R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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> x <- array(list(210907
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+ ,29
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+ ,16
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+ ,1
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+ ,27
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+ ,0
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+ ,1
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+ ,46
+ ,0
+ ,28
+ ,15
+ ,72535
+ ,14
+ ,329
+ ,44
+ ,0
+ ,17
+ ,16)
+ ,dim=c(7
+ ,289)
+ ,dimnames=list(c('time_in_rfc'
+ ,'logins'
+ ,'compendium_views_info'
+ ,'compendium_views_pr'
+ ,'shared_compendiums'
+ ,'blogged_computations'
+ ,'compendiums_reviewed')
+ ,1:289))
> y <- array(NA,dim=c(7,289),dimnames=list(c('time_in_rfc','logins','compendium_views_info','compendium_views_pr','shared_compendiums','blogged_computations','compendiums_reviewed'),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 = '3'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '3'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
compendium_views_info time_in_rfc logins compendium_views_pr
1 396 210907 56 81
2 297 120982 56 55
3 559 176508 54 50
4 967 179321 89 125
5 270 123185 40 40
6 143 52746 25 37
7 1562 385534 92 63
8 109 33170 18 44
9 371 101645 63 88
10 656 149061 44 66
11 511 165446 33 57
12 655 237213 84 74
13 465 173326 88 49
14 525 133131 55 52
15 885 258873 60 88
16 497 180083 66 36
17 1436 324799 154 108
18 612 230964 53 43
19 865 236785 119 75
20 385 135473 41 32
21 567 202925 61 44
22 639 215147 58 85
23 963 344297 75 86
24 398 153935 33 56
25 410 132943 40 50
26 966 174724 92 135
27 801 174415 100 63
28 892 225548 112 81
29 513 223632 73 52
30 469 124817 40 44
31 683 221698 45 113
32 643 210767 60 39
33 535 170266 62 73
34 625 260561 75 48
35 264 84853 31 33
36 992 294424 77 59
37 238 101011 34 41
38 818 215641 46 69
39 937 325107 99 64
40 70 7176 17 1
41 507 167542 66 59
42 260 106408 30 32
43 503 96560 76 129
44 927 265769 146 37
45 1269 269651 67 31
46 537 149112 56 65
47 910 175824 107 107
48 532 152871 58 74
49 345 111665 34 54
50 918 116408 61 76
51 1635 362301 119 715
52 330 78800 42 57
53 557 183167 66 66
54 1178 277965 89 106
55 740 150629 44 54
56 452 168809 66 32
57 218 24188 24 20
58 764 329267 259 71
59 255 65029 17 21
60 454 101097 64 70
61 866 218946 41 112
62 574 244052 68 66
63 1276 341570 168 190
64 379 103597 43 66
65 825 233328 132 165
66 798 256462 105 56
67 663 206161 71 61
68 1069 311473 112 53
69 921 235800 94 127
70 858 177939 82 63
71 711 207176 70 38
72 503 196553 57 50
73 382 174184 53 52
74 464 143246 103 42
75 717 187559 121 76
76 690 187681 62 67
77 462 119016 52 50
78 657 182192 52 53
79 385 73566 32 39
80 577 194979 62 50
81 619 167488 45 77
82 479 143756 46 57
83 817 275541 63 73
84 752 243199 75 34
85 430 182999 88 39
86 451 135649 46 46
87 537 152299 53 63
88 519 120221 37 35
89 1000 346485 90 106
90 637 145790 63 43
91 465 193339 78 47
92 437 80953 25 31
93 711 122774 45 162
94 299 130585 46 57
95 248 112611 41 36
96 1162 286468 144 263
97 714 241066 82 78
98 905 148446 91 63
99 649 204713 71 54
100 512 182079 63 63
101 472 140344 53 77
102 905 220516 62 79
103 786 243060 63 110
104 489 162765 32 56
105 479 182613 39 56
106 617 232138 62 43
107 925 265318 117 111
108 351 85574 34 71
109 1144 310839 92 62
110 669 225060 93 56
111 707 232317 54 74
112 458 144966 144 60
113 214 43287 14 43
114 599 155754 61 68
115 572 164709 109 53
116 897 201940 38 87
117 819 235454 73 46
118 720 220801 75 105
119 273 99466 50 32
120 508 92661 61 133
121 506 133328 55 79
122 451 61361 77 51
123 699 125930 75 207
124 407 100750 72 67
125 465 224549 50 47
126 245 82316 32 34
127 370 102010 53 66
128 316 101523 42 76
129 603 243511 71 65
130 154 22938 10 9
131 229 41566 35 42
132 577 152474 65 45
133 192 61857 25 25
134 617 99923 66 115
135 411 132487 41 97
136 975 317394 86 53
137 146 21054 16 2
138 705 209641 42 52
139 184 22648 19 44
140 200 31414 19 22
141 274 46698 45 35
142 502 131698 65 74
143 382 91735 35 103
144 964 244749 95 144
145 537 184510 49 60
146 438 79863 37 134
147 369 128423 64 89
148 417 97839 38 42
149 276 38214 34 52
150 514 151101 32 98
151 822 272458 65 99
152 389 172494 52 52
153 466 108043 62 29
154 1255 328107 65 125
155 694 250579 83 106
156 1024 351067 95 95
157 400 158015 29 40
158 397 98866 18 140
159 350 85439 33 43
160 719 229242 247 128
161 1277 351619 139 142
162 356 84207 29 73
163 457 120445 118 72
164 1402 324598 110 128
165 600 131069 67 61
166 480 204271 42 73
167 595 165543 65 148
168 436 141722 94 64
169 230 116048 64 45
170 651 250047 81 58
171 1367 299775 95 97
172 564 195838 67 50
173 716 173260 63 37
174 747 254488 83 50
175 467 104389 45 105
176 671 136084 30 69
177 861 199476 70 46
178 319 92499 32 57
179 612 224330 83 52
180 433 135781 31 98
181 434 74408 67 61
182 503 81240 66 89
183 85 14688 10 0
184 564 181633 70 48
185 824 271856 103 91
186 74 7199 5 0
187 259 46660 20 7
188 69 17547 5 3
189 535 133368 36 54
190 239 95227 34 70
191 438 152601 48 36
192 459 98146 40 37
193 426 79619 43 123
194 288 59194 31 247
195 498 139942 42 46
196 454 118612 46 72
197 376 72880 33 41
198 225 65475 18 24
199 555 99643 55 45
200 252 71965 35 33
201 208 77272 59 27
202 130 49289 19 36
203 481 135131 66 87
204 389 108446 60 90
205 565 89746 36 114
206 173 44296 25 31
207 278 77648 47 45
208 609 181528 54 69
209 422 134019 53 51
210 445 124064 40 34
211 387 92630 40 60
212 339 121848 39 45
213 181 52915 14 54
214 245 81872 45 25
215 384 58981 36 38
216 212 53515 28 52
217 399 60812 44 67
218 229 56375 30 74
219 224 65490 22 38
220 203 80949 17 30
221 333 76302 31 26
222 384 104011 55 67
223 636 98104 54 132
224 185 67989 21 42
225 93 30989 14 35
226 581 135458 81 118
227 248 73504 35 68
228 304 63123 43 43
229 344 61254 46 76
230 407 74914 30 64
231 170 31774 23 48
232 312 81437 38 64
233 507 87186 54 56
234 224 50090 20 71
235 340 65745 53 75
236 168 56653 45 39
237 443 158399 39 42
238 204 46455 20 39
239 367 73624 24 93
240 210 38395 31 38
241 335 91899 35 60
242 364 139526 151 71
243 178 52164 52 52
244 206 51567 30 27
245 279 70551 31 59
246 387 84856 29 40
247 490 102538 57 79
248 238 86678 40 44
249 343 85709 44 65
250 232 34662 25 10
251 530 150580 77 124
252 291 99611 35 81
253 67 19349 11 15
254 397 99373 63 92
255 467 86230 44 42
256 178 30837 19 10
257 175 31706 13 24
258 299 89806 42 64
259 154 62088 38 45
260 106 40151 29 22
261 189 27634 20 56
262 194 76990 27 94
263 135 37460 20 19
264 201 54157 19 35
265 207 49862 37 32
266 280 84337 26 35
267 260 64175 42 48
268 227 59382 49 49
269 239 119308 30 48
270 333 76702 49 62
271 428 103425 67 96
272 230 70344 28 45
273 292 43410 19 63
274 350 104838 49 71
275 186 62215 27 26
276 326 69304 30 48
277 155 53117 22 29
278 75 19764 12 19
279 361 86680 31 45
280 261 84105 20 45
281 299 77945 20 67
282 300 89113 39 30
283 450 91005 29 36
284 183 40248 16 34
285 238 64187 27 36
286 165 50857 21 34
287 234 56613 19 37
288 176 62792 35 46
289 329 72535 14 44
shared_compendiums blogged_computations compendiums_reviewed
1 3 79 30
2 4 58 28
3 12 60 38
4 2 108 30
5 1 49 22
6 3 0 26
7 0 121 25
8 0 1 18
9 0 20 11
10 5 43 26
11 0 69 25
12 0 78 38
13 7 86 44
14 7 44 30
15 3 104 40
16 9 63 34
17 0 158 47
18 4 102 30
19 3 77 31
20 0 82 23
21 7 115 36
22 0 101 36
23 1 80 30
24 5 50 25
25 7 83 39
26 0 123 34
27 0 73 31
28 5 81 31
29 0 105 33
30 0 47 25
31 0 105 33
32 3 94 35
33 4 44 42
34 1 114 43
35 4 38 30
36 2 107 33
37 0 30 13
38 0 71 32
39 0 84 36
40 0 0 0
41 2 59 28
42 1 33 14
43 0 42 17
44 2 96 32
45 10 106 30
46 6 56 35
47 0 57 20
48 5 59 28
49 4 39 28
50 1 34 39
51 2 76 34
52 2 20 26
53 0 91 39
54 8 115 39
55 3 85 33
56 0 76 28
57 0 8 4
58 8 79 39
59 5 21 18
60 3 30 14
61 1 76 29
62 5 101 44
63 1 94 21
64 1 27 16
65 5 92 28
66 0 123 35
67 12 75 28
68 8 128 38
69 8 105 23
70 8 55 36
71 8 56 32
72 2 41 29
73 0 72 25
74 5 67 27
75 8 75 36
76 2 114 28
77 5 118 23
78 12 77 40
79 6 22 23
80 7 66 40
81 2 69 28
82 0 105 34
83 4 116 33
84 3 88 28
85 6 73 34
86 2 99 30
87 0 62 33
88 1 53 22
89 0 118 38
90 5 30 26
91 2 100 35
92 0 49 8
93 0 24 24
94 5 67 29
95 0 46 20
96 1 57 29
97 0 75 45
98 1 135 37
99 1 68 33
100 2 124 33
101 6 33 25
102 1 98 32
103 4 58 29
104 2 68 28
105 3 81 28
106 0 131 31
107 10 110 52
108 0 37 21
109 9 130 24
110 7 93 41
111 0 118 33
112 0 39 32
113 4 13 19
114 4 74 20
115 0 81 31
116 0 109 31
117 0 151 32
118 1 51 18
119 0 28 23
120 1 40 17
121 0 56 20
122 0 27 12
123 4 37 17
124 0 83 30
125 4 54 31
126 4 27 10
127 3 28 13
128 0 59 22
129 0 133 42
130 0 12 1
131 5 0 9
132 0 106 32
133 4 23 11
134 0 44 25
135 0 71 36
136 1 116 31
137 0 4 0
138 5 62 24
139 0 12 13
140 0 18 8
141 0 14 13
142 0 60 19
143 0 7 18
144 2 98 33
145 7 64 40
146 1 29 22
147 8 32 38
148 2 25 24
149 0 16 8
150 2 48 35
151 0 100 43
152 0 46 43
153 1 45 14
154 3 129 41
155 0 130 38
156 3 136 45
157 0 59 31
158 0 25 13
159 0 32 28
160 4 63 31
161 4 95 40
162 11 14 30
163 0 36 16
164 0 113 37
165 4 47 30
166 0 92 35
167 1 70 32
168 0 19 27
169 0 50 20
170 0 41 18
171 9 91 31
172 1 111 31
173 3 41 21
174 10 120 39
175 5 135 41
176 0 27 13
177 2 87 32
178 0 25 18
179 1 131 39
180 2 45 14
181 4 29 7
182 0 58 17
183 0 4 0
184 2 47 30
185 1 109 37
186 0 7 0
187 0 12 5
188 0 0 1
189 1 37 16
190 0 37 32
191 2 46 24
192 0 15 17
193 3 42 11
194 6 7 24
195 0 54 22
196 2 54 12
197 0 14 19
198 2 16 13
199 1 33 17
200 1 32 15
201 2 21 16
202 1 15 24
203 0 38 15
204 1 22 17
205 3 28 18
206 0 10 20
207 0 31 16
208 0 32 16
209 0 32 18
210 1 43 22
211 4 27 8
212 0 37 17
213 0 20 18
214 0 32 16
215 7 0 23
216 2 5 22
217 0 26 13
218 7 10 13
219 3 27 16
220 0 11 16
221 0 29 20
222 6 25 22
223 2 55 17
224 0 23 18
225 0 5 17
226 3 43 12
227 0 23 7
228 1 34 17
229 1 36 14
230 0 35 23
231 1 0 17
232 0 37 14
233 0 28 15
234 0 16 17
235 0 26 21
236 0 38 18
237 0 23 18
238 0 22 17
239 0 30 17
240 0 16 16
241 0 18 15
242 0 28 21
243 0 32 16
244 2 21 14
245 0 23 15
246 1 29 17
247 1 50 15
248 0 12 15
249 0 21 10
250 0 18 6
251 0 27 22
252 0 41 21
253 0 13 1
254 1 12 18
255 0 21 17
256 0 8 4
257 0 26 10
258 0 27 16
259 1 13 16
260 0 16 9
261 0 2 16
262 0 42 17
263 0 5 7
264 0 37 15
265 0 17 14
266 0 38 14
267 0 37 18
268 0 29 12
269 0 32 16
270 0 35 21
271 1 17 19
272 0 20 16
273 0 7 1
274 1 46 16
275 0 24 10
276 6 40 19
277 3 3 12
278 1 10 2
279 2 37 14
280 0 17 17
281 0 28 19
282 0 19 14
283 3 29 11
284 1 8 4
285 0 10 16
286 0 15 20
287 1 15 12
288 0 28 15
289 0 17 16
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time_in_rfc logins
56.910838 0.002529 0.582228
compendium_views_pr shared_compendiums blogged_computations
1.131582 6.110852 1.235528
compendiums_reviewed
-4.022962
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-346.28 -66.82 -15.53 46.44 553.98
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 56.9108381 17.5326899 3.246 0.001312 **
time_in_rfc 0.0025287 0.0001872 13.507 < 2e-16 ***
logins 0.5822282 0.2909304 2.001 0.046322 *
compendium_views_pr 1.1315817 0.1441343 7.851 8.67e-14 ***
shared_compendiums 6.1108516 2.7161838 2.250 0.025233 *
blogged_computations 1.2355282 0.3627809 3.406 0.000756 ***
compendiums_reviewed -4.0229625 1.0985256 -3.662 0.000299 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 114.6 on 282 degrees of freedom
Multiple R-squared: 0.8437, Adjusted R-squared: 0.8403
F-statistic: 253.6 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,] 0.9995014 9.971722e-04 4.985861e-04
[2,] 0.9988882 2.223580e-03 1.111790e-03
[3,] 0.9987092 2.581656e-03 1.290828e-03
[4,] 0.9972646 5.470722e-03 2.735361e-03
[5,] 0.9956484 8.703104e-03 4.351552e-03
[6,] 0.9925175 1.496499e-02 7.482494e-03
[7,] 0.9888065 2.238706e-02 1.119353e-02
[8,] 0.9931216 1.375677e-02 6.878383e-03
[9,] 0.9916268 1.674642e-02 8.373209e-03
[10,] 0.9895353 2.092942e-02 1.046471e-02
[11,] 0.9836601 3.267982e-02 1.633991e-02
[12,] 0.9770951 4.580978e-02 2.290489e-02
[13,] 0.9693153 6.136946e-02 3.068473e-02
[14,] 0.9800166 3.996673e-02 1.998337e-02
[15,] 0.9724650 5.507003e-02 2.753501e-02
[16,] 0.9650126 6.997482e-02 3.498741e-02
[17,] 0.9639174 7.216528e-02 3.608264e-02
[18,] 0.9664094 6.718116e-02 3.359058e-02
[19,] 0.9560006 8.799874e-02 4.399937e-02
[20,] 0.9748974 5.020528e-02 2.510264e-02
[21,] 0.9774275 4.514500e-02 2.257250e-02
[22,] 0.9725050 5.498992e-02 2.749496e-02
[23,] 0.9639462 7.210759e-02 3.605379e-02
[24,] 0.9543881 9.122388e-02 4.561194e-02
[25,] 0.9540427 9.191450e-02 4.595725e-02
[26,] 0.9501011 9.979772e-02 4.989886e-02
[27,] 0.9410292 1.179416e-01 5.897082e-02
[28,] 0.9332447 1.335105e-01 6.675527e-02
[29,] 0.9564017 8.719669e-02 4.359835e-02
[30,] 0.9502992 9.940164e-02 4.970082e-02
[31,] 0.9405834 1.188332e-01 5.941660e-02
[32,] 0.9283203 1.433595e-01 7.167974e-02
[33,] 0.9150784 1.698432e-01 8.492158e-02
[34,] 0.9133930 1.732140e-01 8.660700e-02
[35,] 0.9012981 1.974038e-01 9.870189e-02
[36,] 0.9902497 1.950053e-02 9.750263e-03
[37,] 0.9874802 2.503952e-02 1.251976e-02
[38,] 0.9888174 2.236517e-02 1.118259e-02
[39,] 0.9854652 2.906959e-02 1.453480e-02
[40,] 0.9813973 3.720536e-02 1.860268e-02
[41,] 0.9999934 1.314728e-05 6.573641e-06
[42,] 0.9999987 2.592649e-06 1.296324e-06
[43,] 0.9999981 3.875940e-06 1.937970e-06
[44,] 0.9999970 5.918998e-06 2.959499e-06
[45,] 0.9999985 2.960647e-06 1.480323e-06
[46,] 0.9999997 6.786349e-07 3.393174e-07
[47,] 0.9999996 7.644977e-07 3.822489e-07
[48,] 0.9999995 9.626520e-07 4.813260e-07
[49,] 1.0000000 1.214873e-09 6.074366e-10
[50,] 1.0000000 2.140393e-09 1.070196e-09
[51,] 1.0000000 3.739044e-09 1.869522e-09
[52,] 1.0000000 4.090852e-09 2.045426e-09
[53,] 1.0000000 1.624372e-09 8.121862e-10
[54,] 1.0000000 2.941166e-09 1.470583e-09
[55,] 1.0000000 5.237638e-09 2.618819e-09
[56,] 1.0000000 5.120319e-09 2.560160e-09
[57,] 1.0000000 7.050606e-09 3.525303e-09
[58,] 1.0000000 1.041771e-08 5.208856e-09
[59,] 1.0000000 1.678948e-08 8.394738e-09
[60,] 1.0000000 2.843207e-08 1.421604e-08
[61,] 1.0000000 3.174853e-09 1.587427e-09
[62,] 1.0000000 4.635602e-09 2.317801e-09
[63,] 1.0000000 6.445128e-09 3.222564e-09
[64,] 1.0000000 2.523558e-09 1.261779e-09
[65,] 1.0000000 3.704201e-09 1.852100e-09
[66,] 1.0000000 6.151833e-09 3.075916e-09
[67,] 1.0000000 1.031343e-08 5.156715e-09
[68,] 1.0000000 1.401485e-08 7.007423e-09
[69,] 1.0000000 2.196803e-08 1.098401e-08
[70,] 1.0000000 2.272896e-08 1.136448e-08
[71,] 1.0000000 3.721077e-08 1.860538e-08
[72,] 1.0000000 5.898272e-08 2.949136e-08
[73,] 1.0000000 9.067143e-08 4.533571e-08
[74,] 0.9999999 1.112561e-07 5.562806e-08
[75,] 0.9999999 1.804862e-07 9.024309e-08
[76,] 0.9999999 1.080161e-07 5.400807e-08
[77,] 0.9999999 1.628619e-07 8.143094e-08
[78,] 0.9999999 2.437693e-07 1.218846e-07
[79,] 0.9999999 2.499188e-07 1.249594e-07
[80,] 0.9999999 2.831313e-07 1.415656e-07
[81,] 0.9999999 1.735570e-07 8.677852e-08
[82,] 1.0000000 9.886039e-08 4.943020e-08
[83,] 0.9999999 1.162652e-07 5.813259e-08
[84,] 1.0000000 5.317321e-08 2.658660e-08
[85,] 1.0000000 2.869149e-08 1.434575e-08
[86,] 1.0000000 2.406302e-08 1.203151e-08
[87,] 1.0000000 3.840059e-08 1.920029e-08
[88,] 1.0000000 6.226264e-08 3.113132e-08
[89,] 1.0000000 1.776406e-09 8.882029e-10
[90,] 1.0000000 2.994547e-09 1.497274e-09
[91,] 1.0000000 2.224224e-09 1.112112e-09
[92,] 1.0000000 3.579536e-09 1.789768e-09
[93,] 1.0000000 1.948468e-09 9.742342e-10
[94,] 1.0000000 3.149735e-09 1.574867e-09
[95,] 1.0000000 4.931341e-09 2.465671e-09
[96,] 1.0000000 4.250142e-09 2.125071e-09
[97,] 1.0000000 3.134597e-09 1.567299e-09
[98,] 1.0000000 5.222517e-09 2.611259e-09
[99,] 1.0000000 8.649230e-09 4.324615e-09
[100,] 1.0000000 1.212665e-08 6.063325e-09
[101,] 1.0000000 1.715124e-08 8.575618e-09
[102,] 1.0000000 2.410090e-08 1.205045e-08
[103,] 1.0000000 3.628573e-08 1.814287e-08
[104,] 1.0000000 5.755780e-08 2.877890e-08
[105,] 1.0000000 9.294495e-08 4.647247e-08
[106,] 0.9999999 1.449887e-07 7.249434e-08
[107,] 1.0000000 5.306732e-08 2.653366e-08
[108,] 1.0000000 8.115286e-08 4.057643e-08
[109,] 0.9999999 1.120647e-07 5.603234e-08
[110,] 0.9999999 1.685443e-07 8.427215e-08
[111,] 0.9999999 2.516804e-07 1.258402e-07
[112,] 0.9999998 3.961054e-07 1.980527e-07
[113,] 0.9999999 2.581306e-07 1.290653e-07
[114,] 0.9999998 3.915888e-07 1.957944e-07
[115,] 0.9999997 5.760777e-07 2.880388e-07
[116,] 0.9999999 1.517788e-07 7.588938e-08
[117,] 0.9999999 1.625669e-07 8.128346e-08
[118,] 0.9999999 2.283671e-07 1.141835e-07
[119,] 0.9999999 2.747191e-07 1.373595e-07
[120,] 0.9999999 1.487794e-07 7.438970e-08
[121,] 0.9999999 2.354858e-07 1.177429e-07
[122,] 0.9999998 3.705508e-07 1.852754e-07
[123,] 0.9999998 4.902690e-07 2.451345e-07
[124,] 0.9999997 6.045133e-07 3.022567e-07
[125,] 0.9999999 2.143162e-07 1.071581e-07
[126,] 0.9999998 3.108896e-07 1.554448e-07
[127,] 0.9999998 4.625812e-07 2.312906e-07
[128,] 0.9999996 7.179908e-07 3.589954e-07
[129,] 0.9999995 1.053904e-06 5.269522e-07
[130,] 0.9999993 1.463156e-06 7.315781e-07
[131,] 0.9999989 2.118419e-06 1.059210e-06
[132,] 0.9999987 2.619265e-06 1.309632e-06
[133,] 0.9999980 3.948820e-06 1.974410e-06
[134,] 0.9999970 5.920372e-06 2.960186e-06
[135,] 0.9999963 7.446936e-06 3.723468e-06
[136,] 0.9999952 9.556389e-06 4.778195e-06
[137,] 0.9999938 1.239386e-05 6.196931e-06
[138,] 0.9999937 1.264486e-05 6.322430e-06
[139,] 0.9999927 1.450942e-05 7.254712e-06
[140,] 0.9999907 1.853227e-05 9.266137e-06
[141,] 0.9999864 2.719050e-05 1.359525e-05
[142,] 0.9999807 3.868564e-05 1.934282e-05
[143,] 0.9999776 4.482213e-05 2.241107e-05
[144,] 0.9999718 5.632108e-05 2.816054e-05
[145,] 0.9999820 3.591854e-05 1.795927e-05
[146,] 0.9999877 2.459549e-05 1.229775e-05
[147,] 0.9999885 2.302653e-05 1.151326e-05
[148,] 0.9999867 2.660153e-05 1.330077e-05
[149,] 0.9999826 3.483961e-05 1.741980e-05
[150,] 0.9999795 4.099648e-05 2.049824e-05
[151,] 0.9999880 2.403568e-05 1.201784e-05
[152,] 0.9999855 2.898917e-05 1.449458e-05
[153,] 0.9999800 3.997989e-05 1.998995e-05
[154,] 0.9999716 5.678610e-05 2.839305e-05
[155,] 0.9999992 1.605740e-06 8.028698e-07
[156,] 0.9999993 1.325125e-06 6.625624e-07
[157,] 0.9999996 7.546376e-07 3.773188e-07
[158,] 0.9999994 1.140637e-06 5.703183e-07
[159,] 0.9999991 1.760949e-06 8.804747e-07
[160,] 0.9999996 7.287685e-07 3.643842e-07
[161,] 0.9999998 4.001418e-07 2.000709e-07
[162,] 1.0000000 5.220121e-09 2.610060e-09
[163,] 1.0000000 6.142041e-09 3.071021e-09
[164,] 1.0000000 2.918720e-09 1.459360e-09
[165,] 1.0000000 2.521809e-09 1.260904e-09
[166,] 1.0000000 4.314977e-09 2.157489e-09
[167,] 1.0000000 6.383880e-10 3.191940e-10
[168,] 1.0000000 4.794808e-11 2.397404e-11
[169,] 1.0000000 8.981004e-11 4.490502e-11
[170,] 1.0000000 6.661704e-11 3.330852e-11
[171,] 1.0000000 7.449779e-11 3.724890e-11
[172,] 1.0000000 1.139455e-10 5.697277e-11
[173,] 1.0000000 8.484354e-11 4.242177e-11
[174,] 1.0000000 1.555222e-10 7.776110e-11
[175,] 1.0000000 2.914573e-10 1.457287e-10
[176,] 1.0000000 3.981628e-10 1.990814e-10
[177,] 1.0000000 7.328185e-10 3.664092e-10
[178,] 1.0000000 9.340195e-10 4.670098e-10
[179,] 1.0000000 1.630942e-09 8.154708e-10
[180,] 1.0000000 2.052142e-09 1.026071e-09
[181,] 1.0000000 2.106780e-09 1.053390e-09
[182,] 1.0000000 2.893782e-09 1.446891e-09
[183,] 1.0000000 1.396211e-09 6.981053e-10
[184,] 1.0000000 2.544214e-09 1.272107e-09
[185,] 1.0000000 3.748087e-10 1.874043e-10
[186,] 1.0000000 6.209450e-10 3.104725e-10
[187,] 1.0000000 1.112755e-09 5.563777e-10
[188,] 1.0000000 6.044406e-10 3.022203e-10
[189,] 1.0000000 1.137367e-09 5.686833e-10
[190,] 1.0000000 7.969637e-11 3.984819e-11
[191,] 1.0000000 1.540207e-10 7.701037e-11
[192,] 1.0000000 2.187582e-10 1.093791e-10
[193,] 1.0000000 3.257471e-10 1.628735e-10
[194,] 1.0000000 6.232236e-10 3.116118e-10
[195,] 1.0000000 1.080377e-09 5.401887e-10
[196,] 1.0000000 6.045355e-10 3.022678e-10
[197,] 1.0000000 1.172064e-09 5.860319e-10
[198,] 1.0000000 2.239155e-09 1.119578e-09
[199,] 1.0000000 3.231813e-09 1.615907e-09
[200,] 1.0000000 6.099136e-09 3.049568e-09
[201,] 1.0000000 8.687834e-09 4.343917e-09
[202,] 1.0000000 1.639249e-08 8.196243e-09
[203,] 1.0000000 2.636579e-08 1.318289e-08
[204,] 1.0000000 4.231516e-08 2.115758e-08
[205,] 1.0000000 7.449187e-08 3.724593e-08
[206,] 1.0000000 3.233296e-08 1.616648e-08
[207,] 1.0000000 6.092546e-08 3.046273e-08
[208,] 1.0000000 4.221363e-08 2.110681e-08
[209,] 1.0000000 4.100269e-08 2.050134e-08
[210,] 1.0000000 6.223062e-08 3.111531e-08
[211,] 0.9999999 1.034219e-07 5.171096e-08
[212,] 1.0000000 9.950207e-08 4.975104e-08
[213,] 0.9999999 1.453100e-07 7.265500e-08
[214,] 1.0000000 6.506506e-08 3.253253e-08
[215,] 1.0000000 9.210320e-08 4.605160e-08
[216,] 0.9999999 1.424949e-07 7.124746e-08
[217,] 0.9999999 2.538633e-07 1.269317e-07
[218,] 0.9999998 3.633097e-07 1.816549e-07
[219,] 0.9999997 5.895524e-07 2.947762e-07
[220,] 0.9999995 9.481245e-07 4.740623e-07
[221,] 0.9999997 5.467669e-07 2.733834e-07
[222,] 0.9999995 1.040426e-06 5.202130e-07
[223,] 0.9999990 1.945533e-06 9.727663e-07
[224,] 0.9999999 1.221893e-07 6.109464e-08
[225,] 0.9999999 2.433358e-07 1.216679e-07
[226,] 0.9999999 2.905804e-07 1.452902e-07
[227,] 0.9999998 4.917917e-07 2.458959e-07
[228,] 0.9999995 9.482757e-07 4.741379e-07
[229,] 0.9999991 1.825995e-06 9.129973e-07
[230,] 0.9999986 2.726197e-06 1.363099e-06
[231,] 0.9999979 4.209276e-06 2.104638e-06
[232,] 0.9999960 8.025964e-06 4.012982e-06
[233,] 0.9999976 4.736888e-06 2.368444e-06
[234,] 0.9999966 6.735485e-06 3.367743e-06
[235,] 0.9999938 1.247072e-05 6.235358e-06
[236,] 0.9999883 2.332770e-05 1.166385e-05
[237,] 0.9999896 2.082205e-05 1.041103e-05
[238,] 0.9999907 1.855437e-05 9.277187e-06
[239,] 0.9999883 2.343853e-05 1.171927e-05
[240,] 0.9999778 4.434772e-05 2.217386e-05
[241,] 0.9999755 4.896549e-05 2.448274e-05
[242,] 0.9999526 9.474663e-05 4.737332e-05
[243,] 0.9999241 1.518110e-04 7.590551e-05
[244,] 0.9998743 2.514217e-04 1.257108e-04
[245,] 0.9997644 4.712373e-04 2.356186e-04
[246,] 0.9999763 4.749689e-05 2.374845e-05
[247,] 0.9999605 7.891668e-05 3.945834e-05
[248,] 0.9999358 1.284724e-04 6.423620e-05
[249,] 0.9998713 2.574735e-04 1.287367e-04
[250,] 0.9999006 1.988277e-04 9.941383e-05
[251,] 0.9998520 2.960087e-04 1.480044e-04
[252,] 0.9997285 5.430184e-04 2.715092e-04
[253,] 0.9999187 1.626932e-04 8.134660e-05
[254,] 0.9998179 3.641667e-04 1.820833e-04
[255,] 0.9996026 7.947927e-04 3.973964e-04
[256,] 0.9992342 1.531637e-03 7.658185e-04
[257,] 0.9984580 3.084073e-03 1.542036e-03
[258,] 0.9971016 5.796717e-03 2.898358e-03
[259,] 0.9942845 1.143097e-02 5.715485e-03
[260,] 0.9994615 1.076997e-03 5.384983e-04
[261,] 0.9997432 5.135730e-04 2.567865e-04
[262,] 0.9995108 9.784387e-04 4.892194e-04
[263,] 0.9986674 2.665210e-03 1.332605e-03
[264,] 0.9992603 1.479409e-03 7.397045e-04
[265,] 0.9979415 4.117012e-03 2.058506e-03
[266,] 0.9966482 6.703508e-03 3.351754e-03
[267,] 0.9900381 1.992375e-02 9.961875e-03
[268,] 0.9926694 1.466128e-02 7.330638e-03
[269,] 0.9762946 4.741073e-02 2.370536e-02
[270,] 0.9274643 1.450714e-01 7.253572e-02
> postscript(file="/var/fisher/rcomp/tmp/1kuhp1353255341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/26ult1353255341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3bdz51353255341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4td9l1353255341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5kmt81353255341.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
-313.7533193 -144.1458473 -26.8625980 238.3968988 -145.1127521 -17.4515686
7 8 9 10 11 12
356.3940443 -20.8810829 -59.6622589 142.7651222 -32.6719914 -77.9039142
13 14 15 16 17 18
-108.9120233 64.1202176 53.0445253 -90.5133212 339.7484291 -138.2534885
19 20 21 22 23 24
66.4110539 -83.3541137 -128.3961755 -71.8772561 -89.7961456 -122.5112940
25 26 27 28 29 30
-51.3867321 245.7396487 208.0446121 101.9488071 -207.7358503 65.8848113
31 32 33 34 35 36
-85.5693596 -19.6198881 18.9847130 -162.7588361 -13.5779723 67.3067751
37 38 39 40 41 42
-125.2994362 151.9395895 -31.0417727 -16.0865446 -51.2464603 -110.2283769
43 44 45 46 47 48
28.1887252 69.0567465 384.7376727 31.8149428 235.1322884 -19.7957566
49 50 51 52 53 54
-35.1699286 553.9840768 -185.7834234 52.5353873 -31.7417235 212.3446825
55 56 57 58 59 60
224.8692909 -87.6799459 69.5264880 -346.2792057 15.8995432 25.8907836
61 62 63 64 65 66
121.4778479 -192.6633018 4.7639519 -14.7037365 -117.0819236 -43.1056292
67 68 69 70 71 72
-78.9551803 45.1093825 -16.7174286 260.0809444 57.0970482 -86.9210041
73 74 75 76 77 78
-193.4613704 -67.3534682 32.6264289 6.1494309 -66.5448800 41.5756944
79 80 81 82 83 84
107.9782200 -29.0417843 40.3931309 -25.6649216 -90.9754158 -16.4550972
85 86 87 88 89 90
-175.1136232 -41.6174035 48.9717088 113.8449163 -98.3496104 163.0625444
91 92 93 94 95 96
-174.3840700 97.3880720 201.0074335 -176.0778714 -134.6582351 39.3688934
97 98 99 100 101 102
-0.1417016 324.3777117 14.6103866 -145.9809338 -34.6578271 166.5103944
103 104 105 106 107 108
-26.1391153 -45.0959146 -131.5346816 -148.8262345 15.6198208 16.3242886
109 110 111 112 113 114
58.2695506 -67.2837063 -65.5922943 -36.6788687 26.7493562 0.3509172
115 116 117 118 119 120
-0.2198910 198.9021884 14.3016025 -54.4520346 -42.8232664 43.6155875
121 122 123 124 125 126
1.7893474 151.2971349 43.9726928 -4.2778669 -208.4829390 -94.7448047
127 128 129 130 131 132
-51.0390256 -92.4809943 -179.9389265 12.2750077 4.7274997 43.5247060
133 134 135 136 137 138
-72.7843851 185.0616386 -57.4667817 -19.2837959 19.3281219 24.0596336
139 140 141 142 143 144
46.4384782 37.6383508 68.1975035 -7.2182538 19.9488327 69.3771834
145 146 147 148 149 150
-43.8441891 52.5259327 -86.1838602 96.4697605 56.2330943 14.7441903
151 152 153 154 155 156
-24.3234053 -77.0685113 61.5742350 176.3247655 -172.5789213 -88.8113700
157 158 159 160 161 162
-66.8220582 -57.4085834 82.2705631 -183.8271511 108.4213776 22.8334989
163 164 165 166 167 168
-34.7734731 324.6122599 141.7894777 -173.3832457 -49.7081604 -21.2947965
169 170 171 172 173 174
-189.8671151 -129.2504875 344.2418350 -102.2654373 157.9036008 -110.8254654
175 176 177 178 179 180
-31.3090386 193.3612418 215.8794340 -13.4231906 -130.4200050 -107.7088968
181 182 183 184 185 186
48.7818413 98.2461353 -19.8173805 3.1118006 -75.2415022 -12.6750831
187 188 189 190 191 192
69.8209457 -34.5655795 71.3124119 -74.7014792 -45.9880371 138.6031378
193 194 195 196 197 198
-22.4391825 -164.9095961 32.4923993 -41.7709211 128.3250307 -14.8098647
199 200 201 202 203 204
184.6811755 -29.9151840 -83.0162776 -31.4419054 -41.1024403 -43.8208384
205 206 207 208 209 210
150.6702233 22.5452805 -27.4823956 8.3629066 -29.5025152 41.8671443
211 212 213 214 215 216
-20.9511140 -76.9851274 -31.2730142 -48.6032351 163.7333456 14.7247800
217 218 219 220 221 222
107.0521281 -74.5052347 -41.6516277 -51.6786325 80.2998999 -22.8143825
223 224 225 226 227 228
138.4150542 -59.5944571 -27.8178261 -22.3208783 -92.3653699 34.0451691
229 230 231 232 233 234
25.1425611 120.0476335 27.3132857 -34.7828881 160.5590991 -2.9404288
235 236 237 238 239 240
53.4688409 -77.0403053 -40.6980352 15.0489898 36.0270755 39.5479204
241 242 243 244 245 246
-4.4675654 -164.1072904 -75.1077023 -11.1762979 -9.2011500 79.8116232
247 248 249 250 251 252
43.6723308 -65.6576730 -15.5340183 63.4646865 -37.6904451 -96.0118066
253 254 255 256 257 258
-74.2565877 -0.5091748 161.3356241 26.9398476 11.2918632 -50.8736267
259 260 261 262 263 264
-90.7664755 -77.7835221 49.0931369 -163.1892719 -27.7989953 -28.8976666
265 266 267 268 269 270
1.5655156 -35.5491570 -11.2635173 -51.6039898 -166.5621378 24.6811471
271 272 273 274 275 276
11.2344484 -32.3593249 38.3387978 -79.4682186 -62.8007966 12.4045767
277 278 279 280 281 282
-55.6184522 -70.7958747 14.3128697 -23.7699563 -0.6325955 -6.0624453
283 284 285 286 287 288
95.4292439 -23.3802616 14.3318793 -9.2892624 4.6304646 -86.3766408
289
74.0895651
> postscript(file="/var/fisher/rcomp/tmp/6vq471353255341.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 -313.7533193 NA
1 -144.1458473 -313.7533193
2 -26.8625980 -144.1458473
3 238.3968988 -26.8625980
4 -145.1127521 238.3968988
5 -17.4515686 -145.1127521
6 356.3940443 -17.4515686
7 -20.8810829 356.3940443
8 -59.6622589 -20.8810829
9 142.7651222 -59.6622589
10 -32.6719914 142.7651222
11 -77.9039142 -32.6719914
12 -108.9120233 -77.9039142
13 64.1202176 -108.9120233
14 53.0445253 64.1202176
15 -90.5133212 53.0445253
16 339.7484291 -90.5133212
17 -138.2534885 339.7484291
18 66.4110539 -138.2534885
19 -83.3541137 66.4110539
20 -128.3961755 -83.3541137
21 -71.8772561 -128.3961755
22 -89.7961456 -71.8772561
23 -122.5112940 -89.7961456
24 -51.3867321 -122.5112940
25 245.7396487 -51.3867321
26 208.0446121 245.7396487
27 101.9488071 208.0446121
28 -207.7358503 101.9488071
29 65.8848113 -207.7358503
30 -85.5693596 65.8848113
31 -19.6198881 -85.5693596
32 18.9847130 -19.6198881
33 -162.7588361 18.9847130
34 -13.5779723 -162.7588361
35 67.3067751 -13.5779723
36 -125.2994362 67.3067751
37 151.9395895 -125.2994362
38 -31.0417727 151.9395895
39 -16.0865446 -31.0417727
40 -51.2464603 -16.0865446
41 -110.2283769 -51.2464603
42 28.1887252 -110.2283769
43 69.0567465 28.1887252
44 384.7376727 69.0567465
45 31.8149428 384.7376727
46 235.1322884 31.8149428
47 -19.7957566 235.1322884
48 -35.1699286 -19.7957566
49 553.9840768 -35.1699286
50 -185.7834234 553.9840768
51 52.5353873 -185.7834234
52 -31.7417235 52.5353873
53 212.3446825 -31.7417235
54 224.8692909 212.3446825
55 -87.6799459 224.8692909
56 69.5264880 -87.6799459
57 -346.2792057 69.5264880
58 15.8995432 -346.2792057
59 25.8907836 15.8995432
60 121.4778479 25.8907836
61 -192.6633018 121.4778479
62 4.7639519 -192.6633018
63 -14.7037365 4.7639519
64 -117.0819236 -14.7037365
65 -43.1056292 -117.0819236
66 -78.9551803 -43.1056292
67 45.1093825 -78.9551803
68 -16.7174286 45.1093825
69 260.0809444 -16.7174286
70 57.0970482 260.0809444
71 -86.9210041 57.0970482
72 -193.4613704 -86.9210041
73 -67.3534682 -193.4613704
74 32.6264289 -67.3534682
75 6.1494309 32.6264289
76 -66.5448800 6.1494309
77 41.5756944 -66.5448800
78 107.9782200 41.5756944
79 -29.0417843 107.9782200
80 40.3931309 -29.0417843
81 -25.6649216 40.3931309
82 -90.9754158 -25.6649216
83 -16.4550972 -90.9754158
84 -175.1136232 -16.4550972
85 -41.6174035 -175.1136232
86 48.9717088 -41.6174035
87 113.8449163 48.9717088
88 -98.3496104 113.8449163
89 163.0625444 -98.3496104
90 -174.3840700 163.0625444
91 97.3880720 -174.3840700
92 201.0074335 97.3880720
93 -176.0778714 201.0074335
94 -134.6582351 -176.0778714
95 39.3688934 -134.6582351
96 -0.1417016 39.3688934
97 324.3777117 -0.1417016
98 14.6103866 324.3777117
99 -145.9809338 14.6103866
100 -34.6578271 -145.9809338
101 166.5103944 -34.6578271
102 -26.1391153 166.5103944
103 -45.0959146 -26.1391153
104 -131.5346816 -45.0959146
105 -148.8262345 -131.5346816
106 15.6198208 -148.8262345
107 16.3242886 15.6198208
108 58.2695506 16.3242886
109 -67.2837063 58.2695506
110 -65.5922943 -67.2837063
111 -36.6788687 -65.5922943
112 26.7493562 -36.6788687
113 0.3509172 26.7493562
114 -0.2198910 0.3509172
115 198.9021884 -0.2198910
116 14.3016025 198.9021884
117 -54.4520346 14.3016025
118 -42.8232664 -54.4520346
119 43.6155875 -42.8232664
120 1.7893474 43.6155875
121 151.2971349 1.7893474
122 43.9726928 151.2971349
123 -4.2778669 43.9726928
124 -208.4829390 -4.2778669
125 -94.7448047 -208.4829390
126 -51.0390256 -94.7448047
127 -92.4809943 -51.0390256
128 -179.9389265 -92.4809943
129 12.2750077 -179.9389265
130 4.7274997 12.2750077
131 43.5247060 4.7274997
132 -72.7843851 43.5247060
133 185.0616386 -72.7843851
134 -57.4667817 185.0616386
135 -19.2837959 -57.4667817
136 19.3281219 -19.2837959
137 24.0596336 19.3281219
138 46.4384782 24.0596336
139 37.6383508 46.4384782
140 68.1975035 37.6383508
141 -7.2182538 68.1975035
142 19.9488327 -7.2182538
143 69.3771834 19.9488327
144 -43.8441891 69.3771834
145 52.5259327 -43.8441891
146 -86.1838602 52.5259327
147 96.4697605 -86.1838602
148 56.2330943 96.4697605
149 14.7441903 56.2330943
150 -24.3234053 14.7441903
151 -77.0685113 -24.3234053
152 61.5742350 -77.0685113
153 176.3247655 61.5742350
154 -172.5789213 176.3247655
155 -88.8113700 -172.5789213
156 -66.8220582 -88.8113700
157 -57.4085834 -66.8220582
158 82.2705631 -57.4085834
159 -183.8271511 82.2705631
160 108.4213776 -183.8271511
161 22.8334989 108.4213776
162 -34.7734731 22.8334989
163 324.6122599 -34.7734731
164 141.7894777 324.6122599
165 -173.3832457 141.7894777
166 -49.7081604 -173.3832457
167 -21.2947965 -49.7081604
168 -189.8671151 -21.2947965
169 -129.2504875 -189.8671151
170 344.2418350 -129.2504875
171 -102.2654373 344.2418350
172 157.9036008 -102.2654373
173 -110.8254654 157.9036008
174 -31.3090386 -110.8254654
175 193.3612418 -31.3090386
176 215.8794340 193.3612418
177 -13.4231906 215.8794340
178 -130.4200050 -13.4231906
179 -107.7088968 -130.4200050
180 48.7818413 -107.7088968
181 98.2461353 48.7818413
182 -19.8173805 98.2461353
183 3.1118006 -19.8173805
184 -75.2415022 3.1118006
185 -12.6750831 -75.2415022
186 69.8209457 -12.6750831
187 -34.5655795 69.8209457
188 71.3124119 -34.5655795
189 -74.7014792 71.3124119
190 -45.9880371 -74.7014792
191 138.6031378 -45.9880371
192 -22.4391825 138.6031378
193 -164.9095961 -22.4391825
194 32.4923993 -164.9095961
195 -41.7709211 32.4923993
196 128.3250307 -41.7709211
197 -14.8098647 128.3250307
198 184.6811755 -14.8098647
199 -29.9151840 184.6811755
200 -83.0162776 -29.9151840
201 -31.4419054 -83.0162776
202 -41.1024403 -31.4419054
203 -43.8208384 -41.1024403
204 150.6702233 -43.8208384
205 22.5452805 150.6702233
206 -27.4823956 22.5452805
207 8.3629066 -27.4823956
208 -29.5025152 8.3629066
209 41.8671443 -29.5025152
210 -20.9511140 41.8671443
211 -76.9851274 -20.9511140
212 -31.2730142 -76.9851274
213 -48.6032351 -31.2730142
214 163.7333456 -48.6032351
215 14.7247800 163.7333456
216 107.0521281 14.7247800
217 -74.5052347 107.0521281
218 -41.6516277 -74.5052347
219 -51.6786325 -41.6516277
220 80.2998999 -51.6786325
221 -22.8143825 80.2998999
222 138.4150542 -22.8143825
223 -59.5944571 138.4150542
224 -27.8178261 -59.5944571
225 -22.3208783 -27.8178261
226 -92.3653699 -22.3208783
227 34.0451691 -92.3653699
228 25.1425611 34.0451691
229 120.0476335 25.1425611
230 27.3132857 120.0476335
231 -34.7828881 27.3132857
232 160.5590991 -34.7828881
233 -2.9404288 160.5590991
234 53.4688409 -2.9404288
235 -77.0403053 53.4688409
236 -40.6980352 -77.0403053
237 15.0489898 -40.6980352
238 36.0270755 15.0489898
239 39.5479204 36.0270755
240 -4.4675654 39.5479204
241 -164.1072904 -4.4675654
242 -75.1077023 -164.1072904
243 -11.1762979 -75.1077023
244 -9.2011500 -11.1762979
245 79.8116232 -9.2011500
246 43.6723308 79.8116232
247 -65.6576730 43.6723308
248 -15.5340183 -65.6576730
249 63.4646865 -15.5340183
250 -37.6904451 63.4646865
251 -96.0118066 -37.6904451
252 -74.2565877 -96.0118066
253 -0.5091748 -74.2565877
254 161.3356241 -0.5091748
255 26.9398476 161.3356241
256 11.2918632 26.9398476
257 -50.8736267 11.2918632
258 -90.7664755 -50.8736267
259 -77.7835221 -90.7664755
260 49.0931369 -77.7835221
261 -163.1892719 49.0931369
262 -27.7989953 -163.1892719
263 -28.8976666 -27.7989953
264 1.5655156 -28.8976666
265 -35.5491570 1.5655156
266 -11.2635173 -35.5491570
267 -51.6039898 -11.2635173
268 -166.5621378 -51.6039898
269 24.6811471 -166.5621378
270 11.2344484 24.6811471
271 -32.3593249 11.2344484
272 38.3387978 -32.3593249
273 -79.4682186 38.3387978
274 -62.8007966 -79.4682186
275 12.4045767 -62.8007966
276 -55.6184522 12.4045767
277 -70.7958747 -55.6184522
278 14.3128697 -70.7958747
279 -23.7699563 14.3128697
280 -0.6325955 -23.7699563
281 -6.0624453 -0.6325955
282 95.4292439 -6.0624453
283 -23.3802616 95.4292439
284 14.3318793 -23.3802616
285 -9.2892624 14.3318793
286 4.6304646 -9.2892624
287 -86.3766408 4.6304646
288 74.0895651 -86.3766408
289 NA 74.0895651
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -144.1458473 -313.7533193
[2,] -26.8625980 -144.1458473
[3,] 238.3968988 -26.8625980
[4,] -145.1127521 238.3968988
[5,] -17.4515686 -145.1127521
[6,] 356.3940443 -17.4515686
[7,] -20.8810829 356.3940443
[8,] -59.6622589 -20.8810829
[9,] 142.7651222 -59.6622589
[10,] -32.6719914 142.7651222
[11,] -77.9039142 -32.6719914
[12,] -108.9120233 -77.9039142
[13,] 64.1202176 -108.9120233
[14,] 53.0445253 64.1202176
[15,] -90.5133212 53.0445253
[16,] 339.7484291 -90.5133212
[17,] -138.2534885 339.7484291
[18,] 66.4110539 -138.2534885
[19,] -83.3541137 66.4110539
[20,] -128.3961755 -83.3541137
[21,] -71.8772561 -128.3961755
[22,] -89.7961456 -71.8772561
[23,] -122.5112940 -89.7961456
[24,] -51.3867321 -122.5112940
[25,] 245.7396487 -51.3867321
[26,] 208.0446121 245.7396487
[27,] 101.9488071 208.0446121
[28,] -207.7358503 101.9488071
[29,] 65.8848113 -207.7358503
[30,] -85.5693596 65.8848113
[31,] -19.6198881 -85.5693596
[32,] 18.9847130 -19.6198881
[33,] -162.7588361 18.9847130
[34,] -13.5779723 -162.7588361
[35,] 67.3067751 -13.5779723
[36,] -125.2994362 67.3067751
[37,] 151.9395895 -125.2994362
[38,] -31.0417727 151.9395895
[39,] -16.0865446 -31.0417727
[40,] -51.2464603 -16.0865446
[41,] -110.2283769 -51.2464603
[42,] 28.1887252 -110.2283769
[43,] 69.0567465 28.1887252
[44,] 384.7376727 69.0567465
[45,] 31.8149428 384.7376727
[46,] 235.1322884 31.8149428
[47,] -19.7957566 235.1322884
[48,] -35.1699286 -19.7957566
[49,] 553.9840768 -35.1699286
[50,] -185.7834234 553.9840768
[51,] 52.5353873 -185.7834234
[52,] -31.7417235 52.5353873
[53,] 212.3446825 -31.7417235
[54,] 224.8692909 212.3446825
[55,] -87.6799459 224.8692909
[56,] 69.5264880 -87.6799459
[57,] -346.2792057 69.5264880
[58,] 15.8995432 -346.2792057
[59,] 25.8907836 15.8995432
[60,] 121.4778479 25.8907836
[61,] -192.6633018 121.4778479
[62,] 4.7639519 -192.6633018
[63,] -14.7037365 4.7639519
[64,] -117.0819236 -14.7037365
[65,] -43.1056292 -117.0819236
[66,] -78.9551803 -43.1056292
[67,] 45.1093825 -78.9551803
[68,] -16.7174286 45.1093825
[69,] 260.0809444 -16.7174286
[70,] 57.0970482 260.0809444
[71,] -86.9210041 57.0970482
[72,] -193.4613704 -86.9210041
[73,] -67.3534682 -193.4613704
[74,] 32.6264289 -67.3534682
[75,] 6.1494309 32.6264289
[76,] -66.5448800 6.1494309
[77,] 41.5756944 -66.5448800
[78,] 107.9782200 41.5756944
[79,] -29.0417843 107.9782200
[80,] 40.3931309 -29.0417843
[81,] -25.6649216 40.3931309
[82,] -90.9754158 -25.6649216
[83,] -16.4550972 -90.9754158
[84,] -175.1136232 -16.4550972
[85,] -41.6174035 -175.1136232
[86,] 48.9717088 -41.6174035
[87,] 113.8449163 48.9717088
[88,] -98.3496104 113.8449163
[89,] 163.0625444 -98.3496104
[90,] -174.3840700 163.0625444
[91,] 97.3880720 -174.3840700
[92,] 201.0074335 97.3880720
[93,] -176.0778714 201.0074335
[94,] -134.6582351 -176.0778714
[95,] 39.3688934 -134.6582351
[96,] -0.1417016 39.3688934
[97,] 324.3777117 -0.1417016
[98,] 14.6103866 324.3777117
[99,] -145.9809338 14.6103866
[100,] -34.6578271 -145.9809338
[101,] 166.5103944 -34.6578271
[102,] -26.1391153 166.5103944
[103,] -45.0959146 -26.1391153
[104,] -131.5346816 -45.0959146
[105,] -148.8262345 -131.5346816
[106,] 15.6198208 -148.8262345
[107,] 16.3242886 15.6198208
[108,] 58.2695506 16.3242886
[109,] -67.2837063 58.2695506
[110,] -65.5922943 -67.2837063
[111,] -36.6788687 -65.5922943
[112,] 26.7493562 -36.6788687
[113,] 0.3509172 26.7493562
[114,] -0.2198910 0.3509172
[115,] 198.9021884 -0.2198910
[116,] 14.3016025 198.9021884
[117,] -54.4520346 14.3016025
[118,] -42.8232664 -54.4520346
[119,] 43.6155875 -42.8232664
[120,] 1.7893474 43.6155875
[121,] 151.2971349 1.7893474
[122,] 43.9726928 151.2971349
[123,] -4.2778669 43.9726928
[124,] -208.4829390 -4.2778669
[125,] -94.7448047 -208.4829390
[126,] -51.0390256 -94.7448047
[127,] -92.4809943 -51.0390256
[128,] -179.9389265 -92.4809943
[129,] 12.2750077 -179.9389265
[130,] 4.7274997 12.2750077
[131,] 43.5247060 4.7274997
[132,] -72.7843851 43.5247060
[133,] 185.0616386 -72.7843851
[134,] -57.4667817 185.0616386
[135,] -19.2837959 -57.4667817
[136,] 19.3281219 -19.2837959
[137,] 24.0596336 19.3281219
[138,] 46.4384782 24.0596336
[139,] 37.6383508 46.4384782
[140,] 68.1975035 37.6383508
[141,] -7.2182538 68.1975035
[142,] 19.9488327 -7.2182538
[143,] 69.3771834 19.9488327
[144,] -43.8441891 69.3771834
[145,] 52.5259327 -43.8441891
[146,] -86.1838602 52.5259327
[147,] 96.4697605 -86.1838602
[148,] 56.2330943 96.4697605
[149,] 14.7441903 56.2330943
[150,] -24.3234053 14.7441903
[151,] -77.0685113 -24.3234053
[152,] 61.5742350 -77.0685113
[153,] 176.3247655 61.5742350
[154,] -172.5789213 176.3247655
[155,] -88.8113700 -172.5789213
[156,] -66.8220582 -88.8113700
[157,] -57.4085834 -66.8220582
[158,] 82.2705631 -57.4085834
[159,] -183.8271511 82.2705631
[160,] 108.4213776 -183.8271511
[161,] 22.8334989 108.4213776
[162,] -34.7734731 22.8334989
[163,] 324.6122599 -34.7734731
[164,] 141.7894777 324.6122599
[165,] -173.3832457 141.7894777
[166,] -49.7081604 -173.3832457
[167,] -21.2947965 -49.7081604
[168,] -189.8671151 -21.2947965
[169,] -129.2504875 -189.8671151
[170,] 344.2418350 -129.2504875
[171,] -102.2654373 344.2418350
[172,] 157.9036008 -102.2654373
[173,] -110.8254654 157.9036008
[174,] -31.3090386 -110.8254654
[175,] 193.3612418 -31.3090386
[176,] 215.8794340 193.3612418
[177,] -13.4231906 215.8794340
[178,] -130.4200050 -13.4231906
[179,] -107.7088968 -130.4200050
[180,] 48.7818413 -107.7088968
[181,] 98.2461353 48.7818413
[182,] -19.8173805 98.2461353
[183,] 3.1118006 -19.8173805
[184,] -75.2415022 3.1118006
[185,] -12.6750831 -75.2415022
[186,] 69.8209457 -12.6750831
[187,] -34.5655795 69.8209457
[188,] 71.3124119 -34.5655795
[189,] -74.7014792 71.3124119
[190,] -45.9880371 -74.7014792
[191,] 138.6031378 -45.9880371
[192,] -22.4391825 138.6031378
[193,] -164.9095961 -22.4391825
[194,] 32.4923993 -164.9095961
[195,] -41.7709211 32.4923993
[196,] 128.3250307 -41.7709211
[197,] -14.8098647 128.3250307
[198,] 184.6811755 -14.8098647
[199,] -29.9151840 184.6811755
[200,] -83.0162776 -29.9151840
[201,] -31.4419054 -83.0162776
[202,] -41.1024403 -31.4419054
[203,] -43.8208384 -41.1024403
[204,] 150.6702233 -43.8208384
[205,] 22.5452805 150.6702233
[206,] -27.4823956 22.5452805
[207,] 8.3629066 -27.4823956
[208,] -29.5025152 8.3629066
[209,] 41.8671443 -29.5025152
[210,] -20.9511140 41.8671443
[211,] -76.9851274 -20.9511140
[212,] -31.2730142 -76.9851274
[213,] -48.6032351 -31.2730142
[214,] 163.7333456 -48.6032351
[215,] 14.7247800 163.7333456
[216,] 107.0521281 14.7247800
[217,] -74.5052347 107.0521281
[218,] -41.6516277 -74.5052347
[219,] -51.6786325 -41.6516277
[220,] 80.2998999 -51.6786325
[221,] -22.8143825 80.2998999
[222,] 138.4150542 -22.8143825
[223,] -59.5944571 138.4150542
[224,] -27.8178261 -59.5944571
[225,] -22.3208783 -27.8178261
[226,] -92.3653699 -22.3208783
[227,] 34.0451691 -92.3653699
[228,] 25.1425611 34.0451691
[229,] 120.0476335 25.1425611
[230,] 27.3132857 120.0476335
[231,] -34.7828881 27.3132857
[232,] 160.5590991 -34.7828881
[233,] -2.9404288 160.5590991
[234,] 53.4688409 -2.9404288
[235,] -77.0403053 53.4688409
[236,] -40.6980352 -77.0403053
[237,] 15.0489898 -40.6980352
[238,] 36.0270755 15.0489898
[239,] 39.5479204 36.0270755
[240,] -4.4675654 39.5479204
[241,] -164.1072904 -4.4675654
[242,] -75.1077023 -164.1072904
[243,] -11.1762979 -75.1077023
[244,] -9.2011500 -11.1762979
[245,] 79.8116232 -9.2011500
[246,] 43.6723308 79.8116232
[247,] -65.6576730 43.6723308
[248,] -15.5340183 -65.6576730
[249,] 63.4646865 -15.5340183
[250,] -37.6904451 63.4646865
[251,] -96.0118066 -37.6904451
[252,] -74.2565877 -96.0118066
[253,] -0.5091748 -74.2565877
[254,] 161.3356241 -0.5091748
[255,] 26.9398476 161.3356241
[256,] 11.2918632 26.9398476
[257,] -50.8736267 11.2918632
[258,] -90.7664755 -50.8736267
[259,] -77.7835221 -90.7664755
[260,] 49.0931369 -77.7835221
[261,] -163.1892719 49.0931369
[262,] -27.7989953 -163.1892719
[263,] -28.8976666 -27.7989953
[264,] 1.5655156 -28.8976666
[265,] -35.5491570 1.5655156
[266,] -11.2635173 -35.5491570
[267,] -51.6039898 -11.2635173
[268,] -166.5621378 -51.6039898
[269,] 24.6811471 -166.5621378
[270,] 11.2344484 24.6811471
[271,] -32.3593249 11.2344484
[272,] 38.3387978 -32.3593249
[273,] -79.4682186 38.3387978
[274,] -62.8007966 -79.4682186
[275,] 12.4045767 -62.8007966
[276,] -55.6184522 12.4045767
[277,] -70.7958747 -55.6184522
[278,] 14.3128697 -70.7958747
[279,] -23.7699563 14.3128697
[280,] -0.6325955 -23.7699563
[281,] -6.0624453 -0.6325955
[282,] 95.4292439 -6.0624453
[283,] -23.3802616 95.4292439
[284,] 14.3318793 -23.3802616
[285,] -9.2892624 14.3318793
[286,] 4.6304646 -9.2892624
[287,] -86.3766408 4.6304646
[288,] 74.0895651 -86.3766408
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -144.1458473 -313.7533193
2 -26.8625980 -144.1458473
3 238.3968988 -26.8625980
4 -145.1127521 238.3968988
5 -17.4515686 -145.1127521
6 356.3940443 -17.4515686
7 -20.8810829 356.3940443
8 -59.6622589 -20.8810829
9 142.7651222 -59.6622589
10 -32.6719914 142.7651222
11 -77.9039142 -32.6719914
12 -108.9120233 -77.9039142
13 64.1202176 -108.9120233
14 53.0445253 64.1202176
15 -90.5133212 53.0445253
16 339.7484291 -90.5133212
17 -138.2534885 339.7484291
18 66.4110539 -138.2534885
19 -83.3541137 66.4110539
20 -128.3961755 -83.3541137
21 -71.8772561 -128.3961755
22 -89.7961456 -71.8772561
23 -122.5112940 -89.7961456
24 -51.3867321 -122.5112940
25 245.7396487 -51.3867321
26 208.0446121 245.7396487
27 101.9488071 208.0446121
28 -207.7358503 101.9488071
29 65.8848113 -207.7358503
30 -85.5693596 65.8848113
31 -19.6198881 -85.5693596
32 18.9847130 -19.6198881
33 -162.7588361 18.9847130
34 -13.5779723 -162.7588361
35 67.3067751 -13.5779723
36 -125.2994362 67.3067751
37 151.9395895 -125.2994362
38 -31.0417727 151.9395895
39 -16.0865446 -31.0417727
40 -51.2464603 -16.0865446
41 -110.2283769 -51.2464603
42 28.1887252 -110.2283769
43 69.0567465 28.1887252
44 384.7376727 69.0567465
45 31.8149428 384.7376727
46 235.1322884 31.8149428
47 -19.7957566 235.1322884
48 -35.1699286 -19.7957566
49 553.9840768 -35.1699286
50 -185.7834234 553.9840768
51 52.5353873 -185.7834234
52 -31.7417235 52.5353873
53 212.3446825 -31.7417235
54 224.8692909 212.3446825
55 -87.6799459 224.8692909
56 69.5264880 -87.6799459
57 -346.2792057 69.5264880
58 15.8995432 -346.2792057
59 25.8907836 15.8995432
60 121.4778479 25.8907836
61 -192.6633018 121.4778479
62 4.7639519 -192.6633018
63 -14.7037365 4.7639519
64 -117.0819236 -14.7037365
65 -43.1056292 -117.0819236
66 -78.9551803 -43.1056292
67 45.1093825 -78.9551803
68 -16.7174286 45.1093825
69 260.0809444 -16.7174286
70 57.0970482 260.0809444
71 -86.9210041 57.0970482
72 -193.4613704 -86.9210041
73 -67.3534682 -193.4613704
74 32.6264289 -67.3534682
75 6.1494309 32.6264289
76 -66.5448800 6.1494309
77 41.5756944 -66.5448800
78 107.9782200 41.5756944
79 -29.0417843 107.9782200
80 40.3931309 -29.0417843
81 -25.6649216 40.3931309
82 -90.9754158 -25.6649216
83 -16.4550972 -90.9754158
84 -175.1136232 -16.4550972
85 -41.6174035 -175.1136232
86 48.9717088 -41.6174035
87 113.8449163 48.9717088
88 -98.3496104 113.8449163
89 163.0625444 -98.3496104
90 -174.3840700 163.0625444
91 97.3880720 -174.3840700
92 201.0074335 97.3880720
93 -176.0778714 201.0074335
94 -134.6582351 -176.0778714
95 39.3688934 -134.6582351
96 -0.1417016 39.3688934
97 324.3777117 -0.1417016
98 14.6103866 324.3777117
99 -145.9809338 14.6103866
100 -34.6578271 -145.9809338
101 166.5103944 -34.6578271
102 -26.1391153 166.5103944
103 -45.0959146 -26.1391153
104 -131.5346816 -45.0959146
105 -148.8262345 -131.5346816
106 15.6198208 -148.8262345
107 16.3242886 15.6198208
108 58.2695506 16.3242886
109 -67.2837063 58.2695506
110 -65.5922943 -67.2837063
111 -36.6788687 -65.5922943
112 26.7493562 -36.6788687
113 0.3509172 26.7493562
114 -0.2198910 0.3509172
115 198.9021884 -0.2198910
116 14.3016025 198.9021884
117 -54.4520346 14.3016025
118 -42.8232664 -54.4520346
119 43.6155875 -42.8232664
120 1.7893474 43.6155875
121 151.2971349 1.7893474
122 43.9726928 151.2971349
123 -4.2778669 43.9726928
124 -208.4829390 -4.2778669
125 -94.7448047 -208.4829390
126 -51.0390256 -94.7448047
127 -92.4809943 -51.0390256
128 -179.9389265 -92.4809943
129 12.2750077 -179.9389265
130 4.7274997 12.2750077
131 43.5247060 4.7274997
132 -72.7843851 43.5247060
133 185.0616386 -72.7843851
134 -57.4667817 185.0616386
135 -19.2837959 -57.4667817
136 19.3281219 -19.2837959
137 24.0596336 19.3281219
138 46.4384782 24.0596336
139 37.6383508 46.4384782
140 68.1975035 37.6383508
141 -7.2182538 68.1975035
142 19.9488327 -7.2182538
143 69.3771834 19.9488327
144 -43.8441891 69.3771834
145 52.5259327 -43.8441891
146 -86.1838602 52.5259327
147 96.4697605 -86.1838602
148 56.2330943 96.4697605
149 14.7441903 56.2330943
150 -24.3234053 14.7441903
151 -77.0685113 -24.3234053
152 61.5742350 -77.0685113
153 176.3247655 61.5742350
154 -172.5789213 176.3247655
155 -88.8113700 -172.5789213
156 -66.8220582 -88.8113700
157 -57.4085834 -66.8220582
158 82.2705631 -57.4085834
159 -183.8271511 82.2705631
160 108.4213776 -183.8271511
161 22.8334989 108.4213776
162 -34.7734731 22.8334989
163 324.6122599 -34.7734731
164 141.7894777 324.6122599
165 -173.3832457 141.7894777
166 -49.7081604 -173.3832457
167 -21.2947965 -49.7081604
168 -189.8671151 -21.2947965
169 -129.2504875 -189.8671151
170 344.2418350 -129.2504875
171 -102.2654373 344.2418350
172 157.9036008 -102.2654373
173 -110.8254654 157.9036008
174 -31.3090386 -110.8254654
175 193.3612418 -31.3090386
176 215.8794340 193.3612418
177 -13.4231906 215.8794340
178 -130.4200050 -13.4231906
179 -107.7088968 -130.4200050
180 48.7818413 -107.7088968
181 98.2461353 48.7818413
182 -19.8173805 98.2461353
183 3.1118006 -19.8173805
184 -75.2415022 3.1118006
185 -12.6750831 -75.2415022
186 69.8209457 -12.6750831
187 -34.5655795 69.8209457
188 71.3124119 -34.5655795
189 -74.7014792 71.3124119
190 -45.9880371 -74.7014792
191 138.6031378 -45.9880371
192 -22.4391825 138.6031378
193 -164.9095961 -22.4391825
194 32.4923993 -164.9095961
195 -41.7709211 32.4923993
196 128.3250307 -41.7709211
197 -14.8098647 128.3250307
198 184.6811755 -14.8098647
199 -29.9151840 184.6811755
200 -83.0162776 -29.9151840
201 -31.4419054 -83.0162776
202 -41.1024403 -31.4419054
203 -43.8208384 -41.1024403
204 150.6702233 -43.8208384
205 22.5452805 150.6702233
206 -27.4823956 22.5452805
207 8.3629066 -27.4823956
208 -29.5025152 8.3629066
209 41.8671443 -29.5025152
210 -20.9511140 41.8671443
211 -76.9851274 -20.9511140
212 -31.2730142 -76.9851274
213 -48.6032351 -31.2730142
214 163.7333456 -48.6032351
215 14.7247800 163.7333456
216 107.0521281 14.7247800
217 -74.5052347 107.0521281
218 -41.6516277 -74.5052347
219 -51.6786325 -41.6516277
220 80.2998999 -51.6786325
221 -22.8143825 80.2998999
222 138.4150542 -22.8143825
223 -59.5944571 138.4150542
224 -27.8178261 -59.5944571
225 -22.3208783 -27.8178261
226 -92.3653699 -22.3208783
227 34.0451691 -92.3653699
228 25.1425611 34.0451691
229 120.0476335 25.1425611
230 27.3132857 120.0476335
231 -34.7828881 27.3132857
232 160.5590991 -34.7828881
233 -2.9404288 160.5590991
234 53.4688409 -2.9404288
235 -77.0403053 53.4688409
236 -40.6980352 -77.0403053
237 15.0489898 -40.6980352
238 36.0270755 15.0489898
239 39.5479204 36.0270755
240 -4.4675654 39.5479204
241 -164.1072904 -4.4675654
242 -75.1077023 -164.1072904
243 -11.1762979 -75.1077023
244 -9.2011500 -11.1762979
245 79.8116232 -9.2011500
246 43.6723308 79.8116232
247 -65.6576730 43.6723308
248 -15.5340183 -65.6576730
249 63.4646865 -15.5340183
250 -37.6904451 63.4646865
251 -96.0118066 -37.6904451
252 -74.2565877 -96.0118066
253 -0.5091748 -74.2565877
254 161.3356241 -0.5091748
255 26.9398476 161.3356241
256 11.2918632 26.9398476
257 -50.8736267 11.2918632
258 -90.7664755 -50.8736267
259 -77.7835221 -90.7664755
260 49.0931369 -77.7835221
261 -163.1892719 49.0931369
262 -27.7989953 -163.1892719
263 -28.8976666 -27.7989953
264 1.5655156 -28.8976666
265 -35.5491570 1.5655156
266 -11.2635173 -35.5491570
267 -51.6039898 -11.2635173
268 -166.5621378 -51.6039898
269 24.6811471 -166.5621378
270 11.2344484 24.6811471
271 -32.3593249 11.2344484
272 38.3387978 -32.3593249
273 -79.4682186 38.3387978
274 -62.8007966 -79.4682186
275 12.4045767 -62.8007966
276 -55.6184522 12.4045767
277 -70.7958747 -55.6184522
278 14.3128697 -70.7958747
279 -23.7699563 14.3128697
280 -0.6325955 -23.7699563
281 -6.0624453 -0.6325955
282 95.4292439 -6.0624453
283 -23.3802616 95.4292439
284 14.3318793 -23.3802616
285 -9.2892624 14.3318793
286 4.6304646 -9.2892624
287 -86.3766408 4.6304646
288 74.0895651 -86.3766408
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/7ja3e1353255341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/81kv61353255341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/93oqv1353255341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10hn9y1353255341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/11iyrp1353255341.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/12nycm1353255341.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/13kkmz1353255341.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/14osqb1353255341.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/158yx01353255341.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/162jcc1353255341.tab")
+ }
>
> try(system("convert tmp/1kuhp1353255341.ps tmp/1kuhp1353255341.png",intern=TRUE))
character(0)
> try(system("convert tmp/26ult1353255341.ps tmp/26ult1353255341.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bdz51353255341.ps tmp/3bdz51353255341.png",intern=TRUE))
character(0)
> try(system("convert tmp/4td9l1353255341.ps tmp/4td9l1353255341.png",intern=TRUE))
character(0)
> try(system("convert tmp/5kmt81353255341.ps tmp/5kmt81353255341.png",intern=TRUE))
character(0)
> try(system("convert tmp/6vq471353255341.ps tmp/6vq471353255341.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ja3e1353255341.ps tmp/7ja3e1353255341.png",intern=TRUE))
character(0)
> try(system("convert tmp/81kv61353255341.ps tmp/81kv61353255341.png",intern=TRUE))
character(0)
> try(system("convert tmp/93oqv1353255341.ps tmp/93oqv1353255341.png",intern=TRUE))
character(0)
> try(system("convert tmp/10hn9y1353255341.ps tmp/10hn9y1353255341.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
12.142 1.354 13.496