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(56
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+ ,46
+ ,0
+ ,28
+ ,15
+ ,60
+ ,14
+ ,329
+ ,44
+ ,0
+ ,17
+ ,16
+ ,64)
+ ,dim=c(7
+ ,289)
+ ,dimnames=list(c('logins'
+ ,'compendium_views_info'
+ ,'compendium_views_pr'
+ ,'shared_compendiums'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'feedback_messages_p1')
+ ,1:289))
> y <- array(NA,dim=c(7,289),dimnames=list(c('logins','compendium_views_info','compendium_views_pr','shared_compendiums','blogged_computations','compendiums_reviewed','feedback_messages_p1'),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 = '5'
> 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
blogged_computations logins compendium_views_info compendium_views_pr
1 79 56 396 81
2 58 56 297 55
3 60 54 559 50
4 108 89 967 125
5 49 40 270 40
6 0 25 143 37
7 121 92 1562 63
8 1 18 109 44
9 20 63 371 88
10 43 44 656 66
11 69 33 511 57
12 78 84 655 74
13 86 88 465 49
14 44 55 525 52
15 104 60 885 88
16 63 66 497 36
17 158 154 1436 108
18 102 53 612 43
19 77 119 865 75
20 82 41 385 32
21 115 61 567 44
22 101 58 639 85
23 80 75 963 86
24 50 33 398 56
25 83 40 410 50
26 123 92 966 135
27 73 100 801 63
28 81 112 892 81
29 105 73 513 52
30 47 40 469 44
31 105 45 683 113
32 94 60 643 39
33 44 62 535 73
34 114 75 625 48
35 38 31 264 33
36 107 77 992 59
37 30 34 238 41
38 71 46 818 69
39 84 99 937 64
40 0 17 70 1
41 59 66 507 59
42 33 30 260 32
43 42 76 503 129
44 96 146 927 37
45 106 67 1269 31
46 56 56 537 65
47 57 107 910 107
48 59 58 532 74
49 39 34 345 54
50 34 61 918 76
51 76 119 1635 715
52 20 42 330 57
53 91 66 557 66
54 115 89 1178 106
55 85 44 740 54
56 76 66 452 32
57 8 24 218 20
58 79 259 764 71
59 21 17 255 21
60 30 64 454 70
61 76 41 866 112
62 101 68 574 66
63 94 168 1276 190
64 27 43 379 66
65 92 132 825 165
66 123 105 798 56
67 75 71 663 61
68 128 112 1069 53
69 105 94 921 127
70 55 82 858 63
71 56 70 711 38
72 41 57 503 50
73 72 53 382 52
74 67 103 464 42
75 75 121 717 76
76 114 62 690 67
77 118 52 462 50
78 77 52 657 53
79 22 32 385 39
80 66 62 577 50
81 69 45 619 77
82 105 46 479 57
83 116 63 817 73
84 88 75 752 34
85 73 88 430 39
86 99 46 451 46
87 62 53 537 63
88 53 37 519 35
89 118 90 1000 106
90 30 63 637 43
91 100 78 465 47
92 49 25 437 31
93 24 45 711 162
94 67 46 299 57
95 46 41 248 36
96 57 144 1162 263
97 75 82 714 78
98 135 91 905 63
99 68 71 649 54
100 124 63 512 63
101 33 53 472 77
102 98 62 905 79
103 58 63 786 110
104 68 32 489 56
105 81 39 479 56
106 131 62 617 43
107 110 117 925 111
108 37 34 351 71
109 130 92 1144 62
110 93 93 669 56
111 118 54 707 74
112 39 144 458 60
113 13 14 214 43
114 74 61 599 68
115 81 109 572 53
116 109 38 897 87
117 151 73 819 46
118 51 75 720 105
119 28 50 273 32
120 40 61 508 133
121 56 55 506 79
122 27 77 451 51
123 37 75 699 207
124 83 72 407 67
125 54 50 465 47
126 27 32 245 34
127 28 53 370 66
128 59 42 316 76
129 133 71 603 65
130 12 10 154 9
131 0 35 229 42
132 106 65 577 45
133 23 25 192 25
134 44 66 617 115
135 71 41 411 97
136 116 86 975 53
137 4 16 146 2
138 62 42 705 52
139 12 19 184 44
140 18 19 200 22
141 14 45 274 35
142 60 65 502 74
143 7 35 382 103
144 98 95 964 144
145 64 49 537 60
146 29 37 438 134
147 32 64 369 89
148 25 38 417 42
149 16 34 276 52
150 48 32 514 98
151 100 65 822 99
152 46 52 389 52
153 45 62 466 29
154 129 65 1255 125
155 130 83 694 106
156 136 95 1024 95
157 59 29 400 40
158 25 18 397 140
159 32 33 350 43
160 63 247 719 128
161 95 139 1277 142
162 14 29 356 73
163 36 118 457 72
164 113 110 1402 128
165 47 67 600 61
166 92 42 480 73
167 70 65 595 148
168 19 94 436 64
169 50 64 230 45
170 41 81 651 58
171 91 95 1367 97
172 111 67 564 50
173 41 63 716 37
174 120 83 747 50
175 135 45 467 105
176 27 30 671 69
177 87 70 861 46
178 25 32 319 57
179 131 83 612 52
180 45 31 433 98
181 29 67 434 61
182 58 66 503 89
183 4 10 85 0
184 47 70 564 48
185 109 103 824 91
186 7 5 74 0
187 12 20 259 7
188 0 5 69 3
189 37 36 535 54
190 37 34 239 70
191 46 48 438 36
192 15 40 459 37
193 42 43 426 123
194 7 31 288 247
195 54 42 498 46
196 54 46 454 72
197 14 33 376 41
198 16 18 225 24
199 33 55 555 45
200 32 35 252 33
201 21 59 208 27
202 15 19 130 36
203 38 66 481 87
204 22 60 389 90
205 28 36 565 114
206 10 25 173 31
207 31 47 278 45
208 32 54 609 69
209 32 53 422 51
210 43 40 445 34
211 27 40 387 60
212 37 39 339 45
213 20 14 181 54
214 32 45 245 25
215 0 36 384 38
216 5 28 212 52
217 26 44 399 67
218 10 30 229 74
219 27 22 224 38
220 11 17 203 30
221 29 31 333 26
222 25 55 384 67
223 55 54 636 132
224 23 21 185 42
225 5 14 93 35
226 43 81 581 118
227 23 35 248 68
228 34 43 304 43
229 36 46 344 76
230 35 30 407 64
231 0 23 170 48
232 37 38 312 64
233 28 54 507 56
234 16 20 224 71
235 26 53 340 75
236 38 45 168 39
237 23 39 443 42
238 22 20 204 39
239 30 24 367 93
240 16 31 210 38
241 18 35 335 60
242 28 151 364 71
243 32 52 178 52
244 21 30 206 27
245 23 31 279 59
246 29 29 387 40
247 50 57 490 79
248 12 40 238 44
249 21 44 343 65
250 18 25 232 10
251 27 77 530 124
252 41 35 291 81
253 13 11 67 15
254 12 63 397 92
255 21 44 467 42
256 8 19 178 10
257 26 13 175 24
258 27 42 299 64
259 13 38 154 45
260 16 29 106 22
261 2 20 189 56
262 42 27 194 94
263 5 20 135 19
264 37 19 201 35
265 17 37 207 32
266 38 26 280 35
267 37 42 260 48
268 29 49 227 49
269 32 30 239 48
270 35 49 333 62
271 17 67 428 96
272 20 28 230 45
273 7 19 292 63
274 46 49 350 71
275 24 27 186 26
276 40 30 326 48
277 3 22 155 29
278 10 12 75 19
279 37 31 361 45
280 17 20 261 45
281 28 20 299 67
282 19 39 300 30
283 29 29 450 36
284 8 16 183 34
285 10 27 238 36
286 15 21 165 34
287 15 19 234 37
288 28 35 176 46
289 17 14 329 44
shared_compendiums compendiums_reviewed feedback_messages_p1
1 3 30 115
2 4 28 109
3 12 38 146
4 2 30 116
5 1 22 68
6 3 26 101
7 0 25 96
8 0 18 67
9 0 11 44
10 5 26 100
11 0 25 93
12 0 38 140
13 7 44 166
14 7 30 99
15 3 40 139
16 9 34 130
17 0 47 181
18 4 30 116
19 3 31 116
20 0 23 88
21 7 36 139
22 0 36 135
23 1 30 108
24 5 25 89
25 7 39 156
26 0 34 129
27 0 31 118
28 5 31 118
29 0 33 125
30 0 25 95
31 0 33 126
32 3 35 135
33 4 42 154
34 1 43 165
35 4 30 113
36 2 33 127
37 0 13 52
38 0 32 121
39 0 36 136
40 0 0 0
41 2 28 108
42 1 14 46
43 0 17 54
44 2 32 124
45 10 30 115
46 6 35 128
47 0 20 80
48 5 28 97
49 4 28 104
50 1 39 59
51 2 34 125
52 2 26 82
53 0 39 149
54 8 39 149
55 3 33 122
56 0 28 118
57 0 4 12
58 8 39 144
59 5 18 67
60 3 14 52
61 1 29 108
62 5 44 166
63 1 21 80
64 1 16 60
65 5 28 107
66 0 35 127
67 12 28 107
68 8 38 146
69 8 23 84
70 8 36 141
71 8 32 123
72 2 29 111
73 0 25 98
74 5 27 105
75 8 36 135
76 2 28 107
77 5 23 85
78 12 40 155
79 6 23 88
80 7 40 155
81 2 28 104
82 0 34 132
83 4 33 127
84 3 28 108
85 6 34 129
86 2 30 116
87 0 33 122
88 1 22 85
89 0 38 147
90 5 26 99
91 2 35 87
92 0 8 28
93 0 24 90
94 5 29 109
95 0 20 78
96 1 29 111
97 0 45 158
98 1 37 141
99 1 33 122
100 2 33 124
101 6 25 93
102 1 32 124
103 4 29 112
104 2 28 108
105 3 28 99
106 0 31 117
107 10 52 199
108 0 21 78
109 9 24 91
110 7 41 158
111 0 33 126
112 0 32 122
113 4 19 71
114 4 20 75
115 0 31 115
116 0 31 119
117 0 32 124
118 1 18 72
119 0 23 91
120 1 17 45
121 0 20 78
122 0 12 39
123 4 17 68
124 0 30 119
125 4 31 117
126 4 10 39
127 3 13 50
128 0 22 88
129 0 42 155
130 0 1 0
131 5 9 36
132 0 32 123
133 4 11 32
134 0 25 99
135 0 36 136
136 1 31 117
137 0 0 0
138 5 24 88
139 0 13 39
140 0 8 25
141 0 13 52
142 0 19 75
143 0 18 71
144 2 33 124
145 7 40 151
146 1 22 71
147 8 38 145
148 2 24 87
149 0 8 27
150 2 35 131
151 0 43 162
152 0 43 165
153 1 14 54
154 3 41 159
155 0 38 147
156 3 45 170
157 0 31 119
158 0 13 49
159 0 28 104
160 4 31 120
161 4 40 150
162 11 30 112
163 0 16 59
164 0 37 136
165 4 30 107
166 0 35 130
167 1 32 115
168 0 27 107
169 0 20 75
170 0 18 71
171 9 31 120
172 1 31 116
173 3 21 79
174 10 39 150
175 5 41 156
176 0 13 51
177 2 32 118
178 0 18 71
179 1 39 144
180 2 14 47
181 4 7 28
182 0 17 68
183 0 0 0
184 2 30 110
185 1 37 147
186 0 0 0
187 0 5 15
188 0 1 4
189 1 16 64
190 0 32 111
191 2 24 85
192 0 17 68
193 3 11 40
194 6 24 80
195 0 22 88
196 2 12 48
197 0 19 76
198 2 13 51
199 1 17 67
200 1 15 59
201 2 16 61
202 1 24 76
203 0 15 60
204 1 17 68
205 3 18 71
206 0 20 76
207 0 16 62
208 0 16 61
209 0 18 67
210 1 22 88
211 4 8 30
212 0 17 64
213 0 18 68
214 0 16 64
215 7 23 91
216 2 22 88
217 0 13 52
218 7 13 49
219 3 16 62
220 0 16 61
221 0 20 76
222 6 22 88
223 2 17 66
224 0 18 71
225 0 17 68
226 3 12 48
227 0 7 25
228 1 17 68
229 1 14 41
230 0 23 90
231 1 17 66
232 0 14 54
233 0 15 59
234 0 17 60
235 0 21 77
236 0 18 68
237 0 18 72
238 0 17 67
239 0 17 64
240 0 16 63
241 0 15 59
242 0 21 84
243 0 16 64
244 2 14 56
245 0 15 54
246 1 17 67
247 1 15 58
248 0 15 59
249 0 10 40
250 0 6 22
251 0 22 83
252 0 21 81
253 0 1 2
254 1 18 72
255 0 17 61
256 0 4 15
257 0 10 32
258 0 16 62
259 1 16 58
260 0 9 36
261 0 16 59
262 0 17 68
263 0 7 21
264 0 15 55
265 0 14 54
266 0 14 55
267 0 18 72
268 0 12 41
269 0 16 61
270 0 21 67
271 1 19 76
272 0 16 64
273 0 1 3
274 1 16 63
275 0 10 40
276 6 19 69
277 3 12 48
278 1 2 8
279 2 14 52
280 0 17 66
281 0 19 76
282 0 14 43
283 3 11 39
284 1 4 14
285 0 16 61
286 0 20 71
287 1 12 44
288 0 15 60
289 0 16 64
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) logins compendium_views_info
-12.483970 0.002046 0.070739
compendium_views_pr shared_compendiums compendiums_reviewed
-0.125866 -1.416972 0.115793
feedback_messages_p1
0.433976
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-42.207 -12.657 -0.672 11.101 71.523
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -12.483970 2.864708 -4.358 1.84e-05 ***
logins 0.002046 0.047409 0.043 0.96560
compendium_views_info 0.070739 0.006553 10.795 < 2e-16 ***
compendium_views_pr -0.125866 0.025419 -4.952 1.27e-06 ***
shared_compendiums -1.416972 0.451903 -3.136 0.00190 **
compendiums_reviewed 0.115793 0.603540 0.192 0.84799
feedback_messages_p1 0.433976 0.158925 2.731 0.00672 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 19.19 on 282 degrees of freedom
Multiple R-squared: 0.7353, Adjusted R-squared: 0.7297
F-statistic: 130.6 on 6 and 282 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,] 0.27139127 5.427825e-01 7.286087e-01
[2,] 0.33930468 6.786094e-01 6.606953e-01
[3,] 0.68618185 6.276363e-01 3.138182e-01
[4,] 0.57667108 8.466578e-01 4.233289e-01
[5,] 0.57363133 8.527373e-01 4.263687e-01
[6,] 0.47367838 9.473568e-01 5.263216e-01
[7,] 0.39126618 7.825324e-01 6.087338e-01
[8,] 0.34089107 6.817821e-01 6.591089e-01
[9,] 0.62047837 7.590433e-01 3.795216e-01
[10,] 0.57043941 8.591212e-01 4.295606e-01
[11,] 0.70464711 5.907058e-01 2.953529e-01
[12,] 0.84092819 3.181436e-01 1.590718e-01
[13,] 0.79902717 4.019457e-01 2.009728e-01
[14,] 0.76811489 4.637702e-01 2.318851e-01
[15,] 0.71951181 5.609764e-01 2.804882e-01
[16,] 0.65975705 6.804859e-01 3.402429e-01
[17,] 0.64347214 7.130557e-01 3.565279e-01
[18,] 0.63036468 7.392706e-01 3.696353e-01
[19,] 0.56845667 8.630867e-01 4.315433e-01
[20,] 0.60045357 7.990929e-01 3.995464e-01
[21,] 0.58054426 8.389115e-01 4.194557e-01
[22,] 0.53718381 9.256324e-01 4.628162e-01
[23,] 0.47922249 9.584450e-01 5.207775e-01
[24,] 0.73534843 5.293031e-01 2.646516e-01
[25,] 0.69214192 6.157162e-01 3.078581e-01
[26,] 0.66449374 6.710125e-01 3.355063e-01
[27,] 0.61216004 7.756799e-01 3.878400e-01
[28,] 0.56259723 8.748055e-01 4.374028e-01
[29,] 0.60091267 7.981747e-01 3.990873e-01
[30,] 0.62669929 7.466014e-01 3.733007e-01
[31,] 0.59322197 8.135561e-01 4.067780e-01
[32,] 0.54853469 9.029306e-01 4.514653e-01
[33,] 0.51960280 9.607944e-01 4.803972e-01
[34,] 0.47128855 9.425771e-01 5.287115e-01
[35,] 0.42217098 8.443420e-01 5.778290e-01
[36,] 0.37944230 7.588846e-01 6.205577e-01
[37,] 0.35188877 7.037775e-01 6.481112e-01
[38,] 0.36141771 7.228354e-01 6.385823e-01
[39,] 0.32105624 6.421125e-01 6.789438e-01
[40,] 0.29375938 5.875188e-01 7.062406e-01
[41,] 0.31582203 6.316441e-01 6.841780e-01
[42,] 0.29237207 5.847441e-01 7.076279e-01
[43,] 0.29234060 5.846812e-01 7.076594e-01
[44,] 0.25383923 5.076785e-01 7.461608e-01
[45,] 0.21974645 4.394929e-01 7.802536e-01
[46,] 0.18733004 3.746601e-01 8.126700e-01
[47,] 0.16028862 3.205772e-01 8.397114e-01
[48,] 0.13424536 2.684907e-01 8.657546e-01
[49,] 0.11384420 2.276884e-01 8.861558e-01
[50,] 0.09586755 1.917351e-01 9.041325e-01
[51,] 0.07811286 1.562257e-01 9.218871e-01
[52,] 0.06585394 1.317079e-01 9.341461e-01
[53,] 0.05628897 1.125779e-01 9.437110e-01
[54,] 0.04715576 9.431152e-02 9.528442e-01
[55,] 0.03856285 7.712569e-02 9.614372e-01
[56,] 0.04701589 9.403177e-02 9.529841e-01
[57,] 0.06282778 1.256556e-01 9.371722e-01
[58,] 0.06264866 1.252973e-01 9.373513e-01
[59,] 0.05993754 1.198751e-01 9.400625e-01
[60,] 0.12446525 2.489305e-01 8.755347e-01
[61,] 0.23025927 4.605185e-01 7.697407e-01
[62,] 0.24723184 4.944637e-01 7.527682e-01
[63,] 0.27717631 5.543526e-01 7.228237e-01
[64,] 0.27002004 5.400401e-01 7.299800e-01
[65,] 0.24373971 4.874794e-01 7.562603e-01
[66,] 0.21626793 4.325359e-01 7.837321e-01
[67,] 0.32203614 6.440723e-01 6.779639e-01
[68,] 0.77912480 4.417504e-01 2.208752e-01
[69,] 0.75190093 4.961981e-01 2.480991e-01
[70,] 0.76211480 4.757704e-01 2.378852e-01
[71,] 0.75899528 4.820094e-01 2.410047e-01
[72,] 0.72818974 5.436205e-01 2.718103e-01
[73,] 0.76204518 4.759096e-01 2.379548e-01
[74,] 0.78564871 4.287026e-01 2.143513e-01
[75,] 0.75852304 4.829539e-01 2.414770e-01
[76,] 0.73252735 5.349453e-01 2.674727e-01
[77,] 0.78606901 4.278620e-01 2.139310e-01
[78,] 0.77427345 4.514531e-01 2.257265e-01
[79,] 0.74984382 5.003124e-01 2.501562e-01
[80,] 0.72116777 5.576645e-01 2.788322e-01
[81,] 0.80063694 3.987261e-01 1.993631e-01
[82,] 0.89854233 2.029153e-01 1.014577e-01
[83,] 0.89701245 2.059751e-01 1.029875e-01
[84,] 0.93332996 1.333401e-01 6.667004e-02
[85,] 0.93400715 1.319857e-01 6.599285e-02
[86,] 0.92354063 1.529187e-01 7.645937e-02
[87,] 0.94183096 1.163381e-01 5.816904e-02
[88,] 0.95395995 9.208010e-02 4.604005e-02
[89,] 0.96130548 7.738905e-02 3.869452e-02
[90,] 0.95857004 8.285991e-02 4.142996e-02
[91,] 0.98848071 2.303858e-02 1.151929e-02
[92,] 0.98717250 2.565500e-02 1.282750e-02
[93,] 0.98393779 3.212441e-02 1.606221e-02
[94,] 0.98327674 3.344653e-02 1.672326e-02
[95,] 0.97960047 4.079906e-02 2.039953e-02
[96,] 0.98101134 3.797732e-02 1.898866e-02
[97,] 0.99467447 1.065105e-02 5.325527e-03
[98,] 0.99327876 1.344249e-02 6.721245e-03
[99,] 0.99168358 1.663285e-02 8.316423e-03
[100,] 0.99656800 6.864004e-03 3.432002e-03
[101,] 0.99567252 8.654960e-03 4.327480e-03
[102,] 0.99712446 5.751085e-03 2.875543e-03
[103,] 0.99815566 3.688684e-03 1.844342e-03
[104,] 0.99787319 4.253610e-03 2.126805e-03
[105,] 0.99808751 3.824973e-03 1.912486e-03
[106,] 0.99753878 4.922448e-03 2.461224e-03
[107,] 0.99723218 5.535631e-03 2.767815e-03
[108,] 0.99967226 6.554753e-04 3.277376e-04
[109,] 0.99957568 8.486465e-04 4.243233e-04
[110,] 0.99956062 8.787605e-04 4.393803e-04
[111,] 0.99943815 1.123695e-03 5.618475e-04
[112,] 0.99927291 1.454181e-03 7.270906e-04
[113,] 0.99907244 1.855110e-03 9.275550e-04
[114,] 0.99876753 2.464935e-03 1.232468e-03
[115,] 0.99887535 2.249294e-03 1.124647e-03
[116,] 0.99859975 2.800494e-03 1.400247e-03
[117,] 0.99839025 3.219493e-03 1.609747e-03
[118,] 0.99790758 4.184850e-03 2.092425e-03
[119,] 0.99791380 4.172397e-03 2.086199e-03
[120,] 0.99924114 1.517711e-03 7.588553e-04
[121,] 0.99907495 1.850107e-03 9.250534e-04
[122,] 0.99885368 2.292638e-03 1.146319e-03
[123,] 0.99926809 1.463826e-03 7.319131e-04
[124,] 0.99912628 1.747448e-03 8.737239e-04
[125,] 0.99913012 1.739750e-03 8.698752e-04
[126,] 0.99890059 2.198819e-03 1.099409e-03
[127,] 0.99888446 2.231082e-03 1.115541e-03
[128,] 0.99855036 2.899284e-03 1.449642e-03
[129,] 0.99811304 3.773924e-03 1.886962e-03
[130,] 0.99758748 4.825042e-03 2.412521e-03
[131,] 0.99691754 6.164914e-03 3.082457e-03
[132,] 0.99653378 6.932443e-03 3.466222e-03
[133,] 0.99605144 7.897128e-03 3.948564e-03
[134,] 0.99724321 5.513574e-03 2.756787e-03
[135,] 0.99658619 6.827614e-03 3.413807e-03
[136,] 0.99596478 8.070445e-03 4.035223e-03
[137,] 0.99516501 9.669985e-03 4.834992e-03
[138,] 0.99592994 8.140118e-03 4.070059e-03
[139,] 0.99656862 6.862768e-03 3.431384e-03
[140,] 0.99557484 8.850327e-03 4.425164e-03
[141,] 0.99581120 8.377610e-03 4.188805e-03
[142,] 0.99482714 1.034571e-02 5.172856e-03
[143,] 0.99734743 5.305131e-03 2.652565e-03
[144,] 0.99672167 6.556669e-03 3.278334e-03
[145,] 0.99602544 7.949117e-03 3.974558e-03
[146,] 0.99884727 2.305457e-03 1.152728e-03
[147,] 0.99903249 1.935017e-03 9.675083e-04
[148,] 0.99875699 2.486028e-03 1.243014e-03
[149,] 0.99835435 3.291290e-03 1.645645e-03
[150,] 0.99848415 3.031708e-03 1.515854e-03
[151,] 0.99816390 3.672198e-03 1.836099e-03
[152,] 0.99846231 3.075384e-03 1.537692e-03
[153,] 0.99907660 1.846805e-03 9.234023e-04
[154,] 0.99878405 2.431894e-03 1.215947e-03
[155,] 0.99863616 2.727677e-03 1.363838e-03
[156,] 0.99877864 2.442717e-03 1.221359e-03
[157,] 0.99901374 1.972518e-03 9.862591e-04
[158,] 0.99872161 2.556780e-03 1.278390e-03
[159,] 0.99956761 8.647879e-04 4.323939e-04
[160,] 0.99952517 9.496662e-04 4.748331e-04
[161,] 0.99948181 1.036382e-03 5.181908e-04
[162,] 0.99955405 8.918990e-04 4.459495e-04
[163,] 0.99989653 2.069346e-04 1.034673e-04
[164,] 0.99992292 1.541658e-04 7.708292e-05
[165,] 0.99996158 7.684928e-05 3.842464e-05
[166,] 0.99999999 2.343754e-08 1.171877e-08
[167,] 0.99999999 1.711475e-08 8.557374e-09
[168,] 0.99999999 2.696448e-08 1.348224e-08
[169,] 0.99999998 4.172540e-08 2.086270e-08
[170,] 1.00000000 1.020446e-11 5.102231e-12
[171,] 1.00000000 9.876641e-12 4.938320e-12
[172,] 1.00000000 1.817283e-11 9.086413e-12
[173,] 1.00000000 1.598641e-11 7.993203e-12
[174,] 1.00000000 3.044376e-11 1.522188e-11
[175,] 1.00000000 4.505803e-11 2.252902e-11
[176,] 1.00000000 6.229657e-13 3.114828e-13
[177,] 1.00000000 1.227849e-12 6.139243e-13
[178,] 1.00000000 2.011449e-12 1.005725e-12
[179,] 1.00000000 3.265485e-12 1.632742e-12
[180,] 1.00000000 6.161324e-12 3.080662e-12
[181,] 1.00000000 8.561411e-12 4.280705e-12
[182,] 1.00000000 9.930022e-12 4.965011e-12
[183,] 1.00000000 4.377064e-12 2.188532e-12
[184,] 1.00000000 3.769005e-12 1.884502e-12
[185,] 1.00000000 4.873593e-12 2.436796e-12
[186,] 1.00000000 3.054088e-12 1.527044e-12
[187,] 1.00000000 7.746077e-13 3.873039e-13
[188,] 1.00000000 5.639258e-13 2.819629e-13
[189,] 1.00000000 1.174859e-12 5.874297e-13
[190,] 1.00000000 2.137625e-12 1.068812e-12
[191,] 1.00000000 2.986364e-12 1.493182e-12
[192,] 1.00000000 6.169793e-12 3.084897e-12
[193,] 1.00000000 1.112399e-11 5.561996e-12
[194,] 1.00000000 2.235919e-11 1.117960e-11
[195,] 1.00000000 3.472671e-11 1.736335e-11
[196,] 1.00000000 5.427962e-11 2.713981e-11
[197,] 1.00000000 6.779396e-11 3.389698e-11
[198,] 1.00000000 1.218366e-10 6.091828e-11
[199,] 1.00000000 1.773292e-10 8.866458e-11
[200,] 1.00000000 3.462336e-10 1.731168e-10
[201,] 1.00000000 4.000834e-10 2.000417e-10
[202,] 1.00000000 7.436517e-10 3.718258e-10
[203,] 1.00000000 1.093751e-09 5.468755e-10
[204,] 1.00000000 2.148832e-09 1.074416e-09
[205,] 1.00000000 2.833243e-09 1.416622e-09
[206,] 1.00000000 6.557384e-10 3.278692e-10
[207,] 1.00000000 3.828024e-10 1.914012e-10
[208,] 1.00000000 7.738607e-10 3.869303e-10
[209,] 1.00000000 8.448134e-10 4.224067e-10
[210,] 1.00000000 1.616059e-09 8.080297e-10
[211,] 1.00000000 2.421241e-09 1.210621e-09
[212,] 1.00000000 4.527259e-09 2.263630e-09
[213,] 1.00000000 6.172707e-09 3.086354e-09
[214,] 1.00000000 7.674207e-09 3.837103e-09
[215,] 0.99999999 1.519307e-08 7.596534e-09
[216,] 0.99999999 1.734626e-08 8.673128e-09
[217,] 0.99999999 2.965290e-08 1.482645e-08
[218,] 0.99999997 5.377888e-08 2.688944e-08
[219,] 0.99999996 8.538227e-08 4.269113e-08
[220,] 0.99999994 1.261421e-07 6.307104e-08
[221,] 0.99999989 2.291640e-07 1.145820e-07
[222,] 0.99999996 7.266236e-08 3.633118e-08
[223,] 0.99999996 7.973107e-08 3.986553e-08
[224,] 0.99999992 1.545204e-07 7.726018e-08
[225,] 0.99999988 2.389853e-07 1.194926e-07
[226,] 0.99999978 4.372778e-07 2.186389e-07
[227,] 0.99999979 4.116706e-07 2.058353e-07
[228,] 0.99999966 6.807268e-07 3.403634e-07
[229,] 0.99999933 1.345107e-06 6.725535e-07
[230,] 0.99999868 2.638713e-06 1.319357e-06
[231,] 0.99999778 4.446798e-06 2.223399e-06
[232,] 0.99999646 7.077141e-06 3.538571e-06
[233,] 0.99999354 1.291340e-05 6.456701e-06
[234,] 0.99999113 1.773118e-05 8.865588e-06
[235,] 0.99998329 3.341220e-05 1.670610e-05
[236,] 0.99996903 6.194398e-05 3.097199e-05
[237,] 0.99994395 1.121024e-04 5.605122e-05
[238,] 0.99997092 5.815915e-05 2.907958e-05
[239,] 0.99995966 8.068822e-05 4.034411e-05
[240,] 0.99992500 1.500000e-04 7.499999e-05
[241,] 0.99986922 2.615590e-04 1.307795e-04
[242,] 0.99980558 3.888403e-04 1.944201e-04
[243,] 0.99974392 5.121546e-04 2.560773e-04
[244,] 0.99960251 7.949755e-04 3.974878e-04
[245,] 0.99976993 4.601445e-04 2.300723e-04
[246,] 0.99969196 6.160753e-04 3.080376e-04
[247,] 0.99944396 1.112089e-03 5.560447e-04
[248,] 0.99934574 1.308528e-03 6.542641e-04
[249,] 0.99881632 2.367365e-03 1.183682e-03
[250,] 0.99834503 3.309939e-03 1.654970e-03
[251,] 0.99710139 5.797219e-03 2.898610e-03
[252,] 0.99830046 3.399084e-03 1.699542e-03
[253,] 0.99867173 2.656540e-03 1.328270e-03
[254,] 0.99790299 4.194028e-03 2.097014e-03
[255,] 0.99844045 3.119097e-03 1.559549e-03
[256,] 0.99751134 4.977312e-03 2.488656e-03
[257,] 0.99755639 4.887220e-03 2.443610e-03
[258,] 0.99653481 6.930375e-03 3.465188e-03
[259,] 0.99408094 1.183812e-02 5.919062e-03
[260,] 0.99241333 1.517333e-02 7.586666e-03
[261,] 0.98746972 2.506055e-02 1.253028e-02
[262,] 0.99914682 1.706357e-03 8.531784e-04
[263,] 0.99793862 4.122762e-03 2.061381e-03
[264,] 0.99779725 4.405490e-03 2.202745e-03
[265,] 0.99454990 1.090019e-02 5.450095e-03
[266,] 0.99509606 9.807880e-03 4.903940e-03
[267,] 0.98858135 2.283730e-02 1.141865e-02
[268,] 0.99556312 8.873765e-03 4.436883e-03
[269,] 0.99394462 1.211075e-02 6.055377e-03
[270,] 0.98198855 3.602290e-02 1.801145e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1amv21354809784.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2j2re1354809784.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/31tj41354809784.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4cupj1354809784.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5e1ta1354809784.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 289
Frequency = 1
1 2 3 4 5 6
24.4216589 11.4047410 -11.6334468 16.6491814 16.6963166 -35.6171440
7 8 9 10 11 12
-13.8259504 -19.8860077 -3.1816708 -22.0272192 9.1884539 -11.8648229
13 14 15 16 17 18
4.3614615 -10.7402643 4.1296962 -2.8784205 -1.8111241 28.3482112
19 20 21 22 23 24
-12.1889287 30.3400425 38.2156791 16.1062026 -13.8931480 6.8768840
25 26 27 28 29 30
10.3949361 24.0336377 -18.2519954 -7.3633766 29.5222121 -12.3590332
31 32 33 34 35 36
24.7976903 7.3960246 -38.3279107 12.9918601 -10.9462462 0.4769861
37 38 39 40 41 42
6.6668963 -22.0065829 -25.1351528 7.6233009 -4.3674650 10.8910610
43 44 45 46 47 48
9.5801360 -7.4174948 -6.7307012 -12.5361672 -18.6739803 4.7930679
49 50 51 52 53 54
-8.9017068 -37.7171923 7.2259604 -19.5342734 3.0759508 -0.5297681
55 56 57 58 59 60
-0.6716737 5.9511061 1.8601391 -9.8270389 -6.0219494 -0.8889337
61 62 63 64 65 66
-7.5735571 10.9975913 4.0586870 -5.5813188 24.0290833 26.6999727
67 68 69 70 71 72
15.4424066 14.8805652 40.3443013 -39.4719391 -22.9206234 -24.6166056
73 74 75 76 77 78
18.4736765 10.1275199 -5.3374010 39.1363448 71.5229856 -5.3215717
79 80 81 82 83 84
-20.2586486 -18.1453527 1.7542074 29.4583025 26.4810685 5.5533270
85 86 87 88 89 90
8.3767472 34.2952074 -12.4481474 -4.9185387 4.7077414 -36.1829967
91 92 93 94 95 96
46.3715868 21.3439373 -35.3502994 21.8366375 9.2219209 -30.0193117
97 98 99 100 101 102
-27.1529999 27.1503059 -14.1235989 53.2658604 -13.0744943 0.1800645
103 104 105 106 107 108
-17.6961607 5.5978203 24.6136452 50.7584425 -7.4308794 -2.7603783
109 110 111 112 113 114
39.6556012 1.6206747 31.1727575 -30.3077742 -11.6151187 23.3490487
115 116 117 118 119 120
5.9721404 13.6707214 53.6705792 -6.2994075 -17.0575093 13.0833569
121 122 123 124 125 126
6.3547868 -4.4724121 0.1270595 19.8618418 -9.2932870 13.9517068
127 128 129 130 131 132
3.5559531 17.8728994 38.7346135 14.5866653 -8.0809840 26.1139551
133 134 135 136 137 138
15.5044578 -18.6810652 3.3459522 13.0603150 6.3750315 -2.8121736
139 140 141 142 143 144
-1.4632008 7.2905488 -12.6574222 11.4056710 -27.5424184 5.4213876
145 146 147 148 149 150
-14.2946157 -4.6522610 -26.5385927 -24.5066871 2.7916986 -21.6762888
151 152 153 154 155 156
-8.6191826 -39.1801214 4.4038871 -1.1923269 38.3682717 13.0741569
157 158 159 160 161 162
-7.0691634 4.2147619 -23.3057689 -9.7709731 -29.3217508 -26.0627461
163 164 165 166 167 168
-2.4802572 -21.1117760 -19.6601938 19.1617645 6.6936271 -41.0571226
169 170 171 172 173 174
16.8828828 -18.3293756 -24.1159345 37.2293998 -25.1020490 30.3225916
175 176 177 178 179 180
62.2096691 -22.9967826 -7.8565292 -10.8695431 40.9752331 19.9412779
181 182 183 184 185 186
11.0298655 14.4902936 10.4506711 -22.8918501 7.7760179 14.2390346
187 188 189 190 191 192
-0.0859629 6.1186315 -9.8486113 -10.5583819 -4.8999184 -31.8890057
193 194 195 196 197 198
25.3607282 1.1412466 -3.7776210 23.9501513 -30.2032551 -5.2525540
199 200 201 202 203 204
-17.8527922 4.8151260 -3.4434301 -11.5640751 -0.5017807 -11.8903179
205 206 207 208 209 210
-13.8543040 -21.2012720 0.6270486 -18.3472026 -10.2179494 -11.1177691
211 212 213 214 215 216
11.3002510 1.3445815 -5.1463633 0.5802639 -42.2069179 -28.9284115
217 218 219 220 221 222
-5.4700684 2.6860424 3.8679796 -15.4601311 -14.1611577 -13.5949359
223 224 225 226 227 228
11.2206652 -5.2559654 -16.1969720 11.1014524 14.7679515 0.2416040
229 230 231 232 233 234
15.6242078 -15.0339511 -22.7411287 10.3351804 -15.7843138 -6.4731048
235 236 237 238 239 240
-12.0836879 11.8218190 -23.9774989 -6.1238652 -1.5638538 -10.8449795
241 242 243 244 245 246
-13.0748203 -15.5232723 8.7038496 -0.8411406 -2.0612227 -10.5447249
247 248 249 250 251 252
12.1579796 -14.2372023 -1.2053115 5.0377367 -21.1254716 5.4386607
253 254 255 256 257 258
21.6261759 -24.0623361 -22.7959418 2.1393519 14.0536216 -2.4567896
259 260 261 262 263 264
-5.4299926 7.0300424 -19.3354528 21.0578558 0.3606519 14.0262342
265 266 267 268 269 270
-6.2628653 9.5393026 3.7168378 12.3107907 5.2322414 0.1231763
271 272 273 274 275 276
-22.6116712 -7.8065393 5.3010685 14.7852421 8.0267631 11.7605705
277 278 279 280 281 282
-9.8449705 17.2590016 8.1937243 -13.9668294 -7.4572154 -6.3237008
283 284 285 286 287 288
0.1752709 6.6635265 -18.2012721 -13.0796936 -3.5183413 5.9766179
289
-17.9069401
> postscript(file="/var/wessaorg/rcomp/tmp/6nkix1354809784.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 24.4216589 NA
1 11.4047410 24.4216589
2 -11.6334468 11.4047410
3 16.6491814 -11.6334468
4 16.6963166 16.6491814
5 -35.6171440 16.6963166
6 -13.8259504 -35.6171440
7 -19.8860077 -13.8259504
8 -3.1816708 -19.8860077
9 -22.0272192 -3.1816708
10 9.1884539 -22.0272192
11 -11.8648229 9.1884539
12 4.3614615 -11.8648229
13 -10.7402643 4.3614615
14 4.1296962 -10.7402643
15 -2.8784205 4.1296962
16 -1.8111241 -2.8784205
17 28.3482112 -1.8111241
18 -12.1889287 28.3482112
19 30.3400425 -12.1889287
20 38.2156791 30.3400425
21 16.1062026 38.2156791
22 -13.8931480 16.1062026
23 6.8768840 -13.8931480
24 10.3949361 6.8768840
25 24.0336377 10.3949361
26 -18.2519954 24.0336377
27 -7.3633766 -18.2519954
28 29.5222121 -7.3633766
29 -12.3590332 29.5222121
30 24.7976903 -12.3590332
31 7.3960246 24.7976903
32 -38.3279107 7.3960246
33 12.9918601 -38.3279107
34 -10.9462462 12.9918601
35 0.4769861 -10.9462462
36 6.6668963 0.4769861
37 -22.0065829 6.6668963
38 -25.1351528 -22.0065829
39 7.6233009 -25.1351528
40 -4.3674650 7.6233009
41 10.8910610 -4.3674650
42 9.5801360 10.8910610
43 -7.4174948 9.5801360
44 -6.7307012 -7.4174948
45 -12.5361672 -6.7307012
46 -18.6739803 -12.5361672
47 4.7930679 -18.6739803
48 -8.9017068 4.7930679
49 -37.7171923 -8.9017068
50 7.2259604 -37.7171923
51 -19.5342734 7.2259604
52 3.0759508 -19.5342734
53 -0.5297681 3.0759508
54 -0.6716737 -0.5297681
55 5.9511061 -0.6716737
56 1.8601391 5.9511061
57 -9.8270389 1.8601391
58 -6.0219494 -9.8270389
59 -0.8889337 -6.0219494
60 -7.5735571 -0.8889337
61 10.9975913 -7.5735571
62 4.0586870 10.9975913
63 -5.5813188 4.0586870
64 24.0290833 -5.5813188
65 26.6999727 24.0290833
66 15.4424066 26.6999727
67 14.8805652 15.4424066
68 40.3443013 14.8805652
69 -39.4719391 40.3443013
70 -22.9206234 -39.4719391
71 -24.6166056 -22.9206234
72 18.4736765 -24.6166056
73 10.1275199 18.4736765
74 -5.3374010 10.1275199
75 39.1363448 -5.3374010
76 71.5229856 39.1363448
77 -5.3215717 71.5229856
78 -20.2586486 -5.3215717
79 -18.1453527 -20.2586486
80 1.7542074 -18.1453527
81 29.4583025 1.7542074
82 26.4810685 29.4583025
83 5.5533270 26.4810685
84 8.3767472 5.5533270
85 34.2952074 8.3767472
86 -12.4481474 34.2952074
87 -4.9185387 -12.4481474
88 4.7077414 -4.9185387
89 -36.1829967 4.7077414
90 46.3715868 -36.1829967
91 21.3439373 46.3715868
92 -35.3502994 21.3439373
93 21.8366375 -35.3502994
94 9.2219209 21.8366375
95 -30.0193117 9.2219209
96 -27.1529999 -30.0193117
97 27.1503059 -27.1529999
98 -14.1235989 27.1503059
99 53.2658604 -14.1235989
100 -13.0744943 53.2658604
101 0.1800645 -13.0744943
102 -17.6961607 0.1800645
103 5.5978203 -17.6961607
104 24.6136452 5.5978203
105 50.7584425 24.6136452
106 -7.4308794 50.7584425
107 -2.7603783 -7.4308794
108 39.6556012 -2.7603783
109 1.6206747 39.6556012
110 31.1727575 1.6206747
111 -30.3077742 31.1727575
112 -11.6151187 -30.3077742
113 23.3490487 -11.6151187
114 5.9721404 23.3490487
115 13.6707214 5.9721404
116 53.6705792 13.6707214
117 -6.2994075 53.6705792
118 -17.0575093 -6.2994075
119 13.0833569 -17.0575093
120 6.3547868 13.0833569
121 -4.4724121 6.3547868
122 0.1270595 -4.4724121
123 19.8618418 0.1270595
124 -9.2932870 19.8618418
125 13.9517068 -9.2932870
126 3.5559531 13.9517068
127 17.8728994 3.5559531
128 38.7346135 17.8728994
129 14.5866653 38.7346135
130 -8.0809840 14.5866653
131 26.1139551 -8.0809840
132 15.5044578 26.1139551
133 -18.6810652 15.5044578
134 3.3459522 -18.6810652
135 13.0603150 3.3459522
136 6.3750315 13.0603150
137 -2.8121736 6.3750315
138 -1.4632008 -2.8121736
139 7.2905488 -1.4632008
140 -12.6574222 7.2905488
141 11.4056710 -12.6574222
142 -27.5424184 11.4056710
143 5.4213876 -27.5424184
144 -14.2946157 5.4213876
145 -4.6522610 -14.2946157
146 -26.5385927 -4.6522610
147 -24.5066871 -26.5385927
148 2.7916986 -24.5066871
149 -21.6762888 2.7916986
150 -8.6191826 -21.6762888
151 -39.1801214 -8.6191826
152 4.4038871 -39.1801214
153 -1.1923269 4.4038871
154 38.3682717 -1.1923269
155 13.0741569 38.3682717
156 -7.0691634 13.0741569
157 4.2147619 -7.0691634
158 -23.3057689 4.2147619
159 -9.7709731 -23.3057689
160 -29.3217508 -9.7709731
161 -26.0627461 -29.3217508
162 -2.4802572 -26.0627461
163 -21.1117760 -2.4802572
164 -19.6601938 -21.1117760
165 19.1617645 -19.6601938
166 6.6936271 19.1617645
167 -41.0571226 6.6936271
168 16.8828828 -41.0571226
169 -18.3293756 16.8828828
170 -24.1159345 -18.3293756
171 37.2293998 -24.1159345
172 -25.1020490 37.2293998
173 30.3225916 -25.1020490
174 62.2096691 30.3225916
175 -22.9967826 62.2096691
176 -7.8565292 -22.9967826
177 -10.8695431 -7.8565292
178 40.9752331 -10.8695431
179 19.9412779 40.9752331
180 11.0298655 19.9412779
181 14.4902936 11.0298655
182 10.4506711 14.4902936
183 -22.8918501 10.4506711
184 7.7760179 -22.8918501
185 14.2390346 7.7760179
186 -0.0859629 14.2390346
187 6.1186315 -0.0859629
188 -9.8486113 6.1186315
189 -10.5583819 -9.8486113
190 -4.8999184 -10.5583819
191 -31.8890057 -4.8999184
192 25.3607282 -31.8890057
193 1.1412466 25.3607282
194 -3.7776210 1.1412466
195 23.9501513 -3.7776210
196 -30.2032551 23.9501513
197 -5.2525540 -30.2032551
198 -17.8527922 -5.2525540
199 4.8151260 -17.8527922
200 -3.4434301 4.8151260
201 -11.5640751 -3.4434301
202 -0.5017807 -11.5640751
203 -11.8903179 -0.5017807
204 -13.8543040 -11.8903179
205 -21.2012720 -13.8543040
206 0.6270486 -21.2012720
207 -18.3472026 0.6270486
208 -10.2179494 -18.3472026
209 -11.1177691 -10.2179494
210 11.3002510 -11.1177691
211 1.3445815 11.3002510
212 -5.1463633 1.3445815
213 0.5802639 -5.1463633
214 -42.2069179 0.5802639
215 -28.9284115 -42.2069179
216 -5.4700684 -28.9284115
217 2.6860424 -5.4700684
218 3.8679796 2.6860424
219 -15.4601311 3.8679796
220 -14.1611577 -15.4601311
221 -13.5949359 -14.1611577
222 11.2206652 -13.5949359
223 -5.2559654 11.2206652
224 -16.1969720 -5.2559654
225 11.1014524 -16.1969720
226 14.7679515 11.1014524
227 0.2416040 14.7679515
228 15.6242078 0.2416040
229 -15.0339511 15.6242078
230 -22.7411287 -15.0339511
231 10.3351804 -22.7411287
232 -15.7843138 10.3351804
233 -6.4731048 -15.7843138
234 -12.0836879 -6.4731048
235 11.8218190 -12.0836879
236 -23.9774989 11.8218190
237 -6.1238652 -23.9774989
238 -1.5638538 -6.1238652
239 -10.8449795 -1.5638538
240 -13.0748203 -10.8449795
241 -15.5232723 -13.0748203
242 8.7038496 -15.5232723
243 -0.8411406 8.7038496
244 -2.0612227 -0.8411406
245 -10.5447249 -2.0612227
246 12.1579796 -10.5447249
247 -14.2372023 12.1579796
248 -1.2053115 -14.2372023
249 5.0377367 -1.2053115
250 -21.1254716 5.0377367
251 5.4386607 -21.1254716
252 21.6261759 5.4386607
253 -24.0623361 21.6261759
254 -22.7959418 -24.0623361
255 2.1393519 -22.7959418
256 14.0536216 2.1393519
257 -2.4567896 14.0536216
258 -5.4299926 -2.4567896
259 7.0300424 -5.4299926
260 -19.3354528 7.0300424
261 21.0578558 -19.3354528
262 0.3606519 21.0578558
263 14.0262342 0.3606519
264 -6.2628653 14.0262342
265 9.5393026 -6.2628653
266 3.7168378 9.5393026
267 12.3107907 3.7168378
268 5.2322414 12.3107907
269 0.1231763 5.2322414
270 -22.6116712 0.1231763
271 -7.8065393 -22.6116712
272 5.3010685 -7.8065393
273 14.7852421 5.3010685
274 8.0267631 14.7852421
275 11.7605705 8.0267631
276 -9.8449705 11.7605705
277 17.2590016 -9.8449705
278 8.1937243 17.2590016
279 -13.9668294 8.1937243
280 -7.4572154 -13.9668294
281 -6.3237008 -7.4572154
282 0.1752709 -6.3237008
283 6.6635265 0.1752709
284 -18.2012721 6.6635265
285 -13.0796936 -18.2012721
286 -3.5183413 -13.0796936
287 5.9766179 -3.5183413
288 -17.9069401 5.9766179
289 NA -17.9069401
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 11.4047410 24.4216589
[2,] -11.6334468 11.4047410
[3,] 16.6491814 -11.6334468
[4,] 16.6963166 16.6491814
[5,] -35.6171440 16.6963166
[6,] -13.8259504 -35.6171440
[7,] -19.8860077 -13.8259504
[8,] -3.1816708 -19.8860077
[9,] -22.0272192 -3.1816708
[10,] 9.1884539 -22.0272192
[11,] -11.8648229 9.1884539
[12,] 4.3614615 -11.8648229
[13,] -10.7402643 4.3614615
[14,] 4.1296962 -10.7402643
[15,] -2.8784205 4.1296962
[16,] -1.8111241 -2.8784205
[17,] 28.3482112 -1.8111241
[18,] -12.1889287 28.3482112
[19,] 30.3400425 -12.1889287
[20,] 38.2156791 30.3400425
[21,] 16.1062026 38.2156791
[22,] -13.8931480 16.1062026
[23,] 6.8768840 -13.8931480
[24,] 10.3949361 6.8768840
[25,] 24.0336377 10.3949361
[26,] -18.2519954 24.0336377
[27,] -7.3633766 -18.2519954
[28,] 29.5222121 -7.3633766
[29,] -12.3590332 29.5222121
[30,] 24.7976903 -12.3590332
[31,] 7.3960246 24.7976903
[32,] -38.3279107 7.3960246
[33,] 12.9918601 -38.3279107
[34,] -10.9462462 12.9918601
[35,] 0.4769861 -10.9462462
[36,] 6.6668963 0.4769861
[37,] -22.0065829 6.6668963
[38,] -25.1351528 -22.0065829
[39,] 7.6233009 -25.1351528
[40,] -4.3674650 7.6233009
[41,] 10.8910610 -4.3674650
[42,] 9.5801360 10.8910610
[43,] -7.4174948 9.5801360
[44,] -6.7307012 -7.4174948
[45,] -12.5361672 -6.7307012
[46,] -18.6739803 -12.5361672
[47,] 4.7930679 -18.6739803
[48,] -8.9017068 4.7930679
[49,] -37.7171923 -8.9017068
[50,] 7.2259604 -37.7171923
[51,] -19.5342734 7.2259604
[52,] 3.0759508 -19.5342734
[53,] -0.5297681 3.0759508
[54,] -0.6716737 -0.5297681
[55,] 5.9511061 -0.6716737
[56,] 1.8601391 5.9511061
[57,] -9.8270389 1.8601391
[58,] -6.0219494 -9.8270389
[59,] -0.8889337 -6.0219494
[60,] -7.5735571 -0.8889337
[61,] 10.9975913 -7.5735571
[62,] 4.0586870 10.9975913
[63,] -5.5813188 4.0586870
[64,] 24.0290833 -5.5813188
[65,] 26.6999727 24.0290833
[66,] 15.4424066 26.6999727
[67,] 14.8805652 15.4424066
[68,] 40.3443013 14.8805652
[69,] -39.4719391 40.3443013
[70,] -22.9206234 -39.4719391
[71,] -24.6166056 -22.9206234
[72,] 18.4736765 -24.6166056
[73,] 10.1275199 18.4736765
[74,] -5.3374010 10.1275199
[75,] 39.1363448 -5.3374010
[76,] 71.5229856 39.1363448
[77,] -5.3215717 71.5229856
[78,] -20.2586486 -5.3215717
[79,] -18.1453527 -20.2586486
[80,] 1.7542074 -18.1453527
[81,] 29.4583025 1.7542074
[82,] 26.4810685 29.4583025
[83,] 5.5533270 26.4810685
[84,] 8.3767472 5.5533270
[85,] 34.2952074 8.3767472
[86,] -12.4481474 34.2952074
[87,] -4.9185387 -12.4481474
[88,] 4.7077414 -4.9185387
[89,] -36.1829967 4.7077414
[90,] 46.3715868 -36.1829967
[91,] 21.3439373 46.3715868
[92,] -35.3502994 21.3439373
[93,] 21.8366375 -35.3502994
[94,] 9.2219209 21.8366375
[95,] -30.0193117 9.2219209
[96,] -27.1529999 -30.0193117
[97,] 27.1503059 -27.1529999
[98,] -14.1235989 27.1503059
[99,] 53.2658604 -14.1235989
[100,] -13.0744943 53.2658604
[101,] 0.1800645 -13.0744943
[102,] -17.6961607 0.1800645
[103,] 5.5978203 -17.6961607
[104,] 24.6136452 5.5978203
[105,] 50.7584425 24.6136452
[106,] -7.4308794 50.7584425
[107,] -2.7603783 -7.4308794
[108,] 39.6556012 -2.7603783
[109,] 1.6206747 39.6556012
[110,] 31.1727575 1.6206747
[111,] -30.3077742 31.1727575
[112,] -11.6151187 -30.3077742
[113,] 23.3490487 -11.6151187
[114,] 5.9721404 23.3490487
[115,] 13.6707214 5.9721404
[116,] 53.6705792 13.6707214
[117,] -6.2994075 53.6705792
[118,] -17.0575093 -6.2994075
[119,] 13.0833569 -17.0575093
[120,] 6.3547868 13.0833569
[121,] -4.4724121 6.3547868
[122,] 0.1270595 -4.4724121
[123,] 19.8618418 0.1270595
[124,] -9.2932870 19.8618418
[125,] 13.9517068 -9.2932870
[126,] 3.5559531 13.9517068
[127,] 17.8728994 3.5559531
[128,] 38.7346135 17.8728994
[129,] 14.5866653 38.7346135
[130,] -8.0809840 14.5866653
[131,] 26.1139551 -8.0809840
[132,] 15.5044578 26.1139551
[133,] -18.6810652 15.5044578
[134,] 3.3459522 -18.6810652
[135,] 13.0603150 3.3459522
[136,] 6.3750315 13.0603150
[137,] -2.8121736 6.3750315
[138,] -1.4632008 -2.8121736
[139,] 7.2905488 -1.4632008
[140,] -12.6574222 7.2905488
[141,] 11.4056710 -12.6574222
[142,] -27.5424184 11.4056710
[143,] 5.4213876 -27.5424184
[144,] -14.2946157 5.4213876
[145,] -4.6522610 -14.2946157
[146,] -26.5385927 -4.6522610
[147,] -24.5066871 -26.5385927
[148,] 2.7916986 -24.5066871
[149,] -21.6762888 2.7916986
[150,] -8.6191826 -21.6762888
[151,] -39.1801214 -8.6191826
[152,] 4.4038871 -39.1801214
[153,] -1.1923269 4.4038871
[154,] 38.3682717 -1.1923269
[155,] 13.0741569 38.3682717
[156,] -7.0691634 13.0741569
[157,] 4.2147619 -7.0691634
[158,] -23.3057689 4.2147619
[159,] -9.7709731 -23.3057689
[160,] -29.3217508 -9.7709731
[161,] -26.0627461 -29.3217508
[162,] -2.4802572 -26.0627461
[163,] -21.1117760 -2.4802572
[164,] -19.6601938 -21.1117760
[165,] 19.1617645 -19.6601938
[166,] 6.6936271 19.1617645
[167,] -41.0571226 6.6936271
[168,] 16.8828828 -41.0571226
[169,] -18.3293756 16.8828828
[170,] -24.1159345 -18.3293756
[171,] 37.2293998 -24.1159345
[172,] -25.1020490 37.2293998
[173,] 30.3225916 -25.1020490
[174,] 62.2096691 30.3225916
[175,] -22.9967826 62.2096691
[176,] -7.8565292 -22.9967826
[177,] -10.8695431 -7.8565292
[178,] 40.9752331 -10.8695431
[179,] 19.9412779 40.9752331
[180,] 11.0298655 19.9412779
[181,] 14.4902936 11.0298655
[182,] 10.4506711 14.4902936
[183,] -22.8918501 10.4506711
[184,] 7.7760179 -22.8918501
[185,] 14.2390346 7.7760179
[186,] -0.0859629 14.2390346
[187,] 6.1186315 -0.0859629
[188,] -9.8486113 6.1186315
[189,] -10.5583819 -9.8486113
[190,] -4.8999184 -10.5583819
[191,] -31.8890057 -4.8999184
[192,] 25.3607282 -31.8890057
[193,] 1.1412466 25.3607282
[194,] -3.7776210 1.1412466
[195,] 23.9501513 -3.7776210
[196,] -30.2032551 23.9501513
[197,] -5.2525540 -30.2032551
[198,] -17.8527922 -5.2525540
[199,] 4.8151260 -17.8527922
[200,] -3.4434301 4.8151260
[201,] -11.5640751 -3.4434301
[202,] -0.5017807 -11.5640751
[203,] -11.8903179 -0.5017807
[204,] -13.8543040 -11.8903179
[205,] -21.2012720 -13.8543040
[206,] 0.6270486 -21.2012720
[207,] -18.3472026 0.6270486
[208,] -10.2179494 -18.3472026
[209,] -11.1177691 -10.2179494
[210,] 11.3002510 -11.1177691
[211,] 1.3445815 11.3002510
[212,] -5.1463633 1.3445815
[213,] 0.5802639 -5.1463633
[214,] -42.2069179 0.5802639
[215,] -28.9284115 -42.2069179
[216,] -5.4700684 -28.9284115
[217,] 2.6860424 -5.4700684
[218,] 3.8679796 2.6860424
[219,] -15.4601311 3.8679796
[220,] -14.1611577 -15.4601311
[221,] -13.5949359 -14.1611577
[222,] 11.2206652 -13.5949359
[223,] -5.2559654 11.2206652
[224,] -16.1969720 -5.2559654
[225,] 11.1014524 -16.1969720
[226,] 14.7679515 11.1014524
[227,] 0.2416040 14.7679515
[228,] 15.6242078 0.2416040
[229,] -15.0339511 15.6242078
[230,] -22.7411287 -15.0339511
[231,] 10.3351804 -22.7411287
[232,] -15.7843138 10.3351804
[233,] -6.4731048 -15.7843138
[234,] -12.0836879 -6.4731048
[235,] 11.8218190 -12.0836879
[236,] -23.9774989 11.8218190
[237,] -6.1238652 -23.9774989
[238,] -1.5638538 -6.1238652
[239,] -10.8449795 -1.5638538
[240,] -13.0748203 -10.8449795
[241,] -15.5232723 -13.0748203
[242,] 8.7038496 -15.5232723
[243,] -0.8411406 8.7038496
[244,] -2.0612227 -0.8411406
[245,] -10.5447249 -2.0612227
[246,] 12.1579796 -10.5447249
[247,] -14.2372023 12.1579796
[248,] -1.2053115 -14.2372023
[249,] 5.0377367 -1.2053115
[250,] -21.1254716 5.0377367
[251,] 5.4386607 -21.1254716
[252,] 21.6261759 5.4386607
[253,] -24.0623361 21.6261759
[254,] -22.7959418 -24.0623361
[255,] 2.1393519 -22.7959418
[256,] 14.0536216 2.1393519
[257,] -2.4567896 14.0536216
[258,] -5.4299926 -2.4567896
[259,] 7.0300424 -5.4299926
[260,] -19.3354528 7.0300424
[261,] 21.0578558 -19.3354528
[262,] 0.3606519 21.0578558
[263,] 14.0262342 0.3606519
[264,] -6.2628653 14.0262342
[265,] 9.5393026 -6.2628653
[266,] 3.7168378 9.5393026
[267,] 12.3107907 3.7168378
[268,] 5.2322414 12.3107907
[269,] 0.1231763 5.2322414
[270,] -22.6116712 0.1231763
[271,] -7.8065393 -22.6116712
[272,] 5.3010685 -7.8065393
[273,] 14.7852421 5.3010685
[274,] 8.0267631 14.7852421
[275,] 11.7605705 8.0267631
[276,] -9.8449705 11.7605705
[277,] 17.2590016 -9.8449705
[278,] 8.1937243 17.2590016
[279,] -13.9668294 8.1937243
[280,] -7.4572154 -13.9668294
[281,] -6.3237008 -7.4572154
[282,] 0.1752709 -6.3237008
[283,] 6.6635265 0.1752709
[284,] -18.2012721 6.6635265
[285,] -13.0796936 -18.2012721
[286,] -3.5183413 -13.0796936
[287,] 5.9766179 -3.5183413
[288,] -17.9069401 5.9766179
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 11.4047410 24.4216589
2 -11.6334468 11.4047410
3 16.6491814 -11.6334468
4 16.6963166 16.6491814
5 -35.6171440 16.6963166
6 -13.8259504 -35.6171440
7 -19.8860077 -13.8259504
8 -3.1816708 -19.8860077
9 -22.0272192 -3.1816708
10 9.1884539 -22.0272192
11 -11.8648229 9.1884539
12 4.3614615 -11.8648229
13 -10.7402643 4.3614615
14 4.1296962 -10.7402643
15 -2.8784205 4.1296962
16 -1.8111241 -2.8784205
17 28.3482112 -1.8111241
18 -12.1889287 28.3482112
19 30.3400425 -12.1889287
20 38.2156791 30.3400425
21 16.1062026 38.2156791
22 -13.8931480 16.1062026
23 6.8768840 -13.8931480
24 10.3949361 6.8768840
25 24.0336377 10.3949361
26 -18.2519954 24.0336377
27 -7.3633766 -18.2519954
28 29.5222121 -7.3633766
29 -12.3590332 29.5222121
30 24.7976903 -12.3590332
31 7.3960246 24.7976903
32 -38.3279107 7.3960246
33 12.9918601 -38.3279107
34 -10.9462462 12.9918601
35 0.4769861 -10.9462462
36 6.6668963 0.4769861
37 -22.0065829 6.6668963
38 -25.1351528 -22.0065829
39 7.6233009 -25.1351528
40 -4.3674650 7.6233009
41 10.8910610 -4.3674650
42 9.5801360 10.8910610
43 -7.4174948 9.5801360
44 -6.7307012 -7.4174948
45 -12.5361672 -6.7307012
46 -18.6739803 -12.5361672
47 4.7930679 -18.6739803
48 -8.9017068 4.7930679
49 -37.7171923 -8.9017068
50 7.2259604 -37.7171923
51 -19.5342734 7.2259604
52 3.0759508 -19.5342734
53 -0.5297681 3.0759508
54 -0.6716737 -0.5297681
55 5.9511061 -0.6716737
56 1.8601391 5.9511061
57 -9.8270389 1.8601391
58 -6.0219494 -9.8270389
59 -0.8889337 -6.0219494
60 -7.5735571 -0.8889337
61 10.9975913 -7.5735571
62 4.0586870 10.9975913
63 -5.5813188 4.0586870
64 24.0290833 -5.5813188
65 26.6999727 24.0290833
66 15.4424066 26.6999727
67 14.8805652 15.4424066
68 40.3443013 14.8805652
69 -39.4719391 40.3443013
70 -22.9206234 -39.4719391
71 -24.6166056 -22.9206234
72 18.4736765 -24.6166056
73 10.1275199 18.4736765
74 -5.3374010 10.1275199
75 39.1363448 -5.3374010
76 71.5229856 39.1363448
77 -5.3215717 71.5229856
78 -20.2586486 -5.3215717
79 -18.1453527 -20.2586486
80 1.7542074 -18.1453527
81 29.4583025 1.7542074
82 26.4810685 29.4583025
83 5.5533270 26.4810685
84 8.3767472 5.5533270
85 34.2952074 8.3767472
86 -12.4481474 34.2952074
87 -4.9185387 -12.4481474
88 4.7077414 -4.9185387
89 -36.1829967 4.7077414
90 46.3715868 -36.1829967
91 21.3439373 46.3715868
92 -35.3502994 21.3439373
93 21.8366375 -35.3502994
94 9.2219209 21.8366375
95 -30.0193117 9.2219209
96 -27.1529999 -30.0193117
97 27.1503059 -27.1529999
98 -14.1235989 27.1503059
99 53.2658604 -14.1235989
100 -13.0744943 53.2658604
101 0.1800645 -13.0744943
102 -17.6961607 0.1800645
103 5.5978203 -17.6961607
104 24.6136452 5.5978203
105 50.7584425 24.6136452
106 -7.4308794 50.7584425
107 -2.7603783 -7.4308794
108 39.6556012 -2.7603783
109 1.6206747 39.6556012
110 31.1727575 1.6206747
111 -30.3077742 31.1727575
112 -11.6151187 -30.3077742
113 23.3490487 -11.6151187
114 5.9721404 23.3490487
115 13.6707214 5.9721404
116 53.6705792 13.6707214
117 -6.2994075 53.6705792
118 -17.0575093 -6.2994075
119 13.0833569 -17.0575093
120 6.3547868 13.0833569
121 -4.4724121 6.3547868
122 0.1270595 -4.4724121
123 19.8618418 0.1270595
124 -9.2932870 19.8618418
125 13.9517068 -9.2932870
126 3.5559531 13.9517068
127 17.8728994 3.5559531
128 38.7346135 17.8728994
129 14.5866653 38.7346135
130 -8.0809840 14.5866653
131 26.1139551 -8.0809840
132 15.5044578 26.1139551
133 -18.6810652 15.5044578
134 3.3459522 -18.6810652
135 13.0603150 3.3459522
136 6.3750315 13.0603150
137 -2.8121736 6.3750315
138 -1.4632008 -2.8121736
139 7.2905488 -1.4632008
140 -12.6574222 7.2905488
141 11.4056710 -12.6574222
142 -27.5424184 11.4056710
143 5.4213876 -27.5424184
144 -14.2946157 5.4213876
145 -4.6522610 -14.2946157
146 -26.5385927 -4.6522610
147 -24.5066871 -26.5385927
148 2.7916986 -24.5066871
149 -21.6762888 2.7916986
150 -8.6191826 -21.6762888
151 -39.1801214 -8.6191826
152 4.4038871 -39.1801214
153 -1.1923269 4.4038871
154 38.3682717 -1.1923269
155 13.0741569 38.3682717
156 -7.0691634 13.0741569
157 4.2147619 -7.0691634
158 -23.3057689 4.2147619
159 -9.7709731 -23.3057689
160 -29.3217508 -9.7709731
161 -26.0627461 -29.3217508
162 -2.4802572 -26.0627461
163 -21.1117760 -2.4802572
164 -19.6601938 -21.1117760
165 19.1617645 -19.6601938
166 6.6936271 19.1617645
167 -41.0571226 6.6936271
168 16.8828828 -41.0571226
169 -18.3293756 16.8828828
170 -24.1159345 -18.3293756
171 37.2293998 -24.1159345
172 -25.1020490 37.2293998
173 30.3225916 -25.1020490
174 62.2096691 30.3225916
175 -22.9967826 62.2096691
176 -7.8565292 -22.9967826
177 -10.8695431 -7.8565292
178 40.9752331 -10.8695431
179 19.9412779 40.9752331
180 11.0298655 19.9412779
181 14.4902936 11.0298655
182 10.4506711 14.4902936
183 -22.8918501 10.4506711
184 7.7760179 -22.8918501
185 14.2390346 7.7760179
186 -0.0859629 14.2390346
187 6.1186315 -0.0859629
188 -9.8486113 6.1186315
189 -10.5583819 -9.8486113
190 -4.8999184 -10.5583819
191 -31.8890057 -4.8999184
192 25.3607282 -31.8890057
193 1.1412466 25.3607282
194 -3.7776210 1.1412466
195 23.9501513 -3.7776210
196 -30.2032551 23.9501513
197 -5.2525540 -30.2032551
198 -17.8527922 -5.2525540
199 4.8151260 -17.8527922
200 -3.4434301 4.8151260
201 -11.5640751 -3.4434301
202 -0.5017807 -11.5640751
203 -11.8903179 -0.5017807
204 -13.8543040 -11.8903179
205 -21.2012720 -13.8543040
206 0.6270486 -21.2012720
207 -18.3472026 0.6270486
208 -10.2179494 -18.3472026
209 -11.1177691 -10.2179494
210 11.3002510 -11.1177691
211 1.3445815 11.3002510
212 -5.1463633 1.3445815
213 0.5802639 -5.1463633
214 -42.2069179 0.5802639
215 -28.9284115 -42.2069179
216 -5.4700684 -28.9284115
217 2.6860424 -5.4700684
218 3.8679796 2.6860424
219 -15.4601311 3.8679796
220 -14.1611577 -15.4601311
221 -13.5949359 -14.1611577
222 11.2206652 -13.5949359
223 -5.2559654 11.2206652
224 -16.1969720 -5.2559654
225 11.1014524 -16.1969720
226 14.7679515 11.1014524
227 0.2416040 14.7679515
228 15.6242078 0.2416040
229 -15.0339511 15.6242078
230 -22.7411287 -15.0339511
231 10.3351804 -22.7411287
232 -15.7843138 10.3351804
233 -6.4731048 -15.7843138
234 -12.0836879 -6.4731048
235 11.8218190 -12.0836879
236 -23.9774989 11.8218190
237 -6.1238652 -23.9774989
238 -1.5638538 -6.1238652
239 -10.8449795 -1.5638538
240 -13.0748203 -10.8449795
241 -15.5232723 -13.0748203
242 8.7038496 -15.5232723
243 -0.8411406 8.7038496
244 -2.0612227 -0.8411406
245 -10.5447249 -2.0612227
246 12.1579796 -10.5447249
247 -14.2372023 12.1579796
248 -1.2053115 -14.2372023
249 5.0377367 -1.2053115
250 -21.1254716 5.0377367
251 5.4386607 -21.1254716
252 21.6261759 5.4386607
253 -24.0623361 21.6261759
254 -22.7959418 -24.0623361
255 2.1393519 -22.7959418
256 14.0536216 2.1393519
257 -2.4567896 14.0536216
258 -5.4299926 -2.4567896
259 7.0300424 -5.4299926
260 -19.3354528 7.0300424
261 21.0578558 -19.3354528
262 0.3606519 21.0578558
263 14.0262342 0.3606519
264 -6.2628653 14.0262342
265 9.5393026 -6.2628653
266 3.7168378 9.5393026
267 12.3107907 3.7168378
268 5.2322414 12.3107907
269 0.1231763 5.2322414
270 -22.6116712 0.1231763
271 -7.8065393 -22.6116712
272 5.3010685 -7.8065393
273 14.7852421 5.3010685
274 8.0267631 14.7852421
275 11.7605705 8.0267631
276 -9.8449705 11.7605705
277 17.2590016 -9.8449705
278 8.1937243 17.2590016
279 -13.9668294 8.1937243
280 -7.4572154 -13.9668294
281 -6.3237008 -7.4572154
282 0.1752709 -6.3237008
283 6.6635265 0.1752709
284 -18.2012721 6.6635265
285 -13.0796936 -18.2012721
286 -3.5183413 -13.0796936
287 5.9766179 -3.5183413
288 -17.9069401 5.9766179
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/7fexl1354809784.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8yhvp1354809784.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9o2my1354809784.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10pejh1354809784.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/110g3r1354809784.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12tfd81354809784.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/1386dr1354809784.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14grme1354809784.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/156dek1354809784.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/16q9r71354809784.tab")
+ }
>
> try(system("convert tmp/1amv21354809784.ps tmp/1amv21354809784.png",intern=TRUE))
character(0)
> try(system("convert tmp/2j2re1354809784.ps tmp/2j2re1354809784.png",intern=TRUE))
character(0)
> try(system("convert tmp/31tj41354809784.ps tmp/31tj41354809784.png",intern=TRUE))
character(0)
> try(system("convert tmp/4cupj1354809784.ps tmp/4cupj1354809784.png",intern=TRUE))
character(0)
> try(system("convert tmp/5e1ta1354809784.ps tmp/5e1ta1354809784.png",intern=TRUE))
character(0)
> try(system("convert tmp/6nkix1354809784.ps tmp/6nkix1354809784.png",intern=TRUE))
character(0)
> try(system("convert tmp/7fexl1354809784.ps tmp/7fexl1354809784.png",intern=TRUE))
character(0)
> try(system("convert tmp/8yhvp1354809784.ps tmp/8yhvp1354809784.png",intern=TRUE))
character(0)
> try(system("convert tmp/9o2my1354809784.ps tmp/9o2my1354809784.png",intern=TRUE))
character(0)
> try(system("convert tmp/10pejh1354809784.ps tmp/10pejh1354809784.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
13.316 1.026 14.336