R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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+ ,123
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+ ,69
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+ ,73
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+ ,15
+ ,72
+ ,88
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+ ,123
+ ,140
+ ,18
+ ,129
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+ ,15
+ ,83
+ ,97
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+ ,86
+ ,99
+ ,15
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+ ,104
+ ,12
+ ,50
+ ,60
+ ,12
+ ,62
+ ,75
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+ ,79
+ ,91
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+ ,13
+ ,82
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+ ,11
+ ,71
+ ,82
+ ,15
+ ,124
+ ,138
+ ,14
+ ,81
+ ,95
+ ,14
+ ,83
+ ,98
+ ,16
+ ,121
+ ,136
+ ,13
+ ,65
+ ,76
+ ,15
+ ,61
+ ,74
+ ,13
+ ,65
+ ,77
+ ,13
+ ,71
+ ,84
+ ,14
+ ,71
+ ,84
+ ,12
+ ,62
+ ,73
+ ,15
+ ,74
+ ,88
+ ,13
+ ,63
+ ,75
+ ,15
+ ,75
+ ,90
+ ,14
+ ,82
+ ,96
+ ,16
+ ,94
+ ,110
+ ,15
+ ,107
+ ,123
+ ,14
+ ,94
+ ,107
+ ,14
+ ,91
+ ,106
+ ,16
+ ,102
+ ,119
+ ,15
+ ,73
+ ,87
+ ,17
+ ,107
+ ,123
+ ,14
+ ,74
+ ,88
+ ,14
+ ,80
+ ,93
+ ,16
+ ,112
+ ,127
+ ,15
+ ,71
+ ,86
+ ,13
+ ,78
+ ,89
+ ,15
+ ,69
+ ,84
+ ,11
+ ,88
+ ,98
+ ,16
+ ,106
+ ,122
+ ,14
+ ,56
+ ,68
+ ,15
+ ,118
+ ,134
+ ,16
+ ,90
+ ,105
+ ,13
+ ,76
+ ,88
+ ,13
+ ,83
+ ,95
+ ,14
+ ,77
+ ,90
+ ,15
+ ,122
+ ,137
+ ,14
+ ,85
+ ,99
+ ,14
+ ,67
+ ,80
+ ,15
+ ,93
+ ,108
+ ,13
+ ,59
+ ,72
+ ,13
+ ,92
+ ,104
+ ,13
+ ,58
+ ,70
+ ,17
+ ,115
+ ,133
+ ,14
+ ,96
+ ,110
+ ,17
+ ,120
+ ,136
+ ,14
+ ,87
+ ,101
+ ,16
+ ,118
+ ,133
+ ,15
+ ,87
+ ,102
+ ,16
+ ,101
+ ,116
+ ,12
+ ,55
+ ,65
+ ,16
+ ,98
+ ,113
+ ,15
+ ,83
+ ,97
+ ,15
+ ,102
+ ,115
+ ,15
+ ,79
+ ,94)
+ ,dim=c(3
+ ,653)
+ ,dimnames=list(c('Bloeddruk'
+ ,'gewicht'
+ ,'cholesterol')
+ ,1:653))
> y <- array(NA,dim=c(3,653),dimnames=list(c('Bloeddruk','gewicht','cholesterol'),1:653))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Bloeddruk gewicht cholesterol
1 14 83 96
2 13 79 91
3 16 92 108
4 13 83 95
5 14 92 105
6 15 103 117
7 14 82 94
8 13 86 98
9 15 106 120
10 13 79 91
11 13 86 100
12 13 76 90
13 16 108 123
14 16 82 97
15 12 108 120
16 15 118 133
17 16 127 141
18 16 123 138
19 12 72 85
20 16 105 121
21 13 63 74
22 14 86 100
23 11 58 67
24 12 59 73
25 15 100 116
26 15 100 115
27 14 78 92
28 15 94 109
29 15 105 120
30 15 89 105
31 16 101 115
32 15 92 105
33 16 105 122
34 12 76 87
35 16 80 94
36 12 66 78
37 18 117 135
38 18 94 113
39 15 107 123
40 17 110 126
41 17 110 127
42 16 106 120
43 14 94 108
44 14 71 83
45 15 101 117
46 14 84 96
47 14 89 103
48 17 119 134
49 15 97 112
50 14 82 93
51 15 89 103
52 14 70 84
53 15 101 116
54 15 81 97
55 14 74 87
56 15 107 122
57 14 97 111
58 16 83 101
59 15 95 109
60 15 82 96
61 14 88 100
62 16 74 90
63 16 104 120
64 13 73 86
65 13 73 85
66 15 81 96
67 14 79 93
68 13 83 95
69 17 111 127
70 18 138 156
71 13 81 94
72 16 107 123
73 13 66 80
74 15 81 98
75 15 74 88
76 13 96 109
77 14 86 98
78 14 69 83
79 14 73 85
80 15 71 85
81 12 64 76
82 16 79 96
83 13 60 72
84 15 111 125
85 16 107 121
86 14 90 103
87 17 98 113
88 12 77 89
89 16 93 108
90 13 68 80
91 13 74 87
92 14 70 84
93 14 80 93
94 13 81 94
95 15 72 87
96 15 81 95
97 15 92 106
98 12 81 94
99 12 78 91
100 14 92 106
101 12 92 103
102 15 107 121
103 14 98 112
104 15 86 98
105 13 77 91
106 15 96 112
107 14 104 118
108 13 77 90
109 14 65 80
110 14 61 73
111 17 117 135
112 14 84 97
113 12 69 82
114 15 85 99
115 16 116 132
116 16 115 130
117 13 55 67
118 14 64 78
119 15 117 131
120 13 68 80
121 17 104 121
122 13 66 79
123 13 70 82
124 12 89 101
125 14 79 91
126 15 70 83
127 13 63 76
128 15 79 93
129 13 62 73
130 15 94 107
131 14 83 97
132 16 118 133
133 13 62 74
134 15 78 93
135 15 83 99
136 14 91 105
137 13 84 95
138 15 76 90
139 16 100 115
140 15 80 95
141 16 98 115
142 16 89 105
143 16 98 115
144 14 88 102
145 12 81 92
146 13 88 101
147 15 75 90
148 15 77 93
149 15 88 102
150 14 65 79
151 14 69 83
152 14 76 89
153 13 53 65
154 15 82 97
155 13 67 78
156 15 84 99
157 16 112 126
158 15 91 106
159 13 104 115
160 13 79 90
161 14 90 104
162 15 60 76
163 15 79 95
164 16 99 114
165 15 68 81
166 12 79 91
167 14 107 120
168 16 114 132
169 14 81 96
170 14 83 95
171 14 61 74
172 12 82 93
173 18 134 152
174 14 102 116
175 16 132 148
176 12 72 84
177 14 72 87
178 13 102 114
179 14 92 106
180 16 94 110
181 13 86 99
182 13 84 96
183 13 66 80
184 14 129 144
185 13 88 102
186 14 109 125
187 14 84 98
188 14 73 87
189 15 86 100
190 15 113 128
191 14 88 102
192 13 90 104
193 14 82 96
194 17 111 127
195 13 73 85
196 15 91 106
197 14 72 85
198 16 111 126
199 14 108 121
200 14 83 94
201 14 81 94
202 17 111 128
203 13 69 82
204 14 106 118
205 15 115 128
206 18 132 149
207 15 78 92
208 15 90 105
209 16 132 146
210 15 91 106
211 15 115 130
212 12 65 77
213 14 77 92
214 14 71 83
215 15 74 88
216 14 76 89
217 17 115 132
218 15 100 113
219 14 70 83
220 13 71 84
221 14 74 88
222 14 60 74
223 13 58 71
224 14 105 119
225 14 105 120
226 14 100 113
227 14 74 88
228 15 77 92
229 14 77 91
230 15 109 123
231 13 68 80
232 12 67 79
233 14 96 109
234 14 86 98
235 14 85 98
236 15 91 106
237 15 104 117
238 15 94 108
239 13 67 79
240 13 79 93
241 13 73 86
242 14 93 106
243 13 87 100
244 12 66 78
245 14 79 92
246 15 94 111
247 15 84 97
248 10 67 77
249 14 121 134
250 14 82 95
251 18 116 134
252 15 83 96
253 12 66 78
254 13 66 79
255 17 71 87
256 14 83 95
257 16 93 110
258 14 83 96
259 17 112 129
260 15 79 93
261 19 135 154
262 13 85 97
263 17 91 109
264 16 103 118
265 15 77 91
266 15 70 83
267 14 53 65
268 14 85 99
269 14 88 103
270 12 65 75
271 16 119 135
272 17 93 109
273 14 84 98
274 13 70 81
275 14 64 78
276 13 63 75
277 18 152 171
278 14 83 96
279 12 66 78
280 15 83 96
281 14 106 121
282 16 85 100
283 13 85 97
284 15 84 99
285 16 78 92
286 13 94 108
287 15 82 96
288 13 66 77
289 13 69 82
290 12 83 94
291 14 83 98
292 15 124 139
293 14 101 116
294 15 113 126
295 15 107 121
296 15 83 96
297 14 79 91
298 15 85 99
299 13 62 74
300 13 83 95
301 17 101 118
302 13 60 74
303 11 86 96
304 16 101 117
305 13 73 85
306 15 70 84
307 13 88 100
308 14 74 88
309 15 105 120
310 15 82 97
311 13 83 94
312 15 90 105
313 13 70 81
314 13 56 70
315 14 70 83
316 14 79 93
317 16 127 141
318 15 96 109
319 15 101 115
320 15 81 97
321 16 93 109
322 13 92 103
323 14 79 95
324 15 78 92
325 13 68 80
326 17 92 109
327 13 73 86
328 12 61 74
329 13 73 84
330 15 108 121
331 12 88 99
332 12 66 76
333 14 59 73
334 13 61 73
335 13 55 66
336 15 119 134
337 14 89 102
338 13 68 81
339 17 125 144
340 13 66 78
341 16 82 95
342 16 101 116
343 13 104 118
344 14 63 77
345 13 63 77
346 12 63 72
347 15 98 113
348 15 90 104
349 16 97 111
350 13 74 86
351 13 63 76
352 15 102 117
353 14 90 103
354 15 79 95
355 15 74 87
356 16 89 105
357 14 70 84
358 13 77 90
359 13 78 90
360 15 70 84
361 15 95 109
362 13 100 113
363 11 64 73
364 13 90 102
365 16 109 124
366 13 89 102
367 13 66 78
368 15 88 103
369 15 108 122
370 14 97 112
371 12 66 76
372 14 85 97
373 15 79 95
374 13 95 106
375 13 62 77
376 14 76 88
377 15 69 85
378 16 105 121
379 13 74 86
380 16 96 113
381 13 83 95
382 16 76 92
383 16 83 97
384 14 68 83
385 13 68 81
386 14 76 90
387 14 73 89
388 14 71 83
389 15 74 89
390 14 78 90
391 16 95 110
392 15 103 116
393 14 82 95
394 13 67 79
395 12 77 87
396 16 93 109
397 13 76 90
398 13 85 96
399 13 68 81
400 12 81 93
401 14 87 101
402 12 67 80
403 13 78 90
404 15 93 108
405 15 87 102
406 13 77 90
407 14 79 93
408 13 84 97
409 14 114 128
410 16 84 99
411 16 105 118
412 15 117 131
413 16 94 110
414 15 65 79
415 13 75 89
416 13 73 84
417 16 117 132
418 14 75 89
419 14 85 100
420 14 83 97
421 11 63 75
422 14 80 94
423 14 73 86
424 13 86 97
425 15 103 117
426 12 67 79
427 14 83 96
428 15 55 71
429 15 90 103
430 15 123 138
431 16 98 113
432 19 188 207
433 16 76 91
434 14 72 85
435 13 65 78
436 16 99 114
437 12 86 98
438 16 81 97
439 15 99 113
440 11 58 69
441 16 90 107
442 16 97 113
443 15 85 100
444 15 79 92
445 17 110 126
446 15 92 106
447 14 88 100
448 13 56 68
449 14 71 85
450 16 110 124
451 14 77 89
452 14 66 80
453 17 114 132
454 14 76 89
455 15 109 122
456 15 125 139
457 14 74 87
458 14 89 103
459 16 100 116
460 13 77 90
461 15 99 115
462 14 88 101
463 14 96 110
464 16 87 103
465 15 101 116
466 14 78 92
467 17 119 136
468 16 105 122
469 15 80 93
470 13 69 81
471 15 89 105
472 14 69 86
473 10 66 75
474 15 70 84
475 14 83 96
476 16 81 96
477 14 73 87
478 15 100 115
479 15 67 81
480 15 108 124
481 14 105 118
482 17 119 136
483 15 91 104
484 15 102 116
485 15 100 114
486 15 76 90
487 16 100 115
488 13 86 98
489 15 103 119
490 16 93 110
491 13 57 69
492 17 115 135
493 12 82 92
494 15 99 112
495 15 63 77
496 17 166 182
497 13 74 85
498 17 86 102
499 13 87 100
500 15 101 118
501 15 73 88
502 14 102 115
503 16 97 114
504 15 86 101
505 16 116 133
506 14 81 93
507 17 140 156
508 14 93 105
509 16 111 128
510 16 115 131
511 15 70 88
512 13 68 81
513 15 77 91
514 14 81 95
515 14 64 78
516 15 111 125
517 17 126 140
518 16 97 114
519 15 72 86
520 15 88 103
521 14 78 92
522 14 94 107
523 14 78 92
524 13 70 83
525 14 96 109
526 16 99 116
527 14 79 93
528 16 102 118
529 13 89 101
530 13 79 91
531 16 94 110
532 15 89 105
533 16 94 111
534 14 63 78
535 12 76 88
536 15 55 70
537 14 83 95
538 15 70 85
539 14 81 95
540 17 130 146
541 13 64 75
542 14 77 89
543 15 85 100
544 15 104 120
545 15 72 85
546 15 70 83
547 15 84 99
548 16 106 121
549 17 118 136
550 16 70 85
551 14 74 88
552 13 75 87
553 14 95 107
554 16 71 87
555 16 81 96
556 14 103 116
557 14 56 67
558 15 91 105
559 13 54 67
560 15 76 90
561 17 101 119
562 14 83 97
563 10 62 72
564 14 67 80
565 15 91 102
566 15 91 105
567 15 97 111
568 12 63 74
569 16 80 96
570 14 71 84
571 16 83 97
572 15 88 102
573 13 74 85
574 13 89 101
575 12 65 77
576 13 103 116
577 17 122 138
578 18 123 140
579 15 98 114
580 15 97 112
581 12 69 81
582 14 90 103
583 13 85 97
584 14 60 73
585 15 97 112
586 16 111 129
587 14 105 117
588 15 72 88
589 17 123 140
590 18 129 146
591 15 83 97
592 14 86 99
593 15 88 104
594 12 50 60
595 12 62 75
596 13 79 91
597 15 99 114
598 13 82 94
599 11 71 82
600 15 124 138
601 14 81 95
602 14 83 98
603 16 121 136
604 13 65 76
605 15 61 74
606 13 65 77
607 13 71 84
608 14 71 84
609 12 62 73
610 15 74 88
611 13 63 75
612 15 75 90
613 14 82 96
614 16 94 110
615 15 107 123
616 14 94 107
617 14 91 106
618 16 102 119
619 15 73 87
620 17 107 123
621 14 74 88
622 14 80 93
623 16 112 127
624 15 71 86
625 13 78 89
626 15 69 84
627 11 88 98
628 16 106 122
629 14 56 68
630 15 118 134
631 16 90 105
632 13 76 88
633 13 83 95
634 14 77 90
635 15 122 137
636 14 85 99
637 14 67 80
638 15 93 108
639 13 59 72
640 13 92 104
641 13 58 70
642 17 115 133
643 14 96 110
644 17 120 136
645 14 87 101
646 16 118 133
647 15 87 102
648 16 101 116
649 12 55 65
650 16 98 113
651 15 83 97
652 15 102 115
653 15 79 94
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) gewicht cholesterol
5.164 -0.505 0.527
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.99630 -0.45635 0.01463 0.50962 2.17932
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.16368 0.22466 22.98 <2e-16 ***
gewicht -0.50501 0.01996 -25.30 <2e-16 ***
cholesterol 0.52703 0.01888 27.91 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.7447 on 650 degrees of freedom
Multiple R-squared: 0.7315, Adjusted R-squared: 0.7306
F-statistic: 885.2 on 2 and 650 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,] 0.00902435 0.01804870 0.99097565
[2,] 0.12067009 0.24134017 0.87932991
[3,] 0.07789987 0.15579974 0.92210013
[4,] 0.03544474 0.07088948 0.96455526
[5,] 0.01691773 0.03383546 0.98308227
[6,] 0.25578059 0.51156118 0.74421941
[7,] 0.25746642 0.51493283 0.74253358
[8,] 0.19192990 0.38385979 0.80807010
[9,] 0.45226781 0.90453562 0.54773219
[10,] 0.72389629 0.55220742 0.27610371
[11,] 0.68174134 0.63651731 0.31825866
[12,] 0.72867340 0.54265320 0.27132660
[13,] 0.66603503 0.66792993 0.33396497
[14,] 0.77599178 0.44801644 0.22400822
[15,] 0.72345038 0.55309924 0.27654962
[16,] 0.79751586 0.40496829 0.20248414
[17,] 0.75740904 0.48518191 0.24259096
[18,] 0.71741334 0.56517332 0.28258666
[19,] 0.83461023 0.33077955 0.16538977
[20,] 0.81869384 0.36261231 0.18130616
[21,] 0.77750197 0.44499606 0.22249803
[22,] 0.73366122 0.53267755 0.26633878
[23,] 0.68559201 0.62881599 0.31440799
[24,] 0.63901308 0.72197384 0.36098692
[25,] 0.58945446 0.82109108 0.41054554
[26,] 0.70027482 0.59945037 0.29972518
[27,] 0.74575323 0.50849354 0.25424677
[28,] 0.70587808 0.58824384 0.29412192
[29,] 0.67431680 0.65136640 0.32568320
[30,] 0.87727852 0.24544297 0.12272148
[31,] 0.86652495 0.26695010 0.13347505
[32,] 0.86152691 0.27694619 0.13847309
[33,] 0.86081342 0.27837317 0.13918658
[34,] 0.87756470 0.24487059 0.12243530
[35,] 0.88418121 0.23163758 0.11581879
[36,] 0.86394975 0.27210051 0.13605025
[37,] 0.88414721 0.23170557 0.11585279
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[401,] 0.77712576 0.44574848 0.22287424
[402,] 0.76287108 0.47425785 0.23712892
[403,] 0.77136521 0.45726959 0.22863479
[404,] 0.79011387 0.41977226 0.20988613
[405,] 0.80693399 0.38613203 0.19306601
[406,] 0.86351992 0.27296016 0.13648008
[407,] 0.85084554 0.29830892 0.14915446
[408,] 0.83958733 0.32082533 0.16041267
[409,] 0.85061764 0.29876472 0.14938236
[410,] 0.87336560 0.25326880 0.12663440
[411,] 0.86439640 0.27120719 0.13560360
[412,] 0.85423721 0.29152558 0.14576279
[413,] 0.84194406 0.31611187 0.15805594
[414,] 0.85203561 0.29592878 0.14796439
[415,] 0.84247287 0.31505426 0.15752713
[416,] 0.91201134 0.17597733 0.08798866
[417,] 0.90462333 0.19075333 0.09537667
[418,] 0.89642697 0.20714606 0.10357303
[419,] 0.88570570 0.22858860 0.11429430
[420,] 0.87455490 0.25089020 0.12544510
[421,] 0.88622754 0.22754491 0.11377246
[422,] 0.87480725 0.25038550 0.12519275
[423,] 0.86287940 0.27424120 0.13712060
[424,] 0.87186449 0.25627103 0.12813551
[425,] 0.87333668 0.25332664 0.12666332
[426,] 0.87372327 0.25255347 0.12627673
[427,] 0.86270319 0.27459362 0.13729681
[428,] 0.88398464 0.23203072 0.11601536
[429,] 0.87474562 0.25050877 0.12525438
[430,] 0.86841063 0.26317874 0.13158937
[431,] 0.86817078 0.26365843 0.13182922
[432,] 0.90116410 0.19767180 0.09883590
[433,] 0.89754282 0.20491436 0.10245718
[434,] 0.88772683 0.22454635 0.11227317
[435,] 0.91263143 0.17473714 0.08736857
[436,] 0.90292893 0.19414214 0.09707107
[437,] 0.89354848 0.21290304 0.10645152
[438,] 0.88212214 0.23575572 0.11787786
[439,] 0.90009898 0.19980204 0.09990102
[440,] 0.90844372 0.18311256 0.09155628
[441,] 0.90122284 0.19755433 0.09877716
[442,] 0.89576894 0.20846211 0.10423106
[443,] 0.88535951 0.22928098 0.11464049
[444,] 0.87389019 0.25221962 0.12610981
[445,] 0.88553017 0.22893967 0.11446983
[446,] 0.88606636 0.22786727 0.11393364
[447,] 0.87408444 0.25183113 0.12591556
[448,] 0.86143736 0.27712529 0.13856264
[449,] 0.84926401 0.30147198 0.15073599
[450,] 0.84367656 0.31264687 0.15632344
[451,] 0.83065198 0.33869604 0.16934802
[452,] 0.81744414 0.36511171 0.18255586
[453,] 0.80966014 0.38067972 0.19033986
[454,] 0.79383893 0.41232214 0.20616107
[455,] 0.79562290 0.40875419 0.20437710
[456,] 0.79775978 0.40448044 0.20224022
[457,] 0.77998856 0.44002288 0.22001144
[458,] 0.77747761 0.44504479 0.22252239
[459,] 0.76617778 0.46764444 0.23382222
[460,] 0.75018445 0.49963109 0.24981555
[461,] 0.73392584 0.53214833 0.26607416
[462,] 0.71638866 0.56722268 0.28361134
[463,] 0.70213860 0.59572279 0.29786140
[464,] 0.73330818 0.53338364 0.26669182
[465,] 0.71297943 0.57404114 0.28702057
[466,] 0.70481178 0.59037643 0.29518822
[467,] 0.79319912 0.41360176 0.20680088
[468,] 0.84339076 0.31321848 0.15660924
[469,] 0.84752935 0.30494130 0.15247065
[470,] 0.83247000 0.33505999 0.16753000
[471,] 0.85107566 0.29784868 0.14892434
[472,] 0.83753413 0.32493174 0.16246587
[473,] 0.82399700 0.35200599 0.17600300
[474,] 0.83201154 0.33597691 0.16798846
[475,] 0.84393761 0.31212479 0.15606239
[476,] 0.83210618 0.33578764 0.16789382
[477,] 0.81803070 0.36393859 0.18196930
[478,] 0.82796635 0.34406730 0.17203365
[479,] 0.81220371 0.37559259 0.18779629
[480,] 0.79614515 0.40770971 0.20385485
[481,] 0.79535716 0.40928568 0.20464284
[482,] 0.79435768 0.41128465 0.20564232
[483,] 0.78267586 0.43464827 0.21732414
[484,] 0.79004155 0.41991690 0.20995845
[485,] 0.77207303 0.45585394 0.22792697
[486,] 0.75301665 0.49396670 0.24698335
[487,] 0.78756669 0.42486663 0.21243331
[488,] 0.77162638 0.45674725 0.22837362
[489,] 0.77358608 0.45282785 0.22641392
[490,] 0.78857361 0.42285277 0.21142639
[491,] 0.77033085 0.45933829 0.22966915
[492,] 0.75428658 0.49142684 0.24571342
[493,] 0.81224345 0.37551309 0.18775655
[494,] 0.82635942 0.34728115 0.17364058
[495,] 0.86585169 0.26829662 0.13414831
[496,] 0.85280672 0.29438655 0.14719328
[497,] 0.83974280 0.32051440 0.16025720
[498,] 0.82570042 0.34859916 0.17429958
[499,] 0.80791499 0.38417003 0.19208501
[500,] 0.80668892 0.38662217 0.19331108
[501,] 0.80335916 0.39328168 0.19664084
[502,] 0.78757586 0.42484828 0.21242414
[503,] 0.77413524 0.45172953 0.22586476
[504,] 0.76781558 0.46436884 0.23218442
[505,] 0.74767194 0.50465612 0.25232806
[506,] 0.79650053 0.40699894 0.20349947
[507,] 0.79045459 0.41909081 0.20954541
[508,] 0.78724349 0.42551303 0.21275651
[509,] 0.77331452 0.45337096 0.22668548
[510,] 0.75252249 0.49495503 0.24747751
[511,] 0.73011781 0.53976437 0.26988219
[512,] 0.82748102 0.34503796 0.17251898
[513,] 0.81442800 0.37114401 0.18557200
[514,] 0.81538883 0.36922234 0.18461117
[515,] 0.79653551 0.40692898 0.20346449
[516,] 0.78126619 0.43746761 0.21873381
[517,] 0.76012019 0.47975963 0.23987981
[518,] 0.74341037 0.51317926 0.25658963
[519,] 0.73951993 0.52096014 0.26048007
[520,] 0.71653971 0.56692058 0.28346029
[521,] 0.70083212 0.59833576 0.29916788
[522,] 0.68314602 0.63370797 0.31685398
[523,] 0.65761528 0.68476944 0.34238472
[524,] 0.64031600 0.71936801 0.35968400
[525,] 0.61676835 0.76646329 0.38323165
[526,] 0.59158875 0.81682250 0.40841125
[527,] 0.58928492 0.82143015 0.41071508
[528,] 0.56853378 0.86293244 0.43146622
[529,] 0.56835047 0.86329905 0.43164953
[530,] 0.61800790 0.76398420 0.38199210
[531,] 0.59981249 0.80037502 0.40018751
[532,] 0.59366552 0.81266897 0.40633448
[533,] 0.56700084 0.86599833 0.43299916
[534,] 0.54908248 0.90183504 0.45091752
[535,] 0.53932272 0.92135456 0.46067728
[536,] 0.52570959 0.94858081 0.47429041
[537,] 0.52807134 0.94385733 0.47192866
[538,] 0.49903737 0.99807473 0.50096263
[539,] 0.52170314 0.95659371 0.47829686
[540,] 0.58073793 0.83852414 0.41926207
[541,] 0.64533122 0.70933756 0.35466878
[542,] 0.61707380 0.76585240 0.38292620
[543,] 0.60500392 0.78999217 0.39499608
[544,] 0.58378863 0.83242273 0.41621137
[545,] 0.62919227 0.74161547 0.37080773
[546,] 0.60478251 0.79043498 0.39521749
[547,] 0.57594243 0.84811515 0.42405757
[548,] 0.55931851 0.88136298 0.44068149
[549,] 0.54828905 0.90342189 0.45171095
[550,] 0.57513146 0.84973709 0.42486854
[551,] 0.54694166 0.90611668 0.45305834
[552,] 0.69309459 0.61381082 0.30690541
[553,] 0.67395857 0.65208286 0.32604143
[554,] 0.64962783 0.70074435 0.35037217
[555,] 0.64717598 0.70564805 0.35282402
[556,] 0.61726623 0.76546753 0.38273377
[557,] 0.59621359 0.80757282 0.40378641
[558,] 0.73537203 0.52925595 0.26462797
[559,] 0.71716379 0.56567242 0.28283621
[560,] 0.89214704 0.21570591 0.10785296
[561,] 0.88205251 0.23589498 0.11794749
[562,] 0.86866317 0.26267366 0.13133683
[563,] 0.85323097 0.29353805 0.14676903
[564,] 0.84073186 0.31853628 0.15926814
[565,] 0.82490568 0.35018864 0.17509432
[566,] 0.89915649 0.20168702 0.10084351
[567,] 0.89172962 0.21654076 0.10827038
[568,] 0.88440578 0.23118845 0.11559422
[569,] 0.86974381 0.26051238 0.13025619
[570,] 0.88109296 0.23781409 0.11890704
[571,] 0.90879590 0.18240820 0.09120410
[572,] 0.91088167 0.17823666 0.08911833
[573,] 0.93667999 0.12664001 0.06332001
[574,] 0.93931456 0.12137087 0.06068544
[575,] 0.92836699 0.14326603 0.07163301
[576,] 0.94227659 0.11544682 0.05772341
[577,] 0.93060318 0.13879364 0.06939682
[578,] 0.91979409 0.16041182 0.08020591
[579,] 0.91337650 0.17324699 0.08662350
[580,] 0.89873400 0.20253199 0.10126600
[581,] 0.92683585 0.14632831 0.07316415
[582,] 0.91751262 0.16497476 0.08248738
[583,] 0.90954994 0.18090011 0.09045006
[584,] 0.89331817 0.21336366 0.10668183
[585,] 0.91953099 0.16093803 0.08046901
[586,] 0.91453863 0.17092273 0.08546137
[587,] 0.89843833 0.20312333 0.10156167
[588,] 0.89867968 0.20264063 0.10132032
[589,] 0.88729144 0.22541711 0.11270856
[590,] 0.95030425 0.09939149 0.04969575
[591,] 0.93916033 0.12167935 0.06083967
[592,] 0.92727132 0.14545735 0.07272868
[593,] 0.91265981 0.17468039 0.08734019
[594,] 0.96124065 0.07751870 0.03875935
[595,] 0.95147527 0.09704946 0.04852473
[596,] 0.94542029 0.10915943 0.05457971
[597,] 0.96384441 0.07231117 0.03615559
[598,] 0.96086517 0.07826965 0.03913483
[599,] 0.95656629 0.08686741 0.04343371
[600,] 0.97950380 0.04099239 0.02049620
[601,] 0.97296180 0.05407640 0.02703820
[602,] 0.97491207 0.05017586 0.02508793
[603,] 0.96808421 0.06383158 0.03191579
[604,] 0.96271366 0.07457268 0.03728634
[605,] 0.96021656 0.07956687 0.03978344
[606,] 0.94850004 0.10299992 0.05149996
[607,] 0.93403668 0.13192664 0.06596332
[608,] 0.92584373 0.14831254 0.07415627
[609,] 0.90736430 0.18527141 0.09263570
[610,] 0.92797024 0.14405953 0.07202976
[611,] 0.90806985 0.18386031 0.09193015
[612,] 0.95088607 0.09822785 0.04911393
[613,] 0.95228313 0.09543374 0.04771687
[614,] 0.94644244 0.10711512 0.05355756
[615,] 0.95978022 0.08043956 0.04021978
[616,] 0.95347523 0.09304955 0.04652477
[617,] 0.93786475 0.12427050 0.06213525
[618,] 0.93395161 0.13209678 0.06604839
[619,] 0.91356411 0.17287177 0.08643589
[620,] 0.90169652 0.19660697 0.09830348
[621,] 0.87462175 0.25075650 0.12537825
[622,] 0.90940169 0.18119662 0.09059831
[623,] 0.87965909 0.24068182 0.12034091
[624,] 0.91473410 0.17053180 0.08526590
[625,] 0.96603071 0.06793857 0.03396929
[626,] 0.97400281 0.05199438 0.02599719
[627,] 0.96207736 0.07584528 0.03792264
[628,] 0.95091470 0.09817061 0.04908530
[629,] 0.92947237 0.14105526 0.07052763
[630,] 0.95680320 0.08639360 0.04319680
[631,] 0.95273179 0.09453641 0.04726821
[632,] 0.94130944 0.11738113 0.05869056
[633,] 0.91595700 0.16808601 0.08404300
[634,] 0.88766012 0.22467976 0.11233988
[635,] 0.92746536 0.14506928 0.07253464
[636,] 0.88449992 0.23100016 0.11550008
[637,] 0.84551468 0.30897064 0.15448532
[638,] 0.95296461 0.09407077 0.04703539
[639,] 0.91490482 0.17019036 0.08509518
[640,] 0.97770132 0.04459737 0.02229868
[641,] 0.97988750 0.04022501 0.02011250
[642,] 0.98716837 0.02566327 0.01283163
> postscript(file="/var/www/rcomp/tmp/1f7a31321621655.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2np0n1321621655.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3r46i1321621655.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/40ems1321621655.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/58rmf1321621655.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 = 653
Frequency = 1
1 2 3 4 5 6
0.157302057 -0.227590294 0.378039443 -0.315670739 -0.040878945 0.189872626
7 8 9 10 11 12
0.706349372 -0.381731073 0.123812292 -0.227590294 -1.435785481 -1.215584368
13 14 15 16 17 18
0.552744865 1.125267760 -1.866173523 -0.667456248 0.661389954 0.222443195
19 20 21 22 23 24
-1.600476719 0.091777995 0.651758691 -0.435785481 -0.184086344 -1.841242475
25 26 27 28 29 30
-0.798121448 -0.271094244 -0.259624591 -0.138973576 -0.381194801 -0.555900223
31 32 33 34 35 36
1.233912849 0.959121055 -0.435249209 -0.634502756 1.696335187 -0.941328847
37 38 39 40 41 42
0.773482251 0.752917608 -0.952262227 0.981677439 0.454650235 1.123812292
43 44 45 46 47 48
-0.611946372 0.948570597 -0.820141559 0.662309149 -0.501845815 1.310523641
49 50 51 52 53 54
-0.205033910 1.233376576 0.498154185 -0.083463700 -0.293114355 -0.379739333
55 56 57 58 59 60
0.355483059 -0.425235023 -0.678006706 -0.477833963 0.366033517 0.652294964
61 62 63 64 65 66
0.574228704 0.774401447 0.113798107 -0.622496830 -0.095469626 0.147287871
67 68 69 70 71 72
-0.281644702 -0.315670739 0.959657327 0.311059913 -0.798657721 0.047737773
73 74 75 76 77 78
-0.995383255 -0.906766537 0.828455855 -1.128959391 0.618268927 -0.061443589
79 80 81 82 83 84
0.904530374 0.894516189 -0.897288624 0.137273686 0.190791821 0.013711735
85 86 87 88 89 90
1.101792181 0.003161277 1.772945979 -1.183550071 0.883046535 0.014630931
91 92 93 94 95 96
-0.644516941 -0.083463700 0.223362391 -0.798657721 0.345468873 0.674315075
97 98 99 100 101 102
0.432093851 -1.798657721 -1.732597387 -0.567906149 -0.986824537 0.101792181
103 104 105 106 107 108
-0.700026817 1.618268927 -1.237604479 -0.710041003 -0.832147485 -0.710577275
109 110 111 112 113 114
-0.500390347 1.168771710 -0.226517749 0.135281945 -1.534416385 0.586234630
115 116 117 118 119 120
-0.150443229 0.398604086 0.300892378 0.048656968 -0.118408933 0.014630931
121 122 123 124 125 126
0.586770903 -0.468356051 -0.029409292 -1.447791407 0.772409706 1.443563504
127 128 129 130 131 132
-0.402295717 0.718355298 0.673778803 0.915080832 -0.369725147 0.332543752
133 134 135 136 137 138
0.146751599 0.213348205 -0.423779555 -0.545886038 0.189336353 0.784415632
139 140 141 142 143 144
0.728905756 0.169307983 -0.281108429 0.444099777 -0.281108429 -0.479825704
145 146 147 148 149 150
-0.744603313 -0.952798500 0.279408539 -0.291658887 0.520174296 0.026636857
151 152 153 154 155 156
-0.061443589 0.311442836 0.344932601 0.125267760 0.563678246 0.081227537
157 158 159 160 161 162
0.991691624 -0.072913242 -0.251065873 0.299436910 -0.523865927 0.082683005
163 164 165 166 167 168
-0.335699110 0.750925867 1.487603727 -1.227590294 -0.371180615 -1.160457415
169 170 171 172 173 174
-0.852712129 0.684329261 0.641744506 -0.766623424 0.399140359 -0.788107263
175 176 177 178 179 180
-0.502765011 -1.073449515 -0.654531127 -0.734052855 -0.567906149 0.333999220
181 182 183 184 185 186
-0.908758277 -0.337690851 -0.995383255 -1.909677473 -1.479825704 -1.996302450
187 188 189 190 191 192
-0.391745259 -0.149524034 0.564214519 -0.557355691 -0.479825704 -1.523865927
193 194 195 196 197 198
-0.347705036 0.959657327 -0.095469626 -0.072913242 0.399523281 0.486684531
199 200 201 202 203 204
-0.393200727 1.211356465 0.201342279 0.432630123 -0.534416385 0.177866700
205 206 207 208 209 210
0.452658494 0.970207785 0.740375409 -0.050893131 0.551289397 -0.072913242
211 212 213 214 215 216
-0.601395914 -0.919308735 -0.764631683 0.948570597 0.828455855 0.311442836
217 218 219 220 221 222
0.344549678 0.782960164 0.443563504 -0.578456607 -0.171544145 0.136737413
223 224 225 226 227 228
-0.292195160 -0.854167597 -1.381194801 -0.217039836 -0.171544145 0.235368317
229 230 231 232 233 234
-0.237604479 0.057751958 0.014630931 -0.963348958 -0.128959391 0.618268927
235 236 237 238 239 240
0.113261834 -0.072913242 0.694879719 0.388053628 0.036651042 -1.281644702
241 242 243 244 245 246
-0.622496830 -0.062899057 -0.930778389 -0.941328847 0.245382502 -1.193027984
247 248 249 250 251 252
1.135281945 -1.909294550 -0.679462174 0.179322168 0.795502363 1.157302057
253 254 255 256 257 258
-0.941328847 -0.468356051 1.840461781 0.684329261 -0.171007873 0.157302057
259 260 261 262 263 264
0.410610012 0.718355298 0.850093043 -0.359710962 0.346005146 0.662845422
265 266 267 268 269 270
0.762395521 1.443563504 1.344932601 -0.413765370 -1.006852908 0.134745673
271 272 273 274 275 276
-0.216503563 1.356019331 -0.391745259 0.497617912 0.048656968 0.124731487
277 278 279 280 281 282
-0.524248849 0.157302057 -0.941328847 1.157302057 -1.403214912 1.059207426
283 284 285 286 287 288
-0.359710962 0.081227537 1.740375409 -1.611946372 0.652294964 0.585698357
289 290 291 292 293 294
-0.534416385 -0.788643535 -0.896752351 -0.799576916 -1.293114355 0.496698717
295 296 297 298 299 300
0.101792181 1.157302057 0.772409706 0.586234630 0.146751599 -0.315670739
301 302 303 304 305 306
0.652831237 -0.863262587 -1.327676665 0.179858441 -0.095469626 0.916536300
307 308 309 310 311 312
-0.425771296 -0.171544145 -0.381194801 0.125267760 0.211356465 -0.050893131
313 314 315 316 317 318
0.497617912 -0.775182141 0.443563504 -0.281644702 0.661389954 0.871040609
319 320 321 322 323 324
0.233912849 -0.379739333 0.356019331 0.013175463 -1.335699110 0.740375409
325 326 327 328 329 330
0.014630931 0.851012239 -0.622496830 -1.358255494 0.431557578 0.606799273
331 332 333 334 335 336
-0.898744092 0.112725561 0.158757525 0.168771710 0.827919582 -0.689476359
337 338 339 340 341 342
0.025181389 -0.512396273 -0.929705843 0.058671153 2.179322168 0.706885645
343 344 345 346 347 348
-1.832147485 0.070677079 -0.929322921 0.705813099 -0.227054021 0.476134073
349 350 351 352 353 354
1.321993294 -0.117489737 -0.402295717 -0.315134467 0.003161277 -0.335699110
355 356 357 358 359 360
1.355483059 0.444099777 -0.083463700 -0.710577275 -0.205570183 0.916536300
361 362 363 364 365 366
0.366033517 -1.217039836 -0.316207012 -0.469811519 0.530724754 -0.974818611
367 368 369 370 371 372
0.058671153 -0.006852908 0.079772069 -1.205033910 0.112725561 0.640289038
373 374 375 376 377 378
-0.335699110 -0.052884871 -1.434330013 0.838470040 -0.115497997 0.091777995
379 380 381 382 383 384
-0.117489737 -0.237068207 -0.315670739 0.730361224 1.630274853 -0.566450681
385 386 387 388 389 390
-0.512396273 -0.215584368 -1.203578442 0.948570597 0.301428651 0.794429817
391 392 393 394 395 396
0.839006313 0.716899830 0.179322168 0.036651042 -0.129495663 0.356019331
397 398 399 400 401 402
-1.215584368 0.167316242 -0.512396273 -1.271630517 -0.457805593 -1.490376162
403 404 405 406 407 408
-0.205570183 -0.116953465 0.015167203 -0.710577275 -0.281644702 -0.864718055
409 410 411 412 413 414
-1.052348599 1.081227537 1.672859607 -0.118408933 0.333999220 1.026636857
415 416 417 418 419 420
-1.193564257 0.431557578 0.354563863 -0.193564257 -0.940792574 -0.369725147
421 422 423 424 425 426
-1.875268513 -0.303664813 0.377503170 0.145296131 0.189872626 -0.963348958
427 428 429 430 431 432
0.157302057 0.192783562 1.003161277 -0.777556805 0.772945979 -0.316972857
433 434 435 436 437 438
1.257388428 0.399523281 -0.446335939 0.750925867 -1.381731073 0.620260667
439 440 441 442 443 444
0.277953071 -1.238140752 -0.104947539 0.267938886 0.059207426 1.245382502
445 446 447 448 449 450
0.981677439 0.432093851 0.574228704 0.278872267 -0.105483811 1.035731847
451 452 453 454 455 456
0.816449929 0.004616745 -0.160457415 0.311442836 0.584779162 -0.294569823
457 458 459 460 461 462
0.355483059 -0.501845815 0.201878552 -0.710577275 -0.776101337 0.047201500
463 464 465 466 467 468
-0.655986595 0.488139999 -0.293114355 -0.259624591 0.256469233 -0.435249209
469 470 471 472 473 474
1.223362391 -0.007389181 -0.555900223 -1.642525201 -1.360247235 0.916536300
475 476 477 478 479 480
0.157302057 1.147287871 -0.149524034 -0.271094244 0.982596634 -0.974282339
481 482 483 484 485 486
-0.327140393 0.256469233 0.981141166 0.211892737 0.255932960 0.784415632
487 488 489 490 491 492
0.728905756 -0.381731073 -0.864181782 -0.171007873 0.256852155 -1.236531934
493 494 495 496 497 498
-0.239596220 0.804980275 1.070677079 -0.251448796 0.409537467 1.510160111
499 500 501 502 503 504
-0.930778389 -1.347168763 0.323448762 -0.261080059 -0.259088318 0.037187315
505 506 507 508 509 510
-0.677470433 0.728369483 0.321074099 0.464128147 -0.567369877 -0.128423118
511 512 513 514 515 516
-1.191572516 -0.512396273 0.762395521 -0.325684925 0.048656968 0.013711735
517 518 519 520 521 522
1.683410065 -0.259088318 0.872496077 -0.006852908 -0.259624591 -0.084919168
523 524 525 526 527 528
-0.259624591 -0.556436496 -0.128959391 -0.303128541 -0.281644702 0.157838329
529 530 531 532 533 534
-0.447791407 -0.227590294 0.333999220 -0.555900223 -0.193027984 -0.456350125
535 536 537 538 539 540
-1.161529960 0.719810766 0.684329261 0.389509096 -0.325684925 0.541275212
541 542 543 544 545 546
0.629738580 0.816449929 0.059207426 -0.886201893 1.399523281 1.443563504
547 548 549 550 551 552
0.081227537 0.596785088 -0.248537860 1.389509096 -0.171544145 -0.139509849
553 554 555 556 557 558
0.420087925 0.840461781 1.147287871 -0.283100170 1.805899471 0.454113962
559 560 561 562 563 564
-0.204114715 0.784415632 0.125804033 -0.369725147 -1.799193993 0.509623838
565 566 567 568 569 570
2.035195574 0.454113962 0.321993294 -0.348241309 0.642280779 0.421543393
571 572 573 574 575 576
1.630274853 0.520174296 0.409537467 -0.447791407 -0.919308735 -1.283100170
577 578 579 580 581 582
0.717436103 1.168388787 -0.754081225 -0.205033910 -1.007389181 0.003161277
583 584 585 586 587 588
-0.359710962 0.663764617 -0.205033910 -1.094397081 0.199886811 -0.181558331
589 590 591 592 593 594
0.168388787 1.036268119 0.630274853 0.091241723 -0.533880112 0.465047343
595 596 597 598 599 600
-1.380275605 -0.227590294 -0.249074133 -0.293650628 -1.524402199 -0.272549712
601 602 603 604 605 606
-0.325684925 -0.896752351 0.266483418 0.607718469 1.641744506 0.080691265
607 608 609 610 611 612
-0.578456607 0.421543393 -0.326221197 0.828455855 0.124731487 0.279408539
613 614 615 616 617 618
-0.347705036 0.333999220 -0.952262227 -0.084919168 -1.072913242 -0.369188875
619 620 621 622 623 624
0.850475966 1.047737773 -0.171544145 0.223362391 0.464664420 0.367488985
625 626 627 628 629 630
0.321457021 0.411529207 -1.371716888 0.069757884 1.278872267 -1.194483452
631 632 633 634 635 636
0.949106869 -0.161529960 -0.315670739 0.289422725 -0.755536693 -0.413765370
637 638 639 640 641 642
0.509623838 -0.116953465 -0.314215271 -0.513851741 0.234832044 -0.182477526
643 644 645 646 647 648
-0.655986595 0.761476325 -0.457805593 0.332543752 0.015167203 0.706885645
649 650 651 652 653
0.354946786 0.772945979 0.630274853 0.738919941 0.191328094
> postscript(file="/var/www/rcomp/tmp/6crfc1321621655.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 = 653
Frequency = 1
lag(myerror, k = 1) myerror
0 0.157302057 NA
1 -0.227590294 0.157302057
2 0.378039443 -0.227590294
3 -0.315670739 0.378039443
4 -0.040878945 -0.315670739
5 0.189872626 -0.040878945
6 0.706349372 0.189872626
7 -0.381731073 0.706349372
8 0.123812292 -0.381731073
9 -0.227590294 0.123812292
10 -1.435785481 -0.227590294
11 -1.215584368 -1.435785481
12 0.552744865 -1.215584368
13 1.125267760 0.552744865
14 -1.866173523 1.125267760
15 -0.667456248 -1.866173523
16 0.661389954 -0.667456248
17 0.222443195 0.661389954
18 -1.600476719 0.222443195
19 0.091777995 -1.600476719
20 0.651758691 0.091777995
21 -0.435785481 0.651758691
22 -0.184086344 -0.435785481
23 -1.841242475 -0.184086344
24 -0.798121448 -1.841242475
25 -0.271094244 -0.798121448
26 -0.259624591 -0.271094244
27 -0.138973576 -0.259624591
28 -0.381194801 -0.138973576
29 -0.555900223 -0.381194801
30 1.233912849 -0.555900223
31 0.959121055 1.233912849
32 -0.435249209 0.959121055
33 -0.634502756 -0.435249209
34 1.696335187 -0.634502756
35 -0.941328847 1.696335187
36 0.773482251 -0.941328847
37 0.752917608 0.773482251
38 -0.952262227 0.752917608
39 0.981677439 -0.952262227
40 0.454650235 0.981677439
41 1.123812292 0.454650235
42 -0.611946372 1.123812292
43 0.948570597 -0.611946372
44 -0.820141559 0.948570597
45 0.662309149 -0.820141559
46 -0.501845815 0.662309149
47 1.310523641 -0.501845815
48 -0.205033910 1.310523641
49 1.233376576 -0.205033910
50 0.498154185 1.233376576
51 -0.083463700 0.498154185
52 -0.293114355 -0.083463700
53 -0.379739333 -0.293114355
54 0.355483059 -0.379739333
55 -0.425235023 0.355483059
56 -0.678006706 -0.425235023
57 -0.477833963 -0.678006706
58 0.366033517 -0.477833963
59 0.652294964 0.366033517
60 0.574228704 0.652294964
61 0.774401447 0.574228704
62 0.113798107 0.774401447
63 -0.622496830 0.113798107
64 -0.095469626 -0.622496830
65 0.147287871 -0.095469626
66 -0.281644702 0.147287871
67 -0.315670739 -0.281644702
68 0.959657327 -0.315670739
69 0.311059913 0.959657327
70 -0.798657721 0.311059913
71 0.047737773 -0.798657721
72 -0.995383255 0.047737773
73 -0.906766537 -0.995383255
74 0.828455855 -0.906766537
75 -1.128959391 0.828455855
76 0.618268927 -1.128959391
77 -0.061443589 0.618268927
78 0.904530374 -0.061443589
79 0.894516189 0.904530374
80 -0.897288624 0.894516189
81 0.137273686 -0.897288624
82 0.190791821 0.137273686
83 0.013711735 0.190791821
84 1.101792181 0.013711735
85 0.003161277 1.101792181
86 1.772945979 0.003161277
87 -1.183550071 1.772945979
88 0.883046535 -1.183550071
89 0.014630931 0.883046535
90 -0.644516941 0.014630931
91 -0.083463700 -0.644516941
92 0.223362391 -0.083463700
93 -0.798657721 0.223362391
94 0.345468873 -0.798657721
95 0.674315075 0.345468873
96 0.432093851 0.674315075
97 -1.798657721 0.432093851
98 -1.732597387 -1.798657721
99 -0.567906149 -1.732597387
100 -0.986824537 -0.567906149
101 0.101792181 -0.986824537
102 -0.700026817 0.101792181
103 1.618268927 -0.700026817
104 -1.237604479 1.618268927
105 -0.710041003 -1.237604479
106 -0.832147485 -0.710041003
107 -0.710577275 -0.832147485
108 -0.500390347 -0.710577275
109 1.168771710 -0.500390347
110 -0.226517749 1.168771710
111 0.135281945 -0.226517749
112 -1.534416385 0.135281945
113 0.586234630 -1.534416385
114 -0.150443229 0.586234630
115 0.398604086 -0.150443229
116 0.300892378 0.398604086
117 0.048656968 0.300892378
118 -0.118408933 0.048656968
119 0.014630931 -0.118408933
120 0.586770903 0.014630931
121 -0.468356051 0.586770903
122 -0.029409292 -0.468356051
123 -1.447791407 -0.029409292
124 0.772409706 -1.447791407
125 1.443563504 0.772409706
126 -0.402295717 1.443563504
127 0.718355298 -0.402295717
128 0.673778803 0.718355298
129 0.915080832 0.673778803
130 -0.369725147 0.915080832
131 0.332543752 -0.369725147
132 0.146751599 0.332543752
133 0.213348205 0.146751599
134 -0.423779555 0.213348205
135 -0.545886038 -0.423779555
136 0.189336353 -0.545886038
137 0.784415632 0.189336353
138 0.728905756 0.784415632
139 0.169307983 0.728905756
140 -0.281108429 0.169307983
141 0.444099777 -0.281108429
142 -0.281108429 0.444099777
143 -0.479825704 -0.281108429
144 -0.744603313 -0.479825704
145 -0.952798500 -0.744603313
146 0.279408539 -0.952798500
147 -0.291658887 0.279408539
148 0.520174296 -0.291658887
149 0.026636857 0.520174296
150 -0.061443589 0.026636857
151 0.311442836 -0.061443589
152 0.344932601 0.311442836
153 0.125267760 0.344932601
154 0.563678246 0.125267760
155 0.081227537 0.563678246
156 0.991691624 0.081227537
157 -0.072913242 0.991691624
158 -0.251065873 -0.072913242
159 0.299436910 -0.251065873
160 -0.523865927 0.299436910
161 0.082683005 -0.523865927
162 -0.335699110 0.082683005
163 0.750925867 -0.335699110
164 1.487603727 0.750925867
165 -1.227590294 1.487603727
166 -0.371180615 -1.227590294
167 -1.160457415 -0.371180615
168 -0.852712129 -1.160457415
169 0.684329261 -0.852712129
170 0.641744506 0.684329261
171 -0.766623424 0.641744506
172 0.399140359 -0.766623424
173 -0.788107263 0.399140359
174 -0.502765011 -0.788107263
175 -1.073449515 -0.502765011
176 -0.654531127 -1.073449515
177 -0.734052855 -0.654531127
178 -0.567906149 -0.734052855
179 0.333999220 -0.567906149
180 -0.908758277 0.333999220
181 -0.337690851 -0.908758277
182 -0.995383255 -0.337690851
183 -1.909677473 -0.995383255
184 -1.479825704 -1.909677473
185 -1.996302450 -1.479825704
186 -0.391745259 -1.996302450
187 -0.149524034 -0.391745259
188 0.564214519 -0.149524034
189 -0.557355691 0.564214519
190 -0.479825704 -0.557355691
191 -1.523865927 -0.479825704
192 -0.347705036 -1.523865927
193 0.959657327 -0.347705036
194 -0.095469626 0.959657327
195 -0.072913242 -0.095469626
196 0.399523281 -0.072913242
197 0.486684531 0.399523281
198 -0.393200727 0.486684531
199 1.211356465 -0.393200727
200 0.201342279 1.211356465
201 0.432630123 0.201342279
202 -0.534416385 0.432630123
203 0.177866700 -0.534416385
204 0.452658494 0.177866700
205 0.970207785 0.452658494
206 0.740375409 0.970207785
207 -0.050893131 0.740375409
208 0.551289397 -0.050893131
209 -0.072913242 0.551289397
210 -0.601395914 -0.072913242
211 -0.919308735 -0.601395914
212 -0.764631683 -0.919308735
213 0.948570597 -0.764631683
214 0.828455855 0.948570597
215 0.311442836 0.828455855
216 0.344549678 0.311442836
217 0.782960164 0.344549678
218 0.443563504 0.782960164
219 -0.578456607 0.443563504
220 -0.171544145 -0.578456607
221 0.136737413 -0.171544145
222 -0.292195160 0.136737413
223 -0.854167597 -0.292195160
224 -1.381194801 -0.854167597
225 -0.217039836 -1.381194801
226 -0.171544145 -0.217039836
227 0.235368317 -0.171544145
228 -0.237604479 0.235368317
229 0.057751958 -0.237604479
230 0.014630931 0.057751958
231 -0.963348958 0.014630931
232 -0.128959391 -0.963348958
233 0.618268927 -0.128959391
234 0.113261834 0.618268927
235 -0.072913242 0.113261834
236 0.694879719 -0.072913242
237 0.388053628 0.694879719
238 0.036651042 0.388053628
239 -1.281644702 0.036651042
240 -0.622496830 -1.281644702
241 -0.062899057 -0.622496830
242 -0.930778389 -0.062899057
243 -0.941328847 -0.930778389
244 0.245382502 -0.941328847
245 -1.193027984 0.245382502
246 1.135281945 -1.193027984
247 -1.909294550 1.135281945
248 -0.679462174 -1.909294550
249 0.179322168 -0.679462174
250 0.795502363 0.179322168
251 1.157302057 0.795502363
252 -0.941328847 1.157302057
253 -0.468356051 -0.941328847
254 1.840461781 -0.468356051
255 0.684329261 1.840461781
256 -0.171007873 0.684329261
257 0.157302057 -0.171007873
258 0.410610012 0.157302057
259 0.718355298 0.410610012
260 0.850093043 0.718355298
261 -0.359710962 0.850093043
262 0.346005146 -0.359710962
263 0.662845422 0.346005146
264 0.762395521 0.662845422
265 1.443563504 0.762395521
266 1.344932601 1.443563504
267 -0.413765370 1.344932601
268 -1.006852908 -0.413765370
269 0.134745673 -1.006852908
270 -0.216503563 0.134745673
271 1.356019331 -0.216503563
272 -0.391745259 1.356019331
273 0.497617912 -0.391745259
274 0.048656968 0.497617912
275 0.124731487 0.048656968
276 -0.524248849 0.124731487
277 0.157302057 -0.524248849
278 -0.941328847 0.157302057
279 1.157302057 -0.941328847
280 -1.403214912 1.157302057
281 1.059207426 -1.403214912
282 -0.359710962 1.059207426
283 0.081227537 -0.359710962
284 1.740375409 0.081227537
285 -1.611946372 1.740375409
286 0.652294964 -1.611946372
287 0.585698357 0.652294964
288 -0.534416385 0.585698357
289 -0.788643535 -0.534416385
290 -0.896752351 -0.788643535
291 -0.799576916 -0.896752351
292 -1.293114355 -0.799576916
293 0.496698717 -1.293114355
294 0.101792181 0.496698717
295 1.157302057 0.101792181
296 0.772409706 1.157302057
297 0.586234630 0.772409706
298 0.146751599 0.586234630
299 -0.315670739 0.146751599
300 0.652831237 -0.315670739
301 -0.863262587 0.652831237
302 -1.327676665 -0.863262587
303 0.179858441 -1.327676665
304 -0.095469626 0.179858441
305 0.916536300 -0.095469626
306 -0.425771296 0.916536300
307 -0.171544145 -0.425771296
308 -0.381194801 -0.171544145
309 0.125267760 -0.381194801
310 0.211356465 0.125267760
311 -0.050893131 0.211356465
312 0.497617912 -0.050893131
313 -0.775182141 0.497617912
314 0.443563504 -0.775182141
315 -0.281644702 0.443563504
316 0.661389954 -0.281644702
317 0.871040609 0.661389954
318 0.233912849 0.871040609
319 -0.379739333 0.233912849
320 0.356019331 -0.379739333
321 0.013175463 0.356019331
322 -1.335699110 0.013175463
323 0.740375409 -1.335699110
324 0.014630931 0.740375409
325 0.851012239 0.014630931
326 -0.622496830 0.851012239
327 -1.358255494 -0.622496830
328 0.431557578 -1.358255494
329 0.606799273 0.431557578
330 -0.898744092 0.606799273
331 0.112725561 -0.898744092
332 0.158757525 0.112725561
333 0.168771710 0.158757525
334 0.827919582 0.168771710
335 -0.689476359 0.827919582
336 0.025181389 -0.689476359
337 -0.512396273 0.025181389
338 -0.929705843 -0.512396273
339 0.058671153 -0.929705843
340 2.179322168 0.058671153
341 0.706885645 2.179322168
342 -1.832147485 0.706885645
343 0.070677079 -1.832147485
344 -0.929322921 0.070677079
345 0.705813099 -0.929322921
346 -0.227054021 0.705813099
347 0.476134073 -0.227054021
348 1.321993294 0.476134073
349 -0.117489737 1.321993294
350 -0.402295717 -0.117489737
351 -0.315134467 -0.402295717
352 0.003161277 -0.315134467
353 -0.335699110 0.003161277
354 1.355483059 -0.335699110
355 0.444099777 1.355483059
356 -0.083463700 0.444099777
357 -0.710577275 -0.083463700
358 -0.205570183 -0.710577275
359 0.916536300 -0.205570183
360 0.366033517 0.916536300
361 -1.217039836 0.366033517
362 -0.316207012 -1.217039836
363 -0.469811519 -0.316207012
364 0.530724754 -0.469811519
365 -0.974818611 0.530724754
366 0.058671153 -0.974818611
367 -0.006852908 0.058671153
368 0.079772069 -0.006852908
369 -1.205033910 0.079772069
370 0.112725561 -1.205033910
371 0.640289038 0.112725561
372 -0.335699110 0.640289038
373 -0.052884871 -0.335699110
374 -1.434330013 -0.052884871
375 0.838470040 -1.434330013
376 -0.115497997 0.838470040
377 0.091777995 -0.115497997
378 -0.117489737 0.091777995
379 -0.237068207 -0.117489737
380 -0.315670739 -0.237068207
381 0.730361224 -0.315670739
382 1.630274853 0.730361224
383 -0.566450681 1.630274853
384 -0.512396273 -0.566450681
385 -0.215584368 -0.512396273
386 -1.203578442 -0.215584368
387 0.948570597 -1.203578442
388 0.301428651 0.948570597
389 0.794429817 0.301428651
390 0.839006313 0.794429817
391 0.716899830 0.839006313
392 0.179322168 0.716899830
393 0.036651042 0.179322168
394 -0.129495663 0.036651042
395 0.356019331 -0.129495663
396 -1.215584368 0.356019331
397 0.167316242 -1.215584368
398 -0.512396273 0.167316242
399 -1.271630517 -0.512396273
400 -0.457805593 -1.271630517
401 -1.490376162 -0.457805593
402 -0.205570183 -1.490376162
403 -0.116953465 -0.205570183
404 0.015167203 -0.116953465
405 -0.710577275 0.015167203
406 -0.281644702 -0.710577275
407 -0.864718055 -0.281644702
408 -1.052348599 -0.864718055
409 1.081227537 -1.052348599
410 1.672859607 1.081227537
411 -0.118408933 1.672859607
412 0.333999220 -0.118408933
413 1.026636857 0.333999220
414 -1.193564257 1.026636857
415 0.431557578 -1.193564257
416 0.354563863 0.431557578
417 -0.193564257 0.354563863
418 -0.940792574 -0.193564257
419 -0.369725147 -0.940792574
420 -1.875268513 -0.369725147
421 -0.303664813 -1.875268513
422 0.377503170 -0.303664813
423 0.145296131 0.377503170
424 0.189872626 0.145296131
425 -0.963348958 0.189872626
426 0.157302057 -0.963348958
427 0.192783562 0.157302057
428 1.003161277 0.192783562
429 -0.777556805 1.003161277
430 0.772945979 -0.777556805
431 -0.316972857 0.772945979
432 1.257388428 -0.316972857
433 0.399523281 1.257388428
434 -0.446335939 0.399523281
435 0.750925867 -0.446335939
436 -1.381731073 0.750925867
437 0.620260667 -1.381731073
438 0.277953071 0.620260667
439 -1.238140752 0.277953071
440 -0.104947539 -1.238140752
441 0.267938886 -0.104947539
442 0.059207426 0.267938886
443 1.245382502 0.059207426
444 0.981677439 1.245382502
445 0.432093851 0.981677439
446 0.574228704 0.432093851
447 0.278872267 0.574228704
448 -0.105483811 0.278872267
449 1.035731847 -0.105483811
450 0.816449929 1.035731847
451 0.004616745 0.816449929
452 -0.160457415 0.004616745
453 0.311442836 -0.160457415
454 0.584779162 0.311442836
455 -0.294569823 0.584779162
456 0.355483059 -0.294569823
457 -0.501845815 0.355483059
458 0.201878552 -0.501845815
459 -0.710577275 0.201878552
460 -0.776101337 -0.710577275
461 0.047201500 -0.776101337
462 -0.655986595 0.047201500
463 0.488139999 -0.655986595
464 -0.293114355 0.488139999
465 -0.259624591 -0.293114355
466 0.256469233 -0.259624591
467 -0.435249209 0.256469233
468 1.223362391 -0.435249209
469 -0.007389181 1.223362391
470 -0.555900223 -0.007389181
471 -1.642525201 -0.555900223
472 -1.360247235 -1.642525201
473 0.916536300 -1.360247235
474 0.157302057 0.916536300
475 1.147287871 0.157302057
476 -0.149524034 1.147287871
477 -0.271094244 -0.149524034
478 0.982596634 -0.271094244
479 -0.974282339 0.982596634
480 -0.327140393 -0.974282339
481 0.256469233 -0.327140393
482 0.981141166 0.256469233
483 0.211892737 0.981141166
484 0.255932960 0.211892737
485 0.784415632 0.255932960
486 0.728905756 0.784415632
487 -0.381731073 0.728905756
488 -0.864181782 -0.381731073
489 -0.171007873 -0.864181782
490 0.256852155 -0.171007873
491 -1.236531934 0.256852155
492 -0.239596220 -1.236531934
493 0.804980275 -0.239596220
494 1.070677079 0.804980275
495 -0.251448796 1.070677079
496 0.409537467 -0.251448796
497 1.510160111 0.409537467
498 -0.930778389 1.510160111
499 -1.347168763 -0.930778389
500 0.323448762 -1.347168763
501 -0.261080059 0.323448762
502 -0.259088318 -0.261080059
503 0.037187315 -0.259088318
504 -0.677470433 0.037187315
505 0.728369483 -0.677470433
506 0.321074099 0.728369483
507 0.464128147 0.321074099
508 -0.567369877 0.464128147
509 -0.128423118 -0.567369877
510 -1.191572516 -0.128423118
511 -0.512396273 -1.191572516
512 0.762395521 -0.512396273
513 -0.325684925 0.762395521
514 0.048656968 -0.325684925
515 0.013711735 0.048656968
516 1.683410065 0.013711735
517 -0.259088318 1.683410065
518 0.872496077 -0.259088318
519 -0.006852908 0.872496077
520 -0.259624591 -0.006852908
521 -0.084919168 -0.259624591
522 -0.259624591 -0.084919168
523 -0.556436496 -0.259624591
524 -0.128959391 -0.556436496
525 -0.303128541 -0.128959391
526 -0.281644702 -0.303128541
527 0.157838329 -0.281644702
528 -0.447791407 0.157838329
529 -0.227590294 -0.447791407
530 0.333999220 -0.227590294
531 -0.555900223 0.333999220
532 -0.193027984 -0.555900223
533 -0.456350125 -0.193027984
534 -1.161529960 -0.456350125
535 0.719810766 -1.161529960
536 0.684329261 0.719810766
537 0.389509096 0.684329261
538 -0.325684925 0.389509096
539 0.541275212 -0.325684925
540 0.629738580 0.541275212
541 0.816449929 0.629738580
542 0.059207426 0.816449929
543 -0.886201893 0.059207426
544 1.399523281 -0.886201893
545 1.443563504 1.399523281
546 0.081227537 1.443563504
547 0.596785088 0.081227537
548 -0.248537860 0.596785088
549 1.389509096 -0.248537860
550 -0.171544145 1.389509096
551 -0.139509849 -0.171544145
552 0.420087925 -0.139509849
553 0.840461781 0.420087925
554 1.147287871 0.840461781
555 -0.283100170 1.147287871
556 1.805899471 -0.283100170
557 0.454113962 1.805899471
558 -0.204114715 0.454113962
559 0.784415632 -0.204114715
560 0.125804033 0.784415632
561 -0.369725147 0.125804033
562 -1.799193993 -0.369725147
563 0.509623838 -1.799193993
564 2.035195574 0.509623838
565 0.454113962 2.035195574
566 0.321993294 0.454113962
567 -0.348241309 0.321993294
568 0.642280779 -0.348241309
569 0.421543393 0.642280779
570 1.630274853 0.421543393
571 0.520174296 1.630274853
572 0.409537467 0.520174296
573 -0.447791407 0.409537467
574 -0.919308735 -0.447791407
575 -1.283100170 -0.919308735
576 0.717436103 -1.283100170
577 1.168388787 0.717436103
578 -0.754081225 1.168388787
579 -0.205033910 -0.754081225
580 -1.007389181 -0.205033910
581 0.003161277 -1.007389181
582 -0.359710962 0.003161277
583 0.663764617 -0.359710962
584 -0.205033910 0.663764617
585 -1.094397081 -0.205033910
586 0.199886811 -1.094397081
587 -0.181558331 0.199886811
588 0.168388787 -0.181558331
589 1.036268119 0.168388787
590 0.630274853 1.036268119
591 0.091241723 0.630274853
592 -0.533880112 0.091241723
593 0.465047343 -0.533880112
594 -1.380275605 0.465047343
595 -0.227590294 -1.380275605
596 -0.249074133 -0.227590294
597 -0.293650628 -0.249074133
598 -1.524402199 -0.293650628
599 -0.272549712 -1.524402199
600 -0.325684925 -0.272549712
601 -0.896752351 -0.325684925
602 0.266483418 -0.896752351
603 0.607718469 0.266483418
604 1.641744506 0.607718469
605 0.080691265 1.641744506
606 -0.578456607 0.080691265
607 0.421543393 -0.578456607
608 -0.326221197 0.421543393
609 0.828455855 -0.326221197
610 0.124731487 0.828455855
611 0.279408539 0.124731487
612 -0.347705036 0.279408539
613 0.333999220 -0.347705036
614 -0.952262227 0.333999220
615 -0.084919168 -0.952262227
616 -1.072913242 -0.084919168
617 -0.369188875 -1.072913242
618 0.850475966 -0.369188875
619 1.047737773 0.850475966
620 -0.171544145 1.047737773
621 0.223362391 -0.171544145
622 0.464664420 0.223362391
623 0.367488985 0.464664420
624 0.321457021 0.367488985
625 0.411529207 0.321457021
626 -1.371716888 0.411529207
627 0.069757884 -1.371716888
628 1.278872267 0.069757884
629 -1.194483452 1.278872267
630 0.949106869 -1.194483452
631 -0.161529960 0.949106869
632 -0.315670739 -0.161529960
633 0.289422725 -0.315670739
634 -0.755536693 0.289422725
635 -0.413765370 -0.755536693
636 0.509623838 -0.413765370
637 -0.116953465 0.509623838
638 -0.314215271 -0.116953465
639 -0.513851741 -0.314215271
640 0.234832044 -0.513851741
641 -0.182477526 0.234832044
642 -0.655986595 -0.182477526
643 0.761476325 -0.655986595
644 -0.457805593 0.761476325
645 0.332543752 -0.457805593
646 0.015167203 0.332543752
647 0.706885645 0.015167203
648 0.354946786 0.706885645
649 0.772945979 0.354946786
650 0.630274853 0.772945979
651 0.738919941 0.630274853
652 0.191328094 0.738919941
653 NA 0.191328094
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.227590294 0.157302057
[2,] 0.378039443 -0.227590294
[3,] -0.315670739 0.378039443
[4,] -0.040878945 -0.315670739
[5,] 0.189872626 -0.040878945
[6,] 0.706349372 0.189872626
[7,] -0.381731073 0.706349372
[8,] 0.123812292 -0.381731073
[9,] -0.227590294 0.123812292
[10,] -1.435785481 -0.227590294
[11,] -1.215584368 -1.435785481
[12,] 0.552744865 -1.215584368
[13,] 1.125267760 0.552744865
[14,] -1.866173523 1.125267760
[15,] -0.667456248 -1.866173523
[16,] 0.661389954 -0.667456248
[17,] 0.222443195 0.661389954
[18,] -1.600476719 0.222443195
[19,] 0.091777995 -1.600476719
[20,] 0.651758691 0.091777995
[21,] -0.435785481 0.651758691
[22,] -0.184086344 -0.435785481
[23,] -1.841242475 -0.184086344
[24,] -0.798121448 -1.841242475
[25,] -0.271094244 -0.798121448
[26,] -0.259624591 -0.271094244
[27,] -0.138973576 -0.259624591
[28,] -0.381194801 -0.138973576
[29,] -0.555900223 -0.381194801
[30,] 1.233912849 -0.555900223
[31,] 0.959121055 1.233912849
[32,] -0.435249209 0.959121055
[33,] -0.634502756 -0.435249209
[34,] 1.696335187 -0.634502756
[35,] -0.941328847 1.696335187
[36,] 0.773482251 -0.941328847
[37,] 0.752917608 0.773482251
[38,] -0.952262227 0.752917608
[39,] 0.981677439 -0.952262227
[40,] 0.454650235 0.981677439
[41,] 1.123812292 0.454650235
[42,] -0.611946372 1.123812292
[43,] 0.948570597 -0.611946372
[44,] -0.820141559 0.948570597
[45,] 0.662309149 -0.820141559
[46,] -0.501845815 0.662309149
[47,] 1.310523641 -0.501845815
[48,] -0.205033910 1.310523641
[49,] 1.233376576 -0.205033910
[50,] 0.498154185 1.233376576
[51,] -0.083463700 0.498154185
[52,] -0.293114355 -0.083463700
[53,] -0.379739333 -0.293114355
[54,] 0.355483059 -0.379739333
[55,] -0.425235023 0.355483059
[56,] -0.678006706 -0.425235023
[57,] -0.477833963 -0.678006706
[58,] 0.366033517 -0.477833963
[59,] 0.652294964 0.366033517
[60,] 0.574228704 0.652294964
[61,] 0.774401447 0.574228704
[62,] 0.113798107 0.774401447
[63,] -0.622496830 0.113798107
[64,] -0.095469626 -0.622496830
[65,] 0.147287871 -0.095469626
[66,] -0.281644702 0.147287871
[67,] -0.315670739 -0.281644702
[68,] 0.959657327 -0.315670739
[69,] 0.311059913 0.959657327
[70,] -0.798657721 0.311059913
[71,] 0.047737773 -0.798657721
[72,] -0.995383255 0.047737773
[73,] -0.906766537 -0.995383255
[74,] 0.828455855 -0.906766537
[75,] -1.128959391 0.828455855
[76,] 0.618268927 -1.128959391
[77,] -0.061443589 0.618268927
[78,] 0.904530374 -0.061443589
[79,] 0.894516189 0.904530374
[80,] -0.897288624 0.894516189
[81,] 0.137273686 -0.897288624
[82,] 0.190791821 0.137273686
[83,] 0.013711735 0.190791821
[84,] 1.101792181 0.013711735
[85,] 0.003161277 1.101792181
[86,] 1.772945979 0.003161277
[87,] -1.183550071 1.772945979
[88,] 0.883046535 -1.183550071
[89,] 0.014630931 0.883046535
[90,] -0.644516941 0.014630931
[91,] -0.083463700 -0.644516941
[92,] 0.223362391 -0.083463700
[93,] -0.798657721 0.223362391
[94,] 0.345468873 -0.798657721
[95,] 0.674315075 0.345468873
[96,] 0.432093851 0.674315075
[97,] -1.798657721 0.432093851
[98,] -1.732597387 -1.798657721
[99,] -0.567906149 -1.732597387
[100,] -0.986824537 -0.567906149
[101,] 0.101792181 -0.986824537
[102,] -0.700026817 0.101792181
[103,] 1.618268927 -0.700026817
[104,] -1.237604479 1.618268927
[105,] -0.710041003 -1.237604479
[106,] -0.832147485 -0.710041003
[107,] -0.710577275 -0.832147485
[108,] -0.500390347 -0.710577275
[109,] 1.168771710 -0.500390347
[110,] -0.226517749 1.168771710
[111,] 0.135281945 -0.226517749
[112,] -1.534416385 0.135281945
[113,] 0.586234630 -1.534416385
[114,] -0.150443229 0.586234630
[115,] 0.398604086 -0.150443229
[116,] 0.300892378 0.398604086
[117,] 0.048656968 0.300892378
[118,] -0.118408933 0.048656968
[119,] 0.014630931 -0.118408933
[120,] 0.586770903 0.014630931
[121,] -0.468356051 0.586770903
[122,] -0.029409292 -0.468356051
[123,] -1.447791407 -0.029409292
[124,] 0.772409706 -1.447791407
[125,] 1.443563504 0.772409706
[126,] -0.402295717 1.443563504
[127,] 0.718355298 -0.402295717
[128,] 0.673778803 0.718355298
[129,] 0.915080832 0.673778803
[130,] -0.369725147 0.915080832
[131,] 0.332543752 -0.369725147
[132,] 0.146751599 0.332543752
[133,] 0.213348205 0.146751599
[134,] -0.423779555 0.213348205
[135,] -0.545886038 -0.423779555
[136,] 0.189336353 -0.545886038
[137,] 0.784415632 0.189336353
[138,] 0.728905756 0.784415632
[139,] 0.169307983 0.728905756
[140,] -0.281108429 0.169307983
[141,] 0.444099777 -0.281108429
[142,] -0.281108429 0.444099777
[143,] -0.479825704 -0.281108429
[144,] -0.744603313 -0.479825704
[145,] -0.952798500 -0.744603313
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[581,] 0.003161277 -1.007389181
[582,] -0.359710962 0.003161277
[583,] 0.663764617 -0.359710962
[584,] -0.205033910 0.663764617
[585,] -1.094397081 -0.205033910
[586,] 0.199886811 -1.094397081
[587,] -0.181558331 0.199886811
[588,] 0.168388787 -0.181558331
[589,] 1.036268119 0.168388787
[590,] 0.630274853 1.036268119
[591,] 0.091241723 0.630274853
[592,] -0.533880112 0.091241723
[593,] 0.465047343 -0.533880112
[594,] -1.380275605 0.465047343
[595,] -0.227590294 -1.380275605
[596,] -0.249074133 -0.227590294
[597,] -0.293650628 -0.249074133
[598,] -1.524402199 -0.293650628
[599,] -0.272549712 -1.524402199
[600,] -0.325684925 -0.272549712
[601,] -0.896752351 -0.325684925
[602,] 0.266483418 -0.896752351
[603,] 0.607718469 0.266483418
[604,] 1.641744506 0.607718469
[605,] 0.080691265 1.641744506
[606,] -0.578456607 0.080691265
[607,] 0.421543393 -0.578456607
[608,] -0.326221197 0.421543393
[609,] 0.828455855 -0.326221197
[610,] 0.124731487 0.828455855
[611,] 0.279408539 0.124731487
[612,] -0.347705036 0.279408539
[613,] 0.333999220 -0.347705036
[614,] -0.952262227 0.333999220
[615,] -0.084919168 -0.952262227
[616,] -1.072913242 -0.084919168
[617,] -0.369188875 -1.072913242
[618,] 0.850475966 -0.369188875
[619,] 1.047737773 0.850475966
[620,] -0.171544145 1.047737773
[621,] 0.223362391 -0.171544145
[622,] 0.464664420 0.223362391
[623,] 0.367488985 0.464664420
[624,] 0.321457021 0.367488985
[625,] 0.411529207 0.321457021
[626,] -1.371716888 0.411529207
[627,] 0.069757884 -1.371716888
[628,] 1.278872267 0.069757884
[629,] -1.194483452 1.278872267
[630,] 0.949106869 -1.194483452
[631,] -0.161529960 0.949106869
[632,] -0.315670739 -0.161529960
[633,] 0.289422725 -0.315670739
[634,] -0.755536693 0.289422725
[635,] -0.413765370 -0.755536693
[636,] 0.509623838 -0.413765370
[637,] -0.116953465 0.509623838
[638,] -0.314215271 -0.116953465
[639,] -0.513851741 -0.314215271
[640,] 0.234832044 -0.513851741
[641,] -0.182477526 0.234832044
[642,] -0.655986595 -0.182477526
[643,] 0.761476325 -0.655986595
[644,] -0.457805593 0.761476325
[645,] 0.332543752 -0.457805593
[646,] 0.015167203 0.332543752
[647,] 0.706885645 0.015167203
[648,] 0.354946786 0.706885645
[649,] 0.772945979 0.354946786
[650,] 0.630274853 0.772945979
[651,] 0.738919941 0.630274853
[652,] 0.191328094 0.738919941
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.227590294 0.157302057
2 0.378039443 -0.227590294
3 -0.315670739 0.378039443
4 -0.040878945 -0.315670739
5 0.189872626 -0.040878945
6 0.706349372 0.189872626
7 -0.381731073 0.706349372
8 0.123812292 -0.381731073
9 -0.227590294 0.123812292
10 -1.435785481 -0.227590294
11 -1.215584368 -1.435785481
12 0.552744865 -1.215584368
13 1.125267760 0.552744865
14 -1.866173523 1.125267760
15 -0.667456248 -1.866173523
16 0.661389954 -0.667456248
17 0.222443195 0.661389954
18 -1.600476719 0.222443195
19 0.091777995 -1.600476719
20 0.651758691 0.091777995
21 -0.435785481 0.651758691
22 -0.184086344 -0.435785481
23 -1.841242475 -0.184086344
24 -0.798121448 -1.841242475
25 -0.271094244 -0.798121448
26 -0.259624591 -0.271094244
27 -0.138973576 -0.259624591
28 -0.381194801 -0.138973576
29 -0.555900223 -0.381194801
30 1.233912849 -0.555900223
31 0.959121055 1.233912849
32 -0.435249209 0.959121055
33 -0.634502756 -0.435249209
34 1.696335187 -0.634502756
35 -0.941328847 1.696335187
36 0.773482251 -0.941328847
37 0.752917608 0.773482251
38 -0.952262227 0.752917608
39 0.981677439 -0.952262227
40 0.454650235 0.981677439
41 1.123812292 0.454650235
42 -0.611946372 1.123812292
43 0.948570597 -0.611946372
44 -0.820141559 0.948570597
45 0.662309149 -0.820141559
46 -0.501845815 0.662309149
47 1.310523641 -0.501845815
48 -0.205033910 1.310523641
49 1.233376576 -0.205033910
50 0.498154185 1.233376576
51 -0.083463700 0.498154185
52 -0.293114355 -0.083463700
53 -0.379739333 -0.293114355
54 0.355483059 -0.379739333
55 -0.425235023 0.355483059
56 -0.678006706 -0.425235023
57 -0.477833963 -0.678006706
58 0.366033517 -0.477833963
59 0.652294964 0.366033517
60 0.574228704 0.652294964
61 0.774401447 0.574228704
62 0.113798107 0.774401447
63 -0.622496830 0.113798107
64 -0.095469626 -0.622496830
65 0.147287871 -0.095469626
66 -0.281644702 0.147287871
67 -0.315670739 -0.281644702
68 0.959657327 -0.315670739
69 0.311059913 0.959657327
70 -0.798657721 0.311059913
71 0.047737773 -0.798657721
72 -0.995383255 0.047737773
73 -0.906766537 -0.995383255
74 0.828455855 -0.906766537
75 -1.128959391 0.828455855
76 0.618268927 -1.128959391
77 -0.061443589 0.618268927
78 0.904530374 -0.061443589
79 0.894516189 0.904530374
80 -0.897288624 0.894516189
81 0.137273686 -0.897288624
82 0.190791821 0.137273686
83 0.013711735 0.190791821
84 1.101792181 0.013711735
85 0.003161277 1.101792181
86 1.772945979 0.003161277
87 -1.183550071 1.772945979
88 0.883046535 -1.183550071
89 0.014630931 0.883046535
90 -0.644516941 0.014630931
91 -0.083463700 -0.644516941
92 0.223362391 -0.083463700
93 -0.798657721 0.223362391
94 0.345468873 -0.798657721
95 0.674315075 0.345468873
96 0.432093851 0.674315075
97 -1.798657721 0.432093851
98 -1.732597387 -1.798657721
99 -0.567906149 -1.732597387
100 -0.986824537 -0.567906149
101 0.101792181 -0.986824537
102 -0.700026817 0.101792181
103 1.618268927 -0.700026817
104 -1.237604479 1.618268927
105 -0.710041003 -1.237604479
106 -0.832147485 -0.710041003
107 -0.710577275 -0.832147485
108 -0.500390347 -0.710577275
109 1.168771710 -0.500390347
110 -0.226517749 1.168771710
111 0.135281945 -0.226517749
112 -1.534416385 0.135281945
113 0.586234630 -1.534416385
114 -0.150443229 0.586234630
115 0.398604086 -0.150443229
116 0.300892378 0.398604086
117 0.048656968 0.300892378
118 -0.118408933 0.048656968
119 0.014630931 -0.118408933
120 0.586770903 0.014630931
121 -0.468356051 0.586770903
122 -0.029409292 -0.468356051
123 -1.447791407 -0.029409292
124 0.772409706 -1.447791407
125 1.443563504 0.772409706
126 -0.402295717 1.443563504
127 0.718355298 -0.402295717
128 0.673778803 0.718355298
129 0.915080832 0.673778803
130 -0.369725147 0.915080832
131 0.332543752 -0.369725147
132 0.146751599 0.332543752
133 0.213348205 0.146751599
134 -0.423779555 0.213348205
135 -0.545886038 -0.423779555
136 0.189336353 -0.545886038
137 0.784415632 0.189336353
138 0.728905756 0.784415632
139 0.169307983 0.728905756
140 -0.281108429 0.169307983
141 0.444099777 -0.281108429
142 -0.281108429 0.444099777
143 -0.479825704 -0.281108429
144 -0.744603313 -0.479825704
145 -0.952798500 -0.744603313
146 0.279408539 -0.952798500
147 -0.291658887 0.279408539
148 0.520174296 -0.291658887
149 0.026636857 0.520174296
150 -0.061443589 0.026636857
151 0.311442836 -0.061443589
152 0.344932601 0.311442836
153 0.125267760 0.344932601
154 0.563678246 0.125267760
155 0.081227537 0.563678246
156 0.991691624 0.081227537
157 -0.072913242 0.991691624
158 -0.251065873 -0.072913242
159 0.299436910 -0.251065873
160 -0.523865927 0.299436910
161 0.082683005 -0.523865927
162 -0.335699110 0.082683005
163 0.750925867 -0.335699110
164 1.487603727 0.750925867
165 -1.227590294 1.487603727
166 -0.371180615 -1.227590294
167 -1.160457415 -0.371180615
168 -0.852712129 -1.160457415
169 0.684329261 -0.852712129
170 0.641744506 0.684329261
171 -0.766623424 0.641744506
172 0.399140359 -0.766623424
173 -0.788107263 0.399140359
174 -0.502765011 -0.788107263
175 -1.073449515 -0.502765011
176 -0.654531127 -1.073449515
177 -0.734052855 -0.654531127
178 -0.567906149 -0.734052855
179 0.333999220 -0.567906149
180 -0.908758277 0.333999220
181 -0.337690851 -0.908758277
182 -0.995383255 -0.337690851
183 -1.909677473 -0.995383255
184 -1.479825704 -1.909677473
185 -1.996302450 -1.479825704
186 -0.391745259 -1.996302450
187 -0.149524034 -0.391745259
188 0.564214519 -0.149524034
189 -0.557355691 0.564214519
190 -0.479825704 -0.557355691
191 -1.523865927 -0.479825704
192 -0.347705036 -1.523865927
193 0.959657327 -0.347705036
194 -0.095469626 0.959657327
195 -0.072913242 -0.095469626
196 0.399523281 -0.072913242
197 0.486684531 0.399523281
198 -0.393200727 0.486684531
199 1.211356465 -0.393200727
200 0.201342279 1.211356465
201 0.432630123 0.201342279
202 -0.534416385 0.432630123
203 0.177866700 -0.534416385
204 0.452658494 0.177866700
205 0.970207785 0.452658494
206 0.740375409 0.970207785
207 -0.050893131 0.740375409
208 0.551289397 -0.050893131
209 -0.072913242 0.551289397
210 -0.601395914 -0.072913242
211 -0.919308735 -0.601395914
212 -0.764631683 -0.919308735
213 0.948570597 -0.764631683
214 0.828455855 0.948570597
215 0.311442836 0.828455855
216 0.344549678 0.311442836
217 0.782960164 0.344549678
218 0.443563504 0.782960164
219 -0.578456607 0.443563504
220 -0.171544145 -0.578456607
221 0.136737413 -0.171544145
222 -0.292195160 0.136737413
223 -0.854167597 -0.292195160
224 -1.381194801 -0.854167597
225 -0.217039836 -1.381194801
226 -0.171544145 -0.217039836
227 0.235368317 -0.171544145
228 -0.237604479 0.235368317
229 0.057751958 -0.237604479
230 0.014630931 0.057751958
231 -0.963348958 0.014630931
232 -0.128959391 -0.963348958
233 0.618268927 -0.128959391
234 0.113261834 0.618268927
235 -0.072913242 0.113261834
236 0.694879719 -0.072913242
237 0.388053628 0.694879719
238 0.036651042 0.388053628
239 -1.281644702 0.036651042
240 -0.622496830 -1.281644702
241 -0.062899057 -0.622496830
242 -0.930778389 -0.062899057
243 -0.941328847 -0.930778389
244 0.245382502 -0.941328847
245 -1.193027984 0.245382502
246 1.135281945 -1.193027984
247 -1.909294550 1.135281945
248 -0.679462174 -1.909294550
249 0.179322168 -0.679462174
250 0.795502363 0.179322168
251 1.157302057 0.795502363
252 -0.941328847 1.157302057
253 -0.468356051 -0.941328847
254 1.840461781 -0.468356051
255 0.684329261 1.840461781
256 -0.171007873 0.684329261
257 0.157302057 -0.171007873
258 0.410610012 0.157302057
259 0.718355298 0.410610012
260 0.850093043 0.718355298
261 -0.359710962 0.850093043
262 0.346005146 -0.359710962
263 0.662845422 0.346005146
264 0.762395521 0.662845422
265 1.443563504 0.762395521
266 1.344932601 1.443563504
267 -0.413765370 1.344932601
268 -1.006852908 -0.413765370
269 0.134745673 -1.006852908
270 -0.216503563 0.134745673
271 1.356019331 -0.216503563
272 -0.391745259 1.356019331
273 0.497617912 -0.391745259
274 0.048656968 0.497617912
275 0.124731487 0.048656968
276 -0.524248849 0.124731487
277 0.157302057 -0.524248849
278 -0.941328847 0.157302057
279 1.157302057 -0.941328847
280 -1.403214912 1.157302057
281 1.059207426 -1.403214912
282 -0.359710962 1.059207426
283 0.081227537 -0.359710962
284 1.740375409 0.081227537
285 -1.611946372 1.740375409
286 0.652294964 -1.611946372
287 0.585698357 0.652294964
288 -0.534416385 0.585698357
289 -0.788643535 -0.534416385
290 -0.896752351 -0.788643535
291 -0.799576916 -0.896752351
292 -1.293114355 -0.799576916
293 0.496698717 -1.293114355
294 0.101792181 0.496698717
295 1.157302057 0.101792181
296 0.772409706 1.157302057
297 0.586234630 0.772409706
298 0.146751599 0.586234630
299 -0.315670739 0.146751599
300 0.652831237 -0.315670739
301 -0.863262587 0.652831237
302 -1.327676665 -0.863262587
303 0.179858441 -1.327676665
304 -0.095469626 0.179858441
305 0.916536300 -0.095469626
306 -0.425771296 0.916536300
307 -0.171544145 -0.425771296
308 -0.381194801 -0.171544145
309 0.125267760 -0.381194801
310 0.211356465 0.125267760
311 -0.050893131 0.211356465
312 0.497617912 -0.050893131
313 -0.775182141 0.497617912
314 0.443563504 -0.775182141
315 -0.281644702 0.443563504
316 0.661389954 -0.281644702
317 0.871040609 0.661389954
318 0.233912849 0.871040609
319 -0.379739333 0.233912849
320 0.356019331 -0.379739333
321 0.013175463 0.356019331
322 -1.335699110 0.013175463
323 0.740375409 -1.335699110
324 0.014630931 0.740375409
325 0.851012239 0.014630931
326 -0.622496830 0.851012239
327 -1.358255494 -0.622496830
328 0.431557578 -1.358255494
329 0.606799273 0.431557578
330 -0.898744092 0.606799273
331 0.112725561 -0.898744092
332 0.158757525 0.112725561
333 0.168771710 0.158757525
334 0.827919582 0.168771710
335 -0.689476359 0.827919582
336 0.025181389 -0.689476359
337 -0.512396273 0.025181389
338 -0.929705843 -0.512396273
339 0.058671153 -0.929705843
340 2.179322168 0.058671153
341 0.706885645 2.179322168
342 -1.832147485 0.706885645
343 0.070677079 -1.832147485
344 -0.929322921 0.070677079
345 0.705813099 -0.929322921
346 -0.227054021 0.705813099
347 0.476134073 -0.227054021
348 1.321993294 0.476134073
349 -0.117489737 1.321993294
350 -0.402295717 -0.117489737
351 -0.315134467 -0.402295717
352 0.003161277 -0.315134467
353 -0.335699110 0.003161277
354 1.355483059 -0.335699110
355 0.444099777 1.355483059
356 -0.083463700 0.444099777
357 -0.710577275 -0.083463700
358 -0.205570183 -0.710577275
359 0.916536300 -0.205570183
360 0.366033517 0.916536300
361 -1.217039836 0.366033517
362 -0.316207012 -1.217039836
363 -0.469811519 -0.316207012
364 0.530724754 -0.469811519
365 -0.974818611 0.530724754
366 0.058671153 -0.974818611
367 -0.006852908 0.058671153
368 0.079772069 -0.006852908
369 -1.205033910 0.079772069
370 0.112725561 -1.205033910
371 0.640289038 0.112725561
372 -0.335699110 0.640289038
373 -0.052884871 -0.335699110
374 -1.434330013 -0.052884871
375 0.838470040 -1.434330013
376 -0.115497997 0.838470040
377 0.091777995 -0.115497997
378 -0.117489737 0.091777995
379 -0.237068207 -0.117489737
380 -0.315670739 -0.237068207
381 0.730361224 -0.315670739
382 1.630274853 0.730361224
383 -0.566450681 1.630274853
384 -0.512396273 -0.566450681
385 -0.215584368 -0.512396273
386 -1.203578442 -0.215584368
387 0.948570597 -1.203578442
388 0.301428651 0.948570597
389 0.794429817 0.301428651
390 0.839006313 0.794429817
391 0.716899830 0.839006313
392 0.179322168 0.716899830
393 0.036651042 0.179322168
394 -0.129495663 0.036651042
395 0.356019331 -0.129495663
396 -1.215584368 0.356019331
397 0.167316242 -1.215584368
398 -0.512396273 0.167316242
399 -1.271630517 -0.512396273
400 -0.457805593 -1.271630517
401 -1.490376162 -0.457805593
402 -0.205570183 -1.490376162
403 -0.116953465 -0.205570183
404 0.015167203 -0.116953465
405 -0.710577275 0.015167203
406 -0.281644702 -0.710577275
407 -0.864718055 -0.281644702
408 -1.052348599 -0.864718055
409 1.081227537 -1.052348599
410 1.672859607 1.081227537
411 -0.118408933 1.672859607
412 0.333999220 -0.118408933
413 1.026636857 0.333999220
414 -1.193564257 1.026636857
415 0.431557578 -1.193564257
416 0.354563863 0.431557578
417 -0.193564257 0.354563863
418 -0.940792574 -0.193564257
419 -0.369725147 -0.940792574
420 -1.875268513 -0.369725147
421 -0.303664813 -1.875268513
422 0.377503170 -0.303664813
423 0.145296131 0.377503170
424 0.189872626 0.145296131
425 -0.963348958 0.189872626
426 0.157302057 -0.963348958
427 0.192783562 0.157302057
428 1.003161277 0.192783562
429 -0.777556805 1.003161277
430 0.772945979 -0.777556805
431 -0.316972857 0.772945979
432 1.257388428 -0.316972857
433 0.399523281 1.257388428
434 -0.446335939 0.399523281
435 0.750925867 -0.446335939
436 -1.381731073 0.750925867
437 0.620260667 -1.381731073
438 0.277953071 0.620260667
439 -1.238140752 0.277953071
440 -0.104947539 -1.238140752
441 0.267938886 -0.104947539
442 0.059207426 0.267938886
443 1.245382502 0.059207426
444 0.981677439 1.245382502
445 0.432093851 0.981677439
446 0.574228704 0.432093851
447 0.278872267 0.574228704
448 -0.105483811 0.278872267
449 1.035731847 -0.105483811
450 0.816449929 1.035731847
451 0.004616745 0.816449929
452 -0.160457415 0.004616745
453 0.311442836 -0.160457415
454 0.584779162 0.311442836
455 -0.294569823 0.584779162
456 0.355483059 -0.294569823
457 -0.501845815 0.355483059
458 0.201878552 -0.501845815
459 -0.710577275 0.201878552
460 -0.776101337 -0.710577275
461 0.047201500 -0.776101337
462 -0.655986595 0.047201500
463 0.488139999 -0.655986595
464 -0.293114355 0.488139999
465 -0.259624591 -0.293114355
466 0.256469233 -0.259624591
467 -0.435249209 0.256469233
468 1.223362391 -0.435249209
469 -0.007389181 1.223362391
470 -0.555900223 -0.007389181
471 -1.642525201 -0.555900223
472 -1.360247235 -1.642525201
473 0.916536300 -1.360247235
474 0.157302057 0.916536300
475 1.147287871 0.157302057
476 -0.149524034 1.147287871
477 -0.271094244 -0.149524034
478 0.982596634 -0.271094244
479 -0.974282339 0.982596634
480 -0.327140393 -0.974282339
481 0.256469233 -0.327140393
482 0.981141166 0.256469233
483 0.211892737 0.981141166
484 0.255932960 0.211892737
485 0.784415632 0.255932960
486 0.728905756 0.784415632
487 -0.381731073 0.728905756
488 -0.864181782 -0.381731073
489 -0.171007873 -0.864181782
490 0.256852155 -0.171007873
491 -1.236531934 0.256852155
492 -0.239596220 -1.236531934
493 0.804980275 -0.239596220
494 1.070677079 0.804980275
495 -0.251448796 1.070677079
496 0.409537467 -0.251448796
497 1.510160111 0.409537467
498 -0.930778389 1.510160111
499 -1.347168763 -0.930778389
500 0.323448762 -1.347168763
501 -0.261080059 0.323448762
502 -0.259088318 -0.261080059
503 0.037187315 -0.259088318
504 -0.677470433 0.037187315
505 0.728369483 -0.677470433
506 0.321074099 0.728369483
507 0.464128147 0.321074099
508 -0.567369877 0.464128147
509 -0.128423118 -0.567369877
510 -1.191572516 -0.128423118
511 -0.512396273 -1.191572516
512 0.762395521 -0.512396273
513 -0.325684925 0.762395521
514 0.048656968 -0.325684925
515 0.013711735 0.048656968
516 1.683410065 0.013711735
517 -0.259088318 1.683410065
518 0.872496077 -0.259088318
519 -0.006852908 0.872496077
520 -0.259624591 -0.006852908
521 -0.084919168 -0.259624591
522 -0.259624591 -0.084919168
523 -0.556436496 -0.259624591
524 -0.128959391 -0.556436496
525 -0.303128541 -0.128959391
526 -0.281644702 -0.303128541
527 0.157838329 -0.281644702
528 -0.447791407 0.157838329
529 -0.227590294 -0.447791407
530 0.333999220 -0.227590294
531 -0.555900223 0.333999220
532 -0.193027984 -0.555900223
533 -0.456350125 -0.193027984
534 -1.161529960 -0.456350125
535 0.719810766 -1.161529960
536 0.684329261 0.719810766
537 0.389509096 0.684329261
538 -0.325684925 0.389509096
539 0.541275212 -0.325684925
540 0.629738580 0.541275212
541 0.816449929 0.629738580
542 0.059207426 0.816449929
543 -0.886201893 0.059207426
544 1.399523281 -0.886201893
545 1.443563504 1.399523281
546 0.081227537 1.443563504
547 0.596785088 0.081227537
548 -0.248537860 0.596785088
549 1.389509096 -0.248537860
550 -0.171544145 1.389509096
551 -0.139509849 -0.171544145
552 0.420087925 -0.139509849
553 0.840461781 0.420087925
554 1.147287871 0.840461781
555 -0.283100170 1.147287871
556 1.805899471 -0.283100170
557 0.454113962 1.805899471
558 -0.204114715 0.454113962
559 0.784415632 -0.204114715
560 0.125804033 0.784415632
561 -0.369725147 0.125804033
562 -1.799193993 -0.369725147
563 0.509623838 -1.799193993
564 2.035195574 0.509623838
565 0.454113962 2.035195574
566 0.321993294 0.454113962
567 -0.348241309 0.321993294
568 0.642280779 -0.348241309
569 0.421543393 0.642280779
570 1.630274853 0.421543393
571 0.520174296 1.630274853
572 0.409537467 0.520174296
573 -0.447791407 0.409537467
574 -0.919308735 -0.447791407
575 -1.283100170 -0.919308735
576 0.717436103 -1.283100170
577 1.168388787 0.717436103
578 -0.754081225 1.168388787
579 -0.205033910 -0.754081225
580 -1.007389181 -0.205033910
581 0.003161277 -1.007389181
582 -0.359710962 0.003161277
583 0.663764617 -0.359710962
584 -0.205033910 0.663764617
585 -1.094397081 -0.205033910
586 0.199886811 -1.094397081
587 -0.181558331 0.199886811
588 0.168388787 -0.181558331
589 1.036268119 0.168388787
590 0.630274853 1.036268119
591 0.091241723 0.630274853
592 -0.533880112 0.091241723
593 0.465047343 -0.533880112
594 -1.380275605 0.465047343
595 -0.227590294 -1.380275605
596 -0.249074133 -0.227590294
597 -0.293650628 -0.249074133
598 -1.524402199 -0.293650628
599 -0.272549712 -1.524402199
600 -0.325684925 -0.272549712
601 -0.896752351 -0.325684925
602 0.266483418 -0.896752351
603 0.607718469 0.266483418
604 1.641744506 0.607718469
605 0.080691265 1.641744506
606 -0.578456607 0.080691265
607 0.421543393 -0.578456607
608 -0.326221197 0.421543393
609 0.828455855 -0.326221197
610 0.124731487 0.828455855
611 0.279408539 0.124731487
612 -0.347705036 0.279408539
613 0.333999220 -0.347705036
614 -0.952262227 0.333999220
615 -0.084919168 -0.952262227
616 -1.072913242 -0.084919168
617 -0.369188875 -1.072913242
618 0.850475966 -0.369188875
619 1.047737773 0.850475966
620 -0.171544145 1.047737773
621 0.223362391 -0.171544145
622 0.464664420 0.223362391
623 0.367488985 0.464664420
624 0.321457021 0.367488985
625 0.411529207 0.321457021
626 -1.371716888 0.411529207
627 0.069757884 -1.371716888
628 1.278872267 0.069757884
629 -1.194483452 1.278872267
630 0.949106869 -1.194483452
631 -0.161529960 0.949106869
632 -0.315670739 -0.161529960
633 0.289422725 -0.315670739
634 -0.755536693 0.289422725
635 -0.413765370 -0.755536693
636 0.509623838 -0.413765370
637 -0.116953465 0.509623838
638 -0.314215271 -0.116953465
639 -0.513851741 -0.314215271
640 0.234832044 -0.513851741
641 -0.182477526 0.234832044
642 -0.655986595 -0.182477526
643 0.761476325 -0.655986595
644 -0.457805593 0.761476325
645 0.332543752 -0.457805593
646 0.015167203 0.332543752
647 0.706885645 0.015167203
648 0.354946786 0.706885645
649 0.772945979 0.354946786
650 0.630274853 0.772945979
651 0.738919941 0.630274853
652 0.191328094 0.738919941
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/7df7s1321621655.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8chus1321621655.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9p5vc1321621655.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10vwzm1321621655.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/1116411321621655.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/12krtt1321621655.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/13if9v1321621656.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/147p7k1321621656.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/154fch1321621656.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/16w79m1321621656.tab")
+ }
>
> try(system("convert tmp/1f7a31321621655.ps tmp/1f7a31321621655.png",intern=TRUE))
character(0)
> try(system("convert tmp/2np0n1321621655.ps tmp/2np0n1321621655.png",intern=TRUE))
character(0)
> try(system("convert tmp/3r46i1321621655.ps tmp/3r46i1321621655.png",intern=TRUE))
character(0)
> try(system("convert tmp/40ems1321621655.ps tmp/40ems1321621655.png",intern=TRUE))
character(0)
> try(system("convert tmp/58rmf1321621655.ps tmp/58rmf1321621655.png",intern=TRUE))
character(0)
> try(system("convert tmp/6crfc1321621655.ps tmp/6crfc1321621655.png",intern=TRUE))
character(0)
> try(system("convert tmp/7df7s1321621655.ps tmp/7df7s1321621655.png",intern=TRUE))
character(0)
> try(system("convert tmp/8chus1321621655.ps tmp/8chus1321621655.png",intern=TRUE))
character(0)
> try(system("convert tmp/9p5vc1321621655.ps tmp/9p5vc1321621655.png",intern=TRUE))
character(0)
> try(system("convert tmp/10vwzm1321621655.ps tmp/10vwzm1321621655.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
28.165 0.736 29.098