R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(210907
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+ ,0
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+ ,0
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+ ,29
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+ ,3
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+ ,16
+ ,183
+ ,8
+ ,4
+ ,14
+ ,1
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+ ,27
+ ,238
+ ,10
+ ,16
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+ ,0
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+ ,21
+ ,165
+ ,15
+ ,20
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+ ,0
+ ,56613
+ ,19
+ ,234
+ ,15
+ ,12
+ ,44
+ ,1
+ ,62792
+ ,35
+ ,176
+ ,28
+ ,15
+ ,60
+ ,0
+ ,72535
+ ,14
+ ,329
+ ,17
+ ,16
+ ,64
+ ,0)
+ ,dim=c(7
+ ,289)
+ ,dimnames=list(c('time_in_rfc'
+ ,'logins'
+ ,'compendium_views_info'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'feedback_messages_p1'
+ ,'shared_compendiums')
+ ,1:289))
> y <- array(NA,dim=c(7,289),dimnames=list(c('time_in_rfc','logins','compendium_views_info','blogged_computations','compendiums_reviewed','feedback_messages_p1','shared_compendiums'),1:289))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> 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
time_in_rfc logins compendium_views_info blogged_computations
1 210907 56 396 79
2 120982 56 297 58
3 176508 54 559 60
4 179321 89 967 108
5 123185 40 270 49
6 52746 25 143 0
7 385534 92 1562 121
8 33170 18 109 1
9 101645 63 371 20
10 149061 44 656 43
11 165446 33 511 69
12 237213 84 655 78
13 173326 88 465 86
14 133131 55 525 44
15 258873 60 885 104
16 180083 66 497 63
17 324799 154 1436 158
18 230964 53 612 102
19 236785 119 865 77
20 135473 41 385 82
21 202925 61 567 115
22 215147 58 639 101
23 344297 75 963 80
24 153935 33 398 50
25 132943 40 410 83
26 174724 92 966 123
27 174415 100 801 73
28 225548 112 892 81
29 223632 73 513 105
30 124817 40 469 47
31 221698 45 683 105
32 210767 60 643 94
33 170266 62 535 44
34 260561 75 625 114
35 84853 31 264 38
36 294424 77 992 107
37 101011 34 238 30
38 215641 46 818 71
39 325107 99 937 84
40 7176 17 70 0
41 167542 66 507 59
42 106408 30 260 33
43 96560 76 503 42
44 265769 146 927 96
45 269651 67 1269 106
46 149112 56 537 56
47 175824 107 910 57
48 152871 58 532 59
49 111665 34 345 39
50 116408 61 918 34
51 362301 119 1635 76
52 78800 42 330 20
53 183167 66 557 91
54 277965 89 1178 115
55 150629 44 740 85
56 168809 66 452 76
57 24188 24 218 8
58 329267 259 764 79
59 65029 17 255 21
60 101097 64 454 30
61 218946 41 866 76
62 244052 68 574 101
63 341570 168 1276 94
64 103597 43 379 27
65 233328 132 825 92
66 256462 105 798 123
67 206161 71 663 75
68 311473 112 1069 128
69 235800 94 921 105
70 177939 82 858 55
71 207176 70 711 56
72 196553 57 503 41
73 174184 53 382 72
74 143246 103 464 67
75 187559 121 717 75
76 187681 62 690 114
77 119016 52 462 118
78 182192 52 657 77
79 73566 32 385 22
80 194979 62 577 66
81 167488 45 619 69
82 143756 46 479 105
83 275541 63 817 116
84 243199 75 752 88
85 182999 88 430 73
86 135649 46 451 99
87 152299 53 537 62
88 120221 37 519 53
89 346485 90 1000 118
90 145790 63 637 30
91 193339 78 465 100
92 80953 25 437 49
93 122774 45 711 24
94 130585 46 299 67
95 112611 41 248 46
96 286468 144 1162 57
97 241066 82 714 75
98 148446 91 905 135
99 204713 71 649 68
100 182079 63 512 124
101 140344 53 472 33
102 220516 62 905 98
103 243060 63 786 58
104 162765 32 489 68
105 182613 39 479 81
106 232138 62 617 131
107 265318 117 925 110
108 85574 34 351 37
109 310839 92 1144 130
110 225060 93 669 93
111 232317 54 707 118
112 144966 144 458 39
113 43287 14 214 13
114 155754 61 599 74
115 164709 109 572 81
116 201940 38 897 109
117 235454 73 819 151
118 220801 75 720 51
119 99466 50 273 28
120 92661 61 508 40
121 133328 55 506 56
122 61361 77 451 27
123 125930 75 699 37
124 100750 72 407 83
125 224549 50 465 54
126 82316 32 245 27
127 102010 53 370 28
128 101523 42 316 59
129 243511 71 603 133
130 22938 10 154 12
131 41566 35 229 0
132 152474 65 577 106
133 61857 25 192 23
134 99923 66 617 44
135 132487 41 411 71
136 317394 86 975 116
137 21054 16 146 4
138 209641 42 705 62
139 22648 19 184 12
140 31414 19 200 18
141 46698 45 274 14
142 131698 65 502 60
143 91735 35 382 7
144 244749 95 964 98
145 184510 49 537 64
146 79863 37 438 29
147 128423 64 369 32
148 97839 38 417 25
149 38214 34 276 16
150 151101 32 514 48
151 272458 65 822 100
152 172494 52 389 46
153 108043 62 466 45
154 328107 65 1255 129
155 250579 83 694 130
156 351067 95 1024 136
157 158015 29 400 59
158 98866 18 397 25
159 85439 33 350 32
160 229242 247 719 63
161 351619 139 1277 95
162 84207 29 356 14
163 120445 118 457 36
164 324598 110 1402 113
165 131069 67 600 47
166 204271 42 480 92
167 165543 65 595 70
168 141722 94 436 19
169 116048 64 230 50
170 250047 81 651 41
171 299775 95 1367 91
172 195838 67 564 111
173 173260 63 716 41
174 254488 83 747 120
175 104389 45 467 135
176 136084 30 671 27
177 199476 70 861 87
178 92499 32 319 25
179 224330 83 612 131
180 135781 31 433 45
181 74408 67 434 29
182 81240 66 503 58
183 14688 10 85 4
184 181633 70 564 47
185 271856 103 824 109
186 7199 5 74 7
187 46660 20 259 12
188 17547 5 69 0
189 133368 36 535 37
190 95227 34 239 37
191 152601 48 438 46
192 98146 40 459 15
193 79619 43 426 42
194 59194 31 288 7
195 139942 42 498 54
196 118612 46 454 54
197 72880 33 376 14
198 65475 18 225 16
199 99643 55 555 33
200 71965 35 252 32
201 77272 59 208 21
202 49289 19 130 15
203 135131 66 481 38
204 108446 60 389 22
205 89746 36 565 28
206 44296 25 173 10
207 77648 47 278 31
208 181528 54 609 32
209 134019 53 422 32
210 124064 40 445 43
211 92630 40 387 27
212 121848 39 339 37
213 52915 14 181 20
214 81872 45 245 32
215 58981 36 384 0
216 53515 28 212 5
217 60812 44 399 26
218 56375 30 229 10
219 65490 22 224 27
220 80949 17 203 11
221 76302 31 333 29
222 104011 55 384 25
223 98104 54 636 55
224 67989 21 185 23
225 30989 14 93 5
226 135458 81 581 43
227 73504 35 248 23
228 63123 43 304 34
229 61254 46 344 36
230 74914 30 407 35
231 31774 23 170 0
232 81437 38 312 37
233 87186 54 507 28
234 50090 20 224 16
235 65745 53 340 26
236 56653 45 168 38
237 158399 39 443 23
238 46455 20 204 22
239 73624 24 367 30
240 38395 31 210 16
241 91899 35 335 18
242 139526 151 364 28
243 52164 52 178 32
244 51567 30 206 21
245 70551 31 279 23
246 84856 29 387 29
247 102538 57 490 50
248 86678 40 238 12
249 85709 44 343 21
250 34662 25 232 18
251 150580 77 530 27
252 99611 35 291 41
253 19349 11 67 13
254 99373 63 397 12
255 86230 44 467 21
256 30837 19 178 8
257 31706 13 175 26
258 89806 42 299 27
259 62088 38 154 13
260 40151 29 106 16
261 27634 20 189 2
262 76990 27 194 42
263 37460 20 135 5
264 54157 19 201 37
265 49862 37 207 17
266 84337 26 280 38
267 64175 42 260 37
268 59382 49 227 29
269 119308 30 239 32
270 76702 49 333 35
271 103425 67 428 17
272 70344 28 230 20
273 43410 19 292 7
274 104838 49 350 46
275 62215 27 186 24
276 69304 30 326 40
277 53117 22 155 3
278 19764 12 75 10
279 86680 31 361 37
280 84105 20 261 17
281 77945 20 299 28
282 89113 39 300 19
283 91005 29 450 29
284 40248 16 183 8
285 64187 27 238 10
286 50857 21 165 15
287 56613 19 234 15
288 62792 35 176 28
289 72535 14 329 17
compendiums_reviewed feedback_messages_p1 shared_compendiums
1 30 115 3
2 28 109 4
3 38 146 12
4 30 116 2
5 22 68 1
6 26 101 3
7 25 96 0
8 18 67 0
9 11 44 0
10 26 100 5
11 25 93 0
12 38 140 0
13 44 166 7
14 30 99 7
15 40 139 3
16 34 130 9
17 47 181 0
18 30 116 4
19 31 116 3
20 23 88 0
21 36 139 7
22 36 135 0
23 30 108 1
24 25 89 5
25 39 156 7
26 34 129 0
27 31 118 0
28 31 118 5
29 33 125 0
30 25 95 0
31 33 126 0
32 35 135 3
33 42 154 4
34 43 165 1
35 30 113 4
36 33 127 2
37 13 52 0
38 32 121 0
39 36 136 0
40 0 0 0
41 28 108 2
42 14 46 1
43 17 54 0
44 32 124 2
45 30 115 10
46 35 128 6
47 20 80 0
48 28 97 5
49 28 104 4
50 39 59 1
51 34 125 2
52 26 82 2
53 39 149 0
54 39 149 8
55 33 122 3
56 28 118 0
57 4 12 0
58 39 144 8
59 18 67 5
60 14 52 3
61 29 108 1
62 44 166 5
63 21 80 1
64 16 60 1
65 28 107 5
66 35 127 0
67 28 107 12
68 38 146 8
69 23 84 8
70 36 141 8
71 32 123 8
72 29 111 2
73 25 98 0
74 27 105 5
75 36 135 8
76 28 107 2
77 23 85 5
78 40 155 12
79 23 88 6
80 40 155 7
81 28 104 2
82 34 132 0
83 33 127 4
84 28 108 3
85 34 129 6
86 30 116 2
87 33 122 0
88 22 85 1
89 38 147 0
90 26 99 5
91 35 87 2
92 8 28 0
93 24 90 0
94 29 109 5
95 20 78 0
96 29 111 1
97 45 158 0
98 37 141 1
99 33 122 1
100 33 124 2
101 25 93 6
102 32 124 1
103 29 112 4
104 28 108 2
105 28 99 3
106 31 117 0
107 52 199 10
108 21 78 0
109 24 91 9
110 41 158 7
111 33 126 0
112 32 122 0
113 19 71 4
114 20 75 4
115 31 115 0
116 31 119 0
117 32 124 0
118 18 72 1
119 23 91 0
120 17 45 1
121 20 78 0
122 12 39 0
123 17 68 4
124 30 119 0
125 31 117 4
126 10 39 4
127 13 50 3
128 22 88 0
129 42 155 0
130 1 0 0
131 9 36 5
132 32 123 0
133 11 32 4
134 25 99 0
135 36 136 0
136 31 117 1
137 0 0 0
138 24 88 5
139 13 39 0
140 8 25 0
141 13 52 0
142 19 75 0
143 18 71 0
144 33 124 2
145 40 151 7
146 22 71 1
147 38 145 8
148 24 87 2
149 8 27 0
150 35 131 2
151 43 162 0
152 43 165 0
153 14 54 1
154 41 159 3
155 38 147 0
156 45 170 3
157 31 119 0
158 13 49 0
159 28 104 0
160 31 120 4
161 40 150 4
162 30 112 11
163 16 59 0
164 37 136 0
165 30 107 4
166 35 130 0
167 32 115 1
168 27 107 0
169 20 75 0
170 18 71 0
171 31 120 9
172 31 116 1
173 21 79 3
174 39 150 10
175 41 156 5
176 13 51 0
177 32 118 2
178 18 71 0
179 39 144 1
180 14 47 2
181 7 28 4
182 17 68 0
183 0 0 0
184 30 110 2
185 37 147 1
186 0 0 0
187 5 15 0
188 1 4 0
189 16 64 1
190 32 111 0
191 24 85 2
192 17 68 0
193 11 40 3
194 24 80 6
195 22 88 0
196 12 48 2
197 19 76 0
198 13 51 2
199 17 67 1
200 15 59 1
201 16 61 2
202 24 76 1
203 15 60 0
204 17 68 1
205 18 71 3
206 20 76 0
207 16 62 0
208 16 61 0
209 18 67 0
210 22 88 1
211 8 30 4
212 17 64 0
213 18 68 0
214 16 64 0
215 23 91 7
216 22 88 2
217 13 52 0
218 13 49 7
219 16 62 3
220 16 61 0
221 20 76 0
222 22 88 6
223 17 66 2
224 18 71 0
225 17 68 0
226 12 48 3
227 7 25 0
228 17 68 1
229 14 41 1
230 23 90 0
231 17 66 1
232 14 54 0
233 15 59 0
234 17 60 0
235 21 77 0
236 18 68 0
237 18 72 0
238 17 67 0
239 17 64 0
240 16 63 0
241 15 59 0
242 21 84 0
243 16 64 0
244 14 56 2
245 15 54 0
246 17 67 1
247 15 58 1
248 15 59 0
249 10 40 0
250 6 22 0
251 22 83 0
252 21 81 0
253 1 2 0
254 18 72 1
255 17 61 0
256 4 15 0
257 10 32 0
258 16 62 0
259 16 58 1
260 9 36 0
261 16 59 0
262 17 68 0
263 7 21 0
264 15 55 0
265 14 54 0
266 14 55 0
267 18 72 0
268 12 41 0
269 16 61 0
270 21 67 0
271 19 76 1
272 16 64 0
273 1 3 0
274 16 63 1
275 10 40 0
276 19 69 6
277 12 48 3
278 2 8 1
279 14 52 2
280 17 66 0
281 19 76 0
282 14 43 0
283 11 39 3
284 4 14 1
285 16 61 0
286 20 71 0
287 12 44 1
288 15 60 0
289 16 64 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) logins compendium_views_info
-12996.1 301.6 149.0
blogged_computations compendiums_reviewed feedback_messages_p1
489.8 -833.5 634.4
shared_compendiums
-471.5
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-125103 -15258 1364 13843 108970
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -12996.09 4316.83 -3.011 0.00284 **
logins 301.61 69.48 4.341 1.98e-05 ***
compendium_views_info 149.00 10.13 14.710 < 2e-16 ***
blogged_computations 489.78 83.93 5.835 1.47e-08 ***
compendiums_reviewed -833.45 886.54 -0.940 0.34796
feedback_messages_p1 634.36 236.60 2.681 0.00777 **
shared_compendiums -471.52 670.49 -0.703 0.48249
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 28190 on 282 degrees of freedom
Multiple R-squared: 0.8852, Adjusted R-squared: 0.8828
F-statistic: 362.5 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,] 0.9859407 2.811864e-02 1.405932e-02
[2,] 0.9830807 3.383855e-02 1.691928e-02
[3,] 0.9888517 2.229666e-02 1.114833e-02
[4,] 0.9808672 3.826559e-02 1.913280e-02
[5,] 0.9699848 6.003034e-02 3.001517e-02
[6,] 0.9513158 9.736849e-02 4.868424e-02
[7,] 0.9396583 1.206834e-01 6.034170e-02
[8,] 0.9534509 9.309814e-02 4.654907e-02
[9,] 0.9345584 1.308832e-01 6.544161e-02
[10,] 0.9356837 1.286326e-01 6.431631e-02
[11,] 0.9283813 1.432373e-01 7.161867e-02
[12,] 0.9040960 1.918079e-01 9.590396e-02
[13,] 0.8699360 2.601280e-01 1.300640e-01
[14,] 0.9956014 8.797196e-03 4.398598e-03
[15,] 0.9938045 1.239106e-02 6.195529e-03
[16,] 0.9925035 1.499301e-02 7.496505e-03
[17,] 0.9997700 4.599808e-04 2.299904e-04
[18,] 0.9997610 4.780938e-04 2.390469e-04
[19,] 0.9996057 7.886171e-04 3.943085e-04
[20,] 0.9997244 5.511924e-04 2.755962e-04
[21,] 0.9995923 8.153886e-04 4.076943e-04
[22,] 0.9993637 1.272566e-03 6.362829e-04
[23,] 0.9990433 1.913303e-03 9.566515e-04
[24,] 0.9985301 2.939718e-03 1.469859e-03
[25,] 0.9990227 1.954542e-03 9.772711e-04
[26,] 0.9988647 2.270620e-03 1.135310e-03
[27,] 0.9988822 2.235530e-03 1.117765e-03
[28,] 0.9985840 2.831949e-03 1.415974e-03
[29,] 0.9979076 4.184821e-03 2.092410e-03
[30,] 0.9997876 4.247518e-04 2.123759e-04
[31,] 0.9997138 5.724371e-04 2.862185e-04
[32,] 0.9995874 8.252153e-04 4.126076e-04
[33,] 0.9994777 1.044577e-03 5.222883e-04
[34,] 0.9996186 7.627255e-04 3.813628e-04
[35,] 0.9995726 8.547175e-04 4.273588e-04
[36,] 0.9994993 1.001422e-03 5.007110e-04
[37,] 0.9993498 1.300475e-03 6.502377e-04
[38,] 0.9993533 1.293483e-03 6.467413e-04
[39,] 0.9990837 1.832568e-03 9.162841e-04
[40,] 0.9987171 2.565747e-03 1.282873e-03
[41,] 0.9995381 9.237485e-04 4.618743e-04
[42,] 0.9994218 1.156443e-03 5.782213e-04
[43,] 0.9992224 1.555192e-03 7.775961e-04
[44,] 0.9990283 1.943440e-03 9.717199e-04
[45,] 0.9988558 2.288418e-03 1.144209e-03
[46,] 0.9995633 8.734869e-04 4.367435e-04
[47,] 0.9993828 1.234427e-03 6.172137e-04
[48,] 0.9992842 1.431558e-03 7.157792e-04
[49,] 0.9998392 3.215151e-04 1.607576e-04
[50,] 0.9997667 4.665969e-04 2.332984e-04
[51,] 0.9996826 6.348918e-04 3.174459e-04
[52,] 0.9995628 8.743921e-04 4.371961e-04
[53,] 0.9996014 7.972740e-04 3.986370e-04
[54,] 0.9996227 7.545468e-04 3.772734e-04
[55,] 0.9994676 1.064840e-03 5.324199e-04
[56,] 0.9992709 1.458174e-03 7.290872e-04
[57,] 0.9989864 2.027256e-03 1.013628e-03
[58,] 0.9988309 2.338242e-03 1.169121e-03
[59,] 0.9984611 3.077832e-03 1.538916e-03
[60,] 0.9979030 4.193976e-03 2.096988e-03
[61,] 0.9984602 3.079592e-03 1.539796e-03
[62,] 0.9981463 3.707306e-03 1.853653e-03
[63,] 0.9989514 2.097202e-03 1.048601e-03
[64,] 0.9990293 1.941371e-03 9.706855e-04
[65,] 0.9989484 2.103207e-03 1.051603e-03
[66,] 0.9990043 1.991470e-03 9.957351e-04
[67,] 0.9988851 2.229753e-03 1.114877e-03
[68,] 0.9992292 1.541570e-03 7.707852e-04
[69,] 0.9989968 2.006427e-03 1.003213e-03
[70,] 0.9989558 2.088399e-03 1.044200e-03
[71,] 0.9986186 2.762771e-03 1.381385e-03
[72,] 0.9981376 3.724794e-03 1.862397e-03
[73,] 0.9984365 3.126916e-03 1.563458e-03
[74,] 0.9988410 2.318005e-03 1.159002e-03
[75,] 0.9989503 2.099408e-03 1.049704e-03
[76,] 0.9987412 2.517524e-03 1.258762e-03
[77,] 0.9987414 2.517241e-03 1.258620e-03
[78,] 0.9984154 3.169118e-03 1.584559e-03
[79,] 0.9981215 3.756925e-03 1.878463e-03
[80,] 0.9993933 1.213341e-03 6.066705e-04
[81,] 0.9992039 1.592269e-03 7.961345e-04
[82,] 0.9993285 1.342923e-03 6.714615e-04
[83,] 0.9991677 1.664553e-03 8.322764e-04
[84,] 0.9992632 1.473564e-03 7.367822e-04
[85,] 0.9990385 1.923041e-03 9.615204e-04
[86,] 0.9988658 2.268438e-03 1.134219e-03
[87,] 0.9985045 2.990965e-03 1.495482e-03
[88,] 0.9982924 3.415235e-03 1.707618e-03
[89,] 0.9999965 7.046556e-06 3.523278e-06
[90,] 0.9999953 9.409609e-06 4.704804e-06
[91,] 0.9999933 1.337835e-05 6.689173e-06
[92,] 0.9999910 1.790982e-05 8.954908e-06
[93,] 0.9999891 2.175195e-05 1.087598e-05
[94,] 0.9999941 1.183241e-05 5.916207e-06
[95,] 0.9999921 1.577382e-05 7.886910e-06
[96,] 0.9999936 1.287224e-05 6.436122e-06
[97,] 0.9999926 1.480183e-05 7.400914e-06
[98,] 0.9999915 1.692736e-05 8.463681e-06
[99,] 0.9999892 2.166385e-05 1.083193e-05
[100,] 0.9999899 2.018958e-05 1.009479e-05
[101,] 0.9999855 2.909686e-05 1.454843e-05
[102,] 0.9999807 3.863078e-05 1.931539e-05
[103,] 0.9999796 4.078148e-05 2.039074e-05
[104,] 0.9999735 5.309481e-05 2.654740e-05
[105,] 0.9999623 7.545933e-05 3.772967e-05
[106,] 0.9999613 7.742346e-05 3.871173e-05
[107,] 0.9999672 6.565428e-05 3.282714e-05
[108,] 0.9999615 7.700975e-05 3.850488e-05
[109,] 0.9999793 4.148613e-05 2.074307e-05
[110,] 0.9999705 5.901781e-05 2.950891e-05
[111,] 0.9999682 6.351373e-05 3.175687e-05
[112,] 0.9999557 8.855662e-05 4.427831e-05
[113,] 0.9999770 4.593810e-05 2.296905e-05
[114,] 0.9999806 3.876389e-05 1.938195e-05
[115,] 0.9999947 1.066003e-05 5.330016e-06
[116,] 0.9999998 4.301767e-07 2.150883e-07
[117,] 0.9999998 4.974703e-07 2.487352e-07
[118,] 0.9999996 7.192041e-07 3.596020e-07
[119,] 0.9999995 1.033188e-06 5.165939e-07
[120,] 0.9999993 1.330555e-06 6.652774e-07
[121,] 0.9999990 2.031630e-06 1.015815e-06
[122,] 0.9999985 3.038919e-06 1.519459e-06
[123,] 0.9999992 1.610930e-06 8.054652e-07
[124,] 0.9999990 1.968205e-06 9.841026e-07
[125,] 0.9999999 2.500020e-07 1.250010e-07
[126,] 0.9999998 3.111399e-07 1.555700e-07
[127,] 1.0000000 8.847972e-08 4.423986e-08
[128,] 0.9999999 1.392137e-07 6.960685e-08
[129,] 1.0000000 6.544615e-08 3.272307e-08
[130,] 1.0000000 8.617213e-08 4.308607e-08
[131,] 0.9999999 1.304813e-07 6.524067e-08
[132,] 0.9999999 1.405848e-07 7.029241e-08
[133,] 0.9999999 2.054301e-07 1.027151e-07
[134,] 0.9999998 3.251559e-07 1.625779e-07
[135,] 0.9999998 4.545002e-07 2.272501e-07
[136,] 0.9999997 5.617821e-07 2.808911e-07
[137,] 0.9999997 5.945339e-07 2.972670e-07
[138,] 0.9999996 8.766301e-07 4.383151e-07
[139,] 0.9999994 1.298924e-06 6.494619e-07
[140,] 0.9999992 1.571543e-06 7.857717e-07
[141,] 0.9999988 2.413946e-06 1.206973e-06
[142,] 0.9999987 2.500835e-06 1.250418e-06
[143,] 0.9999986 2.822690e-06 1.411345e-06
[144,] 0.9999980 3.953445e-06 1.976723e-06
[145,] 0.9999971 5.884935e-06 2.942468e-06
[146,] 0.9999959 8.175838e-06 4.087919e-06
[147,] 0.9999988 2.304608e-06 1.152304e-06
[148,] 0.9999990 2.098404e-06 1.049202e-06
[149,] 0.9999985 2.901571e-06 1.450786e-06
[150,] 0.9999983 3.479473e-06 1.739737e-06
[151,] 0.9999979 4.165814e-06 2.082907e-06
[152,] 0.9999981 3.856494e-06 1.928247e-06
[153,] 0.9999973 5.396921e-06 2.698460e-06
[154,] 0.9999968 6.484952e-06 3.242476e-06
[155,] 0.9999959 8.263298e-06 4.131649e-06
[156,] 0.9999959 8.217898e-06 4.108949e-06
[157,] 0.9999981 3.749234e-06 1.874617e-06
[158,] 0.9999972 5.586692e-06 2.793346e-06
[159,] 0.9999958 8.411112e-06 4.205556e-06
[160,] 0.9999952 9.661433e-06 4.830716e-06
[161,] 1.0000000 5.972295e-08 2.986147e-08
[162,] 1.0000000 9.586191e-08 4.793095e-08
[163,] 0.9999999 1.281969e-07 6.409846e-08
[164,] 0.9999999 1.869878e-07 9.349391e-08
[165,] 1.0000000 4.626689e-08 2.313345e-08
[166,] 1.0000000 9.888250e-10 4.944125e-10
[167,] 1.0000000 1.640422e-09 8.202111e-10
[168,] 1.0000000 2.070073e-09 1.035036e-09
[169,] 1.0000000 3.461695e-09 1.730847e-09
[170,] 1.0000000 5.955994e-09 2.977997e-09
[171,] 1.0000000 2.664710e-09 1.332355e-09
[172,] 1.0000000 3.334239e-09 1.667120e-09
[173,] 1.0000000 2.067086e-10 1.033543e-10
[174,] 1.0000000 3.718224e-10 1.859112e-10
[175,] 1.0000000 2.612856e-10 1.306428e-10
[176,] 1.0000000 1.639865e-10 8.199325e-11
[177,] 1.0000000 2.965375e-10 1.482688e-10
[178,] 1.0000000 5.477101e-10 2.738550e-10
[179,] 1.0000000 9.423593e-10 4.711797e-10
[180,] 1.0000000 1.247663e-09 6.238314e-10
[181,] 1.0000000 2.096613e-09 1.048307e-09
[182,] 1.0000000 5.191070e-10 2.595535e-10
[183,] 1.0000000 9.548753e-10 4.774376e-10
[184,] 1.0000000 1.393045e-09 6.965226e-10
[185,] 1.0000000 2.474033e-09 1.237017e-09
[186,] 1.0000000 3.584528e-09 1.792264e-09
[187,] 1.0000000 5.710820e-09 2.855410e-09
[188,] 1.0000000 7.619256e-09 3.809628e-09
[189,] 1.0000000 1.170551e-08 5.852757e-09
[190,] 1.0000000 1.034755e-08 5.173773e-09
[191,] 1.0000000 1.877855e-08 9.389274e-09
[192,] 1.0000000 3.168577e-08 1.584289e-08
[193,] 1.0000000 4.843323e-08 2.421661e-08
[194,] 1.0000000 7.144474e-08 3.572237e-08
[195,] 0.9999999 1.193489e-07 5.967444e-08
[196,] 1.0000000 9.856537e-08 4.928268e-08
[197,] 0.9999999 1.552730e-07 7.763650e-08
[198,] 0.9999999 2.684764e-07 1.342382e-07
[199,] 1.0000000 2.728213e-08 1.364106e-08
[200,] 1.0000000 1.467644e-08 7.338218e-09
[201,] 1.0000000 2.088157e-08 1.044078e-08
[202,] 1.0000000 2.822956e-08 1.411478e-08
[203,] 1.0000000 1.033460e-08 5.167300e-09
[204,] 1.0000000 1.965602e-08 9.828009e-09
[205,] 1.0000000 3.617884e-08 1.808942e-08
[206,] 1.0000000 3.281610e-08 1.640805e-08
[207,] 1.0000000 4.853964e-08 2.426982e-08
[208,] 1.0000000 2.599680e-08 1.299840e-08
[209,] 1.0000000 4.889655e-08 2.444827e-08
[210,] 1.0000000 8.810183e-08 4.405092e-08
[211,] 1.0000000 6.547264e-08 3.273632e-08
[212,] 0.9999999 1.156849e-07 5.784243e-08
[213,] 0.9999999 1.973743e-07 9.868716e-08
[214,] 1.0000000 5.040812e-08 2.520406e-08
[215,] 1.0000000 8.590181e-08 4.295091e-08
[216,] 0.9999999 1.558217e-07 7.791084e-08
[217,] 0.9999999 2.957622e-07 1.478811e-07
[218,] 0.9999998 4.270360e-07 2.135180e-07
[219,] 0.9999998 4.116267e-07 2.058133e-07
[220,] 0.9999997 6.165679e-07 3.082839e-07
[221,] 0.9999998 3.730129e-07 1.865064e-07
[222,] 0.9999998 4.598120e-07 2.299060e-07
[223,] 0.9999996 8.861656e-07 4.430828e-07
[224,] 0.9999998 4.158447e-07 2.079223e-07
[225,] 0.9999996 7.765213e-07 3.882607e-07
[226,] 0.9999998 4.418672e-07 2.209336e-07
[227,] 0.9999996 7.590194e-07 3.795097e-07
[228,] 1.0000000 1.316983e-08 6.584917e-09
[229,] 1.0000000 1.787264e-08 8.936322e-09
[230,] 1.0000000 2.840393e-08 1.420197e-08
[231,] 1.0000000 1.343773e-08 6.718865e-09
[232,] 1.0000000 2.584480e-08 1.292240e-08
[233,] 1.0000000 5.802538e-08 2.901269e-08
[234,] 1.0000000 4.255237e-08 2.127618e-08
[235,] 1.0000000 7.602246e-08 3.801123e-08
[236,] 0.9999999 1.745922e-07 8.729612e-08
[237,] 0.9999998 3.588508e-07 1.794254e-07
[238,] 0.9999998 4.262664e-07 2.131332e-07
[239,] 0.9999997 5.254630e-07 2.627315e-07
[240,] 0.9999994 1.161756e-06 5.808778e-07
[241,] 0.9999994 1.293459e-06 6.467293e-07
[242,] 0.9999994 1.204877e-06 6.024386e-07
[243,] 0.9999988 2.389332e-06 1.194666e-06
[244,] 0.9999973 5.353990e-06 2.676995e-06
[245,] 0.9999941 1.185694e-05 5.928472e-06
[246,] 0.9999910 1.805314e-05 9.026572e-06
[247,] 0.9999832 3.350894e-05 1.675447e-05
[248,] 0.9999778 4.442785e-05 2.221392e-05
[249,] 0.9999560 8.797418e-05 4.398709e-05
[250,] 0.9999283 1.433553e-04 7.167766e-05
[251,] 0.9998497 3.005422e-04 1.502711e-04
[252,] 0.9998870 2.259534e-04 1.129767e-04
[253,] 0.9997633 4.734468e-04 2.367234e-04
[254,] 0.9995112 9.775980e-04 4.887990e-04
[255,] 0.9992485 1.502965e-03 7.514826e-04
[256,] 0.9988937 2.212639e-03 1.106320e-03
[257,] 0.9977885 4.422921e-03 2.211460e-03
[258,] 0.9984103 3.179371e-03 1.589685e-03
[259,] 0.9975855 4.829040e-03 2.414520e-03
[260,] 0.9999759 4.824127e-05 2.412064e-05
[261,] 0.9999835 3.293938e-05 1.646969e-05
[262,] 0.9999876 2.484390e-05 1.242195e-05
[263,] 0.9999529 9.411549e-05 4.705774e-05
[264,] 0.9999742 5.160176e-05 2.580088e-05
[265,] 0.9998849 2.301363e-04 1.150681e-04
[266,] 0.9995892 8.216150e-04 4.108075e-04
[267,] 0.9984794 3.041278e-03 1.520639e-03
[268,] 0.9970880 5.824027e-03 2.912014e-03
[269,] 0.9879922 2.401569e-02 1.200784e-02
[270,] 0.9550605 8.987896e-02 4.493948e-02
> postscript(file="/var/wessaorg/rcomp/tmp/118761324302529.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/2nj7d1324302529.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3v59k1324302529.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4rk1c1324302529.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/59hdq1324302529.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
62784.0685 505.9170 5253.5702 -79142.1192 35559.1462 -4090.9450
7 8 9 10 11 12
38722.3481 -3493.4395 11822.0200 -9425.3177 20397.3291 31938.4099
13 14 15 16 17 18
-16955.7726 -4732.9624 17549.2878 18379.1403 -75645.3713 40134.7284
19 20 21 22 23 24
959.3177 1922.9069 1845.5881 10338.3108 108969.5704 39923.8370
25 26 27 28 29 30
-31020.8426 -97697.5275 -46868.3704 -14474.1237 34956.9468 -6578.6828
31 32 33 34 35 36
15504.1597 8768.6364 2497.8375 33618.6349 -14240.8503 31867.4618
37 38 39 40 41 42
31445.6920 8021.6636 71222.8089 4614.8546 11961.8714 38412.9928
43 44 45 46 47 48
-28969.6021 -1456.7733 -21787.8394 -11419.5741 -41037.2267 4371.3435
49 50 51 52 53 54
3150.0774 -46877.5149 8556.6287 -9241.1059 -13319.7086 -25968.7499
55 56 57 58 59 60
-50008.5486 5810.8855 -10732.7935 56547.8948 -524.4215 -7452.1329
61 62 63 64 65 66
9451.8035 35272.0555 34960.5510 9674.8574 -3653.4818 7253.2606
67 68 69 70 71 72
23342.2936 11545.4167 1446.4992 -44243.1053 18110.7717 52029.7342
73 74 75 76 77 78
37682.6261 -18520.9318 -31366.7262 -20262.6090 -42695.9530 -15429.5104
79 80 81 82 83 84
-25053.8450 9291.1313 -806.3206 -35316.6750 39816.6320 34667.9527
85 86 87 88 89 90
18964.5375 -28554.0921 -10956.2433 -16343.6198 63964.9929 -8594.5351
91 92 93 94 95 96
39472.2674 -13796.6793 -32583.9091 9724.0177 20948.7912 9207.1669
97 98 99 100 101 102
23488.7918 -125102.8463 16873.8698 -11159.3071 15535.0670 -19547.4645
103 104 105 106 107 108
46543.2322 15713.6497 34753.9907 21958.7130 -26855.7493 -14082.2168
109 110 111 112 113 114
28482.3007 2020.7652 13465.6046 -23533.7375 -13509.9752 -4163.1887
115 116 117 118 119 120
-27183.5957 -33213.5065 -21543.1289 48719.0482 4434.0070 -21929.0930
121 122 123 124 125 126
-5895.9049 -44027.5410 -33047.5834 -59748.8005 80235.5958 21412.6603
127 128 129 130 131 132
10709.2148 -11616.4527 16785.8930 4928.4760 -3093.0847 -43378.5018
133 134 135 136 137 138
18194.8935 -62434.3391 -19163.8951 54453.0939 5511.5491 41096.6802
139 140 141 142 143 144
-17284.5877 -9127.4260 -23712.5166 -10835.5184 3791.7342 -12753.5550
145 146 147 148 149 150
12219.9855 -23997.1287 -5075.9745 -9246.0262 -18464.5852 1364.1350
151 152 153 154 155 156
27467.6990 20485.4625 -11249.2908 6047.9758 9886.1818 47305.4278
157 158 159 160 161 162
24116.6176 14787.8558 -21976.9239 -18645.4690 25962.4523 -12301.7621
163 164 165 166 167 168
-11965.0230 -15257.8465 -29547.8839 34725.0525 -9813.0776 6724.5141
169 170 171 172 173 174
20074.6334 91496.8166 -10173.9447 2948.9403 9294.0253 14441.6266
175 176 177 178 179 180
-94320.3105 5312.9227 -26779.2469 6031.4217 -1426.7539 35667.6452
181 182 183 184 185 186
-21714.2430 -57990.9555 10044.0696 22629.0749 15684.6509 4232.7717
187 188 189 190 191 192
3808.0208 17050.2110 10878.3234 492.5822 30354.3006 -5626.7229
193 194 195 196 197 198
-19189.7047 -11416.4864 2133.8916 4136.2555 -19332.8463 11106.7319
199 200 201 202 203 204
-30667.7804 -3269.5410 6778.4503 2101.1020 12381.5127 6113.9303
205 206 207 208 209 210
-34636.1902 -12464.8983 -6131.1920 46463.9374 24979.8211 615.0497
211 212 213 214 215 216
12198.4571 28018.9275 -3209.9373 1854.4523 -31352.7600 -12515.1354
217 218 219 220 221 222
-33798.9170 4356.3616 670.6397 27822.8947 -15413.9379 -3699.7139
223 224 225 226 227 228
-53643.1876 5784.3746 -5510.9506 -2637.7895 17702.5601 -27294.2014
229 230 231 232 233 234
-22380.1248 -36845.4902 -14724.1446 -4224.2810 -30285.9412 -8050.9648
235 236 237 238 239 240
-31980.9686 -15700.9431 51689.6419 -16085.1989 -16424.3762 -23714.2667
241 242 243 244 245 246
10683.0330 3246.0090 -19982.0025 -8376.8993 -391.7449 -10622.1736
247 248 249 250 251 252
-22975.0442 21345.3909 7002.7955 -12220.8415 13843.3273 4730.8307
253 254 255 256 257 258
12242.1475 -1862.1029 -18439.2956 1481.0874 -9992.6513 6365.0316
259 260 261 262 263 264
11323.9548 5434.2595 -18634.2620 3398.5841 14372.8917 -9035.8351
265 266 267 268 269 270
-10057.3874 5938.8491 -23029.5374 -6434.2341 46611.7022 -16838.9322
271 272 273 274 275 276
-7788.3496 3566.1515 2670.1187 2218.2622 10559.4782 -20018.7235
277 278 279 280 281 282
15880.3569 10131.6948 -1959.1179 16155.1909 -5730.9616 20732.0277
283 284 285 286 287 288
-155.6071 12157.8137 3319.6367 -2782.5554 4227.4719 -265.4999
289
-3301.6950
> postscript(file="/var/wessaorg/rcomp/tmp/62xlh1324302529.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 62784.0685 NA
1 505.9170 62784.0685
2 5253.5702 505.9170
3 -79142.1192 5253.5702
4 35559.1462 -79142.1192
5 -4090.9450 35559.1462
6 38722.3481 -4090.9450
7 -3493.4395 38722.3481
8 11822.0200 -3493.4395
9 -9425.3177 11822.0200
10 20397.3291 -9425.3177
11 31938.4099 20397.3291
12 -16955.7726 31938.4099
13 -4732.9624 -16955.7726
14 17549.2878 -4732.9624
15 18379.1403 17549.2878
16 -75645.3713 18379.1403
17 40134.7284 -75645.3713
18 959.3177 40134.7284
19 1922.9069 959.3177
20 1845.5881 1922.9069
21 10338.3108 1845.5881
22 108969.5704 10338.3108
23 39923.8370 108969.5704
24 -31020.8426 39923.8370
25 -97697.5275 -31020.8426
26 -46868.3704 -97697.5275
27 -14474.1237 -46868.3704
28 34956.9468 -14474.1237
29 -6578.6828 34956.9468
30 15504.1597 -6578.6828
31 8768.6364 15504.1597
32 2497.8375 8768.6364
33 33618.6349 2497.8375
34 -14240.8503 33618.6349
35 31867.4618 -14240.8503
36 31445.6920 31867.4618
37 8021.6636 31445.6920
38 71222.8089 8021.6636
39 4614.8546 71222.8089
40 11961.8714 4614.8546
41 38412.9928 11961.8714
42 -28969.6021 38412.9928
43 -1456.7733 -28969.6021
44 -21787.8394 -1456.7733
45 -11419.5741 -21787.8394
46 -41037.2267 -11419.5741
47 4371.3435 -41037.2267
48 3150.0774 4371.3435
49 -46877.5149 3150.0774
50 8556.6287 -46877.5149
51 -9241.1059 8556.6287
52 -13319.7086 -9241.1059
53 -25968.7499 -13319.7086
54 -50008.5486 -25968.7499
55 5810.8855 -50008.5486
56 -10732.7935 5810.8855
57 56547.8948 -10732.7935
58 -524.4215 56547.8948
59 -7452.1329 -524.4215
60 9451.8035 -7452.1329
61 35272.0555 9451.8035
62 34960.5510 35272.0555
63 9674.8574 34960.5510
64 -3653.4818 9674.8574
65 7253.2606 -3653.4818
66 23342.2936 7253.2606
67 11545.4167 23342.2936
68 1446.4992 11545.4167
69 -44243.1053 1446.4992
70 18110.7717 -44243.1053
71 52029.7342 18110.7717
72 37682.6261 52029.7342
73 -18520.9318 37682.6261
74 -31366.7262 -18520.9318
75 -20262.6090 -31366.7262
76 -42695.9530 -20262.6090
77 -15429.5104 -42695.9530
78 -25053.8450 -15429.5104
79 9291.1313 -25053.8450
80 -806.3206 9291.1313
81 -35316.6750 -806.3206
82 39816.6320 -35316.6750
83 34667.9527 39816.6320
84 18964.5375 34667.9527
85 -28554.0921 18964.5375
86 -10956.2433 -28554.0921
87 -16343.6198 -10956.2433
88 63964.9929 -16343.6198
89 -8594.5351 63964.9929
90 39472.2674 -8594.5351
91 -13796.6793 39472.2674
92 -32583.9091 -13796.6793
93 9724.0177 -32583.9091
94 20948.7912 9724.0177
95 9207.1669 20948.7912
96 23488.7918 9207.1669
97 -125102.8463 23488.7918
98 16873.8698 -125102.8463
99 -11159.3071 16873.8698
100 15535.0670 -11159.3071
101 -19547.4645 15535.0670
102 46543.2322 -19547.4645
103 15713.6497 46543.2322
104 34753.9907 15713.6497
105 21958.7130 34753.9907
106 -26855.7493 21958.7130
107 -14082.2168 -26855.7493
108 28482.3007 -14082.2168
109 2020.7652 28482.3007
110 13465.6046 2020.7652
111 -23533.7375 13465.6046
112 -13509.9752 -23533.7375
113 -4163.1887 -13509.9752
114 -27183.5957 -4163.1887
115 -33213.5065 -27183.5957
116 -21543.1289 -33213.5065
117 48719.0482 -21543.1289
118 4434.0070 48719.0482
119 -21929.0930 4434.0070
120 -5895.9049 -21929.0930
121 -44027.5410 -5895.9049
122 -33047.5834 -44027.5410
123 -59748.8005 -33047.5834
124 80235.5958 -59748.8005
125 21412.6603 80235.5958
126 10709.2148 21412.6603
127 -11616.4527 10709.2148
128 16785.8930 -11616.4527
129 4928.4760 16785.8930
130 -3093.0847 4928.4760
131 -43378.5018 -3093.0847
132 18194.8935 -43378.5018
133 -62434.3391 18194.8935
134 -19163.8951 -62434.3391
135 54453.0939 -19163.8951
136 5511.5491 54453.0939
137 41096.6802 5511.5491
138 -17284.5877 41096.6802
139 -9127.4260 -17284.5877
140 -23712.5166 -9127.4260
141 -10835.5184 -23712.5166
142 3791.7342 -10835.5184
143 -12753.5550 3791.7342
144 12219.9855 -12753.5550
145 -23997.1287 12219.9855
146 -5075.9745 -23997.1287
147 -9246.0262 -5075.9745
148 -18464.5852 -9246.0262
149 1364.1350 -18464.5852
150 27467.6990 1364.1350
151 20485.4625 27467.6990
152 -11249.2908 20485.4625
153 6047.9758 -11249.2908
154 9886.1818 6047.9758
155 47305.4278 9886.1818
156 24116.6176 47305.4278
157 14787.8558 24116.6176
158 -21976.9239 14787.8558
159 -18645.4690 -21976.9239
160 25962.4523 -18645.4690
161 -12301.7621 25962.4523
162 -11965.0230 -12301.7621
163 -15257.8465 -11965.0230
164 -29547.8839 -15257.8465
165 34725.0525 -29547.8839
166 -9813.0776 34725.0525
167 6724.5141 -9813.0776
168 20074.6334 6724.5141
169 91496.8166 20074.6334
170 -10173.9447 91496.8166
171 2948.9403 -10173.9447
172 9294.0253 2948.9403
173 14441.6266 9294.0253
174 -94320.3105 14441.6266
175 5312.9227 -94320.3105
176 -26779.2469 5312.9227
177 6031.4217 -26779.2469
178 -1426.7539 6031.4217
179 35667.6452 -1426.7539
180 -21714.2430 35667.6452
181 -57990.9555 -21714.2430
182 10044.0696 -57990.9555
183 22629.0749 10044.0696
184 15684.6509 22629.0749
185 4232.7717 15684.6509
186 3808.0208 4232.7717
187 17050.2110 3808.0208
188 10878.3234 17050.2110
189 492.5822 10878.3234
190 30354.3006 492.5822
191 -5626.7229 30354.3006
192 -19189.7047 -5626.7229
193 -11416.4864 -19189.7047
194 2133.8916 -11416.4864
195 4136.2555 2133.8916
196 -19332.8463 4136.2555
197 11106.7319 -19332.8463
198 -30667.7804 11106.7319
199 -3269.5410 -30667.7804
200 6778.4503 -3269.5410
201 2101.1020 6778.4503
202 12381.5127 2101.1020
203 6113.9303 12381.5127
204 -34636.1902 6113.9303
205 -12464.8983 -34636.1902
206 -6131.1920 -12464.8983
207 46463.9374 -6131.1920
208 24979.8211 46463.9374
209 615.0497 24979.8211
210 12198.4571 615.0497
211 28018.9275 12198.4571
212 -3209.9373 28018.9275
213 1854.4523 -3209.9373
214 -31352.7600 1854.4523
215 -12515.1354 -31352.7600
216 -33798.9170 -12515.1354
217 4356.3616 -33798.9170
218 670.6397 4356.3616
219 27822.8947 670.6397
220 -15413.9379 27822.8947
221 -3699.7139 -15413.9379
222 -53643.1876 -3699.7139
223 5784.3746 -53643.1876
224 -5510.9506 5784.3746
225 -2637.7895 -5510.9506
226 17702.5601 -2637.7895
227 -27294.2014 17702.5601
228 -22380.1248 -27294.2014
229 -36845.4902 -22380.1248
230 -14724.1446 -36845.4902
231 -4224.2810 -14724.1446
232 -30285.9412 -4224.2810
233 -8050.9648 -30285.9412
234 -31980.9686 -8050.9648
235 -15700.9431 -31980.9686
236 51689.6419 -15700.9431
237 -16085.1989 51689.6419
238 -16424.3762 -16085.1989
239 -23714.2667 -16424.3762
240 10683.0330 -23714.2667
241 3246.0090 10683.0330
242 -19982.0025 3246.0090
243 -8376.8993 -19982.0025
244 -391.7449 -8376.8993
245 -10622.1736 -391.7449
246 -22975.0442 -10622.1736
247 21345.3909 -22975.0442
248 7002.7955 21345.3909
249 -12220.8415 7002.7955
250 13843.3273 -12220.8415
251 4730.8307 13843.3273
252 12242.1475 4730.8307
253 -1862.1029 12242.1475
254 -18439.2956 -1862.1029
255 1481.0874 -18439.2956
256 -9992.6513 1481.0874
257 6365.0316 -9992.6513
258 11323.9548 6365.0316
259 5434.2595 11323.9548
260 -18634.2620 5434.2595
261 3398.5841 -18634.2620
262 14372.8917 3398.5841
263 -9035.8351 14372.8917
264 -10057.3874 -9035.8351
265 5938.8491 -10057.3874
266 -23029.5374 5938.8491
267 -6434.2341 -23029.5374
268 46611.7022 -6434.2341
269 -16838.9322 46611.7022
270 -7788.3496 -16838.9322
271 3566.1515 -7788.3496
272 2670.1187 3566.1515
273 2218.2622 2670.1187
274 10559.4782 2218.2622
275 -20018.7235 10559.4782
276 15880.3569 -20018.7235
277 10131.6948 15880.3569
278 -1959.1179 10131.6948
279 16155.1909 -1959.1179
280 -5730.9616 16155.1909
281 20732.0277 -5730.9616
282 -155.6071 20732.0277
283 12157.8137 -155.6071
284 3319.6367 12157.8137
285 -2782.5554 3319.6367
286 4227.4719 -2782.5554
287 -265.4999 4227.4719
288 -3301.6950 -265.4999
289 NA -3301.6950
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 505.9170 62784.0685
[2,] 5253.5702 505.9170
[3,] -79142.1192 5253.5702
[4,] 35559.1462 -79142.1192
[5,] -4090.9450 35559.1462
[6,] 38722.3481 -4090.9450
[7,] -3493.4395 38722.3481
[8,] 11822.0200 -3493.4395
[9,] -9425.3177 11822.0200
[10,] 20397.3291 -9425.3177
[11,] 31938.4099 20397.3291
[12,] -16955.7726 31938.4099
[13,] -4732.9624 -16955.7726
[14,] 17549.2878 -4732.9624
[15,] 18379.1403 17549.2878
[16,] -75645.3713 18379.1403
[17,] 40134.7284 -75645.3713
[18,] 959.3177 40134.7284
[19,] 1922.9069 959.3177
[20,] 1845.5881 1922.9069
[21,] 10338.3108 1845.5881
[22,] 108969.5704 10338.3108
[23,] 39923.8370 108969.5704
[24,] -31020.8426 39923.8370
[25,] -97697.5275 -31020.8426
[26,] -46868.3704 -97697.5275
[27,] -14474.1237 -46868.3704
[28,] 34956.9468 -14474.1237
[29,] -6578.6828 34956.9468
[30,] 15504.1597 -6578.6828
[31,] 8768.6364 15504.1597
[32,] 2497.8375 8768.6364
[33,] 33618.6349 2497.8375
[34,] -14240.8503 33618.6349
[35,] 31867.4618 -14240.8503
[36,] 31445.6920 31867.4618
[37,] 8021.6636 31445.6920
[38,] 71222.8089 8021.6636
[39,] 4614.8546 71222.8089
[40,] 11961.8714 4614.8546
[41,] 38412.9928 11961.8714
[42,] -28969.6021 38412.9928
[43,] -1456.7733 -28969.6021
[44,] -21787.8394 -1456.7733
[45,] -11419.5741 -21787.8394
[46,] -41037.2267 -11419.5741
[47,] 4371.3435 -41037.2267
[48,] 3150.0774 4371.3435
[49,] -46877.5149 3150.0774
[50,] 8556.6287 -46877.5149
[51,] -9241.1059 8556.6287
[52,] -13319.7086 -9241.1059
[53,] -25968.7499 -13319.7086
[54,] -50008.5486 -25968.7499
[55,] 5810.8855 -50008.5486
[56,] -10732.7935 5810.8855
[57,] 56547.8948 -10732.7935
[58,] -524.4215 56547.8948
[59,] -7452.1329 -524.4215
[60,] 9451.8035 -7452.1329
[61,] 35272.0555 9451.8035
[62,] 34960.5510 35272.0555
[63,] 9674.8574 34960.5510
[64,] -3653.4818 9674.8574
[65,] 7253.2606 -3653.4818
[66,] 23342.2936 7253.2606
[67,] 11545.4167 23342.2936
[68,] 1446.4992 11545.4167
[69,] -44243.1053 1446.4992
[70,] 18110.7717 -44243.1053
[71,] 52029.7342 18110.7717
[72,] 37682.6261 52029.7342
[73,] -18520.9318 37682.6261
[74,] -31366.7262 -18520.9318
[75,] -20262.6090 -31366.7262
[76,] -42695.9530 -20262.6090
[77,] -15429.5104 -42695.9530
[78,] -25053.8450 -15429.5104
[79,] 9291.1313 -25053.8450
[80,] -806.3206 9291.1313
[81,] -35316.6750 -806.3206
[82,] 39816.6320 -35316.6750
[83,] 34667.9527 39816.6320
[84,] 18964.5375 34667.9527
[85,] -28554.0921 18964.5375
[86,] -10956.2433 -28554.0921
[87,] -16343.6198 -10956.2433
[88,] 63964.9929 -16343.6198
[89,] -8594.5351 63964.9929
[90,] 39472.2674 -8594.5351
[91,] -13796.6793 39472.2674
[92,] -32583.9091 -13796.6793
[93,] 9724.0177 -32583.9091
[94,] 20948.7912 9724.0177
[95,] 9207.1669 20948.7912
[96,] 23488.7918 9207.1669
[97,] -125102.8463 23488.7918
[98,] 16873.8698 -125102.8463
[99,] -11159.3071 16873.8698
[100,] 15535.0670 -11159.3071
[101,] -19547.4645 15535.0670
[102,] 46543.2322 -19547.4645
[103,] 15713.6497 46543.2322
[104,] 34753.9907 15713.6497
[105,] 21958.7130 34753.9907
[106,] -26855.7493 21958.7130
[107,] -14082.2168 -26855.7493
[108,] 28482.3007 -14082.2168
[109,] 2020.7652 28482.3007
[110,] 13465.6046 2020.7652
[111,] -23533.7375 13465.6046
[112,] -13509.9752 -23533.7375
[113,] -4163.1887 -13509.9752
[114,] -27183.5957 -4163.1887
[115,] -33213.5065 -27183.5957
[116,] -21543.1289 -33213.5065
[117,] 48719.0482 -21543.1289
[118,] 4434.0070 48719.0482
[119,] -21929.0930 4434.0070
[120,] -5895.9049 -21929.0930
[121,] -44027.5410 -5895.9049
[122,] -33047.5834 -44027.5410
[123,] -59748.8005 -33047.5834
[124,] 80235.5958 -59748.8005
[125,] 21412.6603 80235.5958
[126,] 10709.2148 21412.6603
[127,] -11616.4527 10709.2148
[128,] 16785.8930 -11616.4527
[129,] 4928.4760 16785.8930
[130,] -3093.0847 4928.4760
[131,] -43378.5018 -3093.0847
[132,] 18194.8935 -43378.5018
[133,] -62434.3391 18194.8935
[134,] -19163.8951 -62434.3391
[135,] 54453.0939 -19163.8951
[136,] 5511.5491 54453.0939
[137,] 41096.6802 5511.5491
[138,] -17284.5877 41096.6802
[139,] -9127.4260 -17284.5877
[140,] -23712.5166 -9127.4260
[141,] -10835.5184 -23712.5166
[142,] 3791.7342 -10835.5184
[143,] -12753.5550 3791.7342
[144,] 12219.9855 -12753.5550
[145,] -23997.1287 12219.9855
[146,] -5075.9745 -23997.1287
[147,] -9246.0262 -5075.9745
[148,] -18464.5852 -9246.0262
[149,] 1364.1350 -18464.5852
[150,] 27467.6990 1364.1350
[151,] 20485.4625 27467.6990
[152,] -11249.2908 20485.4625
[153,] 6047.9758 -11249.2908
[154,] 9886.1818 6047.9758
[155,] 47305.4278 9886.1818
[156,] 24116.6176 47305.4278
[157,] 14787.8558 24116.6176
[158,] -21976.9239 14787.8558
[159,] -18645.4690 -21976.9239
[160,] 25962.4523 -18645.4690
[161,] -12301.7621 25962.4523
[162,] -11965.0230 -12301.7621
[163,] -15257.8465 -11965.0230
[164,] -29547.8839 -15257.8465
[165,] 34725.0525 -29547.8839
[166,] -9813.0776 34725.0525
[167,] 6724.5141 -9813.0776
[168,] 20074.6334 6724.5141
[169,] 91496.8166 20074.6334
[170,] -10173.9447 91496.8166
[171,] 2948.9403 -10173.9447
[172,] 9294.0253 2948.9403
[173,] 14441.6266 9294.0253
[174,] -94320.3105 14441.6266
[175,] 5312.9227 -94320.3105
[176,] -26779.2469 5312.9227
[177,] 6031.4217 -26779.2469
[178,] -1426.7539 6031.4217
[179,] 35667.6452 -1426.7539
[180,] -21714.2430 35667.6452
[181,] -57990.9555 -21714.2430
[182,] 10044.0696 -57990.9555
[183,] 22629.0749 10044.0696
[184,] 15684.6509 22629.0749
[185,] 4232.7717 15684.6509
[186,] 3808.0208 4232.7717
[187,] 17050.2110 3808.0208
[188,] 10878.3234 17050.2110
[189,] 492.5822 10878.3234
[190,] 30354.3006 492.5822
[191,] -5626.7229 30354.3006
[192,] -19189.7047 -5626.7229
[193,] -11416.4864 -19189.7047
[194,] 2133.8916 -11416.4864
[195,] 4136.2555 2133.8916
[196,] -19332.8463 4136.2555
[197,] 11106.7319 -19332.8463
[198,] -30667.7804 11106.7319
[199,] -3269.5410 -30667.7804
[200,] 6778.4503 -3269.5410
[201,] 2101.1020 6778.4503
[202,] 12381.5127 2101.1020
[203,] 6113.9303 12381.5127
[204,] -34636.1902 6113.9303
[205,] -12464.8983 -34636.1902
[206,] -6131.1920 -12464.8983
[207,] 46463.9374 -6131.1920
[208,] 24979.8211 46463.9374
[209,] 615.0497 24979.8211
[210,] 12198.4571 615.0497
[211,] 28018.9275 12198.4571
[212,] -3209.9373 28018.9275
[213,] 1854.4523 -3209.9373
[214,] -31352.7600 1854.4523
[215,] -12515.1354 -31352.7600
[216,] -33798.9170 -12515.1354
[217,] 4356.3616 -33798.9170
[218,] 670.6397 4356.3616
[219,] 27822.8947 670.6397
[220,] -15413.9379 27822.8947
[221,] -3699.7139 -15413.9379
[222,] -53643.1876 -3699.7139
[223,] 5784.3746 -53643.1876
[224,] -5510.9506 5784.3746
[225,] -2637.7895 -5510.9506
[226,] 17702.5601 -2637.7895
[227,] -27294.2014 17702.5601
[228,] -22380.1248 -27294.2014
[229,] -36845.4902 -22380.1248
[230,] -14724.1446 -36845.4902
[231,] -4224.2810 -14724.1446
[232,] -30285.9412 -4224.2810
[233,] -8050.9648 -30285.9412
[234,] -31980.9686 -8050.9648
[235,] -15700.9431 -31980.9686
[236,] 51689.6419 -15700.9431
[237,] -16085.1989 51689.6419
[238,] -16424.3762 -16085.1989
[239,] -23714.2667 -16424.3762
[240,] 10683.0330 -23714.2667
[241,] 3246.0090 10683.0330
[242,] -19982.0025 3246.0090
[243,] -8376.8993 -19982.0025
[244,] -391.7449 -8376.8993
[245,] -10622.1736 -391.7449
[246,] -22975.0442 -10622.1736
[247,] 21345.3909 -22975.0442
[248,] 7002.7955 21345.3909
[249,] -12220.8415 7002.7955
[250,] 13843.3273 -12220.8415
[251,] 4730.8307 13843.3273
[252,] 12242.1475 4730.8307
[253,] -1862.1029 12242.1475
[254,] -18439.2956 -1862.1029
[255,] 1481.0874 -18439.2956
[256,] -9992.6513 1481.0874
[257,] 6365.0316 -9992.6513
[258,] 11323.9548 6365.0316
[259,] 5434.2595 11323.9548
[260,] -18634.2620 5434.2595
[261,] 3398.5841 -18634.2620
[262,] 14372.8917 3398.5841
[263,] -9035.8351 14372.8917
[264,] -10057.3874 -9035.8351
[265,] 5938.8491 -10057.3874
[266,] -23029.5374 5938.8491
[267,] -6434.2341 -23029.5374
[268,] 46611.7022 -6434.2341
[269,] -16838.9322 46611.7022
[270,] -7788.3496 -16838.9322
[271,] 3566.1515 -7788.3496
[272,] 2670.1187 3566.1515
[273,] 2218.2622 2670.1187
[274,] 10559.4782 2218.2622
[275,] -20018.7235 10559.4782
[276,] 15880.3569 -20018.7235
[277,] 10131.6948 15880.3569
[278,] -1959.1179 10131.6948
[279,] 16155.1909 -1959.1179
[280,] -5730.9616 16155.1909
[281,] 20732.0277 -5730.9616
[282,] -155.6071 20732.0277
[283,] 12157.8137 -155.6071
[284,] 3319.6367 12157.8137
[285,] -2782.5554 3319.6367
[286,] 4227.4719 -2782.5554
[287,] -265.4999 4227.4719
[288,] -3301.6950 -265.4999
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 505.9170 62784.0685
2 5253.5702 505.9170
3 -79142.1192 5253.5702
4 35559.1462 -79142.1192
5 -4090.9450 35559.1462
6 38722.3481 -4090.9450
7 -3493.4395 38722.3481
8 11822.0200 -3493.4395
9 -9425.3177 11822.0200
10 20397.3291 -9425.3177
11 31938.4099 20397.3291
12 -16955.7726 31938.4099
13 -4732.9624 -16955.7726
14 17549.2878 -4732.9624
15 18379.1403 17549.2878
16 -75645.3713 18379.1403
17 40134.7284 -75645.3713
18 959.3177 40134.7284
19 1922.9069 959.3177
20 1845.5881 1922.9069
21 10338.3108 1845.5881
22 108969.5704 10338.3108
23 39923.8370 108969.5704
24 -31020.8426 39923.8370
25 -97697.5275 -31020.8426
26 -46868.3704 -97697.5275
27 -14474.1237 -46868.3704
28 34956.9468 -14474.1237
29 -6578.6828 34956.9468
30 15504.1597 -6578.6828
31 8768.6364 15504.1597
32 2497.8375 8768.6364
33 33618.6349 2497.8375
34 -14240.8503 33618.6349
35 31867.4618 -14240.8503
36 31445.6920 31867.4618
37 8021.6636 31445.6920
38 71222.8089 8021.6636
39 4614.8546 71222.8089
40 11961.8714 4614.8546
41 38412.9928 11961.8714
42 -28969.6021 38412.9928
43 -1456.7733 -28969.6021
44 -21787.8394 -1456.7733
45 -11419.5741 -21787.8394
46 -41037.2267 -11419.5741
47 4371.3435 -41037.2267
48 3150.0774 4371.3435
49 -46877.5149 3150.0774
50 8556.6287 -46877.5149
51 -9241.1059 8556.6287
52 -13319.7086 -9241.1059
53 -25968.7499 -13319.7086
54 -50008.5486 -25968.7499
55 5810.8855 -50008.5486
56 -10732.7935 5810.8855
57 56547.8948 -10732.7935
58 -524.4215 56547.8948
59 -7452.1329 -524.4215
60 9451.8035 -7452.1329
61 35272.0555 9451.8035
62 34960.5510 35272.0555
63 9674.8574 34960.5510
64 -3653.4818 9674.8574
65 7253.2606 -3653.4818
66 23342.2936 7253.2606
67 11545.4167 23342.2936
68 1446.4992 11545.4167
69 -44243.1053 1446.4992
70 18110.7717 -44243.1053
71 52029.7342 18110.7717
72 37682.6261 52029.7342
73 -18520.9318 37682.6261
74 -31366.7262 -18520.9318
75 -20262.6090 -31366.7262
76 -42695.9530 -20262.6090
77 -15429.5104 -42695.9530
78 -25053.8450 -15429.5104
79 9291.1313 -25053.8450
80 -806.3206 9291.1313
81 -35316.6750 -806.3206
82 39816.6320 -35316.6750
83 34667.9527 39816.6320
84 18964.5375 34667.9527
85 -28554.0921 18964.5375
86 -10956.2433 -28554.0921
87 -16343.6198 -10956.2433
88 63964.9929 -16343.6198
89 -8594.5351 63964.9929
90 39472.2674 -8594.5351
91 -13796.6793 39472.2674
92 -32583.9091 -13796.6793
93 9724.0177 -32583.9091
94 20948.7912 9724.0177
95 9207.1669 20948.7912
96 23488.7918 9207.1669
97 -125102.8463 23488.7918
98 16873.8698 -125102.8463
99 -11159.3071 16873.8698
100 15535.0670 -11159.3071
101 -19547.4645 15535.0670
102 46543.2322 -19547.4645
103 15713.6497 46543.2322
104 34753.9907 15713.6497
105 21958.7130 34753.9907
106 -26855.7493 21958.7130
107 -14082.2168 -26855.7493
108 28482.3007 -14082.2168
109 2020.7652 28482.3007
110 13465.6046 2020.7652
111 -23533.7375 13465.6046
112 -13509.9752 -23533.7375
113 -4163.1887 -13509.9752
114 -27183.5957 -4163.1887
115 -33213.5065 -27183.5957
116 -21543.1289 -33213.5065
117 48719.0482 -21543.1289
118 4434.0070 48719.0482
119 -21929.0930 4434.0070
120 -5895.9049 -21929.0930
121 -44027.5410 -5895.9049
122 -33047.5834 -44027.5410
123 -59748.8005 -33047.5834
124 80235.5958 -59748.8005
125 21412.6603 80235.5958
126 10709.2148 21412.6603
127 -11616.4527 10709.2148
128 16785.8930 -11616.4527
129 4928.4760 16785.8930
130 -3093.0847 4928.4760
131 -43378.5018 -3093.0847
132 18194.8935 -43378.5018
133 -62434.3391 18194.8935
134 -19163.8951 -62434.3391
135 54453.0939 -19163.8951
136 5511.5491 54453.0939
137 41096.6802 5511.5491
138 -17284.5877 41096.6802
139 -9127.4260 -17284.5877
140 -23712.5166 -9127.4260
141 -10835.5184 -23712.5166
142 3791.7342 -10835.5184
143 -12753.5550 3791.7342
144 12219.9855 -12753.5550
145 -23997.1287 12219.9855
146 -5075.9745 -23997.1287
147 -9246.0262 -5075.9745
148 -18464.5852 -9246.0262
149 1364.1350 -18464.5852
150 27467.6990 1364.1350
151 20485.4625 27467.6990
152 -11249.2908 20485.4625
153 6047.9758 -11249.2908
154 9886.1818 6047.9758
155 47305.4278 9886.1818
156 24116.6176 47305.4278
157 14787.8558 24116.6176
158 -21976.9239 14787.8558
159 -18645.4690 -21976.9239
160 25962.4523 -18645.4690
161 -12301.7621 25962.4523
162 -11965.0230 -12301.7621
163 -15257.8465 -11965.0230
164 -29547.8839 -15257.8465
165 34725.0525 -29547.8839
166 -9813.0776 34725.0525
167 6724.5141 -9813.0776
168 20074.6334 6724.5141
169 91496.8166 20074.6334
170 -10173.9447 91496.8166
171 2948.9403 -10173.9447
172 9294.0253 2948.9403
173 14441.6266 9294.0253
174 -94320.3105 14441.6266
175 5312.9227 -94320.3105
176 -26779.2469 5312.9227
177 6031.4217 -26779.2469
178 -1426.7539 6031.4217
179 35667.6452 -1426.7539
180 -21714.2430 35667.6452
181 -57990.9555 -21714.2430
182 10044.0696 -57990.9555
183 22629.0749 10044.0696
184 15684.6509 22629.0749
185 4232.7717 15684.6509
186 3808.0208 4232.7717
187 17050.2110 3808.0208
188 10878.3234 17050.2110
189 492.5822 10878.3234
190 30354.3006 492.5822
191 -5626.7229 30354.3006
192 -19189.7047 -5626.7229
193 -11416.4864 -19189.7047
194 2133.8916 -11416.4864
195 4136.2555 2133.8916
196 -19332.8463 4136.2555
197 11106.7319 -19332.8463
198 -30667.7804 11106.7319
199 -3269.5410 -30667.7804
200 6778.4503 -3269.5410
201 2101.1020 6778.4503
202 12381.5127 2101.1020
203 6113.9303 12381.5127
204 -34636.1902 6113.9303
205 -12464.8983 -34636.1902
206 -6131.1920 -12464.8983
207 46463.9374 -6131.1920
208 24979.8211 46463.9374
209 615.0497 24979.8211
210 12198.4571 615.0497
211 28018.9275 12198.4571
212 -3209.9373 28018.9275
213 1854.4523 -3209.9373
214 -31352.7600 1854.4523
215 -12515.1354 -31352.7600
216 -33798.9170 -12515.1354
217 4356.3616 -33798.9170
218 670.6397 4356.3616
219 27822.8947 670.6397
220 -15413.9379 27822.8947
221 -3699.7139 -15413.9379
222 -53643.1876 -3699.7139
223 5784.3746 -53643.1876
224 -5510.9506 5784.3746
225 -2637.7895 -5510.9506
226 17702.5601 -2637.7895
227 -27294.2014 17702.5601
228 -22380.1248 -27294.2014
229 -36845.4902 -22380.1248
230 -14724.1446 -36845.4902
231 -4224.2810 -14724.1446
232 -30285.9412 -4224.2810
233 -8050.9648 -30285.9412
234 -31980.9686 -8050.9648
235 -15700.9431 -31980.9686
236 51689.6419 -15700.9431
237 -16085.1989 51689.6419
238 -16424.3762 -16085.1989
239 -23714.2667 -16424.3762
240 10683.0330 -23714.2667
241 3246.0090 10683.0330
242 -19982.0025 3246.0090
243 -8376.8993 -19982.0025
244 -391.7449 -8376.8993
245 -10622.1736 -391.7449
246 -22975.0442 -10622.1736
247 21345.3909 -22975.0442
248 7002.7955 21345.3909
249 -12220.8415 7002.7955
250 13843.3273 -12220.8415
251 4730.8307 13843.3273
252 12242.1475 4730.8307
253 -1862.1029 12242.1475
254 -18439.2956 -1862.1029
255 1481.0874 -18439.2956
256 -9992.6513 1481.0874
257 6365.0316 -9992.6513
258 11323.9548 6365.0316
259 5434.2595 11323.9548
260 -18634.2620 5434.2595
261 3398.5841 -18634.2620
262 14372.8917 3398.5841
263 -9035.8351 14372.8917
264 -10057.3874 -9035.8351
265 5938.8491 -10057.3874
266 -23029.5374 5938.8491
267 -6434.2341 -23029.5374
268 46611.7022 -6434.2341
269 -16838.9322 46611.7022
270 -7788.3496 -16838.9322
271 3566.1515 -7788.3496
272 2670.1187 3566.1515
273 2218.2622 2670.1187
274 10559.4782 2218.2622
275 -20018.7235 10559.4782
276 15880.3569 -20018.7235
277 10131.6948 15880.3569
278 -1959.1179 10131.6948
279 16155.1909 -1959.1179
280 -5730.9616 16155.1909
281 20732.0277 -5730.9616
282 -155.6071 20732.0277
283 12157.8137 -155.6071
284 3319.6367 12157.8137
285 -2782.5554 3319.6367
286 4227.4719 -2782.5554
287 -265.4999 4227.4719
288 -3301.6950 -265.4999
> 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/794fx1324302529.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/8xtmy1324302529.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/92u5p1324302529.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/10dc391324302529.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11ict91324302529.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12wum61324302529.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13bzwe1324302529.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14whv61324302529.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/15mb4j1324302529.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/164qi71324302529.tab")
+ }
>
> try(system("convert tmp/118761324302529.ps tmp/118761324302529.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nj7d1324302529.ps tmp/2nj7d1324302529.png",intern=TRUE))
character(0)
> try(system("convert tmp/3v59k1324302529.ps tmp/3v59k1324302529.png",intern=TRUE))
character(0)
> try(system("convert tmp/4rk1c1324302529.ps tmp/4rk1c1324302529.png",intern=TRUE))
character(0)
> try(system("convert tmp/59hdq1324302529.ps tmp/59hdq1324302529.png",intern=TRUE))
character(0)
> try(system("convert tmp/62xlh1324302529.ps tmp/62xlh1324302529.png",intern=TRUE))
character(0)
> try(system("convert tmp/794fx1324302529.ps tmp/794fx1324302529.png",intern=TRUE))
character(0)
> try(system("convert tmp/8xtmy1324302529.ps tmp/8xtmy1324302529.png",intern=TRUE))
character(0)
> try(system("convert tmp/92u5p1324302529.ps tmp/92u5p1324302529.png",intern=TRUE))
character(0)
> try(system("convert tmp/10dc391324302529.ps tmp/10dc391324302529.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
8.422 0.682 9.123