R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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> x <- array(list(210907
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+ ,16
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+ ,1
+ ,8
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+ ,27
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+ ,0
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+ ,50857
+ ,21
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+ ,0
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+ ,71
+ ,37
+ ,56613
+ ,19
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+ ,37
+ ,1
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+ ,62792
+ ,35
+ ,176
+ ,46
+ ,0
+ ,28
+ ,60
+ ,51
+ ,72535
+ ,14
+ ,329
+ ,44
+ ,0
+ ,17
+ ,64
+ ,39)
+ ,dim=c(8
+ ,289)
+ ,dimnames=list(c('time_in_rfc'
+ ,'logins'
+ ,'compendium_views_info'
+ ,'compendium_views_pr'
+ ,'shared_compendiums'
+ ,'blogged_computations'
+ ,'feedback_messages_p1'
+ ,'feedback_messages_p120')
+ ,1:289))
> y <- array(NA,dim=c(8,289),dimnames=list(c('time_in_rfc','logins','compendium_views_info','compendium_views_pr','shared_compendiums','blogged_computations','feedback_messages_p1','feedback_messages_p120'),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'
> 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
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
time_in_rfc logins compendium_views_info compendium_views_pr
1 210907 56 396 81
2 120982 56 297 55
3 176508 54 559 50
4 179321 89 967 125
5 123185 40 270 40
6 52746 25 143 37
7 385534 92 1562 63
8 33170 18 109 44
9 101645 63 371 88
10 149061 44 656 66
11 165446 33 511 57
12 237213 84 655 74
13 173326 88 465 49
14 133131 55 525 52
15 258873 60 885 88
16 180083 66 497 36
17 324799 154 1436 108
18 230964 53 612 43
19 236785 119 865 75
20 135473 41 385 32
21 202925 61 567 44
22 215147 58 639 85
23 344297 75 963 86
24 153935 33 398 56
25 132943 40 410 50
26 174724 92 966 135
27 174415 100 801 63
28 225548 112 892 81
29 223632 73 513 52
30 124817 40 469 44
31 221698 45 683 113
32 210767 60 643 39
33 170266 62 535 73
34 260561 75 625 48
35 84853 31 264 33
36 294424 77 992 59
37 101011 34 238 41
38 215641 46 818 69
39 325107 99 937 64
40 7176 17 70 1
41 167542 66 507 59
42 106408 30 260 32
43 96560 76 503 129
44 265769 146 927 37
45 269651 67 1269 31
46 149112 56 537 65
47 175824 107 910 107
48 152871 58 532 74
49 111665 34 345 54
50 116408 61 918 76
51 362301 119 1635 715
52 78800 42 330 57
53 183167 66 557 66
54 277965 89 1178 106
55 150629 44 740 54
56 168809 66 452 32
57 24188 24 218 20
58 329267 259 764 71
59 65029 17 255 21
60 101097 64 454 70
61 218946 41 866 112
62 244052 68 574 66
63 341570 168 1276 190
64 103597 43 379 66
65 233328 132 825 165
66 256462 105 798 56
67 206161 71 663 61
68 311473 112 1069 53
69 235800 94 921 127
70 177939 82 858 63
71 207176 70 711 38
72 196553 57 503 50
73 174184 53 382 52
74 143246 103 464 42
75 187559 121 717 76
76 187681 62 690 67
77 119016 52 462 50
78 182192 52 657 53
79 73566 32 385 39
80 194979 62 577 50
81 167488 45 619 77
82 143756 46 479 57
83 275541 63 817 73
84 243199 75 752 34
85 182999 88 430 39
86 135649 46 451 46
87 152299 53 537 63
88 120221 37 519 35
89 346485 90 1000 106
90 145790 63 637 43
91 193339 78 465 47
92 80953 25 437 31
93 122774 45 711 162
94 130585 46 299 57
95 112611 41 248 36
96 286468 144 1162 263
97 241066 82 714 78
98 148446 91 905 63
99 204713 71 649 54
100 182079 63 512 63
101 140344 53 472 77
102 220516 62 905 79
103 243060 63 786 110
104 162765 32 489 56
105 182613 39 479 56
106 232138 62 617 43
107 265318 117 925 111
108 85574 34 351 71
109 310839 92 1144 62
110 225060 93 669 56
111 232317 54 707 74
112 144966 144 458 60
113 43287 14 214 43
114 155754 61 599 68
115 164709 109 572 53
116 201940 38 897 87
117 235454 73 819 46
118 220801 75 720 105
119 99466 50 273 32
120 92661 61 508 133
121 133328 55 506 79
122 61361 77 451 51
123 125930 75 699 207
124 100750 72 407 67
125 224549 50 465 47
126 82316 32 245 34
127 102010 53 370 66
128 101523 42 316 76
129 243511 71 603 65
130 22938 10 154 9
131 41566 35 229 42
132 152474 65 577 45
133 61857 25 192 25
134 99923 66 617 115
135 132487 41 411 97
136 317394 86 975 53
137 21054 16 146 2
138 209641 42 705 52
139 22648 19 184 44
140 31414 19 200 22
141 46698 45 274 35
142 131698 65 502 74
143 91735 35 382 103
144 244749 95 964 144
145 184510 49 537 60
146 79863 37 438 134
147 128423 64 369 89
148 97839 38 417 42
149 38214 34 276 52
150 151101 32 514 98
151 272458 65 822 99
152 172494 52 389 52
153 108043 62 466 29
154 328107 65 1255 125
155 250579 83 694 106
156 351067 95 1024 95
157 158015 29 400 40
158 98866 18 397 140
159 85439 33 350 43
160 229242 247 719 128
161 351619 139 1277 142
162 84207 29 356 73
163 120445 118 457 72
164 324598 110 1402 128
165 131069 67 600 61
166 204271 42 480 73
167 165543 65 595 148
168 141722 94 436 64
169 116048 64 230 45
170 250047 81 651 58
171 299775 95 1367 97
172 195838 67 564 50
173 173260 63 716 37
174 254488 83 747 50
175 104389 45 467 105
176 136084 30 671 69
177 199476 70 861 46
178 92499 32 319 57
179 224330 83 612 52
180 135781 31 433 98
181 74408 67 434 61
182 81240 66 503 89
183 14688 10 85 0
184 181633 70 564 48
185 271856 103 824 91
186 7199 5 74 0
187 46660 20 259 7
188 17547 5 69 3
189 133368 36 535 54
190 95227 34 239 70
191 152601 48 438 36
192 98146 40 459 37
193 79619 43 426 123
194 59194 31 288 247
195 139942 42 498 46
196 118612 46 454 72
197 72880 33 376 41
198 65475 18 225 24
199 99643 55 555 45
200 71965 35 252 33
201 77272 59 208 27
202 49289 19 130 36
203 135131 66 481 87
204 108446 60 389 90
205 89746 36 565 114
206 44296 25 173 31
207 77648 47 278 45
208 181528 54 609 69
209 134019 53 422 51
210 124064 40 445 34
211 92630 40 387 60
212 121848 39 339 45
213 52915 14 181 54
214 81872 45 245 25
215 58981 36 384 38
216 53515 28 212 52
217 60812 44 399 67
218 56375 30 229 74
219 65490 22 224 38
220 80949 17 203 30
221 76302 31 333 26
222 104011 55 384 67
223 98104 54 636 132
224 67989 21 185 42
225 30989 14 93 35
226 135458 81 581 118
227 73504 35 248 68
228 63123 43 304 43
229 61254 46 344 76
230 74914 30 407 64
231 31774 23 170 48
232 81437 38 312 64
233 87186 54 507 56
234 50090 20 224 71
235 65745 53 340 75
236 56653 45 168 39
237 158399 39 443 42
238 46455 20 204 39
239 73624 24 367 93
240 38395 31 210 38
241 91899 35 335 60
242 139526 151 364 71
243 52164 52 178 52
244 51567 30 206 27
245 70551 31 279 59
246 84856 29 387 40
247 102538 57 490 79
248 86678 40 238 44
249 85709 44 343 65
250 34662 25 232 10
251 150580 77 530 124
252 99611 35 291 81
253 19349 11 67 15
254 99373 63 397 92
255 86230 44 467 42
256 30837 19 178 10
257 31706 13 175 24
258 89806 42 299 64
259 62088 38 154 45
260 40151 29 106 22
261 27634 20 189 56
262 76990 27 194 94
263 37460 20 135 19
264 54157 19 201 35
265 49862 37 207 32
266 84337 26 280 35
267 64175 42 260 48
268 59382 49 227 49
269 119308 30 239 48
270 76702 49 333 62
271 103425 67 428 96
272 70344 28 230 45
273 43410 19 292 63
274 104838 49 350 71
275 62215 27 186 26
276 69304 30 326 48
277 53117 22 155 29
278 19764 12 75 19
279 86680 31 361 45
280 84105 20 261 45
281 77945 20 299 67
282 89113 39 300 30
283 91005 29 450 36
284 40248 16 183 34
285 64187 27 238 36
286 50857 21 165 34
287 56613 19 234 37
288 62792 35 176 46
289 72535 14 329 44
shared_compendiums blogged_computations feedback_messages_p1
1 3 79 115
2 4 58 109
3 12 60 146
4 2 108 116
5 1 49 68
6 3 0 101
7 0 121 96
8 0 1 67
9 0 20 44
10 5 43 100
11 0 69 93
12 0 78 140
13 7 86 166
14 7 44 99
15 3 104 139
16 9 63 130
17 0 158 181
18 4 102 116
19 3 77 116
20 0 82 88
21 7 115 139
22 0 101 135
23 1 80 108
24 5 50 89
25 7 83 156
26 0 123 129
27 0 73 118
28 5 81 118
29 0 105 125
30 0 47 95
31 0 105 126
32 3 94 135
33 4 44 154
34 1 114 165
35 4 38 113
36 2 107 127
37 0 30 52
38 0 71 121
39 0 84 136
40 0 0 0
41 2 59 108
42 1 33 46
43 0 42 54
44 2 96 124
45 10 106 115
46 6 56 128
47 0 57 80
48 5 59 97
49 4 39 104
50 1 34 59
51 2 76 125
52 2 20 82
53 0 91 149
54 8 115 149
55 3 85 122
56 0 76 118
57 0 8 12
58 8 79 144
59 5 21 67
60 3 30 52
61 1 76 108
62 5 101 166
63 1 94 80
64 1 27 60
65 5 92 107
66 0 123 127
67 12 75 107
68 8 128 146
69 8 105 84
70 8 55 141
71 8 56 123
72 2 41 111
73 0 72 98
74 5 67 105
75 8 75 135
76 2 114 107
77 5 118 85
78 12 77 155
79 6 22 88
80 7 66 155
81 2 69 104
82 0 105 132
83 4 116 127
84 3 88 108
85 6 73 129
86 2 99 116
87 0 62 122
88 1 53 85
89 0 118 147
90 5 30 99
91 2 100 87
92 0 49 28
93 0 24 90
94 5 67 109
95 0 46 78
96 1 57 111
97 0 75 158
98 1 135 141
99 1 68 122
100 2 124 124
101 6 33 93
102 1 98 124
103 4 58 112
104 2 68 108
105 3 81 99
106 0 131 117
107 10 110 199
108 0 37 78
109 9 130 91
110 7 93 158
111 0 118 126
112 0 39 122
113 4 13 71
114 4 74 75
115 0 81 115
116 0 109 119
117 0 151 124
118 1 51 72
119 0 28 91
120 1 40 45
121 0 56 78
122 0 27 39
123 4 37 68
124 0 83 119
125 4 54 117
126 4 27 39
127 3 28 50
128 0 59 88
129 0 133 155
130 0 12 0
131 5 0 36
132 0 106 123
133 4 23 32
134 0 44 99
135 0 71 136
136 1 116 117
137 0 4 0
138 5 62 88
139 0 12 39
140 0 18 25
141 0 14 52
142 0 60 75
143 0 7 71
144 2 98 124
145 7 64 151
146 1 29 71
147 8 32 145
148 2 25 87
149 0 16 27
150 2 48 131
151 0 100 162
152 0 46 165
153 1 45 54
154 3 129 159
155 0 130 147
156 3 136 170
157 0 59 119
158 0 25 49
159 0 32 104
160 4 63 120
161 4 95 150
162 11 14 112
163 0 36 59
164 0 113 136
165 4 47 107
166 0 92 130
167 1 70 115
168 0 19 107
169 0 50 75
170 0 41 71
171 9 91 120
172 1 111 116
173 3 41 79
174 10 120 150
175 5 135 156
176 0 27 51
177 2 87 118
178 0 25 71
179 1 131 144
180 2 45 47
181 4 29 28
182 0 58 68
183 0 4 0
184 2 47 110
185 1 109 147
186 0 7 0
187 0 12 15
188 0 0 4
189 1 37 64
190 0 37 111
191 2 46 85
192 0 15 68
193 3 42 40
194 6 7 80
195 0 54 88
196 2 54 48
197 0 14 76
198 2 16 51
199 1 33 67
200 1 32 59
201 2 21 61
202 1 15 76
203 0 38 60
204 1 22 68
205 3 28 71
206 0 10 76
207 0 31 62
208 0 32 61
209 0 32 67
210 1 43 88
211 4 27 30
212 0 37 64
213 0 20 68
214 0 32 64
215 7 0 91
216 2 5 88
217 0 26 52
218 7 10 49
219 3 27 62
220 0 11 61
221 0 29 76
222 6 25 88
223 2 55 66
224 0 23 71
225 0 5 68
226 3 43 48
227 0 23 25
228 1 34 68
229 1 36 41
230 0 35 90
231 1 0 66
232 0 37 54
233 0 28 59
234 0 16 60
235 0 26 77
236 0 38 68
237 0 23 72
238 0 22 67
239 0 30 64
240 0 16 63
241 0 18 59
242 0 28 84
243 0 32 64
244 2 21 56
245 0 23 54
246 1 29 67
247 1 50 58
248 0 12 59
249 0 21 40
250 0 18 22
251 0 27 83
252 0 41 81
253 0 13 2
254 1 12 72
255 0 21 61
256 0 8 15
257 0 26 32
258 0 27 62
259 1 13 58
260 0 16 36
261 0 2 59
262 0 42 68
263 0 5 21
264 0 37 55
265 0 17 54
266 0 38 55
267 0 37 72
268 0 29 41
269 0 32 61
270 0 35 67
271 1 17 76
272 0 20 64
273 0 7 3
274 1 46 63
275 0 24 40
276 6 40 69
277 3 3 48
278 1 10 8
279 2 37 52
280 0 17 66
281 0 28 76
282 0 19 43
283 3 29 39
284 1 8 14
285 0 10 61
286 0 15 71
287 1 15 44
288 0 28 60
289 0 17 64
feedback_messages_p120
1 94
2 103
3 93
4 103
5 51
6 70
7 91
8 22
9 38
10 93
11 60
12 123
13 148
14 90
15 124
16 70
17 168
18 115
19 71
20 66
21 134
22 117
23 108
24 84
25 156
26 120
27 114
28 94
29 120
30 81
31 110
32 133
33 122
34 158
35 109
36 124
37 39
38 92
39 126
40 0
41 70
42 37
43 38
44 120
45 93
46 95
47 77
48 90
49 80
50 31
51 110
52 66
53 138
54 133
55 113
56 100
57 7
58 140
59 61
60 41
61 96
62 164
63 78
64 49
65 102
66 124
67 99
68 129
69 62
70 73
71 114
72 99
73 70
74 104
75 116
76 91
77 74
78 138
79 67
80 151
81 72
82 120
83 115
84 105
85 104
86 108
87 98
88 69
89 111
90 99
91 71
92 27
93 69
94 107
95 73
96 107
97 93
98 129
99 69
100 118
101 73
102 119
103 104
104 107
105 99
106 90
107 197
108 36
109 85
110 139
111 106
112 50
113 64
114 31
115 63
116 92
117 106
118 63
119 69
120 41
121 56
122 25
123 65
124 93
125 114
126 38
127 44
128 87
129 110
130 0
131 27
132 83
133 30
134 80
135 98
136 82
137 0
138 60
139 28
140 9
141 33
142 59
143 49
144 115
145 140
146 49
147 120
148 66
149 21
150 124
151 152
152 139
153 38
154 144
155 120
156 160
157 114
158 39
159 78
160 119
161 141
162 101
163 56
164 133
165 83
166 116
167 90
168 36
169 50
170 61
171 97
172 98
173 78
174 117
175 148
176 41
177 105
178 55
179 132
180 44
181 21
182 50
183 0
184 73
185 86
186 0
187 13
188 4
189 57
190 48
191 46
192 48
193 32
194 68
195 87
196 43
197 67
198 46
199 46
200 56
201 48
202 44
203 60
204 65
205 55
206 38
207 52
208 60
209 54
210 86
211 24
212 52
213 49
214 61
215 61
216 81
217 43
218 40
219 40
220 56
221 68
222 79
223 47
224 57
225 41
226 29
227 3
228 60
229 30
230 79
231 47
232 40
233 48
234 36
235 42
236 49
237 57
238 12
239 40
240 43
241 33
242 77
243 43
244 45
245 47
246 43
247 45
248 50
249 35
250 7
251 71
252 67
253 0
254 62
255 54
256 4
257 25
258 40
259 38
260 19
261 17
262 67
263 14
264 30
265 54
266 35
267 59
268 24
269 58
270 42
271 46
272 61
273 3
274 52
275 25
276 40
277 32
278 4
279 49
280 63
281 67
282 32
283 23
284 7
285 54
286 37
287 35
288 51
289 39
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) logins compendium_views_info
-10754.13 312.12 156.73
compendium_views_pr shared_compendiums blogged_computations
-68.43 -795.63 413.21
feedback_messages_p1 feedback_messages_p120
228.95 258.05
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-127288 -14988 676 14184 101742
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -10754.13 4378.04 -2.456 0.0146 *
logins 312.12 69.02 4.522 9.04e-06 ***
compendium_views_info 156.73 11.32 13.844 < 2e-16 ***
compendium_views_pr -68.43 38.62 -1.772 0.0775 .
shared_compendiums -795.63 675.46 -1.178 0.2398
blogged_computations 413.21 88.47 4.671 4.65e-06 ***
feedback_messages_p1 228.95 122.70 1.866 0.0631 .
feedback_messages_p120 258.05 128.63 2.006 0.0458 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 27950 on 281 degrees of freedom
Multiple R-squared: 0.8876, Adjusted R-squared: 0.8848
F-statistic: 317 on 7 and 281 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,] 0.9684503 6.309934e-02 3.154967e-02
[2,] 0.9503049 9.939020e-02 4.969510e-02
[3,] 0.9664604 6.707925e-02 3.353963e-02
[4,] 0.9416166 1.167667e-01 5.838336e-02
[5,] 0.9163108 1.673784e-01 8.368918e-02
[6,] 0.8744901 2.510197e-01 1.255099e-01
[7,] 0.9141479 1.717043e-01 8.585213e-02
[8,] 0.8820347 2.359306e-01 1.179653e-01
[9,] 0.8639932 2.720135e-01 1.360068e-01
[10,] 0.9163955 1.672089e-01 8.360445e-02
[11,] 0.8940414 2.119172e-01 1.059586e-01
[12,] 0.8622295 2.755410e-01 1.377705e-01
[13,] 0.9972664 5.467129e-03 2.733564e-03
[14,] 0.9961074 7.785261e-03 3.892631e-03
[15,] 0.9968031 6.393736e-03 3.196868e-03
[16,] 0.9994691 1.061710e-03 5.308550e-04
[17,] 0.9997567 4.866647e-04 2.433323e-04
[18,] 0.9995933 8.134500e-04 4.067250e-04
[19,] 0.9995572 8.856246e-04 4.428123e-04
[20,] 0.9995313 9.374142e-04 4.687071e-04
[21,] 0.9994736 1.052770e-03 5.263848e-04
[22,] 0.9991725 1.654905e-03 8.274523e-04
[23,] 0.9988805 2.239066e-03 1.119533e-03
[24,] 0.9988317 2.336552e-03 1.168276e-03
[25,] 0.9988895 2.220941e-03 1.110471e-03
[26,] 0.9985317 2.936580e-03 1.468290e-03
[27,] 0.9979829 4.034151e-03 2.017075e-03
[28,] 0.9971029 5.794242e-03 2.897121e-03
[29,] 0.9993796 1.240703e-03 6.203515e-04
[30,] 0.9995400 9.200461e-04 4.600231e-04
[31,] 0.9993285 1.343056e-03 6.715278e-04
[32,] 0.9991534 1.693287e-03 8.466437e-04
[33,] 0.9988283 2.343455e-03 1.171728e-03
[34,] 0.9982977 3.404619e-03 1.702310e-03
[35,] 0.9987273 2.545328e-03 1.272664e-03
[36,] 0.9982083 3.583376e-03 1.791688e-03
[37,] 0.9981170 3.766077e-03 1.883038e-03
[38,] 0.9974043 5.191400e-03 2.595700e-03
[39,] 0.9964080 7.184056e-03 3.592028e-03
[40,] 0.9990551 1.889820e-03 9.449102e-04
[41,] 0.9999096 1.807483e-04 9.037413e-05
[42,] 0.9998811 2.377120e-04 1.188560e-04
[43,] 0.9998529 2.941119e-04 1.470559e-04
[44,] 0.9998207 3.586169e-04 1.793084e-04
[45,] 0.9999449 1.102701e-04 5.513503e-05
[46,] 0.9999161 1.677876e-04 8.389380e-05
[47,] 0.9998944 2.112093e-04 1.056047e-04
[48,] 0.9999684 6.324235e-05 3.162118e-05
[49,] 0.9999523 9.530531e-05 4.765265e-05
[50,] 0.9999314 1.372594e-04 6.862969e-05
[51,] 0.9999035 1.930142e-04 9.650709e-05
[52,] 0.9998981 2.037445e-04 1.018722e-04
[53,] 0.9999132 1.735340e-04 8.676702e-05
[54,] 0.9998737 2.525173e-04 1.262586e-04
[55,] 0.9998256 3.487338e-04 1.743669e-04
[56,] 0.9997471 5.058698e-04 2.529349e-04
[57,] 0.9996983 6.033089e-04 3.016545e-04
[58,] 0.9995857 8.286555e-04 4.143277e-04
[59,] 0.9994315 1.136971e-03 5.684855e-04
[60,] 0.9994504 1.099258e-03 5.496288e-04
[61,] 0.9992874 1.425290e-03 7.126448e-04
[62,] 0.9995763 8.473825e-04 4.236913e-04
[63,] 0.9996608 6.783029e-04 3.391514e-04
[64,] 0.9996583 6.834791e-04 3.417396e-04
[65,] 0.9996909 6.181678e-04 3.090839e-04
[66,] 0.9996379 7.242491e-04 3.621245e-04
[67,] 0.9997493 5.013800e-04 2.506900e-04
[68,] 0.9996789 6.421221e-04 3.210610e-04
[69,] 0.9996648 6.704074e-04 3.352037e-04
[70,] 0.9995303 9.393391e-04 4.696696e-04
[71,] 0.9993489 1.302176e-03 6.510879e-04
[72,] 0.9994706 1.058871e-03 5.294356e-04
[73,] 0.9996170 7.660373e-04 3.830187e-04
[74,] 0.9996093 7.813397e-04 3.906699e-04
[75,] 0.9995192 9.616693e-04 4.808346e-04
[76,] 0.9995378 9.244780e-04 4.622390e-04
[77,] 0.9994040 1.192078e-03 5.960389e-04
[78,] 0.9992889 1.422115e-03 7.110575e-04
[79,] 0.9998495 3.009151e-04 1.504576e-04
[80,] 0.9998131 3.737328e-04 1.868664e-04
[81,] 0.9998179 3.641205e-04 1.820603e-04
[82,] 0.9997734 4.532802e-04 2.266401e-04
[83,] 0.9997723 4.554176e-04 2.277088e-04
[84,] 0.9996915 6.170349e-04 3.085174e-04
[85,] 0.9996186 7.627167e-04 3.813584e-04
[86,] 0.9995338 9.324212e-04 4.662106e-04
[87,] 0.9994964 1.007151e-03 5.035753e-04
[88,] 0.9999997 6.150850e-07 3.075425e-07
[89,] 0.9999996 7.871630e-07 3.935815e-07
[90,] 0.9999994 1.139137e-06 5.695683e-07
[91,] 0.9999992 1.531354e-06 7.656771e-07
[92,] 0.9999992 1.693498e-06 8.467490e-07
[93,] 0.9999996 8.103758e-07 4.051879e-07
[94,] 0.9999994 1.182352e-06 5.911762e-07
[95,] 0.9999994 1.110721e-06 5.553606e-07
[96,] 0.9999994 1.248719e-06 6.243596e-07
[97,] 0.9999994 1.170342e-06 5.851711e-07
[98,] 0.9999992 1.677158e-06 8.385788e-07
[99,] 0.9999992 1.646245e-06 8.231224e-07
[100,] 0.9999987 2.529856e-06 1.264928e-06
[101,] 0.9999983 3.411048e-06 1.705524e-06
[102,] 0.9999978 4.312074e-06 2.156037e-06
[103,] 0.9999973 5.479735e-06 2.739867e-06
[104,] 0.9999960 8.031764e-06 4.015882e-06
[105,] 0.9999953 9.342569e-06 4.671285e-06
[106,] 0.9999957 8.671851e-06 4.335925e-06
[107,] 0.9999951 9.869985e-06 4.934993e-06
[108,] 0.9999980 4.050701e-06 2.025350e-06
[109,] 0.9999969 6.101762e-06 3.050881e-06
[110,] 0.9999965 6.935795e-06 3.467898e-06
[111,] 0.9999949 1.027619e-05 5.138093e-06
[112,] 0.9999977 4.643825e-06 2.321912e-06
[113,] 0.9999974 5.267614e-06 2.633807e-06
[114,] 0.9999993 1.379366e-06 6.896828e-07
[115,] 1.0000000 7.948139e-08 3.974070e-08
[116,] 1.0000000 9.874090e-08 4.937045e-08
[117,] 0.9999999 1.445087e-07 7.225437e-08
[118,] 0.9999999 2.103329e-07 1.051665e-07
[119,] 0.9999999 2.472807e-07 1.236404e-07
[120,] 0.9999998 3.907247e-07 1.953623e-07
[121,] 0.9999997 6.048519e-07 3.024259e-07
[122,] 0.9999998 3.301581e-07 1.650791e-07
[123,] 0.9999998 4.474447e-07 2.237223e-07
[124,] 1.0000000 7.029500e-08 3.514750e-08
[125,] 0.9999999 1.010771e-07 5.053856e-08
[126,] 1.0000000 2.552252e-08 1.276126e-08
[127,] 1.0000000 4.181634e-08 2.090817e-08
[128,] 1.0000000 1.827029e-08 9.135143e-09
[129,] 1.0000000 2.274615e-08 1.137308e-08
[130,] 1.0000000 3.478868e-08 1.739434e-08
[131,] 1.0000000 3.714920e-08 1.857460e-08
[132,] 1.0000000 5.727250e-08 2.863625e-08
[133,] 1.0000000 8.914875e-08 4.457437e-08
[134,] 0.9999999 1.322898e-07 6.614488e-08
[135,] 0.9999999 1.896903e-07 9.484516e-08
[136,] 0.9999999 2.410436e-07 1.205218e-07
[137,] 0.9999998 3.639386e-07 1.819693e-07
[138,] 0.9999997 5.289638e-07 2.644819e-07
[139,] 0.9999997 6.399443e-07 3.199722e-07
[140,] 0.9999995 1.002067e-06 5.010337e-07
[141,] 0.9999994 1.134360e-06 5.671800e-07
[142,] 0.9999993 1.433364e-06 7.166821e-07
[143,] 0.9999990 1.961571e-06 9.807854e-07
[144,] 0.9999985 2.943991e-06 1.471996e-06
[145,] 0.9999981 3.781026e-06 1.890513e-06
[146,] 0.9999994 1.233497e-06 6.167483e-07
[147,] 0.9999993 1.334705e-06 6.673527e-07
[148,] 0.9999993 1.469775e-06 7.348875e-07
[149,] 0.9999992 1.680610e-06 8.403052e-07
[150,] 0.9999991 1.823854e-06 9.119269e-07
[151,] 0.9999991 1.749993e-06 8.749967e-07
[152,] 0.9999987 2.533011e-06 1.266506e-06
[153,] 0.9999986 2.876877e-06 1.438439e-06
[154,] 0.9999982 3.558357e-06 1.779179e-06
[155,] 0.9999984 3.233365e-06 1.616683e-06
[156,] 0.9999993 1.341811e-06 6.709057e-07
[157,] 0.9999990 2.004845e-06 1.002422e-06
[158,] 0.9999986 2.879713e-06 1.439856e-06
[159,] 0.9999984 3.223147e-06 1.611573e-06
[160,] 1.0000000 1.952188e-08 9.760938e-09
[161,] 1.0000000 3.271237e-08 1.635618e-08
[162,] 1.0000000 4.615906e-08 2.307953e-08
[163,] 1.0000000 7.661210e-08 3.830605e-08
[164,] 1.0000000 3.128961e-08 1.564481e-08
[165,] 1.0000000 4.729546e-10 2.364773e-10
[166,] 1.0000000 7.890218e-10 3.945109e-10
[167,] 1.0000000 7.140181e-10 3.570091e-10
[168,] 1.0000000 1.215465e-09 6.077323e-10
[169,] 1.0000000 2.136792e-09 1.068396e-09
[170,] 1.0000000 7.585468e-10 3.792734e-10
[171,] 1.0000000 9.252130e-10 4.626065e-10
[172,] 1.0000000 7.128016e-11 3.564008e-11
[173,] 1.0000000 1.331397e-10 6.656986e-11
[174,] 1.0000000 1.078046e-10 5.390230e-11
[175,] 1.0000000 3.256804e-11 1.628402e-11
[176,] 1.0000000 5.826854e-11 2.913427e-11
[177,] 1.0000000 1.060167e-10 5.300836e-11
[178,] 1.0000000 1.945572e-10 9.727862e-11
[179,] 1.0000000 2.898317e-10 1.449158e-10
[180,] 1.0000000 2.794049e-10 1.397024e-10
[181,] 1.0000000 2.398465e-11 1.199233e-11
[182,] 1.0000000 4.685310e-11 2.342655e-11
[183,] 1.0000000 7.708323e-11 3.854162e-11
[184,] 1.0000000 1.494725e-10 7.473626e-11
[185,] 1.0000000 2.744906e-10 1.372453e-10
[186,] 1.0000000 4.550035e-10 2.275018e-10
[187,] 1.0000000 4.713174e-10 2.356587e-10
[188,] 1.0000000 8.618841e-10 4.309421e-10
[189,] 1.0000000 8.382308e-10 4.191154e-10
[190,] 1.0000000 1.518251e-09 7.591253e-10
[191,] 1.0000000 2.800217e-09 1.400108e-09
[192,] 1.0000000 4.706509e-09 2.353254e-09
[193,] 1.0000000 7.720220e-09 3.860110e-09
[194,] 1.0000000 1.398288e-08 6.991441e-09
[195,] 1.0000000 1.392239e-08 6.961195e-09
[196,] 1.0000000 2.533555e-08 1.266777e-08
[197,] 1.0000000 4.438385e-08 2.219192e-08
[198,] 1.0000000 7.240847e-09 3.620424e-09
[199,] 1.0000000 4.373258e-09 2.186629e-09
[200,] 1.0000000 7.729087e-09 3.864543e-09
[201,] 1.0000000 1.098109e-08 5.490544e-09
[202,] 1.0000000 4.304604e-09 2.152302e-09
[203,] 1.0000000 8.390347e-09 4.195174e-09
[204,] 1.0000000 1.619635e-08 8.098173e-09
[205,] 1.0000000 1.770074e-08 8.850368e-09
[206,] 1.0000000 2.012677e-08 1.006339e-08
[207,] 1.0000000 1.007285e-08 5.036427e-09
[208,] 1.0000000 1.966780e-08 9.833898e-09
[209,] 1.0000000 3.429947e-08 1.714973e-08
[210,] 1.0000000 3.795301e-08 1.897650e-08
[211,] 1.0000000 5.747271e-08 2.873635e-08
[212,] 0.9999999 1.097547e-07 5.487734e-08
[213,] 1.0000000 3.927495e-08 1.963748e-08
[214,] 1.0000000 6.973407e-08 3.486703e-08
[215,] 0.9999999 1.344416e-07 6.722081e-08
[216,] 0.9999999 2.299694e-07 1.149847e-07
[217,] 0.9999999 2.202493e-07 1.101246e-07
[218,] 0.9999999 1.751097e-07 8.755484e-08
[219,] 0.9999999 1.921551e-07 9.607756e-08
[220,] 1.0000000 5.497044e-08 2.748522e-08
[221,] 1.0000000 5.522932e-08 2.761466e-08
[222,] 0.9999999 1.127515e-07 5.637574e-08
[223,] 1.0000000 4.567748e-08 2.283874e-08
[224,] 1.0000000 9.118805e-08 4.559402e-08
[225,] 1.0000000 8.700636e-08 4.350318e-08
[226,] 0.9999999 1.579186e-07 7.895931e-08
[227,] 1.0000000 9.735844e-10 4.867922e-10
[228,] 1.0000000 2.091481e-09 1.045740e-09
[229,] 1.0000000 3.786691e-09 1.893346e-09
[230,] 1.0000000 2.277561e-09 1.138781e-09
[231,] 1.0000000 2.614212e-09 1.307106e-09
[232,] 1.0000000 6.272364e-09 3.136182e-09
[233,] 1.0000000 7.615100e-09 3.807550e-09
[234,] 1.0000000 1.311804e-08 6.559020e-09
[235,] 1.0000000 2.925913e-08 1.462956e-08
[236,] 1.0000000 7.050421e-08 3.525210e-08
[237,] 0.9999999 1.105334e-07 5.526668e-08
[238,] 0.9999999 1.491947e-07 7.459735e-08
[239,] 0.9999998 3.526279e-07 1.763140e-07
[240,] 0.9999997 6.398415e-07 3.199208e-07
[241,] 0.9999996 7.658377e-07 3.829189e-07
[242,] 0.9999992 1.598465e-06 7.992327e-07
[243,] 0.9999982 3.697069e-06 1.848535e-06
[244,] 0.9999958 8.480087e-06 4.240043e-06
[245,] 0.9999963 7.439299e-06 3.719650e-06
[246,] 0.9999921 1.575448e-05 7.877239e-06
[247,] 0.9999918 1.639594e-05 8.197972e-06
[248,] 0.9999868 2.638355e-05 1.319178e-05
[249,] 0.9999777 4.468111e-05 2.234055e-05
[250,] 0.9999494 1.012568e-04 5.062838e-05
[251,] 0.9999001 1.998249e-04 9.991247e-05
[252,] 0.9997844 4.312093e-04 2.156047e-04
[253,] 0.9995361 9.277988e-04 4.638994e-04
[254,] 0.9990830 1.834044e-03 9.170220e-04
[255,] 0.9993695 1.260966e-03 6.304831e-04
[256,] 0.9989212 2.157525e-03 1.078763e-03
[257,] 0.9994156 1.168835e-03 5.844175e-04
[258,] 0.9989322 2.135531e-03 1.067766e-03
[259,] 0.9999962 7.685163e-06 3.842582e-06
[260,] 0.9999974 5.162746e-06 2.581373e-06
[261,] 0.9999901 1.985975e-05 9.929873e-06
[262,] 0.9999654 6.918332e-05 3.459166e-05
[263,] 0.9999252 1.496761e-04 7.483807e-05
[264,] 0.9997686 4.627859e-04 2.313930e-04
[265,] 0.9993752 1.249614e-03 6.248068e-04
[266,] 0.9972754 5.449208e-03 2.724604e-03
[267,] 0.9948212 1.035755e-02 5.178775e-03
[268,] 0.9794051 4.118983e-02 2.059492e-02
> postscript(file="/var/fisher/rcomp/tmp/1ae8w1355851555.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/2vn191355851555.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3e7sw1355851555.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/45ioz1355851555.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/55rm81355851555.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
66818.85452 -844.91802 13548.68431 -76877.67887 33694.50863
6 7 8 9 10
-2983.18177 31616.34629 2803.70532 12467.59037 -12898.03413
11 12 13 14 15
24426.40145 28133.41195 -19074.63459 -10506.94448 13809.37877
16 17 18 19 20
28109.03028 -80262.26888 37002.81581 5650.13431 4218.11372
21 22 23 24 25
434.47558 10632.06805 101741.90548 37109.00931 -34322.63977
26 27 28 29 30
-96722.57832 -53868.06083 -13677.61166 31787.29097 -9480.67784
31 32 33 34 35
18474.61335 3003.92743 1076.37458 28377.96598 -19704.13389
36 37 38 39 40
26012.24872 32292.02285 7775.26988 64126.65769 1721.59176
41 42 43 44 45
16694.84981 36319.45259 -25937.59048 -9232.90229 -23443.83981
46 47 48 49 50
-9513.13573 -43857.29360 1373.46250 4044.21372 -65313.26759
51 52 53 54 55
41772.63257 -13852.33020 -16785.51488 -26018.56086 -54460.12650
56 57 58 59 60
6087.62008 -13206.15340 48926.92501 -3830.98135 -6983.49819
61 62 63 64 65
8734.05205 30055.63113 36415.38459 9304.29238 17.28361
66 67 68 69 70
1308.00474 23531.24693 10114.57913 9306.66931 -34542.41057
71 72 73 74 75
12896.25721 47793.63076 41832.81455 -22579.11867 -32093.54827
76 77 78 79 80
-17967.91382 -38783.46503 -15994.22441 -25092.41763 3217.01185
81 82 83 84 85
3141.23428 -35593.21468 40078.95767 29214.86170 19800.75217
86 87 88 89 90
-29234.29665 -12180.13475 -17890.11161 68616.95612 -16642.92736
91 92 93 94 95
32116.04980 -16089.55006 -29192.76187 7747.24979 18460.18787
96 97 98 99 100
12374.41649 28497.38917 -127287.51527 22246.09165 -11249.76893
101 102 103 104 105
16857.65746 -23309.79684 45227.23377 11879.19895 30658.41771
106 107 108 109 110
25640.64088 -31715.87452 -6873.33823 28499.69265 866.92938
111 112 113 114 115
15514.86932 -13849.97499 -15885.29325 5676.58407 -20635.41212
116 117 118 119 120
-29822.62858 -19925.88097 49468.01895 3807.85367 -22756.24613
121 122 123 124 125
-2431.09587 -45649.21130 -26560.62690 -55711.55062 74699.98535
126 127 128 129 130
20301.72738 10764.39178 -12134.16933 23216.74517 2092.24674
131 132 133 134 135
-2851.92106 -37790.88915 15038.12142 -60245.26563 -13096.71838
136 137 138 139 140
57039.83056 2416.03323 43080.48849 -19467.98811 -9086.13078
141 142 143 144 145
-23347.40696 -8637.66853 6951.01916 -12348.14527 8339.66045
146 147 148 149 150
-20495.71356 -3561.64351 -11437.30495 -19554.43436 -2217.43211
151 152 153 154 155
23235.12928 16956.62804 -11572.66542 5955.36802 15573.37889
156 157 158 159 160
44163.26170 18722.32837 19748.49659 -23179.96301 -22057.01233
161 162 163 164 165
21765.11411 -13627.91782 -15162.86430 -22103.91856 -31104.89544
166 167 168 169 170
33970.18933 -4798.53555 17544.87292 23124.38033 88520.91801
171 172 173 174 175
-9676.72894 3789.98969 1896.40991 19519.66845 -90621.07264
176 177 178 179 180
3619.08642 -31881.57742 6391.49702 -3546.32093 36584.53921
181 182 183 184 185
-20225.64155 -53786.64416 7346.26443 23577.71485 27453.62715
186 187 188 189 190
1902.23805 -688.99160 14183.65216 8877.31811 9612.83184
191 192 193 194 195
33443.03802 -7143.54149 -13780.70492 -1945.28698 -2226.26376
196 197 198 199 200
5973.55413 -23263.87462 8423.00512 -30723.87216 -5827.89597
201 202 203 204 205
5421.04471 2045.04422 10930.84239 5027.93677 -31117.27459
206 207 208 209 210
-9083.39204 -7181.22171 42030.85434 23084.85595 -4395.60776
211 212 213 214 215
13315.77138 27018.23165 -1850.07920 -1723.03696 -30089.90766
216 217 218 219 220
-15662.17692 -33861.50685 6835.58091 3584.38031 23672.53074
221 222 223 224 225
-19960.97052 -4089.71008 -47016.61645 5600.19912 -3021.67409
226 227 228 229 230
4092.17988 23116.87799 -28551.55041 -22271.36119 -38557.48419
231 232 233 234 235
-14452.89996 -2162.87262 -32007.23660 -5284.79644 -27408.94637
236 237 238 239 240
-14214.57972 49727.45922 -5863.71759 -11638.80076 -22970.19985
241 242 243 244 245
13869.63817 288.34720 -16622.82114 -9000.10363 -2055.53229
246 247 248 249 250
-8980.70931 -20645.33687 19288.22496 6553.15964 -12344.31296
251 252 253 254 255
14239.66948 6600.33543 11365.84186 -2107.94167 -23644.60866
256 257 258 259 260
675.56342 -11903.42418 9295.61384 12263.89481 6989.54139
261 262 263 264 265
-12364.98375 5131.50778 11627.03607 -5748.72164 -14507.48416
266 267 268 269 270
8161.54450 -22642.31296 -4945.05601 44369.94439 -16425.33058
271 272 273 274 275
-2742.37797 732.99602 2426.92446 4247.80273 11643.56605
276 277 278 279 280
-14987.96964 16596.41035 10118.00240 -3988.01104 12398.06825
281 282 283 284 285
-6079.15749 16775.80914 183.50715 12131.97943 -356.27046
286 287 288 289
-478.07433 2786.60609 -281.59432 -1374.08521
> postscript(file="/var/fisher/rcomp/tmp/6pn2x1355851555.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 66818.85452 NA
1 -844.91802 66818.85452
2 13548.68431 -844.91802
3 -76877.67887 13548.68431
4 33694.50863 -76877.67887
5 -2983.18177 33694.50863
6 31616.34629 -2983.18177
7 2803.70532 31616.34629
8 12467.59037 2803.70532
9 -12898.03413 12467.59037
10 24426.40145 -12898.03413
11 28133.41195 24426.40145
12 -19074.63459 28133.41195
13 -10506.94448 -19074.63459
14 13809.37877 -10506.94448
15 28109.03028 13809.37877
16 -80262.26888 28109.03028
17 37002.81581 -80262.26888
18 5650.13431 37002.81581
19 4218.11372 5650.13431
20 434.47558 4218.11372
21 10632.06805 434.47558
22 101741.90548 10632.06805
23 37109.00931 101741.90548
24 -34322.63977 37109.00931
25 -96722.57832 -34322.63977
26 -53868.06083 -96722.57832
27 -13677.61166 -53868.06083
28 31787.29097 -13677.61166
29 -9480.67784 31787.29097
30 18474.61335 -9480.67784
31 3003.92743 18474.61335
32 1076.37458 3003.92743
33 28377.96598 1076.37458
34 -19704.13389 28377.96598
35 26012.24872 -19704.13389
36 32292.02285 26012.24872
37 7775.26988 32292.02285
38 64126.65769 7775.26988
39 1721.59176 64126.65769
40 16694.84981 1721.59176
41 36319.45259 16694.84981
42 -25937.59048 36319.45259
43 -9232.90229 -25937.59048
44 -23443.83981 -9232.90229
45 -9513.13573 -23443.83981
46 -43857.29360 -9513.13573
47 1373.46250 -43857.29360
48 4044.21372 1373.46250
49 -65313.26759 4044.21372
50 41772.63257 -65313.26759
51 -13852.33020 41772.63257
52 -16785.51488 -13852.33020
53 -26018.56086 -16785.51488
54 -54460.12650 -26018.56086
55 6087.62008 -54460.12650
56 -13206.15340 6087.62008
57 48926.92501 -13206.15340
58 -3830.98135 48926.92501
59 -6983.49819 -3830.98135
60 8734.05205 -6983.49819
61 30055.63113 8734.05205
62 36415.38459 30055.63113
63 9304.29238 36415.38459
64 17.28361 9304.29238
65 1308.00474 17.28361
66 23531.24693 1308.00474
67 10114.57913 23531.24693
68 9306.66931 10114.57913
69 -34542.41057 9306.66931
70 12896.25721 -34542.41057
71 47793.63076 12896.25721
72 41832.81455 47793.63076
73 -22579.11867 41832.81455
74 -32093.54827 -22579.11867
75 -17967.91382 -32093.54827
76 -38783.46503 -17967.91382
77 -15994.22441 -38783.46503
78 -25092.41763 -15994.22441
79 3217.01185 -25092.41763
80 3141.23428 3217.01185
81 -35593.21468 3141.23428
82 40078.95767 -35593.21468
83 29214.86170 40078.95767
84 19800.75217 29214.86170
85 -29234.29665 19800.75217
86 -12180.13475 -29234.29665
87 -17890.11161 -12180.13475
88 68616.95612 -17890.11161
89 -16642.92736 68616.95612
90 32116.04980 -16642.92736
91 -16089.55006 32116.04980
92 -29192.76187 -16089.55006
93 7747.24979 -29192.76187
94 18460.18787 7747.24979
95 12374.41649 18460.18787
96 28497.38917 12374.41649
97 -127287.51527 28497.38917
98 22246.09165 -127287.51527
99 -11249.76893 22246.09165
100 16857.65746 -11249.76893
101 -23309.79684 16857.65746
102 45227.23377 -23309.79684
103 11879.19895 45227.23377
104 30658.41771 11879.19895
105 25640.64088 30658.41771
106 -31715.87452 25640.64088
107 -6873.33823 -31715.87452
108 28499.69265 -6873.33823
109 866.92938 28499.69265
110 15514.86932 866.92938
111 -13849.97499 15514.86932
112 -15885.29325 -13849.97499
113 5676.58407 -15885.29325
114 -20635.41212 5676.58407
115 -29822.62858 -20635.41212
116 -19925.88097 -29822.62858
117 49468.01895 -19925.88097
118 3807.85367 49468.01895
119 -22756.24613 3807.85367
120 -2431.09587 -22756.24613
121 -45649.21130 -2431.09587
122 -26560.62690 -45649.21130
123 -55711.55062 -26560.62690
124 74699.98535 -55711.55062
125 20301.72738 74699.98535
126 10764.39178 20301.72738
127 -12134.16933 10764.39178
128 23216.74517 -12134.16933
129 2092.24674 23216.74517
130 -2851.92106 2092.24674
131 -37790.88915 -2851.92106
132 15038.12142 -37790.88915
133 -60245.26563 15038.12142
134 -13096.71838 -60245.26563
135 57039.83056 -13096.71838
136 2416.03323 57039.83056
137 43080.48849 2416.03323
138 -19467.98811 43080.48849
139 -9086.13078 -19467.98811
140 -23347.40696 -9086.13078
141 -8637.66853 -23347.40696
142 6951.01916 -8637.66853
143 -12348.14527 6951.01916
144 8339.66045 -12348.14527
145 -20495.71356 8339.66045
146 -3561.64351 -20495.71356
147 -11437.30495 -3561.64351
148 -19554.43436 -11437.30495
149 -2217.43211 -19554.43436
150 23235.12928 -2217.43211
151 16956.62804 23235.12928
152 -11572.66542 16956.62804
153 5955.36802 -11572.66542
154 15573.37889 5955.36802
155 44163.26170 15573.37889
156 18722.32837 44163.26170
157 19748.49659 18722.32837
158 -23179.96301 19748.49659
159 -22057.01233 -23179.96301
160 21765.11411 -22057.01233
161 -13627.91782 21765.11411
162 -15162.86430 -13627.91782
163 -22103.91856 -15162.86430
164 -31104.89544 -22103.91856
165 33970.18933 -31104.89544
166 -4798.53555 33970.18933
167 17544.87292 -4798.53555
168 23124.38033 17544.87292
169 88520.91801 23124.38033
170 -9676.72894 88520.91801
171 3789.98969 -9676.72894
172 1896.40991 3789.98969
173 19519.66845 1896.40991
174 -90621.07264 19519.66845
175 3619.08642 -90621.07264
176 -31881.57742 3619.08642
177 6391.49702 -31881.57742
178 -3546.32093 6391.49702
179 36584.53921 -3546.32093
180 -20225.64155 36584.53921
181 -53786.64416 -20225.64155
182 7346.26443 -53786.64416
183 23577.71485 7346.26443
184 27453.62715 23577.71485
185 1902.23805 27453.62715
186 -688.99160 1902.23805
187 14183.65216 -688.99160
188 8877.31811 14183.65216
189 9612.83184 8877.31811
190 33443.03802 9612.83184
191 -7143.54149 33443.03802
192 -13780.70492 -7143.54149
193 -1945.28698 -13780.70492
194 -2226.26376 -1945.28698
195 5973.55413 -2226.26376
196 -23263.87462 5973.55413
197 8423.00512 -23263.87462
198 -30723.87216 8423.00512
199 -5827.89597 -30723.87216
200 5421.04471 -5827.89597
201 2045.04422 5421.04471
202 10930.84239 2045.04422
203 5027.93677 10930.84239
204 -31117.27459 5027.93677
205 -9083.39204 -31117.27459
206 -7181.22171 -9083.39204
207 42030.85434 -7181.22171
208 23084.85595 42030.85434
209 -4395.60776 23084.85595
210 13315.77138 -4395.60776
211 27018.23165 13315.77138
212 -1850.07920 27018.23165
213 -1723.03696 -1850.07920
214 -30089.90766 -1723.03696
215 -15662.17692 -30089.90766
216 -33861.50685 -15662.17692
217 6835.58091 -33861.50685
218 3584.38031 6835.58091
219 23672.53074 3584.38031
220 -19960.97052 23672.53074
221 -4089.71008 -19960.97052
222 -47016.61645 -4089.71008
223 5600.19912 -47016.61645
224 -3021.67409 5600.19912
225 4092.17988 -3021.67409
226 23116.87799 4092.17988
227 -28551.55041 23116.87799
228 -22271.36119 -28551.55041
229 -38557.48419 -22271.36119
230 -14452.89996 -38557.48419
231 -2162.87262 -14452.89996
232 -32007.23660 -2162.87262
233 -5284.79644 -32007.23660
234 -27408.94637 -5284.79644
235 -14214.57972 -27408.94637
236 49727.45922 -14214.57972
237 -5863.71759 49727.45922
238 -11638.80076 -5863.71759
239 -22970.19985 -11638.80076
240 13869.63817 -22970.19985
241 288.34720 13869.63817
242 -16622.82114 288.34720
243 -9000.10363 -16622.82114
244 -2055.53229 -9000.10363
245 -8980.70931 -2055.53229
246 -20645.33687 -8980.70931
247 19288.22496 -20645.33687
248 6553.15964 19288.22496
249 -12344.31296 6553.15964
250 14239.66948 -12344.31296
251 6600.33543 14239.66948
252 11365.84186 6600.33543
253 -2107.94167 11365.84186
254 -23644.60866 -2107.94167
255 675.56342 -23644.60866
256 -11903.42418 675.56342
257 9295.61384 -11903.42418
258 12263.89481 9295.61384
259 6989.54139 12263.89481
260 -12364.98375 6989.54139
261 5131.50778 -12364.98375
262 11627.03607 5131.50778
263 -5748.72164 11627.03607
264 -14507.48416 -5748.72164
265 8161.54450 -14507.48416
266 -22642.31296 8161.54450
267 -4945.05601 -22642.31296
268 44369.94439 -4945.05601
269 -16425.33058 44369.94439
270 -2742.37797 -16425.33058
271 732.99602 -2742.37797
272 2426.92446 732.99602
273 4247.80273 2426.92446
274 11643.56605 4247.80273
275 -14987.96964 11643.56605
276 16596.41035 -14987.96964
277 10118.00240 16596.41035
278 -3988.01104 10118.00240
279 12398.06825 -3988.01104
280 -6079.15749 12398.06825
281 16775.80914 -6079.15749
282 183.50715 16775.80914
283 12131.97943 183.50715
284 -356.27046 12131.97943
285 -478.07433 -356.27046
286 2786.60609 -478.07433
287 -281.59432 2786.60609
288 -1374.08521 -281.59432
289 NA -1374.08521
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -844.91802 66818.85452
[2,] 13548.68431 -844.91802
[3,] -76877.67887 13548.68431
[4,] 33694.50863 -76877.67887
[5,] -2983.18177 33694.50863
[6,] 31616.34629 -2983.18177
[7,] 2803.70532 31616.34629
[8,] 12467.59037 2803.70532
[9,] -12898.03413 12467.59037
[10,] 24426.40145 -12898.03413
[11,] 28133.41195 24426.40145
[12,] -19074.63459 28133.41195
[13,] -10506.94448 -19074.63459
[14,] 13809.37877 -10506.94448
[15,] 28109.03028 13809.37877
[16,] -80262.26888 28109.03028
[17,] 37002.81581 -80262.26888
[18,] 5650.13431 37002.81581
[19,] 4218.11372 5650.13431
[20,] 434.47558 4218.11372
[21,] 10632.06805 434.47558
[22,] 101741.90548 10632.06805
[23,] 37109.00931 101741.90548
[24,] -34322.63977 37109.00931
[25,] -96722.57832 -34322.63977
[26,] -53868.06083 -96722.57832
[27,] -13677.61166 -53868.06083
[28,] 31787.29097 -13677.61166
[29,] -9480.67784 31787.29097
[30,] 18474.61335 -9480.67784
[31,] 3003.92743 18474.61335
[32,] 1076.37458 3003.92743
[33,] 28377.96598 1076.37458
[34,] -19704.13389 28377.96598
[35,] 26012.24872 -19704.13389
[36,] 32292.02285 26012.24872
[37,] 7775.26988 32292.02285
[38,] 64126.65769 7775.26988
[39,] 1721.59176 64126.65769
[40,] 16694.84981 1721.59176
[41,] 36319.45259 16694.84981
[42,] -25937.59048 36319.45259
[43,] -9232.90229 -25937.59048
[44,] -23443.83981 -9232.90229
[45,] -9513.13573 -23443.83981
[46,] -43857.29360 -9513.13573
[47,] 1373.46250 -43857.29360
[48,] 4044.21372 1373.46250
[49,] -65313.26759 4044.21372
[50,] 41772.63257 -65313.26759
[51,] -13852.33020 41772.63257
[52,] -16785.51488 -13852.33020
[53,] -26018.56086 -16785.51488
[54,] -54460.12650 -26018.56086
[55,] 6087.62008 -54460.12650
[56,] -13206.15340 6087.62008
[57,] 48926.92501 -13206.15340
[58,] -3830.98135 48926.92501
[59,] -6983.49819 -3830.98135
[60,] 8734.05205 -6983.49819
[61,] 30055.63113 8734.05205
[62,] 36415.38459 30055.63113
[63,] 9304.29238 36415.38459
[64,] 17.28361 9304.29238
[65,] 1308.00474 17.28361
[66,] 23531.24693 1308.00474
[67,] 10114.57913 23531.24693
[68,] 9306.66931 10114.57913
[69,] -34542.41057 9306.66931
[70,] 12896.25721 -34542.41057
[71,] 47793.63076 12896.25721
[72,] 41832.81455 47793.63076
[73,] -22579.11867 41832.81455
[74,] -32093.54827 -22579.11867
[75,] -17967.91382 -32093.54827
[76,] -38783.46503 -17967.91382
[77,] -15994.22441 -38783.46503
[78,] -25092.41763 -15994.22441
[79,] 3217.01185 -25092.41763
[80,] 3141.23428 3217.01185
[81,] -35593.21468 3141.23428
[82,] 40078.95767 -35593.21468
[83,] 29214.86170 40078.95767
[84,] 19800.75217 29214.86170
[85,] -29234.29665 19800.75217
[86,] -12180.13475 -29234.29665
[87,] -17890.11161 -12180.13475
[88,] 68616.95612 -17890.11161
[89,] -16642.92736 68616.95612
[90,] 32116.04980 -16642.92736
[91,] -16089.55006 32116.04980
[92,] -29192.76187 -16089.55006
[93,] 7747.24979 -29192.76187
[94,] 18460.18787 7747.24979
[95,] 12374.41649 18460.18787
[96,] 28497.38917 12374.41649
[97,] -127287.51527 28497.38917
[98,] 22246.09165 -127287.51527
[99,] -11249.76893 22246.09165
[100,] 16857.65746 -11249.76893
[101,] -23309.79684 16857.65746
[102,] 45227.23377 -23309.79684
[103,] 11879.19895 45227.23377
[104,] 30658.41771 11879.19895
[105,] 25640.64088 30658.41771
[106,] -31715.87452 25640.64088
[107,] -6873.33823 -31715.87452
[108,] 28499.69265 -6873.33823
[109,] 866.92938 28499.69265
[110,] 15514.86932 866.92938
[111,] -13849.97499 15514.86932
[112,] -15885.29325 -13849.97499
[113,] 5676.58407 -15885.29325
[114,] -20635.41212 5676.58407
[115,] -29822.62858 -20635.41212
[116,] -19925.88097 -29822.62858
[117,] 49468.01895 -19925.88097
[118,] 3807.85367 49468.01895
[119,] -22756.24613 3807.85367
[120,] -2431.09587 -22756.24613
[121,] -45649.21130 -2431.09587
[122,] -26560.62690 -45649.21130
[123,] -55711.55062 -26560.62690
[124,] 74699.98535 -55711.55062
[125,] 20301.72738 74699.98535
[126,] 10764.39178 20301.72738
[127,] -12134.16933 10764.39178
[128,] 23216.74517 -12134.16933
[129,] 2092.24674 23216.74517
[130,] -2851.92106 2092.24674
[131,] -37790.88915 -2851.92106
[132,] 15038.12142 -37790.88915
[133,] -60245.26563 15038.12142
[134,] -13096.71838 -60245.26563
[135,] 57039.83056 -13096.71838
[136,] 2416.03323 57039.83056
[137,] 43080.48849 2416.03323
[138,] -19467.98811 43080.48849
[139,] -9086.13078 -19467.98811
[140,] -23347.40696 -9086.13078
[141,] -8637.66853 -23347.40696
[142,] 6951.01916 -8637.66853
[143,] -12348.14527 6951.01916
[144,] 8339.66045 -12348.14527
[145,] -20495.71356 8339.66045
[146,] -3561.64351 -20495.71356
[147,] -11437.30495 -3561.64351
[148,] -19554.43436 -11437.30495
[149,] -2217.43211 -19554.43436
[150,] 23235.12928 -2217.43211
[151,] 16956.62804 23235.12928
[152,] -11572.66542 16956.62804
[153,] 5955.36802 -11572.66542
[154,] 15573.37889 5955.36802
[155,] 44163.26170 15573.37889
[156,] 18722.32837 44163.26170
[157,] 19748.49659 18722.32837
[158,] -23179.96301 19748.49659
[159,] -22057.01233 -23179.96301
[160,] 21765.11411 -22057.01233
[161,] -13627.91782 21765.11411
[162,] -15162.86430 -13627.91782
[163,] -22103.91856 -15162.86430
[164,] -31104.89544 -22103.91856
[165,] 33970.18933 -31104.89544
[166,] -4798.53555 33970.18933
[167,] 17544.87292 -4798.53555
[168,] 23124.38033 17544.87292
[169,] 88520.91801 23124.38033
[170,] -9676.72894 88520.91801
[171,] 3789.98969 -9676.72894
[172,] 1896.40991 3789.98969
[173,] 19519.66845 1896.40991
[174,] -90621.07264 19519.66845
[175,] 3619.08642 -90621.07264
[176,] -31881.57742 3619.08642
[177,] 6391.49702 -31881.57742
[178,] -3546.32093 6391.49702
[179,] 36584.53921 -3546.32093
[180,] -20225.64155 36584.53921
[181,] -53786.64416 -20225.64155
[182,] 7346.26443 -53786.64416
[183,] 23577.71485 7346.26443
[184,] 27453.62715 23577.71485
[185,] 1902.23805 27453.62715
[186,] -688.99160 1902.23805
[187,] 14183.65216 -688.99160
[188,] 8877.31811 14183.65216
[189,] 9612.83184 8877.31811
[190,] 33443.03802 9612.83184
[191,] -7143.54149 33443.03802
[192,] -13780.70492 -7143.54149
[193,] -1945.28698 -13780.70492
[194,] -2226.26376 -1945.28698
[195,] 5973.55413 -2226.26376
[196,] -23263.87462 5973.55413
[197,] 8423.00512 -23263.87462
[198,] -30723.87216 8423.00512
[199,] -5827.89597 -30723.87216
[200,] 5421.04471 -5827.89597
[201,] 2045.04422 5421.04471
[202,] 10930.84239 2045.04422
[203,] 5027.93677 10930.84239
[204,] -31117.27459 5027.93677
[205,] -9083.39204 -31117.27459
[206,] -7181.22171 -9083.39204
[207,] 42030.85434 -7181.22171
[208,] 23084.85595 42030.85434
[209,] -4395.60776 23084.85595
[210,] 13315.77138 -4395.60776
[211,] 27018.23165 13315.77138
[212,] -1850.07920 27018.23165
[213,] -1723.03696 -1850.07920
[214,] -30089.90766 -1723.03696
[215,] -15662.17692 -30089.90766
[216,] -33861.50685 -15662.17692
[217,] 6835.58091 -33861.50685
[218,] 3584.38031 6835.58091
[219,] 23672.53074 3584.38031
[220,] -19960.97052 23672.53074
[221,] -4089.71008 -19960.97052
[222,] -47016.61645 -4089.71008
[223,] 5600.19912 -47016.61645
[224,] -3021.67409 5600.19912
[225,] 4092.17988 -3021.67409
[226,] 23116.87799 4092.17988
[227,] -28551.55041 23116.87799
[228,] -22271.36119 -28551.55041
[229,] -38557.48419 -22271.36119
[230,] -14452.89996 -38557.48419
[231,] -2162.87262 -14452.89996
[232,] -32007.23660 -2162.87262
[233,] -5284.79644 -32007.23660
[234,] -27408.94637 -5284.79644
[235,] -14214.57972 -27408.94637
[236,] 49727.45922 -14214.57972
[237,] -5863.71759 49727.45922
[238,] -11638.80076 -5863.71759
[239,] -22970.19985 -11638.80076
[240,] 13869.63817 -22970.19985
[241,] 288.34720 13869.63817
[242,] -16622.82114 288.34720
[243,] -9000.10363 -16622.82114
[244,] -2055.53229 -9000.10363
[245,] -8980.70931 -2055.53229
[246,] -20645.33687 -8980.70931
[247,] 19288.22496 -20645.33687
[248,] 6553.15964 19288.22496
[249,] -12344.31296 6553.15964
[250,] 14239.66948 -12344.31296
[251,] 6600.33543 14239.66948
[252,] 11365.84186 6600.33543
[253,] -2107.94167 11365.84186
[254,] -23644.60866 -2107.94167
[255,] 675.56342 -23644.60866
[256,] -11903.42418 675.56342
[257,] 9295.61384 -11903.42418
[258,] 12263.89481 9295.61384
[259,] 6989.54139 12263.89481
[260,] -12364.98375 6989.54139
[261,] 5131.50778 -12364.98375
[262,] 11627.03607 5131.50778
[263,] -5748.72164 11627.03607
[264,] -14507.48416 -5748.72164
[265,] 8161.54450 -14507.48416
[266,] -22642.31296 8161.54450
[267,] -4945.05601 -22642.31296
[268,] 44369.94439 -4945.05601
[269,] -16425.33058 44369.94439
[270,] -2742.37797 -16425.33058
[271,] 732.99602 -2742.37797
[272,] 2426.92446 732.99602
[273,] 4247.80273 2426.92446
[274,] 11643.56605 4247.80273
[275,] -14987.96964 11643.56605
[276,] 16596.41035 -14987.96964
[277,] 10118.00240 16596.41035
[278,] -3988.01104 10118.00240
[279,] 12398.06825 -3988.01104
[280,] -6079.15749 12398.06825
[281,] 16775.80914 -6079.15749
[282,] 183.50715 16775.80914
[283,] 12131.97943 183.50715
[284,] -356.27046 12131.97943
[285,] -478.07433 -356.27046
[286,] 2786.60609 -478.07433
[287,] -281.59432 2786.60609
[288,] -1374.08521 -281.59432
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -844.91802 66818.85452
2 13548.68431 -844.91802
3 -76877.67887 13548.68431
4 33694.50863 -76877.67887
5 -2983.18177 33694.50863
6 31616.34629 -2983.18177
7 2803.70532 31616.34629
8 12467.59037 2803.70532
9 -12898.03413 12467.59037
10 24426.40145 -12898.03413
11 28133.41195 24426.40145
12 -19074.63459 28133.41195
13 -10506.94448 -19074.63459
14 13809.37877 -10506.94448
15 28109.03028 13809.37877
16 -80262.26888 28109.03028
17 37002.81581 -80262.26888
18 5650.13431 37002.81581
19 4218.11372 5650.13431
20 434.47558 4218.11372
21 10632.06805 434.47558
22 101741.90548 10632.06805
23 37109.00931 101741.90548
24 -34322.63977 37109.00931
25 -96722.57832 -34322.63977
26 -53868.06083 -96722.57832
27 -13677.61166 -53868.06083
28 31787.29097 -13677.61166
29 -9480.67784 31787.29097
30 18474.61335 -9480.67784
31 3003.92743 18474.61335
32 1076.37458 3003.92743
33 28377.96598 1076.37458
34 -19704.13389 28377.96598
35 26012.24872 -19704.13389
36 32292.02285 26012.24872
37 7775.26988 32292.02285
38 64126.65769 7775.26988
39 1721.59176 64126.65769
40 16694.84981 1721.59176
41 36319.45259 16694.84981
42 -25937.59048 36319.45259
43 -9232.90229 -25937.59048
44 -23443.83981 -9232.90229
45 -9513.13573 -23443.83981
46 -43857.29360 -9513.13573
47 1373.46250 -43857.29360
48 4044.21372 1373.46250
49 -65313.26759 4044.21372
50 41772.63257 -65313.26759
51 -13852.33020 41772.63257
52 -16785.51488 -13852.33020
53 -26018.56086 -16785.51488
54 -54460.12650 -26018.56086
55 6087.62008 -54460.12650
56 -13206.15340 6087.62008
57 48926.92501 -13206.15340
58 -3830.98135 48926.92501
59 -6983.49819 -3830.98135
60 8734.05205 -6983.49819
61 30055.63113 8734.05205
62 36415.38459 30055.63113
63 9304.29238 36415.38459
64 17.28361 9304.29238
65 1308.00474 17.28361
66 23531.24693 1308.00474
67 10114.57913 23531.24693
68 9306.66931 10114.57913
69 -34542.41057 9306.66931
70 12896.25721 -34542.41057
71 47793.63076 12896.25721
72 41832.81455 47793.63076
73 -22579.11867 41832.81455
74 -32093.54827 -22579.11867
75 -17967.91382 -32093.54827
76 -38783.46503 -17967.91382
77 -15994.22441 -38783.46503
78 -25092.41763 -15994.22441
79 3217.01185 -25092.41763
80 3141.23428 3217.01185
81 -35593.21468 3141.23428
82 40078.95767 -35593.21468
83 29214.86170 40078.95767
84 19800.75217 29214.86170
85 -29234.29665 19800.75217
86 -12180.13475 -29234.29665
87 -17890.11161 -12180.13475
88 68616.95612 -17890.11161
89 -16642.92736 68616.95612
90 32116.04980 -16642.92736
91 -16089.55006 32116.04980
92 -29192.76187 -16089.55006
93 7747.24979 -29192.76187
94 18460.18787 7747.24979
95 12374.41649 18460.18787
96 28497.38917 12374.41649
97 -127287.51527 28497.38917
98 22246.09165 -127287.51527
99 -11249.76893 22246.09165
100 16857.65746 -11249.76893
101 -23309.79684 16857.65746
102 45227.23377 -23309.79684
103 11879.19895 45227.23377
104 30658.41771 11879.19895
105 25640.64088 30658.41771
106 -31715.87452 25640.64088
107 -6873.33823 -31715.87452
108 28499.69265 -6873.33823
109 866.92938 28499.69265
110 15514.86932 866.92938
111 -13849.97499 15514.86932
112 -15885.29325 -13849.97499
113 5676.58407 -15885.29325
114 -20635.41212 5676.58407
115 -29822.62858 -20635.41212
116 -19925.88097 -29822.62858
117 49468.01895 -19925.88097
118 3807.85367 49468.01895
119 -22756.24613 3807.85367
120 -2431.09587 -22756.24613
121 -45649.21130 -2431.09587
122 -26560.62690 -45649.21130
123 -55711.55062 -26560.62690
124 74699.98535 -55711.55062
125 20301.72738 74699.98535
126 10764.39178 20301.72738
127 -12134.16933 10764.39178
128 23216.74517 -12134.16933
129 2092.24674 23216.74517
130 -2851.92106 2092.24674
131 -37790.88915 -2851.92106
132 15038.12142 -37790.88915
133 -60245.26563 15038.12142
134 -13096.71838 -60245.26563
135 57039.83056 -13096.71838
136 2416.03323 57039.83056
137 43080.48849 2416.03323
138 -19467.98811 43080.48849
139 -9086.13078 -19467.98811
140 -23347.40696 -9086.13078
141 -8637.66853 -23347.40696
142 6951.01916 -8637.66853
143 -12348.14527 6951.01916
144 8339.66045 -12348.14527
145 -20495.71356 8339.66045
146 -3561.64351 -20495.71356
147 -11437.30495 -3561.64351
148 -19554.43436 -11437.30495
149 -2217.43211 -19554.43436
150 23235.12928 -2217.43211
151 16956.62804 23235.12928
152 -11572.66542 16956.62804
153 5955.36802 -11572.66542
154 15573.37889 5955.36802
155 44163.26170 15573.37889
156 18722.32837 44163.26170
157 19748.49659 18722.32837
158 -23179.96301 19748.49659
159 -22057.01233 -23179.96301
160 21765.11411 -22057.01233
161 -13627.91782 21765.11411
162 -15162.86430 -13627.91782
163 -22103.91856 -15162.86430
164 -31104.89544 -22103.91856
165 33970.18933 -31104.89544
166 -4798.53555 33970.18933
167 17544.87292 -4798.53555
168 23124.38033 17544.87292
169 88520.91801 23124.38033
170 -9676.72894 88520.91801
171 3789.98969 -9676.72894
172 1896.40991 3789.98969
173 19519.66845 1896.40991
174 -90621.07264 19519.66845
175 3619.08642 -90621.07264
176 -31881.57742 3619.08642
177 6391.49702 -31881.57742
178 -3546.32093 6391.49702
179 36584.53921 -3546.32093
180 -20225.64155 36584.53921
181 -53786.64416 -20225.64155
182 7346.26443 -53786.64416
183 23577.71485 7346.26443
184 27453.62715 23577.71485
185 1902.23805 27453.62715
186 -688.99160 1902.23805
187 14183.65216 -688.99160
188 8877.31811 14183.65216
189 9612.83184 8877.31811
190 33443.03802 9612.83184
191 -7143.54149 33443.03802
192 -13780.70492 -7143.54149
193 -1945.28698 -13780.70492
194 -2226.26376 -1945.28698
195 5973.55413 -2226.26376
196 -23263.87462 5973.55413
197 8423.00512 -23263.87462
198 -30723.87216 8423.00512
199 -5827.89597 -30723.87216
200 5421.04471 -5827.89597
201 2045.04422 5421.04471
202 10930.84239 2045.04422
203 5027.93677 10930.84239
204 -31117.27459 5027.93677
205 -9083.39204 -31117.27459
206 -7181.22171 -9083.39204
207 42030.85434 -7181.22171
208 23084.85595 42030.85434
209 -4395.60776 23084.85595
210 13315.77138 -4395.60776
211 27018.23165 13315.77138
212 -1850.07920 27018.23165
213 -1723.03696 -1850.07920
214 -30089.90766 -1723.03696
215 -15662.17692 -30089.90766
216 -33861.50685 -15662.17692
217 6835.58091 -33861.50685
218 3584.38031 6835.58091
219 23672.53074 3584.38031
220 -19960.97052 23672.53074
221 -4089.71008 -19960.97052
222 -47016.61645 -4089.71008
223 5600.19912 -47016.61645
224 -3021.67409 5600.19912
225 4092.17988 -3021.67409
226 23116.87799 4092.17988
227 -28551.55041 23116.87799
228 -22271.36119 -28551.55041
229 -38557.48419 -22271.36119
230 -14452.89996 -38557.48419
231 -2162.87262 -14452.89996
232 -32007.23660 -2162.87262
233 -5284.79644 -32007.23660
234 -27408.94637 -5284.79644
235 -14214.57972 -27408.94637
236 49727.45922 -14214.57972
237 -5863.71759 49727.45922
238 -11638.80076 -5863.71759
239 -22970.19985 -11638.80076
240 13869.63817 -22970.19985
241 288.34720 13869.63817
242 -16622.82114 288.34720
243 -9000.10363 -16622.82114
244 -2055.53229 -9000.10363
245 -8980.70931 -2055.53229
246 -20645.33687 -8980.70931
247 19288.22496 -20645.33687
248 6553.15964 19288.22496
249 -12344.31296 6553.15964
250 14239.66948 -12344.31296
251 6600.33543 14239.66948
252 11365.84186 6600.33543
253 -2107.94167 11365.84186
254 -23644.60866 -2107.94167
255 675.56342 -23644.60866
256 -11903.42418 675.56342
257 9295.61384 -11903.42418
258 12263.89481 9295.61384
259 6989.54139 12263.89481
260 -12364.98375 6989.54139
261 5131.50778 -12364.98375
262 11627.03607 5131.50778
263 -5748.72164 11627.03607
264 -14507.48416 -5748.72164
265 8161.54450 -14507.48416
266 -22642.31296 8161.54450
267 -4945.05601 -22642.31296
268 44369.94439 -4945.05601
269 -16425.33058 44369.94439
270 -2742.37797 -16425.33058
271 732.99602 -2742.37797
272 2426.92446 732.99602
273 4247.80273 2426.92446
274 11643.56605 4247.80273
275 -14987.96964 11643.56605
276 16596.41035 -14987.96964
277 10118.00240 16596.41035
278 -3988.01104 10118.00240
279 12398.06825 -3988.01104
280 -6079.15749 12398.06825
281 16775.80914 -6079.15749
282 183.50715 16775.80914
283 12131.97943 183.50715
284 -356.27046 12131.97943
285 -478.07433 -356.27046
286 2786.60609 -478.07433
287 -281.59432 2786.60609
288 -1374.08521 -281.59432
> 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/fisher/rcomp/tmp/75j4e1355851555.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/8onvd1355851555.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/9qufb1355851555.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10utkd1355851555.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/fisher/rcomp/tmp/110n741355851555.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/fisher/rcomp/tmp/12vo2u1355851555.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/fisher/rcomp/tmp/139phk1355851555.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/fisher/rcomp/tmp/14b9c41355851555.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/fisher/rcomp/tmp/151dxk1355851555.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/fisher/rcomp/tmp/16ab6f1355851555.tab")
+ }
>
> try(system("convert tmp/1ae8w1355851555.ps tmp/1ae8w1355851555.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vn191355851555.ps tmp/2vn191355851555.png",intern=TRUE))
character(0)
> try(system("convert tmp/3e7sw1355851555.ps tmp/3e7sw1355851555.png",intern=TRUE))
character(0)
> try(system("convert tmp/45ioz1355851555.ps tmp/45ioz1355851555.png",intern=TRUE))
character(0)
> try(system("convert tmp/55rm81355851555.ps tmp/55rm81355851555.png",intern=TRUE))
character(0)
> try(system("convert tmp/6pn2x1355851555.ps tmp/6pn2x1355851555.png",intern=TRUE))
character(0)
> try(system("convert tmp/75j4e1355851555.ps tmp/75j4e1355851555.png",intern=TRUE))
character(0)
> try(system("convert tmp/8onvd1355851555.ps tmp/8onvd1355851555.png",intern=TRUE))
character(0)
> try(system("convert tmp/9qufb1355851555.ps tmp/9qufb1355851555.png",intern=TRUE))
character(0)
> try(system("convert tmp/10utkd1355851555.ps tmp/10utkd1355851555.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
14.539 1.979 16.539