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(1418
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+ ,894
+ ,72535
+ ,14
+ ,329
+ ,44
+ ,0
+ ,17
+ ,16
+ ,64
+ ,39)
+ ,dim=c(10
+ ,289)
+ ,dimnames=list(c('pageviews'
+ ,'time_in_rfc'
+ ,'logins'
+ ,'compendium_views_info'
+ ,'compendium_views_pr'
+ ,'shared_compendiums'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'feedback_messages_p1'
+ ,'feedback_messages_p120')
+ ,1:289))
> y <- array(NA,dim=c(10,289),dimnames=list(c('pageviews','time_in_rfc','logins','compendium_views_info','compendium_views_pr','shared_compendiums','blogged_computations','compendiums_reviewed','feedback_messages_p1','feedback_messages_p120'),1:289))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '2'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '2'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
time_in_rfc pageviews logins compendium_views_info compendium_views_pr
1 210907 1418 56 396 81
2 120982 869 56 297 55
3 176508 1530 54 559 50
4 179321 2172 89 967 125
5 123185 901 40 270 40
6 52746 463 25 143 37
7 385534 3201 92 1562 63
8 33170 371 18 109 44
9 101645 1192 63 371 88
10 149061 1583 44 656 66
11 165446 1439 33 511 57
12 237213 1764 84 655 74
13 173326 1495 88 465 49
14 133131 1373 55 525 52
15 258873 2187 60 885 88
16 180083 1491 66 497 36
17 324799 4041 154 1436 108
18 230964 1706 53 612 43
19 236785 2152 119 865 75
20 135473 1036 41 385 32
21 202925 1882 61 567 44
22 215147 1929 58 639 85
23 344297 2242 75 963 86
24 153935 1220 33 398 56
25 132943 1289 40 410 50
26 174724 2515 92 966 135
27 174415 2147 100 801 63
28 225548 2352 112 892 81
29 223632 1638 73 513 52
30 124817 1222 40 469 44
31 221698 1812 45 683 113
32 210767 1677 60 643 39
33 170266 1579 62 535 73
34 260561 1731 75 625 48
35 84853 807 31 264 33
36 294424 2452 77 992 59
37 101011 829 34 238 41
38 215641 1940 46 818 69
39 325107 2662 99 937 64
40 7176 186 17 70 1
41 167542 1499 66 507 59
42 106408 865 30 260 32
43 96560 1793 76 503 129
44 265769 2527 146 927 37
45 269651 2747 67 1269 31
46 149112 1324 56 537 65
47 175824 2702 107 910 107
48 152871 1383 58 532 74
49 111665 1179 34 345 54
50 116408 2099 61 918 76
51 362301 4308 119 1635 715
52 78800 918 42 330 57
53 183167 1831 66 557 66
54 277965 3373 89 1178 106
55 150629 1713 44 740 54
56 168809 1438 66 452 32
57 24188 496 24 218 20
58 329267 2253 259 764 71
59 65029 744 17 255 21
60 101097 1161 64 454 70
61 218946 2352 41 866 112
62 244052 2144 68 574 66
63 341570 4691 168 1276 190
64 103597 1112 43 379 66
65 233328 2694 132 825 165
66 256462 1973 105 798 56
67 206161 1769 71 663 61
68 311473 3148 112 1069 53
69 235800 2474 94 921 127
70 177939 2084 82 858 63
71 207176 1954 70 711 38
72 196553 1226 57 503 50
73 174184 1389 53 382 52
74 143246 1496 103 464 42
75 187559 2269 121 717 76
76 187681 1833 62 690 67
77 119016 1268 52 462 50
78 182192 1943 52 657 53
79 73566 893 32 385 39
80 194979 1762 62 577 50
81 167488 1403 45 619 77
82 143756 1425 46 479 57
83 275541 1857 63 817 73
84 243199 1840 75 752 34
85 182999 1502 88 430 39
86 135649 1441 46 451 46
87 152299 1420 53 537 63
88 120221 1416 37 519 35
89 346485 2970 90 1000 106
90 145790 1317 63 637 43
91 193339 1644 78 465 47
92 80953 870 25 437 31
93 122774 1654 45 711 162
94 130585 1054 46 299 57
95 112611 937 41 248 36
96 286468 3004 144 1162 263
97 241066 2008 82 714 78
98 148446 2547 91 905 63
99 204713 1885 71 649 54
100 182079 1626 63 512 63
101 140344 1468 53 472 77
102 220516 2445 62 905 79
103 243060 1964 63 786 110
104 162765 1381 32 489 56
105 182613 1369 39 479 56
106 232138 1659 62 617 43
107 265318 2888 117 925 111
108 85574 1290 34 351 71
109 310839 2845 92 1144 62
110 225060 1982 93 669 56
111 232317 1904 54 707 74
112 144966 1391 144 458 60
113 43287 602 14 214 43
114 155754 1743 61 599 68
115 164709 1559 109 572 53
116 201940 2014 38 897 87
117 235454 2143 73 819 46
118 220801 2146 75 720 105
119 99466 874 50 273 32
120 92661 1590 61 508 133
121 133328 1590 55 506 79
122 61361 1210 77 451 51
123 125930 2072 75 699 207
124 100750 1281 72 407 67
125 224549 1401 50 465 47
126 82316 834 32 245 34
127 102010 1105 53 370 66
128 101523 1272 42 316 76
129 243511 1944 71 603 65
130 22938 391 10 154 9
131 41566 761 35 229 42
132 152474 1605 65 577 45
133 61857 530 25 192 25
134 99923 1988 66 617 115
135 132487 1386 41 411 97
136 317394 2395 86 975 53
137 21054 387 16 146 2
138 209641 1742 42 705 52
139 22648 620 19 184 44
140 31414 449 19 200 22
141 46698 800 45 274 35
142 131698 1684 65 502 74
143 91735 1050 35 382 103
144 244749 2699 95 964 144
145 184510 1606 49 537 60
146 79863 1502 37 438 134
147 128423 1204 64 369 89
148 97839 1138 38 417 42
149 38214 568 34 276 52
150 151101 1459 32 514 98
151 272458 2158 65 822 99
152 172494 1111 52 389 52
153 108043 1421 62 466 29
154 328107 2833 65 1255 125
155 250579 1955 83 694 106
156 351067 2922 95 1024 95
157 158015 1002 29 400 40
158 98866 1060 18 397 140
159 85439 956 33 350 43
160 229242 2186 247 719 128
161 351619 3604 139 1277 142
162 84207 1035 29 356 73
163 120445 1417 118 457 72
164 324598 3261 110 1402 128
165 131069 1587 67 600 61
166 204271 1424 42 480 73
167 165543 1701 65 595 148
168 141722 1249 94 436 64
169 116048 946 64 230 45
170 250047 1926 81 651 58
171 299775 3352 95 1367 97
172 195838 1641 67 564 50
173 173260 2035 63 716 37
174 254488 2312 83 747 50
175 104389 1369 45 467 105
176 136084 1577 30 671 69
177 199476 2201 70 861 46
178 92499 961 32 319 57
179 224330 1900 83 612 52
180 135781 1254 31 433 98
181 74408 1335 67 434 61
182 81240 1597 66 503 89
183 14688 207 10 85 0
184 181633 1645 70 564 48
185 271856 2429 103 824 91
186 7199 151 5 74 0
187 46660 474 20 259 7
188 17547 141 5 69 3
189 133368 1639 36 535 54
190 95227 872 34 239 70
191 152601 1318 48 438 36
192 98146 1018 40 459 37
193 79619 1383 43 426 123
194 59194 1314 31 288 247
195 139942 1335 42 498 46
196 118612 1403 46 454 72
197 72880 910 33 376 41
198 65475 616 18 225 24
199 99643 1407 55 555 45
200 71965 771 35 252 33
201 77272 766 59 208 27
202 49289 473 19 130 36
203 135131 1376 66 481 87
204 108446 1232 60 389 90
205 89746 1521 36 565 114
206 44296 572 25 173 31
207 77648 1059 47 278 45
208 181528 1544 54 609 69
209 134019 1230 53 422 51
210 124064 1206 40 445 34
211 92630 1205 40 387 60
212 121848 1255 39 339 45
213 52915 613 14 181 54
214 81872 721 45 245 25
215 58981 1109 36 384 38
216 53515 740 28 212 52
217 60812 1126 44 399 67
218 56375 728 30 229 74
219 65490 689 22 224 38
220 80949 592 17 203 30
221 76302 995 31 333 26
222 104011 1613 55 384 67
223 98104 2048 54 636 132
224 67989 705 21 185 42
225 30989 301 14 93 35
226 135458 1803 81 581 118
227 73504 799 35 248 68
228 63123 861 43 304 43
229 61254 1186 46 344 76
230 74914 1451 30 407 64
231 31774 628 23 170 48
232 81437 1161 38 312 64
233 87186 1463 54 507 56
234 50090 742 20 224 71
235 65745 979 53 340 75
236 56653 675 45 168 39
237 158399 1241 39 443 42
238 46455 676 20 204 39
239 73624 1049 24 367 93
240 38395 620 31 210 38
241 91899 1081 35 335 60
242 139526 1688 151 364 71
243 52164 736 52 178 52
244 51567 617 30 206 27
245 70551 812 31 279 59
246 84856 1051 29 387 40
247 102538 1656 57 490 79
248 86678 705 40 238 44
249 85709 945 44 343 65
250 34662 554 25 232 10
251 150580 1597 77 530 124
252 99611 982 35 291 81
253 19349 222 11 67 15
254 99373 1212 63 397 92
255 86230 1143 44 467 42
256 30837 435 19 178 10
257 31706 532 13 175 24
258 89806 882 42 299 64
259 62088 608 38 154 45
260 40151 459 29 106 22
261 27634 578 20 189 56
262 76990 826 27 194 94
263 37460 509 20 135 19
264 54157 717 19 201 35
265 49862 637 37 207 32
266 84337 857 26 280 35
267 64175 830 42 260 48
268 59382 652 49 227 49
269 119308 707 30 239 48
270 76702 954 49 333 62
271 103425 1461 67 428 96
272 70344 672 28 230 45
273 43410 778 19 292 63
274 104838 1141 49 350 71
275 62215 680 27 186 26
276 69304 1090 30 326 48
277 53117 616 22 155 29
278 19764 285 12 75 19
279 86680 1145 31 361 45
280 84105 733 20 261 45
281 77945 888 20 299 67
282 89113 849 39 300 30
283 91005 1182 29 450 36
284 40248 528 16 183 34
285 64187 642 27 238 36
286 50857 947 21 165 34
287 56613 819 19 234 37
288 62792 757 35 176 46
289 72535 894 14 329 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
feedback_messages_p1 feedback_messages_p120
1 115 94
2 109 103
3 146 93
4 116 103
5 68 51
6 101 70
7 96 91
8 67 22
9 44 38
10 100 93
11 93 60
12 140 123
13 166 148
14 99 90
15 139 124
16 130 70
17 181 168
18 116 115
19 116 71
20 88 66
21 139 134
22 135 117
23 108 108
24 89 84
25 156 156
26 129 120
27 118 114
28 118 94
29 125 120
30 95 81
31 126 110
32 135 133
33 154 122
34 165 158
35 113 109
36 127 124
37 52 39
38 121 92
39 136 126
40 0 0
41 108 70
42 46 37
43 54 38
44 124 120
45 115 93
46 128 95
47 80 77
48 97 90
49 104 80
50 59 31
51 125 110
52 82 66
53 149 138
54 149 133
55 122 113
56 118 100
57 12 7
58 144 140
59 67 61
60 52 41
61 108 96
62 166 164
63 80 78
64 60 49
65 107 102
66 127 124
67 107 99
68 146 129
69 84 62
70 141 73
71 123 114
72 111 99
73 98 70
74 105 104
75 135 116
76 107 91
77 85 74
78 155 138
79 88 67
80 155 151
81 104 72
82 132 120
83 127 115
84 108 105
85 129 104
86 116 108
87 122 98
88 85 69
89 147 111
90 99 99
91 87 71
92 28 27
93 90 69
94 109 107
95 78 73
96 111 107
97 158 93
98 141 129
99 122 69
100 124 118
101 93 73
102 124 119
103 112 104
104 108 107
105 99 99
106 117 90
107 199 197
108 78 36
109 91 85
110 158 139
111 126 106
112 122 50
113 71 64
114 75 31
115 115 63
116 119 92
117 124 106
118 72 63
119 91 69
120 45 41
121 78 56
122 39 25
123 68 65
124 119 93
125 117 114
126 39 38
127 50 44
128 88 87
129 155 110
130 0 0
131 36 27
132 123 83
133 32 30
134 99 80
135 136 98
136 117 82
137 0 0
138 88 60
139 39 28
140 25 9
141 52 33
142 75 59
143 71 49
144 124 115
145 151 140
146 71 49
147 145 120
148 87 66
149 27 21
150 131 124
151 162 152
152 165 139
153 54 38
154 159 144
155 147 120
156 170 160
157 119 114
158 49 39
159 104 78
160 120 119
161 150 141
162 112 101
163 59 56
164 136 133
165 107 83
166 130 116
167 115 90
168 107 36
169 75 50
170 71 61
171 120 97
172 116 98
173 79 78
174 150 117
175 156 148
176 51 41
177 118 105
178 71 55
179 144 132
180 47 44
181 28 21
182 68 50
183 0 0
184 110 73
185 147 86
186 0 0
187 15 13
188 4 4
189 64 57
190 111 48
191 85 46
192 68 48
193 40 32
194 80 68
195 88 87
196 48 43
197 76 67
198 51 46
199 67 46
200 59 56
201 61 48
202 76 44
203 60 60
204 68 65
205 71 55
206 76 38
207 62 52
208 61 60
209 67 54
210 88 86
211 30 24
212 64 52
213 68 49
214 64 61
215 91 61
216 88 81
217 52 43
218 49 40
219 62 40
220 61 56
221 76 68
222 88 79
223 66 47
224 71 57
225 68 41
226 48 29
227 25 3
228 68 60
229 41 30
230 90 79
231 66 47
232 54 40
233 59 48
234 60 36
235 77 42
236 68 49
237 72 57
238 67 12
239 64 40
240 63 43
241 59 33
242 84 77
243 64 43
244 56 45
245 54 47
246 67 43
247 58 45
248 59 50
249 40 35
250 22 7
251 83 71
252 81 67
253 2 0
254 72 62
255 61 54
256 15 4
257 32 25
258 62 40
259 58 38
260 36 19
261 59 17
262 68 67
263 21 14
264 55 30
265 54 54
266 55 35
267 72 59
268 41 24
269 61 58
270 67 42
271 76 46
272 64 61
273 3 3
274 63 52
275 40 25
276 69 40
277 48 32
278 8 4
279 52 49
280 66 63
281 76 67
282 43 32
283 39 23
284 14 7
285 61 54
286 71 37
287 44 35
288 60 51
289 64 39
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) pageviews logins
-11651.90 12.07 269.81
compendium_views_info compendium_views_pr shared_compendiums
135.30 -85.70 -847.14
blogged_computations compendiums_reviewed feedback_messages_p1
392.07 -505.90 363.45
feedback_messages_p120
245.15
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-128484 -14028 1105 15056 104654
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -11651.90 4496.83 -2.591 0.010069 *
pageviews 12.07 10.38 1.163 0.245639
logins 269.81 77.51 3.481 0.000579 ***
compendium_views_info 135.30 22.02 6.145 2.75e-09 ***
compendium_views_pr -85.70 41.69 -2.056 0.040727 *
shared_compendiums -847.14 678.54 -1.248 0.212905
blogged_computations 392.07 90.80 4.318 2.19e-05 ***
compendiums_reviewed -505.90 889.06 -0.569 0.569795
feedback_messages_p1 363.45 270.01 1.346 0.179384
feedback_messages_p120 245.15 129.89 1.887 0.060144 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 27960 on 279 degrees of freedom
Multiple R-squared: 0.8883, Adjusted R-squared: 0.8847
F-statistic: 246.5 on 9 and 279 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,] 0.8578185 2.843630e-01 1.421815e-01
[2,] 0.7549924 4.900152e-01 2.450076e-01
[3,] 0.6571932 6.856136e-01 3.428068e-01
[4,] 0.5400857 9.198287e-01 4.599143e-01
[5,] 0.9590892 8.182155e-02 4.091077e-02
[6,] 0.9416718 1.166564e-01 5.832821e-02
[7,] 0.9334402 1.331195e-01 6.655975e-02
[8,] 0.9548502 9.029966e-02 4.514983e-02
[9,] 0.9400644 1.198713e-01 5.993565e-02
[10,] 0.9157969 1.684061e-01 8.420306e-02
[11,] 0.9985653 2.869461e-03 1.434730e-03
[12,] 0.9977703 4.459431e-03 2.229716e-03
[13,] 0.9973300 5.339928e-03 2.669964e-03
[14,] 0.9995051 9.897071e-04 4.948535e-04
[15,] 0.9997583 4.834795e-04 2.417397e-04
[16,] 0.9995874 8.251710e-04 4.125855e-04
[17,] 0.9995534 8.932669e-04 4.466334e-04
[18,] 0.9994749 1.050223e-03 5.251113e-04
[19,] 0.9994581 1.083785e-03 5.418925e-04
[20,] 0.9991154 1.769112e-03 8.845562e-04
[21,] 0.9986425 2.715051e-03 1.357525e-03
[22,] 0.9986910 2.618033e-03 1.309016e-03
[23,] 0.9987076 2.584722e-03 1.292361e-03
[24,] 0.9983686 3.262751e-03 1.631375e-03
[25,] 0.9977871 4.425776e-03 2.212888e-03
[26,] 0.9967693 6.461440e-03 3.230720e-03
[27,] 0.9990038 1.992347e-03 9.961733e-04
[28,] 0.9991717 1.656512e-03 8.282558e-04
[29,] 0.9988126 2.374843e-03 1.187421e-03
[30,] 0.9984605 3.078908e-03 1.539454e-03
[31,] 0.9980736 3.852888e-03 1.926444e-03
[32,] 0.9972210 5.558025e-03 2.779012e-03
[33,] 0.9979010 4.197953e-03 2.098976e-03
[34,] 0.9970604 5.879233e-03 2.939617e-03
[35,] 0.9969459 6.108249e-03 3.054125e-03
[36,] 0.9956929 8.614192e-03 4.307096e-03
[37,] 0.9942340 1.153195e-02 5.765977e-03
[38,] 0.9991317 1.736583e-03 8.682913e-04
[39,] 0.9999166 1.667681e-04 8.338403e-05
[40,] 0.9998846 2.307296e-04 1.153648e-04
[41,] 0.9998584 2.832769e-04 1.416385e-04
[42,] 0.9998395 3.209178e-04 1.604589e-04
[43,] 0.9999518 9.642799e-05 4.821399e-05
[44,] 0.9999267 1.466324e-04 7.331622e-05
[45,] 0.9999135 1.730764e-04 8.653818e-05
[46,] 0.9999791 4.181606e-05 2.090803e-05
[47,] 0.9999682 6.351763e-05 3.175881e-05
[48,] 0.9999552 8.957767e-05 4.478883e-05
[49,] 0.9999374 1.252377e-04 6.261886e-05
[50,] 0.9999376 1.248973e-04 6.244865e-05
[51,] 0.9999306 1.387024e-04 6.935118e-05
[52,] 0.9998976 2.048201e-04 1.024101e-04
[53,] 0.9998576 2.848644e-04 1.424322e-04
[54,] 0.9997919 4.161200e-04 2.080600e-04
[55,] 0.9997575 4.849838e-04 2.424919e-04
[56,] 0.9996564 6.871661e-04 3.435830e-04
[57,] 0.9995294 9.412480e-04 4.706240e-04
[58,] 0.9995528 8.943673e-04 4.471836e-04
[59,] 0.9993993 1.201344e-03 6.006719e-04
[60,] 0.9996539 6.922271e-04 3.461135e-04
[61,] 0.9997058 5.884217e-04 2.942108e-04
[62,] 0.9997017 5.965966e-04 2.982983e-04
[63,] 0.9997401 5.198078e-04 2.599039e-04
[64,] 0.9996848 6.303310e-04 3.151655e-04
[65,] 0.9997457 5.086653e-04 2.543327e-04
[66,] 0.9996800 6.399646e-04 3.199823e-04
[67,] 0.9996627 6.746107e-04 3.373053e-04
[68,] 0.9995253 9.493888e-04 4.746944e-04
[69,] 0.9993450 1.309910e-03 6.549552e-04
[70,] 0.9994530 1.094011e-03 5.470055e-04
[71,] 0.9996644 6.711128e-04 3.355564e-04
[72,] 0.9996649 6.701621e-04 3.350810e-04
[73,] 0.9995865 8.270004e-04 4.135002e-04
[74,] 0.9996021 7.958218e-04 3.979109e-04
[75,] 0.9994813 1.037372e-03 5.186858e-04
[76,] 0.9994015 1.196922e-03 5.984608e-04
[77,] 0.9998436 3.128744e-04 1.564372e-04
[78,] 0.9997990 4.019056e-04 2.009528e-04
[79,] 0.9998102 3.795322e-04 1.897661e-04
[80,] 0.9997576 4.847404e-04 2.423702e-04
[81,] 0.9997483 5.033053e-04 2.516526e-04
[82,] 0.9996589 6.822401e-04 3.411201e-04
[83,] 0.9995706 8.588460e-04 4.294230e-04
[84,] 0.9994949 1.010169e-03 5.050846e-04
[85,] 0.9994431 1.113801e-03 5.569004e-04
[86,] 0.9999997 5.714507e-07 2.857253e-07
[87,] 0.9999996 7.740789e-07 3.870394e-07
[88,] 0.9999994 1.128446e-06 5.642232e-07
[89,] 0.9999992 1.563957e-06 7.819786e-07
[90,] 0.9999992 1.623604e-06 8.118021e-07
[91,] 0.9999997 6.932251e-07 3.466126e-07
[92,] 0.9999995 1.024105e-06 5.120523e-07
[93,] 0.9999995 9.570695e-07 4.785348e-07
[94,] 0.9999995 1.028014e-06 5.140069e-07
[95,] 0.9999996 8.641890e-07 4.320945e-07
[96,] 0.9999994 1.176702e-06 5.883510e-07
[97,] 0.9999994 1.132955e-06 5.664775e-07
[98,] 0.9999991 1.758006e-06 8.790029e-07
[99,] 0.9999988 2.358658e-06 1.179329e-06
[100,] 0.9999985 3.076491e-06 1.538245e-06
[101,] 0.9999980 3.997439e-06 1.998719e-06
[102,] 0.9999970 5.901292e-06 2.950646e-06
[103,] 0.9999963 7.359075e-06 3.679537e-06
[104,] 0.9999961 7.813721e-06 3.906860e-06
[105,] 0.9999954 9.260571e-06 4.630286e-06
[106,] 0.9999977 4.572146e-06 2.286073e-06
[107,] 0.9999966 6.875574e-06 3.437787e-06
[108,] 0.9999962 7.517330e-06 3.758665e-06
[109,] 0.9999945 1.096927e-05 5.484636e-06
[110,] 0.9999976 4.790172e-06 2.395086e-06
[111,] 0.9999974 5.283138e-06 2.641569e-06
[112,] 0.9999992 1.588836e-06 7.944179e-07
[113,] 0.9999999 1.034442e-07 5.172209e-08
[114,] 0.9999999 1.308265e-07 6.541325e-08
[115,] 0.9999999 1.898448e-07 9.492238e-08
[116,] 0.9999999 2.637383e-07 1.318692e-07
[117,] 0.9999998 3.253067e-07 1.626534e-07
[118,] 0.9999997 5.132636e-07 2.566318e-07
[119,] 0.9999996 7.846643e-07 3.923321e-07
[120,] 0.9999998 4.551594e-07 2.275797e-07
[121,] 0.9999997 6.160117e-07 3.080058e-07
[122,] 1.0000000 7.262050e-08 3.631025e-08
[123,] 0.9999999 1.025274e-07 5.126368e-08
[124,] 1.0000000 2.261405e-08 1.130702e-08
[125,] 1.0000000 3.720960e-08 1.860480e-08
[126,] 1.0000000 1.476000e-08 7.380000e-09
[127,] 1.0000000 1.796227e-08 8.981135e-09
[128,] 1.0000000 2.851017e-08 1.425508e-08
[129,] 1.0000000 3.111185e-08 1.555592e-08
[130,] 1.0000000 4.501955e-08 2.250977e-08
[131,] 1.0000000 6.904405e-08 3.452203e-08
[132,] 0.9999999 1.011876e-07 5.059380e-08
[133,] 0.9999999 1.486623e-07 7.433116e-08
[134,] 0.9999999 1.676842e-07 8.384210e-08
[135,] 0.9999999 2.467155e-07 1.233577e-07
[136,] 0.9999998 3.583833e-07 1.791916e-07
[137,] 0.9999998 4.893645e-07 2.446823e-07
[138,] 0.9999996 7.725559e-07 3.862779e-07
[139,] 0.9999996 8.670669e-07 4.335334e-07
[140,] 0.9999995 1.061972e-06 5.309860e-07
[141,] 0.9999993 1.382145e-06 6.910725e-07
[142,] 0.9999991 1.828921e-06 9.144604e-07
[143,] 0.9999990 2.068181e-06 1.034090e-06
[144,] 0.9999996 8.110590e-07 4.055295e-07
[145,] 0.9999996 7.785659e-07 3.892830e-07
[146,] 0.9999996 7.236779e-07 3.618389e-07
[147,] 0.9999996 8.498662e-07 4.249331e-07
[148,] 0.9999994 1.214522e-06 6.072608e-07
[149,] 0.9999993 1.379653e-06 6.898263e-07
[150,] 0.9999990 1.962532e-06 9.812658e-07
[151,] 0.9999988 2.393149e-06 1.196575e-06
[152,] 0.9999984 3.246068e-06 1.623034e-06
[153,] 0.9999986 2.895942e-06 1.447971e-06
[154,] 0.9999994 1.243947e-06 6.219737e-07
[155,] 0.9999991 1.848968e-06 9.244841e-07
[156,] 0.9999988 2.492841e-06 1.246421e-06
[157,] 0.9999986 2.835946e-06 1.417973e-06
[158,] 1.0000000 2.451328e-08 1.225664e-08
[159,] 1.0000000 4.049745e-08 2.024872e-08
[160,] 1.0000000 5.700536e-08 2.850268e-08
[161,] 1.0000000 9.523623e-08 4.761811e-08
[162,] 1.0000000 3.856379e-08 1.928189e-08
[163,] 1.0000000 1.076506e-09 5.382530e-10
[164,] 1.0000000 1.783663e-09 8.918317e-10
[165,] 1.0000000 1.369920e-09 6.849598e-10
[166,] 1.0000000 2.284609e-09 1.142304e-09
[167,] 1.0000000 3.743425e-09 1.871713e-09
[168,] 1.0000000 1.683135e-09 8.415673e-10
[169,] 1.0000000 2.048424e-09 1.024212e-09
[170,] 1.0000000 1.765299e-10 8.826494e-11
[171,] 1.0000000 3.262716e-10 1.631358e-10
[172,] 1.0000000 2.983669e-10 1.491835e-10
[173,] 1.0000000 7.656598e-11 3.828299e-11
[174,] 1.0000000 1.375254e-10 6.876271e-11
[175,] 1.0000000 2.448815e-10 1.224408e-10
[176,] 1.0000000 4.451322e-10 2.225661e-10
[177,] 1.0000000 6.867195e-10 3.433598e-10
[178,] 1.0000000 7.455133e-10 3.727566e-10
[179,] 1.0000000 7.852465e-11 3.926233e-11
[180,] 1.0000000 1.520268e-10 7.601341e-11
[181,] 1.0000000 2.462537e-10 1.231269e-10
[182,] 1.0000000 4.706393e-10 2.353196e-10
[183,] 1.0000000 8.460111e-10 4.230056e-10
[184,] 1.0000000 1.395412e-09 6.977061e-10
[185,] 1.0000000 1.504591e-09 7.522954e-10
[186,] 1.0000000 2.712855e-09 1.356427e-09
[187,] 1.0000000 2.700362e-09 1.350181e-09
[188,] 1.0000000 4.839012e-09 2.419506e-09
[189,] 1.0000000 8.803035e-09 4.401517e-09
[190,] 1.0000000 1.385215e-08 6.926074e-09
[191,] 1.0000000 2.262132e-08 1.131066e-08
[192,] 1.0000000 4.059855e-08 2.029927e-08
[193,] 1.0000000 3.998734e-08 1.999367e-08
[194,] 1.0000000 7.167047e-08 3.583523e-08
[195,] 0.9999999 1.223867e-07 6.119336e-08
[196,] 1.0000000 1.995790e-08 9.978951e-09
[197,] 1.0000000 1.153355e-08 5.766775e-09
[198,] 1.0000000 1.996321e-08 9.981603e-09
[199,] 1.0000000 2.912376e-08 1.456188e-08
[200,] 1.0000000 1.310874e-08 6.554369e-09
[201,] 1.0000000 2.520725e-08 1.260362e-08
[202,] 1.0000000 4.808947e-08 2.404474e-08
[203,] 1.0000000 5.121371e-08 2.560685e-08
[204,] 1.0000000 5.757311e-08 2.878656e-08
[205,] 1.0000000 2.625725e-08 1.312863e-08
[206,] 1.0000000 5.075143e-08 2.537572e-08
[207,] 1.0000000 8.954974e-08 4.477487e-08
[208,] 1.0000000 9.627231e-08 4.813615e-08
[209,] 0.9999999 1.482386e-07 7.411929e-08
[210,] 0.9999999 2.755881e-07 1.377940e-07
[211,] 1.0000000 8.342355e-08 4.171177e-08
[212,] 0.9999999 1.511895e-07 7.559474e-08
[213,] 0.9999999 2.868663e-07 1.434332e-07
[214,] 0.9999997 5.198273e-07 2.599136e-07
[215,] 0.9999997 5.378111e-07 2.689055e-07
[216,] 0.9999998 4.051665e-07 2.025832e-07
[217,] 0.9999997 5.696720e-07 2.848360e-07
[218,] 0.9999999 1.146780e-07 5.733900e-08
[219,] 0.9999999 1.080168e-07 5.400838e-08
[220,] 0.9999999 2.193383e-07 1.096692e-07
[221,] 1.0000000 6.015878e-08 3.007939e-08
[222,] 0.9999999 1.242503e-07 6.212515e-08
[223,] 0.9999999 1.704044e-07 8.520222e-08
[224,] 0.9999998 3.258153e-07 1.629076e-07
[225,] 1.0000000 3.617337e-09 1.808668e-09
[226,] 1.0000000 7.394762e-09 3.697381e-09
[227,] 1.0000000 1.373741e-08 6.868706e-09
[228,] 1.0000000 1.003804e-08 5.019021e-09
[229,] 1.0000000 1.275398e-08 6.376990e-09
[230,] 1.0000000 3.076246e-08 1.538123e-08
[231,] 1.0000000 3.836310e-08 1.918155e-08
[232,] 1.0000000 6.676529e-08 3.338265e-08
[233,] 0.9999999 1.486190e-07 7.430951e-08
[234,] 0.9999998 3.491110e-07 1.745555e-07
[235,] 0.9999998 4.449718e-07 2.224859e-07
[236,] 0.9999997 5.740587e-07 2.870294e-07
[237,] 0.9999993 1.332321e-06 6.661607e-07
[238,] 0.9999988 2.477481e-06 1.238741e-06
[239,] 0.9999985 3.096943e-06 1.548471e-06
[240,] 0.9999969 6.241875e-06 3.120938e-06
[241,] 0.9999929 1.414403e-05 7.072017e-06
[242,] 0.9999842 3.152532e-05 1.576266e-05
[243,] 0.9999845 3.101005e-05 1.550503e-05
[244,] 0.9999682 6.362543e-05 3.181272e-05
[245,] 0.9999626 7.489305e-05 3.744653e-05
[246,] 0.9999429 1.141924e-04 5.709618e-05
[247,] 0.9999087 1.825167e-04 9.125836e-05
[248,] 0.9997994 4.012367e-04 2.006184e-04
[249,] 0.9995805 8.389750e-04 4.194875e-04
[250,] 0.9991255 1.749007e-03 8.745034e-04
[251,] 0.9982007 3.598683e-03 1.799342e-03
[252,] 0.9965638 6.872444e-03 3.436222e-03
[253,] 0.9974412 5.117570e-03 2.558785e-03
[254,] 0.9956730 8.653961e-03 4.326980e-03
[255,] 0.9975000 4.999902e-03 2.499951e-03
[256,] 0.9955018 8.996308e-03 4.498154e-03
[257,] 0.9999789 4.213779e-05 2.106890e-05
[258,] 0.9999540 9.203813e-05 4.601906e-05
[259,] 0.9998409 3.181174e-04 1.590587e-04
[260,] 0.9994993 1.001369e-03 5.006846e-04
[261,] 0.9986950 2.609913e-03 1.304956e-03
[262,] 0.9958214 8.357121e-03 4.178561e-03
[263,] 0.9892632 2.147351e-02 1.073675e-02
[264,] 0.9665925 6.681509e-02 3.340754e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1edrt1355263341.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2ard01355263341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wtc31355263341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4x1g51355263341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/528xq1355263341.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
65599.3177 1511.2357 13775.9023 -72265.9569 35613.3455 -2287.2950
7 8 9 10 11 12
35787.6264 3479.7633 11670.5210 -11983.0078 23654.4680 30232.9705
13 14 15 16 17 18
-17670.6295 -7396.4828 16820.4026 27485.1473 -84057.0054 36825.2158
19 20 21 22 23 24
8212.5572 5530.9469 -1859.6510 9556.7358 104653.7392 37245.7425
25 26 27 28 29 30
-34768.5455 -95264.5394 -53581.1384 -12928.2638 31540.2523 -8924.7408
31 32 33 34 35 36
19375.1448 4053.1507 1504.9811 29834.3932 -18616.0375 26419.5875
37 38 39 40 41 42
31148.6595 8520.6472 61581.4487 2610.3148 16064.4038 36290.1774
43 44 45 46 47 48
-27747.5654 -8971.0044 -21482.3661 -6391.3691 -48147.9357 4491.5416
49 50 51 52 53 54
2712.6717 -53226.6850 46600.5995 -10702.5091 -18730.3397 -30753.5779
55 56 57 58 59 60
-51896.6309 3847.1017 -11595.2275 55431.1589 -3785.7915 -5050.3785
61 62 63 64 65 66
6505.3212 25828.6495 21323.4946 9137.0501 -2202.3504 5721.0387
67 68 69 70 71 72
24591.7715 5938.6396 10012.7968 -34096.5773 11769.6124 49932.5467
73 74 75 76 77 78
39180.3433 -22163.1706 -33242.7802 -17172.1861 -36319.7142 -17944.4994
79 80 81 82 83 84
-23259.9686 1786.4602 6266.9749 -35488.9740 43746.2777 30782.0932
85 86 87 88 89 90
19221.1444 -30163.4044 -10726.9981 -19036.3228 64106.1616 -12580.4983
91 92 93 94 95 96
36381.3709 -13072.4273 -26891.2543 8323.8218 17258.3317 14919.8507
97 98 99 100 101 102
29570.0795 -128483.8227 20895.9904 -10992.9333 15807.2415 -25379.6999
103 104 105 106 107 108
46203.5404 11464.7599 31904.4297 26974.4427 -34071.1668 -9982.7335
109 110 111 112 113 114
28738.6479 685.4864 15749.3060 -11552.4926 -14965.2800 4324.1393
115 116 117 118 119 120
-18033.8600 -27738.8561 -19395.9632 46238.2536 3550.8150 -21315.7182
121 122 123 124 125 126
-4660.6197 -43837.7728 -27668.4593 -55227.4097 74340.4572 19402.8860
127 128 129 130 131 132
10798.8412 -15067.4291 22325.3421 2907.7094 -3710.9001 -37420.7355
133 134 135 136 137 138
17481.4668 -64052.8839 -14027.9119 57978.4154 2566.2303 43377.8017
139 140 141 142 143 144
-18602.1569 -6958.0907 -23423.3912 -11730.0527 6955.1735 -13195.2035
145 146 147 148 149 150
7911.8611 -21587.5710 -2688.3608 -11086.1819 -16238.2299 -2067.9923
151 152 153 154 155 156
24194.3291 18202.7169 -13407.4907 8548.7012 16832.7730 42382.5500
157 158 159 160 161 162
20408.0067 20554.3858 -22324.6389 -16865.5025 18945.6135 -12830.2009
163 164 165 166 167 168
-13700.4820 -19136.9417 -29565.0304 34663.5403 -2965.5806 17923.3866
169 170 171 172 173 174
22748.2282 85756.1548 -11077.6749 4404.3157 -1100.3678 17004.9311
175 176 177 178 179 180
-87744.5850 3134.5809 -31735.0719 5656.6061 -3175.9452 37009.5440
181 182 183 184 185 186
-21390.9671 -55734.6220 8074.0120 22912.9974 25026.4373 2922.2123
187 188 189 190 191 192
1936.4707 15140.5313 4963.8669 10413.7141 32845.7368 -5978.2494
193 194 195 196 197 198
-14866.2065 -2444.3206 -2644.7369 4266.3675 -22640.4428 8633.4779
199 200 201 202 203 204
-30883.9468 -5683.7039 5547.2606 4300.0392 10914.9970 4290.7809
205 206 207 208 209 210
-31969.7336 -9192.9617 -9263.3838 42155.2479 22767.4019 -4878.2968
211 212 213 214 215 216
11786.5034 23902.2990 -1933.7063 -993.9917 -31628.9188 -16524.7528
217 218 219 220 221 222
-34301.4309 7473.5369 3548.2676 23855.6878 -20792.6606 -9801.0060
223 224 225 226 227 228
-51054.2349 4343.6544 -2478.9012 2191.1867 23042.3805 -27973.2710
229 230 231 232 233 234
-22293.1650 -42790.6342 -15310.2602 -4764.1115 -33791.2286 -5138.9973
235 236 237 238 239 240
-26147.5728 -13892.1666 48155.2494 -7026.6860 -11776.2481 -22575.4880
241 242 243 244 245 246
11872.2333 -2865.5112 -16979.8399 -8723.0126 -1233.2436 -9752.3572
247 248 249 250 251 252
-23986.5503 19778.9697 6951.1852 -11385.7589 14067.6038 6219.4263
253 254 255 256 257 258
12255.5388 -2553.0266 -22415.5021 1339.3727 -11086.3850 9677.3838
259 260 261 262 263 264
12616.8351 6519.1264 -12160.9645 4187.6801 11450.3466 -6430.8166
265 266 267 268 269 270
-13870.3897 7357.8859 -22621.4899 -2655.6633 45266.9902 -13870.6896
271 272 273 274 275 276
-5423.4625 1104.7338 2370.5278 3486.3539 10418.2933 -16162.5474
277 278 279 280 281 282
15056.4127 10268.5886 -5482.6148 12558.4239 -6644.6359 18134.3467
283 284 285 286 287 288
-313.2582 12292.6779 452.9734 -4637.9126 1227.3614 -1707.1601
289
-2517.9042
> postscript(file="/var/wessaorg/rcomp/tmp/66y901355263341.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 65599.3177 NA
1 1511.2357 65599.3177
2 13775.9023 1511.2357
3 -72265.9569 13775.9023
4 35613.3455 -72265.9569
5 -2287.2950 35613.3455
6 35787.6264 -2287.2950
7 3479.7633 35787.6264
8 11670.5210 3479.7633
9 -11983.0078 11670.5210
10 23654.4680 -11983.0078
11 30232.9705 23654.4680
12 -17670.6295 30232.9705
13 -7396.4828 -17670.6295
14 16820.4026 -7396.4828
15 27485.1473 16820.4026
16 -84057.0054 27485.1473
17 36825.2158 -84057.0054
18 8212.5572 36825.2158
19 5530.9469 8212.5572
20 -1859.6510 5530.9469
21 9556.7358 -1859.6510
22 104653.7392 9556.7358
23 37245.7425 104653.7392
24 -34768.5455 37245.7425
25 -95264.5394 -34768.5455
26 -53581.1384 -95264.5394
27 -12928.2638 -53581.1384
28 31540.2523 -12928.2638
29 -8924.7408 31540.2523
30 19375.1448 -8924.7408
31 4053.1507 19375.1448
32 1504.9811 4053.1507
33 29834.3932 1504.9811
34 -18616.0375 29834.3932
35 26419.5875 -18616.0375
36 31148.6595 26419.5875
37 8520.6472 31148.6595
38 61581.4487 8520.6472
39 2610.3148 61581.4487
40 16064.4038 2610.3148
41 36290.1774 16064.4038
42 -27747.5654 36290.1774
43 -8971.0044 -27747.5654
44 -21482.3661 -8971.0044
45 -6391.3691 -21482.3661
46 -48147.9357 -6391.3691
47 4491.5416 -48147.9357
48 2712.6717 4491.5416
49 -53226.6850 2712.6717
50 46600.5995 -53226.6850
51 -10702.5091 46600.5995
52 -18730.3397 -10702.5091
53 -30753.5779 -18730.3397
54 -51896.6309 -30753.5779
55 3847.1017 -51896.6309
56 -11595.2275 3847.1017
57 55431.1589 -11595.2275
58 -3785.7915 55431.1589
59 -5050.3785 -3785.7915
60 6505.3212 -5050.3785
61 25828.6495 6505.3212
62 21323.4946 25828.6495
63 9137.0501 21323.4946
64 -2202.3504 9137.0501
65 5721.0387 -2202.3504
66 24591.7715 5721.0387
67 5938.6396 24591.7715
68 10012.7968 5938.6396
69 -34096.5773 10012.7968
70 11769.6124 -34096.5773
71 49932.5467 11769.6124
72 39180.3433 49932.5467
73 -22163.1706 39180.3433
74 -33242.7802 -22163.1706
75 -17172.1861 -33242.7802
76 -36319.7142 -17172.1861
77 -17944.4994 -36319.7142
78 -23259.9686 -17944.4994
79 1786.4602 -23259.9686
80 6266.9749 1786.4602
81 -35488.9740 6266.9749
82 43746.2777 -35488.9740
83 30782.0932 43746.2777
84 19221.1444 30782.0932
85 -30163.4044 19221.1444
86 -10726.9981 -30163.4044
87 -19036.3228 -10726.9981
88 64106.1616 -19036.3228
89 -12580.4983 64106.1616
90 36381.3709 -12580.4983
91 -13072.4273 36381.3709
92 -26891.2543 -13072.4273
93 8323.8218 -26891.2543
94 17258.3317 8323.8218
95 14919.8507 17258.3317
96 29570.0795 14919.8507
97 -128483.8227 29570.0795
98 20895.9904 -128483.8227
99 -10992.9333 20895.9904
100 15807.2415 -10992.9333
101 -25379.6999 15807.2415
102 46203.5404 -25379.6999
103 11464.7599 46203.5404
104 31904.4297 11464.7599
105 26974.4427 31904.4297
106 -34071.1668 26974.4427
107 -9982.7335 -34071.1668
108 28738.6479 -9982.7335
109 685.4864 28738.6479
110 15749.3060 685.4864
111 -11552.4926 15749.3060
112 -14965.2800 -11552.4926
113 4324.1393 -14965.2800
114 -18033.8600 4324.1393
115 -27738.8561 -18033.8600
116 -19395.9632 -27738.8561
117 46238.2536 -19395.9632
118 3550.8150 46238.2536
119 -21315.7182 3550.8150
120 -4660.6197 -21315.7182
121 -43837.7728 -4660.6197
122 -27668.4593 -43837.7728
123 -55227.4097 -27668.4593
124 74340.4572 -55227.4097
125 19402.8860 74340.4572
126 10798.8412 19402.8860
127 -15067.4291 10798.8412
128 22325.3421 -15067.4291
129 2907.7094 22325.3421
130 -3710.9001 2907.7094
131 -37420.7355 -3710.9001
132 17481.4668 -37420.7355
133 -64052.8839 17481.4668
134 -14027.9119 -64052.8839
135 57978.4154 -14027.9119
136 2566.2303 57978.4154
137 43377.8017 2566.2303
138 -18602.1569 43377.8017
139 -6958.0907 -18602.1569
140 -23423.3912 -6958.0907
141 -11730.0527 -23423.3912
142 6955.1735 -11730.0527
143 -13195.2035 6955.1735
144 7911.8611 -13195.2035
145 -21587.5710 7911.8611
146 -2688.3608 -21587.5710
147 -11086.1819 -2688.3608
148 -16238.2299 -11086.1819
149 -2067.9923 -16238.2299
150 24194.3291 -2067.9923
151 18202.7169 24194.3291
152 -13407.4907 18202.7169
153 8548.7012 -13407.4907
154 16832.7730 8548.7012
155 42382.5500 16832.7730
156 20408.0067 42382.5500
157 20554.3858 20408.0067
158 -22324.6389 20554.3858
159 -16865.5025 -22324.6389
160 18945.6135 -16865.5025
161 -12830.2009 18945.6135
162 -13700.4820 -12830.2009
163 -19136.9417 -13700.4820
164 -29565.0304 -19136.9417
165 34663.5403 -29565.0304
166 -2965.5806 34663.5403
167 17923.3866 -2965.5806
168 22748.2282 17923.3866
169 85756.1548 22748.2282
170 -11077.6749 85756.1548
171 4404.3157 -11077.6749
172 -1100.3678 4404.3157
173 17004.9311 -1100.3678
174 -87744.5850 17004.9311
175 3134.5809 -87744.5850
176 -31735.0719 3134.5809
177 5656.6061 -31735.0719
178 -3175.9452 5656.6061
179 37009.5440 -3175.9452
180 -21390.9671 37009.5440
181 -55734.6220 -21390.9671
182 8074.0120 -55734.6220
183 22912.9974 8074.0120
184 25026.4373 22912.9974
185 2922.2123 25026.4373
186 1936.4707 2922.2123
187 15140.5313 1936.4707
188 4963.8669 15140.5313
189 10413.7141 4963.8669
190 32845.7368 10413.7141
191 -5978.2494 32845.7368
192 -14866.2065 -5978.2494
193 -2444.3206 -14866.2065
194 -2644.7369 -2444.3206
195 4266.3675 -2644.7369
196 -22640.4428 4266.3675
197 8633.4779 -22640.4428
198 -30883.9468 8633.4779
199 -5683.7039 -30883.9468
200 5547.2606 -5683.7039
201 4300.0392 5547.2606
202 10914.9970 4300.0392
203 4290.7809 10914.9970
204 -31969.7336 4290.7809
205 -9192.9617 -31969.7336
206 -9263.3838 -9192.9617
207 42155.2479 -9263.3838
208 22767.4019 42155.2479
209 -4878.2968 22767.4019
210 11786.5034 -4878.2968
211 23902.2990 11786.5034
212 -1933.7063 23902.2990
213 -993.9917 -1933.7063
214 -31628.9188 -993.9917
215 -16524.7528 -31628.9188
216 -34301.4309 -16524.7528
217 7473.5369 -34301.4309
218 3548.2676 7473.5369
219 23855.6878 3548.2676
220 -20792.6606 23855.6878
221 -9801.0060 -20792.6606
222 -51054.2349 -9801.0060
223 4343.6544 -51054.2349
224 -2478.9012 4343.6544
225 2191.1867 -2478.9012
226 23042.3805 2191.1867
227 -27973.2710 23042.3805
228 -22293.1650 -27973.2710
229 -42790.6342 -22293.1650
230 -15310.2602 -42790.6342
231 -4764.1115 -15310.2602
232 -33791.2286 -4764.1115
233 -5138.9973 -33791.2286
234 -26147.5728 -5138.9973
235 -13892.1666 -26147.5728
236 48155.2494 -13892.1666
237 -7026.6860 48155.2494
238 -11776.2481 -7026.6860
239 -22575.4880 -11776.2481
240 11872.2333 -22575.4880
241 -2865.5112 11872.2333
242 -16979.8399 -2865.5112
243 -8723.0126 -16979.8399
244 -1233.2436 -8723.0126
245 -9752.3572 -1233.2436
246 -23986.5503 -9752.3572
247 19778.9697 -23986.5503
248 6951.1852 19778.9697
249 -11385.7589 6951.1852
250 14067.6038 -11385.7589
251 6219.4263 14067.6038
252 12255.5388 6219.4263
253 -2553.0266 12255.5388
254 -22415.5021 -2553.0266
255 1339.3727 -22415.5021
256 -11086.3850 1339.3727
257 9677.3838 -11086.3850
258 12616.8351 9677.3838
259 6519.1264 12616.8351
260 -12160.9645 6519.1264
261 4187.6801 -12160.9645
262 11450.3466 4187.6801
263 -6430.8166 11450.3466
264 -13870.3897 -6430.8166
265 7357.8859 -13870.3897
266 -22621.4899 7357.8859
267 -2655.6633 -22621.4899
268 45266.9902 -2655.6633
269 -13870.6896 45266.9902
270 -5423.4625 -13870.6896
271 1104.7338 -5423.4625
272 2370.5278 1104.7338
273 3486.3539 2370.5278
274 10418.2933 3486.3539
275 -16162.5474 10418.2933
276 15056.4127 -16162.5474
277 10268.5886 15056.4127
278 -5482.6148 10268.5886
279 12558.4239 -5482.6148
280 -6644.6359 12558.4239
281 18134.3467 -6644.6359
282 -313.2582 18134.3467
283 12292.6779 -313.2582
284 452.9734 12292.6779
285 -4637.9126 452.9734
286 1227.3614 -4637.9126
287 -1707.1601 1227.3614
288 -2517.9042 -1707.1601
289 NA -2517.9042
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1511.2357 65599.3177
[2,] 13775.9023 1511.2357
[3,] -72265.9569 13775.9023
[4,] 35613.3455 -72265.9569
[5,] -2287.2950 35613.3455
[6,] 35787.6264 -2287.2950
[7,] 3479.7633 35787.6264
[8,] 11670.5210 3479.7633
[9,] -11983.0078 11670.5210
[10,] 23654.4680 -11983.0078
[11,] 30232.9705 23654.4680
[12,] -17670.6295 30232.9705
[13,] -7396.4828 -17670.6295
[14,] 16820.4026 -7396.4828
[15,] 27485.1473 16820.4026
[16,] -84057.0054 27485.1473
[17,] 36825.2158 -84057.0054
[18,] 8212.5572 36825.2158
[19,] 5530.9469 8212.5572
[20,] -1859.6510 5530.9469
[21,] 9556.7358 -1859.6510
[22,] 104653.7392 9556.7358
[23,] 37245.7425 104653.7392
[24,] -34768.5455 37245.7425
[25,] -95264.5394 -34768.5455
[26,] -53581.1384 -95264.5394
[27,] -12928.2638 -53581.1384
[28,] 31540.2523 -12928.2638
[29,] -8924.7408 31540.2523
[30,] 19375.1448 -8924.7408
[31,] 4053.1507 19375.1448
[32,] 1504.9811 4053.1507
[33,] 29834.3932 1504.9811
[34,] -18616.0375 29834.3932
[35,] 26419.5875 -18616.0375
[36,] 31148.6595 26419.5875
[37,] 8520.6472 31148.6595
[38,] 61581.4487 8520.6472
[39,] 2610.3148 61581.4487
[40,] 16064.4038 2610.3148
[41,] 36290.1774 16064.4038
[42,] -27747.5654 36290.1774
[43,] -8971.0044 -27747.5654
[44,] -21482.3661 -8971.0044
[45,] -6391.3691 -21482.3661
[46,] -48147.9357 -6391.3691
[47,] 4491.5416 -48147.9357
[48,] 2712.6717 4491.5416
[49,] -53226.6850 2712.6717
[50,] 46600.5995 -53226.6850
[51,] -10702.5091 46600.5995
[52,] -18730.3397 -10702.5091
[53,] -30753.5779 -18730.3397
[54,] -51896.6309 -30753.5779
[55,] 3847.1017 -51896.6309
[56,] -11595.2275 3847.1017
[57,] 55431.1589 -11595.2275
[58,] -3785.7915 55431.1589
[59,] -5050.3785 -3785.7915
[60,] 6505.3212 -5050.3785
[61,] 25828.6495 6505.3212
[62,] 21323.4946 25828.6495
[63,] 9137.0501 21323.4946
[64,] -2202.3504 9137.0501
[65,] 5721.0387 -2202.3504
[66,] 24591.7715 5721.0387
[67,] 5938.6396 24591.7715
[68,] 10012.7968 5938.6396
[69,] -34096.5773 10012.7968
[70,] 11769.6124 -34096.5773
[71,] 49932.5467 11769.6124
[72,] 39180.3433 49932.5467
[73,] -22163.1706 39180.3433
[74,] -33242.7802 -22163.1706
[75,] -17172.1861 -33242.7802
[76,] -36319.7142 -17172.1861
[77,] -17944.4994 -36319.7142
[78,] -23259.9686 -17944.4994
[79,] 1786.4602 -23259.9686
[80,] 6266.9749 1786.4602
[81,] -35488.9740 6266.9749
[82,] 43746.2777 -35488.9740
[83,] 30782.0932 43746.2777
[84,] 19221.1444 30782.0932
[85,] -30163.4044 19221.1444
[86,] -10726.9981 -30163.4044
[87,] -19036.3228 -10726.9981
[88,] 64106.1616 -19036.3228
[89,] -12580.4983 64106.1616
[90,] 36381.3709 -12580.4983
[91,] -13072.4273 36381.3709
[92,] -26891.2543 -13072.4273
[93,] 8323.8218 -26891.2543
[94,] 17258.3317 8323.8218
[95,] 14919.8507 17258.3317
[96,] 29570.0795 14919.8507
[97,] -128483.8227 29570.0795
[98,] 20895.9904 -128483.8227
[99,] -10992.9333 20895.9904
[100,] 15807.2415 -10992.9333
[101,] -25379.6999 15807.2415
[102,] 46203.5404 -25379.6999
[103,] 11464.7599 46203.5404
[104,] 31904.4297 11464.7599
[105,] 26974.4427 31904.4297
[106,] -34071.1668 26974.4427
[107,] -9982.7335 -34071.1668
[108,] 28738.6479 -9982.7335
[109,] 685.4864 28738.6479
[110,] 15749.3060 685.4864
[111,] -11552.4926 15749.3060
[112,] -14965.2800 -11552.4926
[113,] 4324.1393 -14965.2800
[114,] -18033.8600 4324.1393
[115,] -27738.8561 -18033.8600
[116,] -19395.9632 -27738.8561
[117,] 46238.2536 -19395.9632
[118,] 3550.8150 46238.2536
[119,] -21315.7182 3550.8150
[120,] -4660.6197 -21315.7182
[121,] -43837.7728 -4660.6197
[122,] -27668.4593 -43837.7728
[123,] -55227.4097 -27668.4593
[124,] 74340.4572 -55227.4097
[125,] 19402.8860 74340.4572
[126,] 10798.8412 19402.8860
[127,] -15067.4291 10798.8412
[128,] 22325.3421 -15067.4291
[129,] 2907.7094 22325.3421
[130,] -3710.9001 2907.7094
[131,] -37420.7355 -3710.9001
[132,] 17481.4668 -37420.7355
[133,] -64052.8839 17481.4668
[134,] -14027.9119 -64052.8839
[135,] 57978.4154 -14027.9119
[136,] 2566.2303 57978.4154
[137,] 43377.8017 2566.2303
[138,] -18602.1569 43377.8017
[139,] -6958.0907 -18602.1569
[140,] -23423.3912 -6958.0907
[141,] -11730.0527 -23423.3912
[142,] 6955.1735 -11730.0527
[143,] -13195.2035 6955.1735
[144,] 7911.8611 -13195.2035
[145,] -21587.5710 7911.8611
[146,] -2688.3608 -21587.5710
[147,] -11086.1819 -2688.3608
[148,] -16238.2299 -11086.1819
[149,] -2067.9923 -16238.2299
[150,] 24194.3291 -2067.9923
[151,] 18202.7169 24194.3291
[152,] -13407.4907 18202.7169
[153,] 8548.7012 -13407.4907
[154,] 16832.7730 8548.7012
[155,] 42382.5500 16832.7730
[156,] 20408.0067 42382.5500
[157,] 20554.3858 20408.0067
[158,] -22324.6389 20554.3858
[159,] -16865.5025 -22324.6389
[160,] 18945.6135 -16865.5025
[161,] -12830.2009 18945.6135
[162,] -13700.4820 -12830.2009
[163,] -19136.9417 -13700.4820
[164,] -29565.0304 -19136.9417
[165,] 34663.5403 -29565.0304
[166,] -2965.5806 34663.5403
[167,] 17923.3866 -2965.5806
[168,] 22748.2282 17923.3866
[169,] 85756.1548 22748.2282
[170,] -11077.6749 85756.1548
[171,] 4404.3157 -11077.6749
[172,] -1100.3678 4404.3157
[173,] 17004.9311 -1100.3678
[174,] -87744.5850 17004.9311
[175,] 3134.5809 -87744.5850
[176,] -31735.0719 3134.5809
[177,] 5656.6061 -31735.0719
[178,] -3175.9452 5656.6061
[179,] 37009.5440 -3175.9452
[180,] -21390.9671 37009.5440
[181,] -55734.6220 -21390.9671
[182,] 8074.0120 -55734.6220
[183,] 22912.9974 8074.0120
[184,] 25026.4373 22912.9974
[185,] 2922.2123 25026.4373
[186,] 1936.4707 2922.2123
[187,] 15140.5313 1936.4707
[188,] 4963.8669 15140.5313
[189,] 10413.7141 4963.8669
[190,] 32845.7368 10413.7141
[191,] -5978.2494 32845.7368
[192,] -14866.2065 -5978.2494
[193,] -2444.3206 -14866.2065
[194,] -2644.7369 -2444.3206
[195,] 4266.3675 -2644.7369
[196,] -22640.4428 4266.3675
[197,] 8633.4779 -22640.4428
[198,] -30883.9468 8633.4779
[199,] -5683.7039 -30883.9468
[200,] 5547.2606 -5683.7039
[201,] 4300.0392 5547.2606
[202,] 10914.9970 4300.0392
[203,] 4290.7809 10914.9970
[204,] -31969.7336 4290.7809
[205,] -9192.9617 -31969.7336
[206,] -9263.3838 -9192.9617
[207,] 42155.2479 -9263.3838
[208,] 22767.4019 42155.2479
[209,] -4878.2968 22767.4019
[210,] 11786.5034 -4878.2968
[211,] 23902.2990 11786.5034
[212,] -1933.7063 23902.2990
[213,] -993.9917 -1933.7063
[214,] -31628.9188 -993.9917
[215,] -16524.7528 -31628.9188
[216,] -34301.4309 -16524.7528
[217,] 7473.5369 -34301.4309
[218,] 3548.2676 7473.5369
[219,] 23855.6878 3548.2676
[220,] -20792.6606 23855.6878
[221,] -9801.0060 -20792.6606
[222,] -51054.2349 -9801.0060
[223,] 4343.6544 -51054.2349
[224,] -2478.9012 4343.6544
[225,] 2191.1867 -2478.9012
[226,] 23042.3805 2191.1867
[227,] -27973.2710 23042.3805
[228,] -22293.1650 -27973.2710
[229,] -42790.6342 -22293.1650
[230,] -15310.2602 -42790.6342
[231,] -4764.1115 -15310.2602
[232,] -33791.2286 -4764.1115
[233,] -5138.9973 -33791.2286
[234,] -26147.5728 -5138.9973
[235,] -13892.1666 -26147.5728
[236,] 48155.2494 -13892.1666
[237,] -7026.6860 48155.2494
[238,] -11776.2481 -7026.6860
[239,] -22575.4880 -11776.2481
[240,] 11872.2333 -22575.4880
[241,] -2865.5112 11872.2333
[242,] -16979.8399 -2865.5112
[243,] -8723.0126 -16979.8399
[244,] -1233.2436 -8723.0126
[245,] -9752.3572 -1233.2436
[246,] -23986.5503 -9752.3572
[247,] 19778.9697 -23986.5503
[248,] 6951.1852 19778.9697
[249,] -11385.7589 6951.1852
[250,] 14067.6038 -11385.7589
[251,] 6219.4263 14067.6038
[252,] 12255.5388 6219.4263
[253,] -2553.0266 12255.5388
[254,] -22415.5021 -2553.0266
[255,] 1339.3727 -22415.5021
[256,] -11086.3850 1339.3727
[257,] 9677.3838 -11086.3850
[258,] 12616.8351 9677.3838
[259,] 6519.1264 12616.8351
[260,] -12160.9645 6519.1264
[261,] 4187.6801 -12160.9645
[262,] 11450.3466 4187.6801
[263,] -6430.8166 11450.3466
[264,] -13870.3897 -6430.8166
[265,] 7357.8859 -13870.3897
[266,] -22621.4899 7357.8859
[267,] -2655.6633 -22621.4899
[268,] 45266.9902 -2655.6633
[269,] -13870.6896 45266.9902
[270,] -5423.4625 -13870.6896
[271,] 1104.7338 -5423.4625
[272,] 2370.5278 1104.7338
[273,] 3486.3539 2370.5278
[274,] 10418.2933 3486.3539
[275,] -16162.5474 10418.2933
[276,] 15056.4127 -16162.5474
[277,] 10268.5886 15056.4127
[278,] -5482.6148 10268.5886
[279,] 12558.4239 -5482.6148
[280,] -6644.6359 12558.4239
[281,] 18134.3467 -6644.6359
[282,] -313.2582 18134.3467
[283,] 12292.6779 -313.2582
[284,] 452.9734 12292.6779
[285,] -4637.9126 452.9734
[286,] 1227.3614 -4637.9126
[287,] -1707.1601 1227.3614
[288,] -2517.9042 -1707.1601
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1511.2357 65599.3177
2 13775.9023 1511.2357
3 -72265.9569 13775.9023
4 35613.3455 -72265.9569
5 -2287.2950 35613.3455
6 35787.6264 -2287.2950
7 3479.7633 35787.6264
8 11670.5210 3479.7633
9 -11983.0078 11670.5210
10 23654.4680 -11983.0078
11 30232.9705 23654.4680
12 -17670.6295 30232.9705
13 -7396.4828 -17670.6295
14 16820.4026 -7396.4828
15 27485.1473 16820.4026
16 -84057.0054 27485.1473
17 36825.2158 -84057.0054
18 8212.5572 36825.2158
19 5530.9469 8212.5572
20 -1859.6510 5530.9469
21 9556.7358 -1859.6510
22 104653.7392 9556.7358
23 37245.7425 104653.7392
24 -34768.5455 37245.7425
25 -95264.5394 -34768.5455
26 -53581.1384 -95264.5394
27 -12928.2638 -53581.1384
28 31540.2523 -12928.2638
29 -8924.7408 31540.2523
30 19375.1448 -8924.7408
31 4053.1507 19375.1448
32 1504.9811 4053.1507
33 29834.3932 1504.9811
34 -18616.0375 29834.3932
35 26419.5875 -18616.0375
36 31148.6595 26419.5875
37 8520.6472 31148.6595
38 61581.4487 8520.6472
39 2610.3148 61581.4487
40 16064.4038 2610.3148
41 36290.1774 16064.4038
42 -27747.5654 36290.1774
43 -8971.0044 -27747.5654
44 -21482.3661 -8971.0044
45 -6391.3691 -21482.3661
46 -48147.9357 -6391.3691
47 4491.5416 -48147.9357
48 2712.6717 4491.5416
49 -53226.6850 2712.6717
50 46600.5995 -53226.6850
51 -10702.5091 46600.5995
52 -18730.3397 -10702.5091
53 -30753.5779 -18730.3397
54 -51896.6309 -30753.5779
55 3847.1017 -51896.6309
56 -11595.2275 3847.1017
57 55431.1589 -11595.2275
58 -3785.7915 55431.1589
59 -5050.3785 -3785.7915
60 6505.3212 -5050.3785
61 25828.6495 6505.3212
62 21323.4946 25828.6495
63 9137.0501 21323.4946
64 -2202.3504 9137.0501
65 5721.0387 -2202.3504
66 24591.7715 5721.0387
67 5938.6396 24591.7715
68 10012.7968 5938.6396
69 -34096.5773 10012.7968
70 11769.6124 -34096.5773
71 49932.5467 11769.6124
72 39180.3433 49932.5467
73 -22163.1706 39180.3433
74 -33242.7802 -22163.1706
75 -17172.1861 -33242.7802
76 -36319.7142 -17172.1861
77 -17944.4994 -36319.7142
78 -23259.9686 -17944.4994
79 1786.4602 -23259.9686
80 6266.9749 1786.4602
81 -35488.9740 6266.9749
82 43746.2777 -35488.9740
83 30782.0932 43746.2777
84 19221.1444 30782.0932
85 -30163.4044 19221.1444
86 -10726.9981 -30163.4044
87 -19036.3228 -10726.9981
88 64106.1616 -19036.3228
89 -12580.4983 64106.1616
90 36381.3709 -12580.4983
91 -13072.4273 36381.3709
92 -26891.2543 -13072.4273
93 8323.8218 -26891.2543
94 17258.3317 8323.8218
95 14919.8507 17258.3317
96 29570.0795 14919.8507
97 -128483.8227 29570.0795
98 20895.9904 -128483.8227
99 -10992.9333 20895.9904
100 15807.2415 -10992.9333
101 -25379.6999 15807.2415
102 46203.5404 -25379.6999
103 11464.7599 46203.5404
104 31904.4297 11464.7599
105 26974.4427 31904.4297
106 -34071.1668 26974.4427
107 -9982.7335 -34071.1668
108 28738.6479 -9982.7335
109 685.4864 28738.6479
110 15749.3060 685.4864
111 -11552.4926 15749.3060
112 -14965.2800 -11552.4926
113 4324.1393 -14965.2800
114 -18033.8600 4324.1393
115 -27738.8561 -18033.8600
116 -19395.9632 -27738.8561
117 46238.2536 -19395.9632
118 3550.8150 46238.2536
119 -21315.7182 3550.8150
120 -4660.6197 -21315.7182
121 -43837.7728 -4660.6197
122 -27668.4593 -43837.7728
123 -55227.4097 -27668.4593
124 74340.4572 -55227.4097
125 19402.8860 74340.4572
126 10798.8412 19402.8860
127 -15067.4291 10798.8412
128 22325.3421 -15067.4291
129 2907.7094 22325.3421
130 -3710.9001 2907.7094
131 -37420.7355 -3710.9001
132 17481.4668 -37420.7355
133 -64052.8839 17481.4668
134 -14027.9119 -64052.8839
135 57978.4154 -14027.9119
136 2566.2303 57978.4154
137 43377.8017 2566.2303
138 -18602.1569 43377.8017
139 -6958.0907 -18602.1569
140 -23423.3912 -6958.0907
141 -11730.0527 -23423.3912
142 6955.1735 -11730.0527
143 -13195.2035 6955.1735
144 7911.8611 -13195.2035
145 -21587.5710 7911.8611
146 -2688.3608 -21587.5710
147 -11086.1819 -2688.3608
148 -16238.2299 -11086.1819
149 -2067.9923 -16238.2299
150 24194.3291 -2067.9923
151 18202.7169 24194.3291
152 -13407.4907 18202.7169
153 8548.7012 -13407.4907
154 16832.7730 8548.7012
155 42382.5500 16832.7730
156 20408.0067 42382.5500
157 20554.3858 20408.0067
158 -22324.6389 20554.3858
159 -16865.5025 -22324.6389
160 18945.6135 -16865.5025
161 -12830.2009 18945.6135
162 -13700.4820 -12830.2009
163 -19136.9417 -13700.4820
164 -29565.0304 -19136.9417
165 34663.5403 -29565.0304
166 -2965.5806 34663.5403
167 17923.3866 -2965.5806
168 22748.2282 17923.3866
169 85756.1548 22748.2282
170 -11077.6749 85756.1548
171 4404.3157 -11077.6749
172 -1100.3678 4404.3157
173 17004.9311 -1100.3678
174 -87744.5850 17004.9311
175 3134.5809 -87744.5850
176 -31735.0719 3134.5809
177 5656.6061 -31735.0719
178 -3175.9452 5656.6061
179 37009.5440 -3175.9452
180 -21390.9671 37009.5440
181 -55734.6220 -21390.9671
182 8074.0120 -55734.6220
183 22912.9974 8074.0120
184 25026.4373 22912.9974
185 2922.2123 25026.4373
186 1936.4707 2922.2123
187 15140.5313 1936.4707
188 4963.8669 15140.5313
189 10413.7141 4963.8669
190 32845.7368 10413.7141
191 -5978.2494 32845.7368
192 -14866.2065 -5978.2494
193 -2444.3206 -14866.2065
194 -2644.7369 -2444.3206
195 4266.3675 -2644.7369
196 -22640.4428 4266.3675
197 8633.4779 -22640.4428
198 -30883.9468 8633.4779
199 -5683.7039 -30883.9468
200 5547.2606 -5683.7039
201 4300.0392 5547.2606
202 10914.9970 4300.0392
203 4290.7809 10914.9970
204 -31969.7336 4290.7809
205 -9192.9617 -31969.7336
206 -9263.3838 -9192.9617
207 42155.2479 -9263.3838
208 22767.4019 42155.2479
209 -4878.2968 22767.4019
210 11786.5034 -4878.2968
211 23902.2990 11786.5034
212 -1933.7063 23902.2990
213 -993.9917 -1933.7063
214 -31628.9188 -993.9917
215 -16524.7528 -31628.9188
216 -34301.4309 -16524.7528
217 7473.5369 -34301.4309
218 3548.2676 7473.5369
219 23855.6878 3548.2676
220 -20792.6606 23855.6878
221 -9801.0060 -20792.6606
222 -51054.2349 -9801.0060
223 4343.6544 -51054.2349
224 -2478.9012 4343.6544
225 2191.1867 -2478.9012
226 23042.3805 2191.1867
227 -27973.2710 23042.3805
228 -22293.1650 -27973.2710
229 -42790.6342 -22293.1650
230 -15310.2602 -42790.6342
231 -4764.1115 -15310.2602
232 -33791.2286 -4764.1115
233 -5138.9973 -33791.2286
234 -26147.5728 -5138.9973
235 -13892.1666 -26147.5728
236 48155.2494 -13892.1666
237 -7026.6860 48155.2494
238 -11776.2481 -7026.6860
239 -22575.4880 -11776.2481
240 11872.2333 -22575.4880
241 -2865.5112 11872.2333
242 -16979.8399 -2865.5112
243 -8723.0126 -16979.8399
244 -1233.2436 -8723.0126
245 -9752.3572 -1233.2436
246 -23986.5503 -9752.3572
247 19778.9697 -23986.5503
248 6951.1852 19778.9697
249 -11385.7589 6951.1852
250 14067.6038 -11385.7589
251 6219.4263 14067.6038
252 12255.5388 6219.4263
253 -2553.0266 12255.5388
254 -22415.5021 -2553.0266
255 1339.3727 -22415.5021
256 -11086.3850 1339.3727
257 9677.3838 -11086.3850
258 12616.8351 9677.3838
259 6519.1264 12616.8351
260 -12160.9645 6519.1264
261 4187.6801 -12160.9645
262 11450.3466 4187.6801
263 -6430.8166 11450.3466
264 -13870.3897 -6430.8166
265 7357.8859 -13870.3897
266 -22621.4899 7357.8859
267 -2655.6633 -22621.4899
268 45266.9902 -2655.6633
269 -13870.6896 45266.9902
270 -5423.4625 -13870.6896
271 1104.7338 -5423.4625
272 2370.5278 1104.7338
273 3486.3539 2370.5278
274 10418.2933 3486.3539
275 -16162.5474 10418.2933
276 15056.4127 -16162.5474
277 10268.5886 15056.4127
278 -5482.6148 10268.5886
279 12558.4239 -5482.6148
280 -6644.6359 12558.4239
281 18134.3467 -6644.6359
282 -313.2582 18134.3467
283 12292.6779 -313.2582
284 452.9734 12292.6779
285 -4637.9126 452.9734
286 1227.3614 -4637.9126
287 -1707.1601 1227.3614
288 -2517.9042 -1707.1601
> 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/7mrmo1355263341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8ri3r1355263341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9r3co1355263341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10cs021355263341.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11n60j1355263341.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/122s6t1355263341.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/13c1xj1355263341.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/143zn81355263341.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/15fbr01355263341.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/169a2y1355263341.tab")
+ }
>
> try(system("convert tmp/1edrt1355263341.ps tmp/1edrt1355263341.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ard01355263341.ps tmp/2ard01355263341.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wtc31355263341.ps tmp/3wtc31355263341.png",intern=TRUE))
character(0)
> try(system("convert tmp/4x1g51355263341.ps tmp/4x1g51355263341.png",intern=TRUE))
character(0)
> try(system("convert tmp/528xq1355263341.ps tmp/528xq1355263341.png",intern=TRUE))
character(0)
> try(system("convert tmp/66y901355263341.ps tmp/66y901355263341.png",intern=TRUE))
character(0)
> try(system("convert tmp/7mrmo1355263341.ps tmp/7mrmo1355263341.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ri3r1355263341.ps tmp/8ri3r1355263341.png",intern=TRUE))
character(0)
> try(system("convert tmp/9r3co1355263341.ps tmp/9r3co1355263341.png",intern=TRUE))
character(0)
> try(system("convert tmp/10cs021355263341.ps tmp/10cs021355263341.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
16.874 1.112 17.994