18635.78140 -6448.25300
109 110 111 112 113 114
27158.06511 6663.86598 9775.50999 -9024.68155 5333.67761 -9970.85067
115 116 117 118 119 120
-18090.64437 -8952.78597 -2862.75428 -8390.63878 98283.33560 2089.95568
121 122 123 124 125 126
-13390.06556 -9449.20709 -12112.92033 82600.65684 18046.34019 -5599.64707
127 128 129 130 131 132
13317.65309 -1573.82611 10585.58086 -2819.09347 4965.33231 -12430.46948
133 134 135 136 137 138
1172.47472 -14497.19094 -18214.22042 -28880.79643 -1946.76648 29467.44106
139 140 141 142 143 144
22653.66860 -2626.64490 -9204.70988 9092.21356 -1660.30423 -22927.62830
145 146 147 148 149 150
25735.45131 1283.30030 45889.30499 36551.50867 -5942.11638 10572.55383
151 152 153 154 155 156
-23617.12252 -19844.74944 4111.64102 -22208.67772 -9275.04755 50624.90514
157 158 159 160 161 162
-14784.06538 -5527.10530 4845.20604 15548.40715 -6449.28124 77816.23488
163 164 165 166 167 168
4666.24948 25409.69143 -7605.16052 -31917.77477 -24504.05064 39119.85964
169 170 171 172 173 174
-19862.39783 32607.86497 26712.77529 -700.89086 14092.25841 -438.41150
175 176 177 178 179 180
40480.05665 -12475.55979 32173.05004 -7362.25349 10734.62373 -10995.60897
181 182 183 184 185 186
16140.58777 25840.77248 772.78383 -6000.87945 -39109.45480 -1499.12594
187 188 189 190 191 192
-7847.35711 -2686.71316 -15727.91348 9064.60117 24631.58733 -1503.75527
193 194 195 196 197 198
-7292.47996 -718.29589 -9162.56839 -7316.90609 -12156.23972 32791.76011
199 200 201 202 203 204
20468.33762 7096.43103 -10991.02754 -17862.01818 -511.68727 -1185.64186
205 206 207 208 209 210
-8509.14554 -1568.66596 -10485.99070 -5599.07880 -10220.89592 -24855.95354
211 212 213 214 215 216
-9066.11801 -1602.15344 -6394.17804 -13915.11673 18489.99148 -24238.62608
217 218 219 220 221 222
-5661.80729 12961.94587 -12018.23324 -11481.21463 -12078.25692 -5551.35276
223 224 225 226 227 228
-14180.78841 -7801.26753 -12095.28569 -8930.21233 18516.55944 -366.44522
229 230 231 232 233 234
-10063.82520 25999.60678 -13888.74019 -7269.46900 8026.41605 -4448.87662
235 236 237 238 239 240
3312.06314 -4917.50937 1653.61645 -9045.00556 -11816.91940 -6970.02329
241 242 243 244 245 246
7184.01632 -12364.77650 -9375.26556 -169.05391 -4774.33206 6286.61305
247 248 249 250 251 252
6882.92571 -1974.36617 15534.31788 15768.23411 -3699.27298 -1868.75549
253 254 255 256 257 258
-1943.27887 -3048.15872 -13973.91323 -1475.69958 2942.10877 4024.05936
259 260 261 262 263 264
-10827.68778 -4433.03922 -3312.39926 -17328.34757 -4094.43091 -8685.72662
265 266 267 268 269 270
7434.37466 -5444.68371 -14753.18220 5276.34290 -17693.96613 9272.64743
271 272 273 274 275 276
-4987.42090 -3068.82077 2989.43244 -5382.53856 -258.20322 3450.50680
277 278 279 280 281 282
21551.44953 -2022.33327 -15556.22386 -13628.49188 -6682.67532 61711.50265
283 284 285 286 287 288
14951.47248 425.04197 -6922.21966 15620.80978 -9926.58940 -12079.58717
289
-9333.11201
> postscript(file="/var/wessaorg/rcomp/tmp/6pkfn1324586272.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 6911.28039 NA
1 -1054.69519 6911.28039
2 8353.16470 -1054.69519
3 3840.57892 8353.16470
4 -16913.88879 3840.57892
5 20007.06243 -16913.88879
6 3173.10341 20007.06243
7 9437.62518 3173.10341
8 -4765.63147 9437.62518
9 29120.71162 -4765.63147
10 -6147.81649 29120.71162
11 -40867.14985 -6147.81649
12 -15612.15938 -40867.14985
13 -2644.54265 -15612.15938
14 -10218.98471 -2644.54265
15 -10829.60509 -10218.98471
16 -25968.11214 -10829.60509
17 24912.42914 -25968.11214
18 25554.13556 24912.42914
19 19609.46899 25554.13556
20 21854.41142 19609.46899
21 -12191.29734 21854.41142
22 -18526.51424 -12191.29734
23 -9068.33032 -18526.51424
24 6062.41807 -9068.33032
25 -23357.27782 6062.41807
26 -8178.65966 -23357.27782
27 -4106.28368 -8178.65966
28 -28754.33433 -4106.28368
29 -19376.85212 -28754.33433
30 -29242.78097 -19376.85212
31 -6775.12034 -29242.78097
32 -8503.06976 -6775.12034
33 -36402.96695 -8503.06976
34 16438.98630 -36402.96695
35 -24980.73727 16438.98630
36 -12103.50124 -24980.73727
37 -2993.74857 -12103.50124
38 -27782.84162 -2993.74857
39 -471.22485 -27782.84162
40 -11385.98743 -471.22485
41 -12771.55129 -11385.98743
42 -10450.97084 -12771.55129
43 -22564.91614 -10450.97084
44 -15849.11328 -22564.91614
45 -9286.34319 -15849.11328
46 -10203.77490 -9286.34319
47 -6133.76074 -10203.77490
48 -3741.51483 -6133.76074
49 5210.53265 -3741.51483
50 40234.19060 5210.53265
51 -17972.81387 40234.19060
52 -12045.38640 -17972.81387
53 25128.09616 -12045.38640
54 -16132.94262 25128.09616
55 -20402.92624 -16132.94262
56 -5188.01169 -20402.92624
57 7802.84890 -5188.01169
58 1498.74593 7802.84890
59 -1007.55246 1498.74593
60 -7177.72473 -1007.55246
61 11205.54388 -7177.72473
62 30635.59357 11205.54388
63 -11419.99339 30635.59357
64 -9735.38855 -11419.99339
65 -27305.49722 -9735.38855
66 11088.84895 -27305.49722
67 11416.75885 11088.84895
68 19836.53781 11416.75885
69 -10328.85033 19836.53781
70 58.88186 -10328.85033
71 -8822.53445 58.88186
72 -24059.42665 -8822.53445
73 31708.17854 -24059.42665
74 -21833.77033 31708.17854
75 15240.83689 -21833.77033
76 14419.17726 15240.83689
77 -14648.66927 14419.17726
78 -9661.59218 -14648.66927
79 -17543.40644 -9661.59218
80 8654.15100 -17543.40644
81 -13037.03521 8654.15100
82 8077.82267 -13037.03521
83 -2287.77636 8077.82267
84 142470.11982 -2287.77636
85 -9381.90573 142470.11982
86 -7343.79419 -9381.90573
87 -9043.61539 -7343.79419
88 12151.17326 -9043.61539
89 -20646.22333 12151.17326
90 -8628.85169 -20646.22333
91 19779.69619 -8628.85169
92 -16724.95949 19779.69619
93 5614.32473 -16724.95949
94 -20827.16459 5614.32473
95 14379.87424 -20827.16459
96 -28608.54100 14379.87424
97 25775.86627 -28608.54100
98 -19088.17857 25775.86627
99 7369.83693 -19088.17857
100 -3197.93755 7369.83693
101 -17253.83938 -3197.93755
102 10186.42847 -17253.83938
103 31063.28949 10186.42847
104 26468.17100 31063.28949
105 32499.76283 26468.17100
106 -18635.78140 32499.76283
107 -6448.25300 -18635.78140
108 27158.06511 -6448.25300
109 6663.86598 27158.06511
110 9775.50999 6663.86598
111 -9024.68155 9775.50999
112 5333.67761 -9024.68155
113 -9970.85067 5333.67761
114 -18090.64437 -9970.85067
115 -8952.78597 -18090.64437
116 -2862.75428 -8952.78597
117 -8390.63878 -2862.75428
118 98283.33560 -8390.63878
119 2089.95568 98283.33560
120 -13390.06556 2089.95568
121 -9449.20709 -13390.06556
122 -12112.92033 -9449.20709
123 82600.65684 -12112.92033
124 18046.34019 82600.65684
125 -5599.64707 18046.34019
126 13317.65309 -5599.64707
127 -1573.82611 13317.65309
128 10585.58086 -1573.82611
129 -2819.09347 10585.58086
130 4965.33231 -2819.09347
131 -12430.46948 4965.33231
132 1172.47472 -12430.46948
133 -14497.19094 1172.47472
134 -18214.22042 -14497.19094
135 -28880.79643 -18214.22042
136 -1946.76648 -28880.79643
137 29467.44106 -1946.76648
138 22653.66860 29467.44106
139 -2626.64490 22653.66860
140 -9204.70988 -2626.64490
141 9092.21356 -9204.70988
142 -1660.30423 9092.21356
143 -22927.62830 -1660.30423
144 25735.45131 -22927.62830
145 1283.30030 25735.45131
146 45889.30499 1283.30030
147 36551.50867 45889.30499
148 -5942.11638 36551.50867
149 10572.55383 -5942.11638
150 -23617.12252 10572.55383
151 -19844.74944 -23617.12252
152 4111.64102 -19844.74944
153 -22208.67772 4111.64102
154 -9275.04755 -22208.67772
155 50624.90514 -9275.04755
156 -14784.06538 50624.90514
157 -5527.10530 -14784.06538
158 4845.20604 -5527.10530
159 15548.40715 4845.20604
160 -6449.28124 15548.40715
161 77816.23488 -6449.28124
162 4666.24948 77816.23488
163 25409.69143 4666.24948
164 -7605.16052 25409.69143
165 -31917.77477 -7605.16052
166 -24504.05064 -31917.77477
167 39119.85964 -24504.05064
168 -19862.39783 39119.85964
169 32607.86497 -19862.39783
170 26712.77529 32607.86497
171 -700.89086 26712.77529
172 14092.25841 -700.89086
173 -438.41150 14092.25841
174 40480.05665 -438.41150
175 -12475.55979 40480.05665
176 32173.05004 -12475.55979
177 -7362.25349 32173.05004
178 10734.62373 -7362.25349
179 -10995.60897 10734.62373
180 16140.58777 -10995.60897
181 25840.77248 16140.58777
182 772.78383 25840.77248
183 -6000.87945 772.78383
184 -39109.45480 -6000.87945
185 -1499.12594 -39109.45480
186 -7847.35711 -1499.12594
187 -2686.71316 -7847.35711
188 -15727.91348 -2686.71316
189 9064.60117 -15727.91348
190 24631.58733 9064.60117
191 -1503.75527 24631.58733
192 -7292.47996 -1503.75527
193 -718.29589 -7292.47996
194 -9162.56839 -718.29589
195 -7316.90609 -9162.56839
196 -12156.23972 -7316.90609
197 32791.76011 -12156.23972
198 20468.33762 32791.76011
199 7096.43103 20468.33762
200 -10991.02754 7096.43103
201 -17862.01818 -10991.02754
202 -511.68727 -17862.01818
203 -1185.64186 -511.68727
204 -8509.14554 -1185.64186
205 -1568.66596 -8509.14554
206 -10485.99070 -1568.66596
207 -5599.07880 -10485.99070
208 -10220.89592 -5599.07880
209 -24855.95354 -10220.89592
210 -9066.11801 -24855.95354
211 -1602.15344 -9066.11801
212 -6394.17804 -1602.15344
213 -13915.11673 -6394.17804
214 18489.99148 -13915.11673
215 -24238.62608 18489.99148
216 -5661.80729 -24238.62608
217 12961.94587 -5661.80729
218 -12018.23324 12961.94587
219 -11481.21463 -12018.23324
220 -12078.25692 -11481.21463
221 -5551.35276 -12078.25692
222 -14180.78841 -5551.35276
223 -7801.26753 -14180.78841
224 -12095.28569 -7801.26753
225 -8930.21233 -12095.28569
226 18516.55944 -8930.21233
227 -366.44522 18516.55944
228 -10063.82520 -366.44522
229 25999.60678 -10063.82520
230 -13888.74019 25999.60678
231 -7269.46900 -13888.74019
232 8026.41605 -7269.46900
233 -4448.87662 8026.41605
234 3312.06314 -4448.87662
235 -4917.50937 3312.06314
236 1653.61645 -4917.50937
237 -9045.00556 1653.61645
238 -11816.91940 -9045.00556
239 -6970.02329 -11816.91940
240 7184.01632 -6970.02329
241 -12364.77650 7184.01632
242 -9375.26556 -12364.77650
243 -169.05391 -9375.26556
244 -4774.33206 -169.05391
245 6286.61305 -4774.33206
246 6882.92571 6286.61305
247 -1974.36617 6882.92571
248 15534.31788 -1974.36617
249 15768.23411 15534.31788
250 -3699.27298 15768.23411
251 -1868.75549 -3699.27298
252 -1943.27887 -1868.75549
253 -3048.15872 -1943.27887
254 -13973.91323 -3048.15872
255 -1475.69958 -13973.91323
256 2942.10877 -1475.69958
257 4024.05936 2942.10877
258 -10827.68778 4024.05936
259 -4433.03922 -10827.68778
260 -3312.39926 -4433.03922
261 -17328.34757 -3312.39926
262 -4094.43091 -17328.34757
263 -8685.72662 -4094.43091
264 7434.37466 -8685.72662
265 -5444.68371 7434.37466
266 -14753.18220 -5444.68371
267 5276.34290 -14753.18220
268 -17693.96613 5276.34290
269 9272.64743 -17693.96613
270 -4987.42090 9272.64743
271 -3068.82077 -4987.42090
272 2989.43244 -3068.82077
273 -5382.53856 2989.43244
274 -258.20322 -5382.53856
275 3450.50680 -258.20322
276 21551.44953 3450.50680
277 -2022.33327 21551.44953
278 -15556.22386 -2022.33327
279 -13628.49188 -15556.22386
280 -6682.67532 -13628.49188
281 61711.50265 -6682.67532
282 14951.47248 61711.50265
283 425.04197 14951.47248
284 -6922.21966 425.04197
285 15620.80978 -6922.21966
286 -9926.58940 15620.80978
287 -12079.58717 -9926.58940
288 -9333.11201 -12079.58717
289 NA -9333.11201
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1054.69519 6911.28039
[2,] 8353.16470 -1054.69519
[3,] 3840.57892 8353.16470
[4,] -16913.88879 3840.57892
[5,] 20007.06243 -16913.88879
[6,] 3173.10341 20007.06243
[7,] 9437.62518 3173.10341
[8,] -4765.63147 9437.62518
[9,] 29120.71162 -4765.63147
[10,] -6147.81649 29120.71162
[11,] -40867.14985 -6147.81649
[12,] -15612.15938 -40867.14985
[13,] -2644.54265 -15612.15938
[14,] -10218.98471 -2644.54265
[15,] -10829.60509 -10218.98471
[16,] -25968.11214 -10829.60509
[17,] 24912.42914 -25968.11214
[18,] 25554.13556 24912.42914
[19,] 19609.46899 25554.13556
[20,] 21854.41142 19609.46899
[21,] -12191.29734 21854.41142
[22,] -18526.51424 -12191.29734
[23,] -9068.33032 -18526.51424
[24,] 6062.41807 -9068.33032
[25,] -23357.27782 6062.41807
[26,] -8178.65966 -23357.27782
[27,] -4106.28368 -8178.65966
[28,] -28754.33433 -4106.28368
[29,] -19376.85212 -28754.33433
[30,] -29242.78097 -19376.85212
[31,] -6775.12034 -29242.78097
[32,] -8503.06976 -6775.12034
[33,] -36402.96695 -8503.06976
[34,] 16438.98630 -36402.96695
[35,] -24980.73727 16438.98630
[36,] -12103.50124 -24980.73727
[37,] -2993.74857 -12103.50124
[38,] -27782.84162 -2993.74857
[39,] -471.22485 -27782.84162
[40,] -11385.98743 -471.22485
[41,] -12771.55129 -11385.98743
[42,] -10450.97084 -12771.55129
[43,] -22564.91614 -10450.97084
[44,] -15849.11328 -22564.91614
[45,] -9286.34319 -15849.11328
[46,] -10203.77490 -9286.34319
[47,] -6133.76074 -10203.77490
[48,] -3741.51483 -6133.76074
[49,] 5210.53265 -3741.51483
[50,] 40234.19060 5210.53265
[51,] -17972.81387 40234.19060
[52,] -12045.38640 -17972.81387
[53,] 25128.09616 -12045.38640
[54,] -16132.94262 25128.09616
[55,] -20402.92624 -16132.94262
[56,] -5188.01169 -20402.92624
[57,] 7802.84890 -5188.01169
[58,] 1498.74593 7802.84890
[59,] -1007.55246 1498.74593
[60,] -7177.72473 -1007.55246
[61,] 11205.54388 -7177.72473
[62,] 30635.59357 11205.54388
[63,] -11419.99339 30635.59357
[64,] -9735.38855 -11419.99339
[65,] -27305.49722 -9735.38855
[66,] 11088.84895 -27305.49722
[67,] 11416.75885 11088.84895
[68,] 19836.53781 11416.75885
[69,] -10328.85033 19836.53781
[70,] 58.88186 -10328.85033
[71,] -8822.53445 58.88186
[72,] -24059.42665 -8822.53445
[73,] 31708.17854 -24059.42665
[74,] -21833.77033 31708.17854
[75,] 15240.83689 -21833.77033
[76,] 14419.17726 15240.83689
[77,] -14648.66927 14419.17726
[78,] -9661.59218 -14648.66927
[79,] -17543.40644 -9661.59218
[80,] 8654.15100 -17543.40644
[81,] -13037.03521 8654.15100
[82,] 8077.82267 -13037.03521
[83,] -2287.77636 8077.82267
[84,] 142470.11982 -2287.77636
[85,] -9381.90573 142470.11982
[86,] -7343.79419 -9381.90573
[87,] -9043.61539 -7343.79419
[88,] 12151.17326 -9043.61539
[89,] -20646.22333 12151.17326
[90,] -8628.85169 -20646.22333
[91,] 19779.69619 -8628.85169
[92,] -16724.95949 19779.69619
[93,] 5614.32473 -16724.95949
[94,] -20827.16459 5614.32473
[95,] 14379.87424 -20827.16459
[96,] -28608.54100 14379.87424
[97,] 25775.86627 -28608.54100
[98,] -19088.17857 25775.86627
[99,] 7369.83693 -19088.17857
[100,] -3197.93755 7369.83693
[101,] -17253.83938 -3197.93755
[102,] 10186.42847 -17253.83938
[103,] 31063.28949 10186.42847
[104,] 26468.17100 31063.28949
[105,] 32499.76283 26468.17100
[106,] -18635.78140 32499.76283
[107,] -6448.25300 -18635.78140
[108,] 27158.06511 -6448.25300
[109,] 6663.86598 27158.06511
[110,] 9775.50999 6663.86598
[111,] -9024.68155 9775.50999
[112,] 5333.67761 -9024.68155
[113,] -9970.85067 5333.67761
[114,] -18090.64437 -9970.85067
[115,] -8952.78597 -18090.64437
[116,] -2862.75428 -8952.78597
[117,] -8390.63878 -2862.75428
[118,] 98283.33560 -8390.63878
[119,] 2089.95568 98283.33560
[120,] -13390.06556 2089.95568
[121,] -9449.20709 -13390.06556
[122,] -12112.92033 -9449.20709
[123,] 82600.65684 -12112.92033
[124,] 18046.34019 82600.65684
[125,] -5599.64707 18046.34019
[126,] 13317.65309 -5599.64707
[127,] -1573.82611 13317.65309
[128,] 10585.58086 -1573.82611
[129,] -2819.09347 10585.58086
[130,] 4965.33231 -2819.09347
[131,] -12430.46948 4965.33231
[132,] 1172.47472 -12430.46948
[133,] -14497.19094 1172.47472
[134,] -18214.22042 -14497.19094
[135,] -28880.79643 -18214.22042
[136,] -1946.76648 -28880.79643
[137,] 29467.44106 -1946.76648
[138,] 22653.66860 29467.44106
[139,] -2626.64490 22653.66860
[140,] -9204.70988 -2626.64490
[141,] 9092.21356 -9204.70988
[142,] -1660.30423 9092.21356
[143,] -22927.62830 -1660.30423
[144,] 25735.45131 -22927.62830
[145,] 1283.30030 25735.45131
[146,] 45889.30499 1283.30030
[147,] 36551.50867 45889.30499
[148,] -5942.11638 36551.50867
[149,] 10572.55383 -5942.11638
[150,] -23617.12252 10572.55383
[151,] -19844.74944 -23617.12252
[152,] 4111.64102 -19844.74944
[153,] -22208.67772 4111.64102
[154,] -9275.04755 -22208.67772
[155,] 50624.90514 -9275.04755
[156,] -14784.06538 50624.90514
[157,] -5527.10530 -14784.06538
[158,] 4845.20604 -5527.10530
[159,] 15548.40715 4845.20604
[160,] -6449.28124 15548.40715
[161,] 77816.23488 -6449.28124
[162,] 4666.24948 77816.23488
[163,] 25409.69143 4666.24948
[164,] -7605.16052 25409.69143
[165,] -31917.77477 -7605.16052
[166,] -24504.05064 -31917.77477
[167,] 39119.85964 -24504.05064
[168,] -19862.39783 39119.85964
[169,] 32607.86497 -19862.39783
[170,] 26712.77529 32607.86497
[171,] -700.89086 26712.77529
[172,] 14092.25841 -700.89086
[173,] -438.41150 14092.25841
[174,] 40480.05665 -438.41150
[175,] -12475.55979 40480.05665
[176,] 32173.05004 -12475.55979
[177,] -7362.25349 32173.05004
[178,] 10734.62373 -7362.25349
[179,] -10995.60897 10734.62373
[180,] 16140.58777 -10995.60897
[181,] 25840.77248 16140.58777
[182,] 772.78383 25840.77248
[183,] -6000.87945 772.78383
[184,] -39109.45480 -6000.87945
[185,] -1499.12594 -39109.45480
[186,] -7847.35711 -1499.12594
[187,] -2686.71316 -7847.35711
[188,] -15727.91348 -2686.71316
[189,] 9064.60117 -15727.91348
[190,] 24631.58733 9064.60117
[191,] -1503.75527 24631.58733
[192,] -7292.47996 -1503.75527
[193,] -718.29589 -7292.47996
[194,] -9162.56839 -718.29589
[195,] -7316.90609 -9162.56839
[196,] -12156.23972 -7316.90609
[197,] 32791.76011 -12156.23972
[198,] 20468.33762 32791.76011
[199,] 7096.43103 20468.33762
[200,] -10991.02754 7096.43103
[201,] -17862.01818 -10991.02754
[202,] -511.68727 -17862.01818
[203,] -1185.64186 -511.68727
[204,] -8509.14554 -1185.64186
[205,] -1568.66596 -8509.14554
[206,] -10485.99070 -1568.66596
[207,] -5599.07880 -10485.99070
[208,] -10220.89592 -5599.07880
[209,] -24855.95354 -10220.89592
[210,] -9066.11801 -24855.95354
[211,] -1602.15344 -9066.11801
[212,] -6394.17804 -1602.15344
[213,] -13915.11673 -6394.17804
[214,] 18489.99148 -13915.11673
[215,] -24238.62608 18489.99148
[216,] -5661.80729 -24238.62608
[217,] 12961.94587 -5661.80729
[218,] -12018.23324 12961.94587
[219,] -11481.21463 -12018.23324
[220,] -12078.25692 -11481.21463
[221,] -5551.35276 -12078.25692
[222,] -14180.78841 -5551.35276
[223,] -7801.26753 -14180.78841
[224,] -12095.28569 -7801.26753
[225,] -8930.21233 -12095.28569
[226,] 18516.55944 -8930.21233
[227,] -366.44522 18516.55944
[228,] -10063.82520 -366.44522
[229,] 25999.60678 -10063.82520
[230,] -13888.74019 25999.60678
[231,] -7269.46900 -13888.74019
[232,] 8026.41605 -7269.46900
[233,] -4448.87662 8026.41605
[234,] 3312.06314 -4448.87662
[235,] -4917.50937 3312.06314
[236,] 1653.61645 -4917.50937
[237,] -9045.00556 1653.61645
[238,] -11816.91940 -9045.00556
[239,] -6970.02329 -11816.91940
[240,] 7184.01632 -6970.02329
[241,] -12364.77650 7184.01632
[242,] -9375.26556 -12364.77650
[243,] -169.05391 -9375.26556
[244,] -4774.33206 -169.05391
[245,] 6286.61305 -4774.33206
[246,] 6882.92571 6286.61305
[247,] -1974.36617 6882.92571
[248,] 15534.31788 -1974.36617
[249,] 15768.23411 15534.31788
[250,] -3699.27298 15768.23411
[251,] -1868.75549 -3699.27298
[252,] -1943.27887 -1868.75549
[253,] -3048.15872 -1943.27887
[254,] -13973.91323 -3048.15872
[255,] -1475.69958 -13973.91323
[256,] 2942.10877 -1475.69958
[257,] 4024.05936 2942.10877
[258,] -10827.68778 4024.05936
[259,] -4433.03922 -10827.68778
[260,] -3312.39926 -4433.03922
[261,] -17328.34757 -3312.39926
[262,] -4094.43091 -17328.34757
[263,] -8685.72662 -4094.43091
[264,] 7434.37466 -8685.72662
[265,] -5444.68371 7434.37466
[266,] -14753.18220 -5444.68371
[267,] 5276.34290 -14753.18220
[268,] -17693.96613 5276.34290
[269,] 9272.64743 -17693.96613
[270,] -4987.42090 9272.64743
[271,] -3068.82077 -4987.42090
[272,] 2989.43244 -3068.82077
[273,] -5382.53856 2989.43244
[274,] -258.20322 -5382.53856
[275,] 3450.50680 -258.20322
[276,] 21551.44953 3450.50680
[277,] -2022.33327 21551.44953
[278,] -15556.22386 -2022.33327
[279,] -13628.49188 -15556.22386
[280,] -6682.67532 -13628.49188
[281,] 61711.50265 -6682.67532
[282,] 14951.47248 61711.50265
[283,] 425.04197 14951.47248
[284,] -6922.21966 425.04197
[285,] 15620.80978 -6922.21966
[286,] -9926.58940 15620.80978
[287,] -12079.58717 -9926.58940
[288,] -9333.11201 -12079.58717
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1054.69519 6911.28039
2 8353.16470 -1054.69519
3 3840.57892 8353.16470
4 -16913.88879 3840.57892
5 20007.06243 -16913.88879
6 3173.10341 20007.06243
7 9437.62518 3173.10341
8 -4765.63147 9437.62518
9 29120.71162 -4765.63147
10 -6147.81649 29120.71162
11 -40867.14985 -6147.81649
12 -15612.15938 -40867.14985
13 -2644.54265 -15612.15938
14 -10218.98471 -2644.54265
15 -10829.60509 -10218.98471
16 -25968.11214 -10829.60509
17 24912.42914 -25968.11214
18 25554.13556 24912.42914
19 19609.46899 25554.13556
20 21854.41142 19609.46899
21 -12191.29734 21854.41142
22 -18526.51424 -12191.29734
23 -9068.33032 -18526.51424
24 6062.41807 -9068.33032
25 -23357.27782 6062.41807
26 -8178.65966 -23357.27782
27 -4106.28368 -8178.65966
28 -28754.33433 -4106.28368
29 -19376.85212 -28754.33433
30 -29242.78097 -19376.85212
31 -6775.12034 -29242.78097
32 -8503.06976 -6775.12034
33 -36402.96695 -8503.06976
34 16438.98630 -36402.96695
35 -24980.73727 16438.98630
36 -12103.50124 -24980.73727
37 -2993.74857 -12103.50124
38 -27782.84162 -2993.74857
39 -471.22485 -27782.84162
40 -11385.98743 -471.22485
41 -12771.55129 -11385.98743
42 -10450.97084 -12771.55129
43 -22564.91614 -10450.97084
44 -15849.11328 -22564.91614
45 -9286.34319 -15849.11328
46 -10203.77490 -9286.34319
47 -6133.76074 -10203.77490
48 -3741.51483 -6133.76074
49 5210.53265 -3741.51483
50 40234.19060 5210.53265
51 -17972.81387 40234.19060
52 -12045.38640 -17972.81387
53 25128.09616 -12045.38640
54 -16132.94262 25128.09616
55 -20402.92624 -16132.94262
56 -5188.01169 -20402.92624
57 7802.84890 -5188.01169
58 1498.74593 7802.84890
59 -1007.55246 1498.74593
60 -7177.72473 -1007.55246
61 11205.54388 -7177.72473
62 30635.59357 11205.54388
63 -11419.99339 30635.59357
64 -9735.38855 -11419.99339
65 -27305.49722 -9735.38855
66 11088.84895 -27305.49722
67 11416.75885 11088.84895
68 19836.53781 11416.75885
69 -10328.85033 19836.53781
70 58.88186 -10328.85033
71 -8822.53445 58.88186
72 -24059.42665 -8822.53445
73 31708.17854 -24059.42665
74 -21833.77033 31708.17854
75 15240.83689 -21833.77033
76 14419.17726 15240.83689
77 -14648.66927 14419.17726
78 -9661.59218 -14648.66927
79 -17543.40644 -9661.59218
80 8654.15100 -17543.40644
81 -13037.03521 8654.15100
82 8077.82267 -13037.03521
83 -2287.77636 8077.82267
84 142470.11982 -2287.77636
85 -9381.90573 142470.11982
86 -7343.79419 -9381.90573
87 -9043.61539 -7343.79419
88 12151.17326 -9043.61539
89 -20646.22333 12151.17326
90 -8628.85169 -20646.22333
91 19779.69619 -8628.85169
92 -16724.95949 19779.69619
93 5614.32473 -16724.95949
94 -20827.16459 5614.32473
95 14379.87424 -20827.16459
96 -28608.54100 14379.87424
97 25775.86627 -28608.54100
98 -19088.17857 25775.86627
99 7369.83693 -19088.17857
100 -3197.93755 7369.83693
101 -17253.83938 -3197.93755
102 10186.42847 -17253.83938
103 31063.28949 10186.42847
104 26468.17100 31063.28949
105 32499.76283 26468.17100
106 -18635.78140 32499.76283
107 -6448.25300 -18635.78140
108 27158.06511 -6448.25300
109 6663.86598 27158.06511
110 9775.50999 6663.86598
111 -9024.68155 9775.50999
112 5333.67761 -9024.68155
113 -9970.85067 5333.67761
114 -18090.64437 -9970.85067
115 -8952.78597 -18090.64437
116 -2862.75428 -8952.78597
117 -8390.63878 -2862.75428
118 98283.33560 -8390.63878
119 2089.95568 98283.33560
120 -13390.06556 2089.95568
121 -9449.20709 -13390.06556
122 -12112.92033 -9449.20709
123 82600.65684 -12112.92033
124 18046.34019 82600.65684
125 -5599.64707 18046.34019
126 13317.65309 -5599.64707
127 -1573.82611 13317.65309
128 10585.58086 -1573.82611
129 -2819.09347 10585.58086
130 4965.33231 -2819.09347
131 -12430.46948 4965.33231
132 1172.47472 -12430.46948
133 -14497.19094 1172.47472
134 -18214.22042 -14497.19094
135 -28880.79643 -18214.22042
136 -1946.76648 -28880.79643
137 29467.44106 -1946.76648
138 22653.66860 29467.44106
139 -2626.64490 22653.66860
140 -9204.70988 -2626.64490
141 9092.21356 -9204.70988
142 -1660.30423 9092.21356
143 -22927.62830 -1660.30423
144 25735.45131 -22927.62830
145 1283.30030 25735.45131
146 45889.30499 1283.30030
147 36551.50867 45889.30499
148 -5942.11638 36551.50867
149 10572.55383 -5942.11638
150 -23617.12252 10572.55383
151 -19844.74944 -23617.12252
152 4111.64102 -19844.74944
153 -22208.67772 4111.64102
154 -9275.04755 -22208.67772
155 50624.90514 -9275.04755
156 -14784.06538 50624.90514
157 -5527.10530 -14784.06538
158 4845.20604 -5527.10530
159 15548.40715 4845.20604
160 -6449.28124 15548.40715
161 77816.23488 -6449.28124
162 4666.24948 77816.23488
163 25409.69143 4666.24948
164 -7605.16052 25409.69143
165 -31917.77477 -7605.16052
166 -24504.05064 -31917.77477
167 39119.85964 -24504.05064
168 -19862.39783 39119.85964
169 32607.86497 -19862.39783
170 26712.77529 32607.86497
171 -700.89086 26712.77529
172 14092.25841 -700.89086
173 -438.41150 14092.25841
174 40480.05665 -438.41150
175 -12475.55979 40480.05665
176 32173.05004 -12475.55979
177 -7362.25349 32173.05004
178 10734.62373 -7362.25349
179 -10995.60897 10734.62373
180 16140.58777 -10995.60897
181 25840.77248 16140.58777
182 772.78383 25840.77248
183 -6000.87945 772.78383
184 -39109.45480 -6000.87945
185 -1499.12594 -39109.45480
186 -7847.35711 -1499.12594
187 -2686.71316 -7847.35711
188 -15727.91348 -2686.71316
189 9064.60117 -15727.91348
190 24631.58733 9064.60117
191 -1503.75527 24631.58733
192 -7292.47996 -1503.75527
193 -718.29589 -7292.47996
194 -9162.56839 -718.29589
195 -7316.90609 -9162.56839
196 -12156.23972 -7316.90609
197 32791.76011 -12156.23972
198 20468.33762 32791.76011
199 7096.43103 20468.33762
200 -10991.02754 7096.43103
201 -17862.01818 -10991.02754
202 -511.68727 -17862.01818
203 -1185.64186 -511.68727
204 -8509.14554 -1185.64186
205 -1568.66596 -8509.14554
206 -10485.99070 -1568.66596
207 -5599.07880 -10485.99070
208 -10220.89592 -5599.07880
209 -24855.95354 -10220.89592
210 -9066.11801 -24855.95354
211 -1602.15344 -9066.11801
212 -6394.17804 -1602.15344
213 -13915.11673 -6394.17804
214 18489.99148 -13915.11673
215 -24238.62608 18489.99148
216 -5661.80729 -24238.62608
217 12961.94587 -5661.80729
218 -12018.23324 12961.94587
219 -11481.21463 -12018.23324
220 -12078.25692 -11481.21463
221 -5551.35276 -12078.25692
222 -14180.78841 -5551.35276
223 -7801.26753 -14180.78841
224 -12095.28569 -7801.26753
225 -8930.21233 -12095.28569
226 18516.55944 -8930.21233
227 -366.44522 18516.55944
228 -10063.82520 -366.44522
229 25999.60678 -10063.82520
230 -13888.74019 25999.60678
231 -7269.46900 -13888.74019
232 8026.41605 -7269.46900
233 -4448.87662 8026.41605
234 3312.06314 -4448.87662
235 -4917.50937 3312.06314
236 1653.61645 -4917.50937
237 -9045.00556 1653.61645
238 -11816.91940 -9045.00556
239 -6970.02329 -11816.91940
240 7184.01632 -6970.02329
241 -12364.77650 7184.01632
242 -9375.26556 -12364.77650
243 -169.05391 -9375.26556
244 -4774.33206 -169.05391
245 6286.61305 -4774.33206
246 6882.92571 6286.61305
247 -1974.36617 6882.92571
248 15534.31788 -1974.36617
249 15768.23411 15534.31788
250 -3699.27298 15768.23411
251 -1868.75549 -3699.27298
252 -1943.27887 -1868.75549
253 -3048.15872 -1943.27887
254 -13973.91323 -3048.15872
255 -1475.69958 -13973.91323
256 2942.10877 -1475.69958
257 4024.05936 2942.10877
258 -10827.68778 4024.05936
259 -4433.03922 -10827.68778
260 -3312.39926 -4433.03922
261 -17328.34757 -3312.39926
262 -4094.43091 -17328.34757
263 -8685.72662 -4094.43091
264 7434.37466 -8685.72662
265 -5444.68371 7434.37466
266 -14753.18220 -5444.68371
267 5276.34290 -14753.18220
268 -17693.96613 5276.34290
269 9272.64743 -17693.96613
270 -4987.42090 9272.64743
271 -3068.82077 -4987.42090
272 2989.43244 -3068.82077
273 -5382.53856 2989.43244
274 -258.20322 -5382.53856
275 3450.50680 -258.20322
276 21551.44953 3450.50680
277 -2022.33327 21551.44953
278 -15556.22386 -2022.33327
279 -13628.49188 -15556.22386
280 -6682.67532 -13628.49188
281 61711.50265 -6682.67532
282 14951.47248 61711.50265
283 425.04197 14951.47248
284 -6922.21966 425.04197
285 15620.80978 -6922.21966
286 -9926.58940 15620.80978
287 -12079.58717 -9926.58940
288 -9333.11201 -12079.58717
> 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/wessaorg/rcomp/tmp/7y3qq1324586272.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8i5vc1324586272.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/95ker1324586272.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10rw7f1324586272.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/11lgwo1324586272.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/wessaorg/rcomp/tmp/12a7pe1324586272.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/wessaorg/rcomp/tmp/13nubd1324586272.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/wessaorg/rcomp/tmp/14fr0d1324586272.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/wessaorg/rcomp/tmp/15uq3c1324586272.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/wessaorg/rcomp/tmp/16wyp21324586272.tab")
+ }
>
> try(system("convert tmp/1u0o11324586272.ps tmp/1u0o11324586272.png",intern=TRUE))
character(0)
> try(system("convert tmp/2l7ig1324586272.ps tmp/2l7ig1324586272.png",intern=TRUE))
character(0)
> try(system("convert tmp/3oo8g1324586272.ps tmp/3oo8g1324586272.png",intern=TRUE))
character(0)
> try(system("convert tmp/43ta01324586272.ps tmp/43ta01324586272.png",intern=TRUE))
character(0)
> try(system("convert tmp/54f5w1324586272.ps tmp/54f5w1324586272.png",intern=TRUE))
character(0)
> try(system("convert tmp/6pkfn1324586272.ps tmp/6pkfn1324586272.png",intern=TRUE))
character(0)
> try(system("convert tmp/7y3qq1324586272.ps tmp/7y3qq1324586272.png",intern=TRUE))
character(0)
> try(system("convert tmp/8i5vc1324586272.ps tmp/8i5vc1324586272.png",intern=TRUE))
character(0)
> try(system("convert tmp/95ker1324586272.ps tmp/95ker1324586272.png",intern=TRUE))
character(0)
> try(system("convert tmp/10rw7f1324586272.ps tmp/10rw7f1324586272.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
9.664 0.628 10.311