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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+ ,72535
+ ,14
+ ,329
+ ,44
+ ,0
+ ,17
+ ,16
+ ,64)
+ ,dim=c(9
+ ,289)
+ ,dimnames=list(c('pageviews'
+ ,'time_in_rfc'
+ ,'logins'
+ ,'compendium_views_info'
+ ,'compendium_views_pr'
+ ,'shared_compendiums'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'feedback_messages_p1')
+ ,1:289))
> y <- array(NA,dim=c(9,289),dimnames=list(c('pageviews','time_in_rfc','logins','compendium_views_info','compendium_views_pr','shared_compendiums','blogged_computations','compendiums_reviewed','feedback_messages_p1'),1:289))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
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
pageviews time_in_rfc logins compendium_views_info compendium_views_pr
1 1418 210907 56 396 81
2 869 120982 56 297 55
3 1530 176508 54 559 50
4 2172 179321 89 967 125
5 901 123185 40 270 40
6 463 52746 25 143 37
7 3201 385534 92 1562 63
8 371 33170 18 109 44
9 1192 101645 63 371 88
10 1583 149061 44 656 66
11 1439 165446 33 511 57
12 1764 237213 84 655 74
13 1495 173326 88 465 49
14 1373 133131 55 525 52
15 2187 258873 60 885 88
16 1491 180083 66 497 36
17 4041 324799 154 1436 108
18 1706 230964 53 612 43
19 2152 236785 119 865 75
20 1036 135473 41 385 32
21 1882 202925 61 567 44
22 1929 215147 58 639 85
23 2242 344297 75 963 86
24 1220 153935 33 398 56
25 1289 132943 40 410 50
26 2515 174724 92 966 135
27 2147 174415 100 801 63
28 2352 225548 112 892 81
29 1638 223632 73 513 52
30 1222 124817 40 469 44
31 1812 221698 45 683 113
32 1677 210767 60 643 39
33 1579 170266 62 535 73
34 1731 260561 75 625 48
35 807 84853 31 264 33
36 2452 294424 77 992 59
37 829 101011 34 238 41
38 1940 215641 46 818 69
39 2662 325107 99 937 64
40 186 7176 17 70 1
41 1499 167542 66 507 59
42 865 106408 30 260 32
43 1793 96560 76 503 129
44 2527 265769 146 927 37
45 2747 269651 67 1269 31
46 1324 149112 56 537 65
47 2702 175824 107 910 107
48 1383 152871 58 532 74
49 1179 111665 34 345 54
50 2099 116408 61 918 76
51 4308 362301 119 1635 715
52 918 78800 42 330 57
53 1831 183167 66 557 66
54 3373 277965 89 1178 106
55 1713 150629 44 740 54
56 1438 168809 66 452 32
57 496 24188 24 218 20
58 2253 329267 259 764 71
59 744 65029 17 255 21
60 1161 101097 64 454 70
61 2352 218946 41 866 112
62 2144 244052 68 574 66
63 4691 341570 168 1276 190
64 1112 103597 43 379 66
65 2694 233328 132 825 165
66 1973 256462 105 798 56
67 1769 206161 71 663 61
68 3148 311473 112 1069 53
69 2474 235800 94 921 127
70 2084 177939 82 858 63
71 1954 207176 70 711 38
72 1226 196553 57 503 50
73 1389 174184 53 382 52
74 1496 143246 103 464 42
75 2269 187559 121 717 76
76 1833 187681 62 690 67
77 1268 119016 52 462 50
78 1943 182192 52 657 53
79 893 73566 32 385 39
80 1762 194979 62 577 50
81 1403 167488 45 619 77
82 1425 143756 46 479 57
83 1857 275541 63 817 73
84 1840 243199 75 752 34
85 1502 182999 88 430 39
86 1441 135649 46 451 46
87 1420 152299 53 537 63
88 1416 120221 37 519 35
89 2970 346485 90 1000 106
90 1317 145790 63 637 43
91 1644 193339 78 465 47
92 870 80953 25 437 31
93 1654 122774 45 711 162
94 1054 130585 46 299 57
95 937 112611 41 248 36
96 3004 286468 144 1162 263
97 2008 241066 82 714 78
98 2547 148446 91 905 63
99 1885 204713 71 649 54
100 1626 182079 63 512 63
101 1468 140344 53 472 77
102 2445 220516 62 905 79
103 1964 243060 63 786 110
104 1381 162765 32 489 56
105 1369 182613 39 479 56
106 1659 232138 62 617 43
107 2888 265318 117 925 111
108 1290 85574 34 351 71
109 2845 310839 92 1144 62
110 1982 225060 93 669 56
111 1904 232317 54 707 74
112 1391 144966 144 458 60
113 602 43287 14 214 43
114 1743 155754 61 599 68
115 1559 164709 109 572 53
116 2014 201940 38 897 87
117 2143 235454 73 819 46
118 2146 220801 75 720 105
119 874 99466 50 273 32
120 1590 92661 61 508 133
121 1590 133328 55 506 79
122 1210 61361 77 451 51
123 2072 125930 75 699 207
124 1281 100750 72 407 67
125 1401 224549 50 465 47
126 834 82316 32 245 34
127 1105 102010 53 370 66
128 1272 101523 42 316 76
129 1944 243511 71 603 65
130 391 22938 10 154 9
131 761 41566 35 229 42
132 1605 152474 65 577 45
133 530 61857 25 192 25
134 1988 99923 66 617 115
135 1386 132487 41 411 97
136 2395 317394 86 975 53
137 387 21054 16 146 2
138 1742 209641 42 705 52
139 620 22648 19 184 44
140 449 31414 19 200 22
141 800 46698 45 274 35
142 1684 131698 65 502 74
143 1050 91735 35 382 103
144 2699 244749 95 964 144
145 1606 184510 49 537 60
146 1502 79863 37 438 134
147 1204 128423 64 369 89
148 1138 97839 38 417 42
149 568 38214 34 276 52
150 1459 151101 32 514 98
151 2158 272458 65 822 99
152 1111 172494 52 389 52
153 1421 108043 62 466 29
154 2833 328107 65 1255 125
155 1955 250579 83 694 106
156 2922 351067 95 1024 95
157 1002 158015 29 400 40
158 1060 98866 18 397 140
159 956 85439 33 350 43
160 2186 229242 247 719 128
161 3604 351619 139 1277 142
162 1035 84207 29 356 73
163 1417 120445 118 457 72
164 3261 324598 110 1402 128
165 1587 131069 67 600 61
166 1424 204271 42 480 73
167 1701 165543 65 595 148
168 1249 141722 94 436 64
169 946 116048 64 230 45
170 1926 250047 81 651 58
171 3352 299775 95 1367 97
172 1641 195838 67 564 50
173 2035 173260 63 716 37
174 2312 254488 83 747 50
175 1369 104389 45 467 105
176 1577 136084 30 671 69
177 2201 199476 70 861 46
178 961 92499 32 319 57
179 1900 224330 83 612 52
180 1254 135781 31 433 98
181 1335 74408 67 434 61
182 1597 81240 66 503 89
183 207 14688 10 85 0
184 1645 181633 70 564 48
185 2429 271856 103 824 91
186 151 7199 5 74 0
187 474 46660 20 259 7
188 141 17547 5 69 3
189 1639 133368 36 535 54
190 872 95227 34 239 70
191 1318 152601 48 438 36
192 1018 98146 40 459 37
193 1383 79619 43 426 123
194 1314 59194 31 288 247
195 1335 139942 42 498 46
196 1403 118612 46 454 72
197 910 72880 33 376 41
198 616 65475 18 225 24
199 1407 99643 55 555 45
200 771 71965 35 252 33
201 766 77272 59 208 27
202 473 49289 19 130 36
203 1376 135131 66 481 87
204 1232 108446 60 389 90
205 1521 89746 36 565 114
206 572 44296 25 173 31
207 1059 77648 47 278 45
208 1544 181528 54 609 69
209 1230 134019 53 422 51
210 1206 124064 40 445 34
211 1205 92630 40 387 60
212 1255 121848 39 339 45
213 613 52915 14 181 54
214 721 81872 45 245 25
215 1109 58981 36 384 38
216 740 53515 28 212 52
217 1126 60812 44 399 67
218 728 56375 30 229 74
219 689 65490 22 224 38
220 592 80949 17 203 30
221 995 76302 31 333 26
222 1613 104011 55 384 67
223 2048 98104 54 636 132
224 705 67989 21 185 42
225 301 30989 14 93 35
226 1803 135458 81 581 118
227 799 73504 35 248 68
228 861 63123 43 304 43
229 1186 61254 46 344 76
230 1451 74914 30 407 64
231 628 31774 23 170 48
232 1161 81437 38 312 64
233 1463 87186 54 507 56
234 742 50090 20 224 71
235 979 65745 53 340 75
236 675 56653 45 168 39
237 1241 158399 39 443 42
238 676 46455 20 204 39
239 1049 73624 24 367 93
240 620 38395 31 210 38
241 1081 91899 35 335 60
242 1688 139526 151 364 71
243 736 52164 52 178 52
244 617 51567 30 206 27
245 812 70551 31 279 59
246 1051 84856 29 387 40
247 1656 102538 57 490 79
248 705 86678 40 238 44
249 945 85709 44 343 65
250 554 34662 25 232 10
251 1597 150580 77 530 124
252 982 99611 35 291 81
253 222 19349 11 67 15
254 1212 99373 63 397 92
255 1143 86230 44 467 42
256 435 30837 19 178 10
257 532 31706 13 175 24
258 882 89806 42 299 64
259 608 62088 38 154 45
260 459 40151 29 106 22
261 578 27634 20 189 56
262 826 76990 27 194 94
263 509 37460 20 135 19
264 717 54157 19 201 35
265 637 49862 37 207 32
266 857 84337 26 280 35
267 830 64175 42 260 48
268 652 59382 49 227 49
269 707 119308 30 239 48
270 954 76702 49 333 62
271 1461 103425 67 428 96
272 672 70344 28 230 45
273 778 43410 19 292 63
274 1141 104838 49 350 71
275 680 62215 27 186 26
276 1090 69304 30 326 48
277 616 53117 22 155 29
278 285 19764 12 75 19
279 1145 86680 31 361 45
280 733 84105 20 261 45
281 888 77945 20 299 67
282 849 89113 39 300 30
283 1182 91005 29 450 36
284 528 40248 16 183 34
285 642 64187 27 238 36
286 947 50857 21 165 34
287 819 56613 19 234 37
288 757 62792 35 176 46
289 894 72535 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
1 115
2 109
3 146
4 116
5 68
6 101
7 96
8 67
9 44
10 100
11 93
12 140
13 166
14 99
15 139
16 130
17 181
18 116
19 116
20 88
21 139
22 135
23 108
24 89
25 156
26 129
27 118
28 118
29 125
30 95
31 126
32 135
33 154
34 165
35 113
36 127
37 52
38 121
39 136
40 0
41 108
42 46
43 54
44 124
45 115
46 128
47 80
48 97
49 104
50 59
51 125
52 82
53 149
54 149
55 122
56 118
57 12
58 144
59 67
60 52
61 108
62 166
63 80
64 60
65 107
66 127
67 107
68 146
69 84
70 141
71 123
72 111
73 98
74 105
75 135
76 107
77 85
78 155
79 88
80 155
81 104
82 132
83 127
84 108
85 129
86 116
87 122
88 85
89 147
90 99
91 87
92 28
93 90
94 109
95 78
96 111
97 158
98 141
99 122
100 124
101 93
102 124
103 112
104 108
105 99
106 117
107 199
108 78
109 91
110 158
111 126
112 122
113 71
114 75
115 115
116 119
117 124
118 72
119 91
120 45
121 78
122 39
123 68
124 119
125 117
126 39
127 50
128 88
129 155
130 0
131 36
132 123
133 32
134 99
135 136
136 117
137 0
138 88
139 39
140 25
141 52
142 75
143 71
144 124
145 151
146 71
147 145
148 87
149 27
150 131
151 162
152 165
153 54
154 159
155 147
156 170
157 119
158 49
159 104
160 120
161 150
162 112
163 59
164 136
165 107
166 130
167 115
168 107
169 75
170 71
171 120
172 116
173 79
174 150
175 156
176 51
177 118
178 71
179 144
180 47
181 28
182 68
183 0
184 110
185 147
186 0
187 15
188 4
189 64
190 111
191 85
192 68
193 40
194 80
195 88
196 48
197 76
198 51
199 67
200 59
201 61
202 76
203 60
204 68
205 71
206 76
207 62
208 61
209 67
210 88
211 30
212 64
213 68
214 64
215 91
216 88
217 52
218 49
219 62
220 61
221 76
222 88
223 66
224 71
225 68
226 48
227 25
228 68
229 41
230 90
231 66
232 54
233 59
234 60
235 77
236 68
237 72
238 67
239 64
240 63
241 59
242 84
243 64
244 56
245 54
246 67
247 58
248 59
249 40
250 22
251 83
252 81
253 2
254 72
255 61
256 15
257 32
258 62
259 58
260 36
261 59
262 68
263 21
264 55
265 54
266 55
267 72
268 41
269 61
270 67
271 76
272 64
273 3
274 63
275 40
276 69
277 48
278 8
279 52
280 66
281 76
282 43
283 39
284 14
285 61
286 71
287 44
288 60
289 64
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time_in_rfc logins
96.3523151 0.0004025 3.2605752
compendium_views_info compendium_views_pr shared_compendiums
1.7549834 1.5306145 5.8290647
blogged_computations compendiums_reviewed feedback_messages_p1
1.7682318 -4.5291022 1.3585625
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-475.16 -80.05 -11.40 72.24 1193.61
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 96.3523151 25.1247745 3.835 0.000155 ***
time_in_rfc 0.0004025 0.0003410 1.180 0.238873
logins 3.2605752 0.4108065 7.937 5.02e-14 ***
compendium_views_info 1.7549834 0.0845551 20.756 < 2e-16 ***
compendium_views_pr 1.5306145 0.2229820 6.864 4.30e-11 ***
shared_compendiums 5.8290647 3.8549636 1.512 0.131638
blogged_computations 1.7682318 0.5216106 3.390 0.000800 ***
compendiums_reviewed -4.5291022 5.0612472 -0.895 0.371631
feedback_messages_p1 1.3585625 1.3654257 0.995 0.320608
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 160.7 on 280 degrees of freedom
Multiple R-squared: 0.9537, Adjusted R-squared: 0.9524
F-statistic: 721 on 8 and 280 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,] 0.16398427 3.279685e-01 8.360157e-01
[2,] 0.31866777 6.373355e-01 6.813322e-01
[3,] 0.19507689 3.901538e-01 8.049231e-01
[4,] 0.11255626 2.251125e-01 8.874437e-01
[5,] 0.07197142 1.439428e-01 9.280286e-01
[6,] 0.87129191 2.574162e-01 1.287081e-01
[7,] 0.82832636 3.433473e-01 1.716736e-01
[8,] 0.84061462 3.187708e-01 1.593854e-01
[9,] 0.80087214 3.982557e-01 1.991279e-01
[10,] 0.81502540 3.699492e-01 1.849746e-01
[11,] 0.77286271 4.542746e-01 2.271373e-01
[12,] 0.72498207 5.500359e-01 2.750179e-01
[13,] 0.70697210 5.860558e-01 2.930279e-01
[14,] 0.64561028 7.087794e-01 3.543897e-01
[15,] 0.58150470 8.369906e-01 4.184953e-01
[16,] 0.52351684 9.529663e-01 4.764832e-01
[17,] 0.45893829 9.178766e-01 5.410617e-01
[18,] 0.39594812 7.918962e-01 6.040519e-01
[19,] 0.33473556 6.694711e-01 6.652644e-01
[20,] 0.28291827 5.658365e-01 7.170817e-01
[21,] 0.24625909 4.925182e-01 7.537409e-01
[22,] 0.20366206 4.073241e-01 7.963379e-01
[23,] 0.21951120 4.390224e-01 7.804888e-01
[24,] 0.17762476 3.552495e-01 8.223752e-01
[25,] 0.14664886 2.932977e-01 8.533511e-01
[26,] 0.13403939 2.680788e-01 8.659606e-01
[27,] 0.10790736 2.158147e-01 8.920926e-01
[28,] 0.15836610 3.167322e-01 8.416339e-01
[29,] 0.12796390 2.559278e-01 8.720361e-01
[30,] 0.10174646 2.034929e-01 8.982535e-01
[31,] 0.09348525 1.869705e-01 9.065148e-01
[32,] 0.15917468 3.183494e-01 8.408253e-01
[33,] 0.13151902 2.630380e-01 8.684810e-01
[34,] 0.12010303 2.402061e-01 8.798970e-01
[35,] 0.12724346 2.544869e-01 8.727565e-01
[36,] 0.25905517 5.181103e-01 7.409448e-01
[37,] 0.24165132 4.833026e-01 7.583487e-01
[38,] 0.25218563 5.043713e-01 7.478144e-01
[39,] 0.22056191 4.411238e-01 7.794381e-01
[40,] 0.31528566 6.305713e-01 6.847143e-01
[41,] 0.28035910 5.607182e-01 7.196409e-01
[42,] 0.28208986 5.641797e-01 7.179101e-01
[43,] 0.66712540 6.657492e-01 3.328746e-01
[44,] 0.64520721 7.095856e-01 3.547928e-01
[45,] 0.60504964 7.899007e-01 3.949504e-01
[46,] 0.56973692 8.605262e-01 4.302631e-01
[47,] 0.81022657 3.795469e-01 1.897734e-01
[48,] 0.78198718 4.360256e-01 2.180128e-01
[49,] 0.76482991 4.703402e-01 2.351701e-01
[50,] 0.78781946 4.243611e-01 2.121805e-01
[51,] 0.90394069 1.921186e-01 9.605931e-02
[52,] 1.00000000 8.921657e-11 4.460828e-11
[53,] 1.00000000 1.678490e-10 8.392452e-11
[54,] 1.00000000 1.953451e-10 9.767254e-11
[55,] 1.00000000 4.611120e-11 2.305560e-11
[56,] 1.00000000 6.549174e-11 3.274587e-11
[57,] 1.00000000 1.591261e-11 7.956305e-12
[58,] 1.00000000 2.558858e-11 1.279429e-11
[59,] 1.00000000 3.780615e-11 1.890307e-11
[60,] 1.00000000 5.792834e-11 2.896417e-11
[61,] 1.00000000 5.109205e-11 2.554603e-11
[62,] 1.00000000 5.840464e-11 2.920232e-11
[63,] 1.00000000 1.053992e-10 5.269959e-11
[64,] 1.00000000 1.309124e-10 6.545620e-11
[65,] 1.00000000 1.960352e-10 9.801758e-11
[66,] 1.00000000 1.701660e-10 8.508300e-11
[67,] 1.00000000 1.840583e-10 9.202915e-11
[68,] 1.00000000 2.008155e-10 1.004077e-10
[69,] 1.00000000 2.736189e-10 1.368094e-10
[70,] 1.00000000 1.205675e-10 6.028376e-11
[71,] 1.00000000 2.176398e-10 1.088199e-10
[72,] 1.00000000 2.401328e-11 1.200664e-11
[73,] 1.00000000 2.488561e-11 1.244281e-11
[74,] 1.00000000 4.383842e-11 2.191921e-11
[75,] 1.00000000 7.071934e-11 3.535967e-11
[76,] 1.00000000 1.142201e-10 5.711004e-11
[77,] 1.00000000 1.776865e-10 8.884325e-11
[78,] 1.00000000 5.473131e-11 2.736565e-11
[79,] 1.00000000 8.802486e-12 4.401243e-12
[80,] 1.00000000 7.913079e-12 3.956539e-12
[81,] 1.00000000 4.402351e-12 2.201175e-12
[82,] 1.00000000 3.061055e-12 1.530528e-12
[83,] 1.00000000 5.520399e-12 2.760200e-12
[84,] 1.00000000 8.388971e-12 4.194485e-12
[85,] 1.00000000 2.338947e-12 1.169474e-12
[86,] 1.00000000 4.219802e-12 2.109901e-12
[87,] 1.00000000 4.603799e-12 2.301900e-12
[88,] 1.00000000 5.912584e-12 2.956292e-12
[89,] 1.00000000 1.068825e-11 5.344127e-12
[90,] 1.00000000 1.499447e-11 7.497237e-12
[91,] 1.00000000 1.635209e-11 8.176047e-12
[92,] 1.00000000 1.532995e-11 7.664973e-12
[93,] 1.00000000 2.726813e-11 1.363407e-11
[94,] 1.00000000 4.870978e-11 2.435489e-11
[95,] 1.00000000 5.901985e-11 2.950993e-11
[96,] 1.00000000 4.197337e-11 2.098669e-11
[97,] 1.00000000 1.486456e-11 7.432280e-12
[98,] 1.00000000 2.214874e-11 1.107437e-11
[99,] 1.00000000 3.997207e-11 1.998603e-11
[100,] 1.00000000 6.758833e-11 3.379416e-11
[101,] 1.00000000 4.706549e-11 2.353274e-11
[102,] 1.00000000 7.413977e-11 3.706989e-11
[103,] 1.00000000 1.178618e-10 5.893092e-11
[104,] 1.00000000 9.561012e-11 4.780506e-11
[105,] 1.00000000 5.240120e-11 2.620060e-11
[106,] 1.00000000 7.954446e-11 3.977223e-11
[107,] 1.00000000 6.968301e-11 3.484150e-11
[108,] 1.00000000 1.235946e-10 6.179732e-11
[109,] 1.00000000 1.642297e-10 8.211485e-11
[110,] 1.00000000 1.815076e-10 9.075378e-11
[111,] 1.00000000 2.995978e-10 1.497989e-10
[112,] 1.00000000 4.349719e-10 2.174859e-10
[113,] 1.00000000 6.617217e-10 3.308609e-10
[114,] 1.00000000 1.125622e-09 5.628108e-10
[115,] 1.00000000 1.826715e-09 9.133573e-10
[116,] 1.00000000 2.970856e-09 1.485428e-09
[117,] 1.00000000 2.022835e-09 1.011418e-09
[118,] 1.00000000 2.376893e-09 1.188446e-09
[119,] 1.00000000 3.959137e-09 1.979568e-09
[120,] 1.00000000 6.331552e-09 3.165776e-09
[121,] 0.99999999 1.021977e-08 5.109883e-09
[122,] 0.99999999 1.375124e-08 6.875619e-09
[123,] 1.00000000 4.497013e-09 2.248507e-09
[124,] 1.00000000 6.351071e-09 3.175535e-09
[125,] 1.00000000 7.248183e-09 3.624091e-09
[126,] 0.99999999 1.188469e-08 5.942343e-09
[127,] 0.99999999 1.669584e-08 8.347920e-09
[128,] 0.99999999 2.558748e-08 1.279374e-08
[129,] 0.99999999 2.976018e-08 1.488009e-08
[130,] 0.99999998 4.845557e-08 2.422779e-08
[131,] 0.99999999 2.931642e-08 1.465821e-08
[132,] 0.99999998 4.276675e-08 2.138338e-08
[133,] 0.99999997 6.426133e-08 3.213066e-08
[134,] 0.99999995 9.941740e-08 4.970870e-08
[135,] 0.99999997 5.891818e-08 2.945909e-08
[136,] 0.99999996 7.155935e-08 3.577968e-08
[137,] 0.99999994 1.152349e-07 5.761747e-08
[138,] 0.99999997 5.381760e-08 2.690880e-08
[139,] 0.99999996 8.685031e-08 4.342515e-08
[140,] 0.99999993 1.308648e-07 6.543238e-08
[141,] 0.99999991 1.735043e-07 8.675214e-08
[142,] 0.99999991 1.898794e-07 9.493969e-08
[143,] 0.99999999 2.213997e-08 1.106998e-08
[144,] 0.99999999 1.860050e-08 9.300250e-09
[145,] 0.99999999 2.510994e-08 1.255497e-08
[146,] 0.99999999 2.139905e-08 1.069952e-08
[147,] 0.99999999 1.858299e-08 9.291497e-09
[148,] 0.99999998 3.040948e-08 1.520474e-08
[149,] 1.00000000 3.689859e-10 1.844930e-10
[150,] 1.00000000 3.177981e-10 1.588991e-10
[151,] 1.00000000 2.762923e-10 1.381462e-10
[152,] 1.00000000 3.184016e-10 1.592008e-10
[153,] 1.00000000 9.108079e-11 4.554040e-11
[154,] 1.00000000 1.194238e-10 5.971190e-11
[155,] 1.00000000 2.086034e-10 1.043017e-10
[156,] 1.00000000 1.703089e-10 8.515447e-11
[157,] 1.00000000 8.186077e-11 4.093038e-11
[158,] 1.00000000 1.499059e-10 7.495295e-11
[159,] 1.00000000 2.070025e-10 1.035012e-10
[160,] 1.00000000 1.475560e-10 7.377798e-11
[161,] 1.00000000 2.432560e-10 1.216280e-10
[162,] 1.00000000 1.536640e-10 7.683202e-11
[163,] 1.00000000 2.459680e-10 1.229840e-10
[164,] 1.00000000 1.416575e-11 7.082877e-12
[165,] 1.00000000 2.662995e-11 1.331498e-11
[166,] 1.00000000 3.964904e-11 1.982452e-11
[167,] 1.00000000 7.465624e-11 3.732812e-11
[168,] 1.00000000 8.033134e-11 4.016567e-11
[169,] 1.00000000 1.358871e-10 6.794357e-11
[170,] 1.00000000 2.419401e-10 1.209701e-10
[171,] 1.00000000 3.992385e-10 1.996193e-10
[172,] 1.00000000 7.233553e-10 3.616777e-10
[173,] 1.00000000 1.268734e-09 6.343669e-10
[174,] 1.00000000 1.031062e-09 5.155310e-10
[175,] 1.00000000 1.827339e-09 9.136697e-10
[176,] 1.00000000 1.792612e-09 8.963059e-10
[177,] 1.00000000 3.194573e-09 1.597287e-09
[178,] 1.00000000 9.315527e-10 4.657764e-10
[179,] 1.00000000 1.563955e-09 7.819776e-10
[180,] 1.00000000 2.787097e-09 1.393548e-09
[181,] 1.00000000 2.335917e-09 1.167958e-09
[182,] 1.00000000 3.999284e-09 1.999642e-09
[183,] 1.00000000 6.017240e-09 3.008620e-09
[184,] 1.00000000 8.535769e-09 4.267884e-09
[185,] 0.99999999 1.483744e-08 7.418722e-09
[186,] 0.99999999 1.903084e-08 9.515418e-09
[187,] 0.99999998 3.156683e-08 1.578342e-08
[188,] 0.99999998 3.896422e-08 1.948211e-08
[189,] 0.99999997 5.983464e-08 2.991732e-08
[190,] 0.99999995 9.629136e-08 4.814568e-08
[191,] 0.99999992 1.607613e-07 8.038065e-08
[192,] 0.99999990 2.067938e-07 1.033969e-07
[193,] 0.99999983 3.459009e-07 1.729504e-07
[194,] 0.99999978 4.493625e-07 2.246812e-07
[195,] 0.99999961 7.741031e-07 3.870515e-07
[196,] 0.99999961 7.872873e-07 3.936437e-07
[197,] 0.99999952 9.691461e-07 4.845730e-07
[198,] 0.99999920 1.593006e-06 7.965030e-07
[199,] 0.99999909 1.822833e-06 9.114164e-07
[200,] 0.99999853 2.932073e-06 1.466036e-06
[201,] 0.99999932 1.361881e-06 6.809407e-07
[202,] 0.99999883 2.349351e-06 1.174676e-06
[203,] 0.99999868 2.633941e-06 1.316971e-06
[204,] 0.99999827 3.455953e-06 1.727976e-06
[205,] 0.99999712 5.754893e-06 2.877447e-06
[206,] 0.99999552 8.966179e-06 4.483090e-06
[207,] 0.99999755 4.904950e-06 2.452475e-06
[208,] 0.99999736 5.282963e-06 2.641482e-06
[209,] 0.99999547 9.054345e-06 4.527173e-06
[210,] 0.99999270 1.459754e-05 7.298772e-06
[211,] 0.99999793 4.144890e-06 2.072445e-06
[212,] 0.99999850 2.993951e-06 1.496976e-06
[213,] 0.99999766 4.673939e-06 2.336970e-06
[214,] 0.99999674 6.510975e-06 3.255488e-06
[215,] 0.99999447 1.106960e-05 5.534801e-06
[216,] 0.99999041 1.918765e-05 9.593824e-06
[217,] 0.99999148 1.704954e-05 8.524769e-06
[218,] 0.99999004 1.991183e-05 9.955916e-06
[219,] 0.99999875 2.494108e-06 1.247054e-06
[220,] 0.99999785 4.305637e-06 2.152818e-06
[221,] 0.99999888 2.240860e-06 1.120430e-06
[222,] 0.99999861 2.783352e-06 1.391676e-06
[223,] 0.99999753 4.949657e-06 2.474829e-06
[224,] 0.99999712 5.764669e-06 2.882335e-06
[225,] 0.99999510 9.808862e-06 4.904431e-06
[226,] 0.99999145 1.710874e-05 8.554368e-06
[227,] 0.99998458 3.083980e-05 1.541990e-05
[228,] 0.99997215 5.570198e-05 2.785099e-05
[229,] 0.99995927 8.145007e-05 4.072503e-05
[230,] 0.99995460 9.079481e-05 4.539740e-05
[231,] 0.99998435 3.129529e-05 1.564764e-05
[232,] 0.99997081 5.838799e-05 2.919400e-05
[233,] 0.99996345 7.309871e-05 3.654936e-05
[234,] 0.99993945 1.210941e-04 6.054705e-05
[235,] 0.99989386 2.122710e-04 1.061355e-04
[236,] 0.99998721 2.557602e-05 1.278801e-05
[237,] 0.99997933 4.134853e-05 2.067426e-05
[238,] 0.99996040 7.919196e-05 3.959598e-05
[239,] 0.99992833 1.433372e-04 7.166859e-05
[240,] 0.99987199 2.560205e-04 1.280103e-04
[241,] 0.99976346 4.730701e-04 2.365351e-04
[242,] 0.99958534 8.293118e-04 4.146559e-04
[243,] 0.99925103 1.497937e-03 7.489687e-04
[244,] 0.99877760 2.444799e-03 1.222399e-03
[245,] 0.99802373 3.952538e-03 1.976269e-03
[246,] 0.99663121 6.737576e-03 3.368788e-03
[247,] 0.99490038 1.019925e-02 5.099623e-03
[248,] 0.99215182 1.569636e-02 7.848182e-03
[249,] 0.98717202 2.565595e-02 1.282798e-02
[250,] 0.98618082 2.763836e-02 1.381918e-02
[251,] 0.97777484 4.445032e-02 2.222516e-02
[252,] 0.96806182 6.387636e-02 3.193818e-02
[253,] 0.95281437 9.437126e-02 4.718563e-02
[254,] 0.93636214 1.272757e-01 6.363786e-02
[255,] 0.91062077 1.787585e-01 8.937923e-02
[256,] 0.88034325 2.393135e-01 1.196567e-01
[257,] 0.89031490 2.193702e-01 1.096851e-01
[258,] 0.83967940 3.206412e-01 1.603206e-01
[259,] 0.93497141 1.300572e-01 6.502859e-02
[260,] 0.92016472 1.596706e-01 7.983528e-02
[261,] 0.89809114 2.038177e-01 1.019089e-01
[262,] 0.86045296 2.790941e-01 1.395470e-01
[263,] 0.81732857 3.653429e-01 1.826714e-01
[264,] 0.70991011 5.801798e-01 2.900899e-01
[265,] 0.93233045 1.353391e-01 6.766955e-02
[266,] 0.83905838 3.218832e-01 1.609416e-01
> postscript(file="/var/fisher/rcomp/tmp/13jr21355757840.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/2jqdy1355757840.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3vzhn1355757840.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4ox301355757840.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5tlns1355757840.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
57.6798828 -211.1919006 -73.3155276 -399.4575428 4.3621656 -80.6359710
7 8 9 10 11 12
-419.3535238 -67.3008317 18.2084336 -92.3784247 49.2937272 -120.5057620
13 14 15 16 17 18
-68.2207169 -74.4534012 -106.0886503 -6.8405877 313.9228077 -21.3807140
19 20 21 22 23 24
-231.3479483 -133.5868430 172.7165836 106.4582983 -217.2850490 44.6556044
25 26 27 28 29 30
-10.2219703 -92.3505370 3.2342002 -82.0178130 27.6983108 -44.3871727
31 32 33 34 35 36
-99.3004364 -96.5503859 41.1996790 -121.9158838 -46.5602033 -69.0985607
37 38 39 40 41 42
35.8793400 -79.3153985 199.3785887 -93.0496558 4.0429352 59.4621346
43 44 45 46 47 48
259.1423884 -40.8009629 -216.9445208 -206.2461204 306.2998277 -149.3446683
49 50 51 52 53 54
131.9711728 60.0315105 -447.8370309 -54.0687155 180.4846784 369.1989524
55 56 57 58 59 60
-152.8529938 48.3962509 -113.8718793 -475.1624331 10.6041186 -166.3948585
61 62 63 64 65 66
187.0054782 385.3468704 1193.6078568 4.9697952 162.5580897 -286.6329361
67 68 69 70 71 72
-119.8652769 304.6951656 -76.7227921 -125.9335690 72.2437938 -198.2108275
73 74 75 76 77 78
152.5138856 -40.4217227 128.3736714 -86.3211290 -182.2405238 134.1089792
79 80 81 82 83 84
-161.9208793 108.9432629 -259.8205232 -18.0831195 -352.7294299 -163.5651040
85 86 87 88 89 90
45.4086461 69.7278337 -75.2276623 70.8305166 287.2641839 -326.1184885
91 92 93 94 95 96
179.3462745 -243.2747568 -190.2532591 -21.2362904 74.5793076 -245.0863518
97 98 99 100 101 102
31.3524865 140.9810244 110.7659733 6.0500566 89.6989880 145.9166551
103 104 105 106 107 108
-130.0656520 19.0925394 -22.7588475 -131.7652288 222.4838210 247.3932436
109 110 111 112 113 114
-76.2894734 -2.1722051 -46.3320695 -218.6129482 -55.5131295 64.2742346
115 116 117 118 119 120
-203.0774446 -208.9161228 -84.4101044 179.6351448 -22.4733925 101.6573247
121 122 123 124 125 126
137.3088693 -78.0482568 32.7228342 -80.0508839 25.8886129 39.4164839
127 128 129 130 131 132
-31.6304327 202.7034093 104.8668642 -47.9225275 30.3299155 -55.7631372
133 134 135 136 137 138
-105.6237845 278.3161756 85.6132949 -131.2276168 -36.3568089 -42.1562115
139 140 141 142 143 144
46.9932911 -136.1759841 -32.8317664 206.5058036 -52.7614988 78.2307490
145 146 147 148 149 150
63.4080808 225.1535720 -64.6304226 16.8944862 -247.2992277 29.4479437
151 152 153 154 155 156
-56.2313634 -97.3560742 121.4436705 -277.0805184 -150.5065774 146.9757689
157 158 159 160 161 162
-141.3153230 -97.7445120 -33.4574105 -423.0688184 240.5327911 -31.4694389
163 164 165 166 167 168
-96.1529741 -198.0591179 -42.8357032 -26.4077259 -85.5701983 -130.6938423
169 170 171 172 173 174
22.0197279 146.2038038 41.7153381 -38.2645734 248.0990391 157.4655504
175 176 177 178 179 180
-190.4823536 -13.2958764 33.8023816 16.8567896 32.6271117 0.3407809
181 182 183 184 185 186
54.2810268 115.8269403 -84.1160307 75.6920271 71.3046863 -106.7989518
187 188 189 190 191 192
-190.5496774 -105.3081391 264.2853478 28.5845417 80.1620898 -152.3570334
193 194 195 196 197 198
82.2350536 161.9106251 -14.4063869 83.9525917 -87.8651558 -47.3584557
199 200 201 202 203 204
-29.8901543 -35.8332720 -19.3865537 -15.2952793 -48.0166510 15.8056306
205 206 207 208 209 210
23.1596475 -5.1066091 154.8063703 -42.8699293 22.1512730 -5.4918744
211 212 213 214 215 216
94.3460670 243.2504973 3.1748268 -94.3311176 79.1887566 38.7525424
217 218 219 220 221 222
1.1770079 -70.1923666 -33.7169081 -24.3987473 78.7078792 419.8967425
223 224 225 226 227 228
296.3011019 68.2510590 -94.4860759 83.3828141 -23.3027836 -81.6298584
229 230 231 232 233 234
133.1884317 334.4529979 53.5503181 187.0763910 118.2669256 25.6759390
235 236 237 238 239 240
-83.5856812 -23.4616002 55.0293154 25.0989118 -4.6636791 -61.0082732
241 242 243 244 245 246
109.7380326 227.1399328 -13.9413349 -62.2398652 -39.8664466 14.3993051
247 248 249 250 251 252
246.5654994 -75.1309458 -76.9463277 -94.8212632 8.1797032 9.3274750
253 254 255 256 257 258
-79.7241323 -10.6484316 -58.3959220 -79.8152172 -7.5142844 -69.6473553
259 260 261 262 263 264
-11.5347536 -4.2082769 -23.3179041 36.6283743 60.6880479 58.3681575
265 266 267 268 269 270
-52.3375583 18.4566316 -40.6072596 -154.0317411 -95.0878150 -70.0988083
271 272 273 274 275 276
153.4052178 -66.3304476 -18.5824444 19.4762366 52.8606925 108.9521865
277 278 279 280 281 282
76.4732404 -44.4606989 125.9367620 -32.0720174 1.0663252 -11.4004737
283 284 285 286 287 288
37.6900412 -30.8012814 -69.0982104 387.6947786 132.8329310 78.8827456
289
33.5277500
> postscript(file="/var/fisher/rcomp/tmp/61ph51355757840.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 57.6798828 NA
1 -211.1919006 57.6798828
2 -73.3155276 -211.1919006
3 -399.4575428 -73.3155276
4 4.3621656 -399.4575428
5 -80.6359710 4.3621656
6 -419.3535238 -80.6359710
7 -67.3008317 -419.3535238
8 18.2084336 -67.3008317
9 -92.3784247 18.2084336
10 49.2937272 -92.3784247
11 -120.5057620 49.2937272
12 -68.2207169 -120.5057620
13 -74.4534012 -68.2207169
14 -106.0886503 -74.4534012
15 -6.8405877 -106.0886503
16 313.9228077 -6.8405877
17 -21.3807140 313.9228077
18 -231.3479483 -21.3807140
19 -133.5868430 -231.3479483
20 172.7165836 -133.5868430
21 106.4582983 172.7165836
22 -217.2850490 106.4582983
23 44.6556044 -217.2850490
24 -10.2219703 44.6556044
25 -92.3505370 -10.2219703
26 3.2342002 -92.3505370
27 -82.0178130 3.2342002
28 27.6983108 -82.0178130
29 -44.3871727 27.6983108
30 -99.3004364 -44.3871727
31 -96.5503859 -99.3004364
32 41.1996790 -96.5503859
33 -121.9158838 41.1996790
34 -46.5602033 -121.9158838
35 -69.0985607 -46.5602033
36 35.8793400 -69.0985607
37 -79.3153985 35.8793400
38 199.3785887 -79.3153985
39 -93.0496558 199.3785887
40 4.0429352 -93.0496558
41 59.4621346 4.0429352
42 259.1423884 59.4621346
43 -40.8009629 259.1423884
44 -216.9445208 -40.8009629
45 -206.2461204 -216.9445208
46 306.2998277 -206.2461204
47 -149.3446683 306.2998277
48 131.9711728 -149.3446683
49 60.0315105 131.9711728
50 -447.8370309 60.0315105
51 -54.0687155 -447.8370309
52 180.4846784 -54.0687155
53 369.1989524 180.4846784
54 -152.8529938 369.1989524
55 48.3962509 -152.8529938
56 -113.8718793 48.3962509
57 -475.1624331 -113.8718793
58 10.6041186 -475.1624331
59 -166.3948585 10.6041186
60 187.0054782 -166.3948585
61 385.3468704 187.0054782
62 1193.6078568 385.3468704
63 4.9697952 1193.6078568
64 162.5580897 4.9697952
65 -286.6329361 162.5580897
66 -119.8652769 -286.6329361
67 304.6951656 -119.8652769
68 -76.7227921 304.6951656
69 -125.9335690 -76.7227921
70 72.2437938 -125.9335690
71 -198.2108275 72.2437938
72 152.5138856 -198.2108275
73 -40.4217227 152.5138856
74 128.3736714 -40.4217227
75 -86.3211290 128.3736714
76 -182.2405238 -86.3211290
77 134.1089792 -182.2405238
78 -161.9208793 134.1089792
79 108.9432629 -161.9208793
80 -259.8205232 108.9432629
81 -18.0831195 -259.8205232
82 -352.7294299 -18.0831195
83 -163.5651040 -352.7294299
84 45.4086461 -163.5651040
85 69.7278337 45.4086461
86 -75.2276623 69.7278337
87 70.8305166 -75.2276623
88 287.2641839 70.8305166
89 -326.1184885 287.2641839
90 179.3462745 -326.1184885
91 -243.2747568 179.3462745
92 -190.2532591 -243.2747568
93 -21.2362904 -190.2532591
94 74.5793076 -21.2362904
95 -245.0863518 74.5793076
96 31.3524865 -245.0863518
97 140.9810244 31.3524865
98 110.7659733 140.9810244
99 6.0500566 110.7659733
100 89.6989880 6.0500566
101 145.9166551 89.6989880
102 -130.0656520 145.9166551
103 19.0925394 -130.0656520
104 -22.7588475 19.0925394
105 -131.7652288 -22.7588475
106 222.4838210 -131.7652288
107 247.3932436 222.4838210
108 -76.2894734 247.3932436
109 -2.1722051 -76.2894734
110 -46.3320695 -2.1722051
111 -218.6129482 -46.3320695
112 -55.5131295 -218.6129482
113 64.2742346 -55.5131295
114 -203.0774446 64.2742346
115 -208.9161228 -203.0774446
116 -84.4101044 -208.9161228
117 179.6351448 -84.4101044
118 -22.4733925 179.6351448
119 101.6573247 -22.4733925
120 137.3088693 101.6573247
121 -78.0482568 137.3088693
122 32.7228342 -78.0482568
123 -80.0508839 32.7228342
124 25.8886129 -80.0508839
125 39.4164839 25.8886129
126 -31.6304327 39.4164839
127 202.7034093 -31.6304327
128 104.8668642 202.7034093
129 -47.9225275 104.8668642
130 30.3299155 -47.9225275
131 -55.7631372 30.3299155
132 -105.6237845 -55.7631372
133 278.3161756 -105.6237845
134 85.6132949 278.3161756
135 -131.2276168 85.6132949
136 -36.3568089 -131.2276168
137 -42.1562115 -36.3568089
138 46.9932911 -42.1562115
139 -136.1759841 46.9932911
140 -32.8317664 -136.1759841
141 206.5058036 -32.8317664
142 -52.7614988 206.5058036
143 78.2307490 -52.7614988
144 63.4080808 78.2307490
145 225.1535720 63.4080808
146 -64.6304226 225.1535720
147 16.8944862 -64.6304226
148 -247.2992277 16.8944862
149 29.4479437 -247.2992277
150 -56.2313634 29.4479437
151 -97.3560742 -56.2313634
152 121.4436705 -97.3560742
153 -277.0805184 121.4436705
154 -150.5065774 -277.0805184
155 146.9757689 -150.5065774
156 -141.3153230 146.9757689
157 -97.7445120 -141.3153230
158 -33.4574105 -97.7445120
159 -423.0688184 -33.4574105
160 240.5327911 -423.0688184
161 -31.4694389 240.5327911
162 -96.1529741 -31.4694389
163 -198.0591179 -96.1529741
164 -42.8357032 -198.0591179
165 -26.4077259 -42.8357032
166 -85.5701983 -26.4077259
167 -130.6938423 -85.5701983
168 22.0197279 -130.6938423
169 146.2038038 22.0197279
170 41.7153381 146.2038038
171 -38.2645734 41.7153381
172 248.0990391 -38.2645734
173 157.4655504 248.0990391
174 -190.4823536 157.4655504
175 -13.2958764 -190.4823536
176 33.8023816 -13.2958764
177 16.8567896 33.8023816
178 32.6271117 16.8567896
179 0.3407809 32.6271117
180 54.2810268 0.3407809
181 115.8269403 54.2810268
182 -84.1160307 115.8269403
183 75.6920271 -84.1160307
184 71.3046863 75.6920271
185 -106.7989518 71.3046863
186 -190.5496774 -106.7989518
187 -105.3081391 -190.5496774
188 264.2853478 -105.3081391
189 28.5845417 264.2853478
190 80.1620898 28.5845417
191 -152.3570334 80.1620898
192 82.2350536 -152.3570334
193 161.9106251 82.2350536
194 -14.4063869 161.9106251
195 83.9525917 -14.4063869
196 -87.8651558 83.9525917
197 -47.3584557 -87.8651558
198 -29.8901543 -47.3584557
199 -35.8332720 -29.8901543
200 -19.3865537 -35.8332720
201 -15.2952793 -19.3865537
202 -48.0166510 -15.2952793
203 15.8056306 -48.0166510
204 23.1596475 15.8056306
205 -5.1066091 23.1596475
206 154.8063703 -5.1066091
207 -42.8699293 154.8063703
208 22.1512730 -42.8699293
209 -5.4918744 22.1512730
210 94.3460670 -5.4918744
211 243.2504973 94.3460670
212 3.1748268 243.2504973
213 -94.3311176 3.1748268
214 79.1887566 -94.3311176
215 38.7525424 79.1887566
216 1.1770079 38.7525424
217 -70.1923666 1.1770079
218 -33.7169081 -70.1923666
219 -24.3987473 -33.7169081
220 78.7078792 -24.3987473
221 419.8967425 78.7078792
222 296.3011019 419.8967425
223 68.2510590 296.3011019
224 -94.4860759 68.2510590
225 83.3828141 -94.4860759
226 -23.3027836 83.3828141
227 -81.6298584 -23.3027836
228 133.1884317 -81.6298584
229 334.4529979 133.1884317
230 53.5503181 334.4529979
231 187.0763910 53.5503181
232 118.2669256 187.0763910
233 25.6759390 118.2669256
234 -83.5856812 25.6759390
235 -23.4616002 -83.5856812
236 55.0293154 -23.4616002
237 25.0989118 55.0293154
238 -4.6636791 25.0989118
239 -61.0082732 -4.6636791
240 109.7380326 -61.0082732
241 227.1399328 109.7380326
242 -13.9413349 227.1399328
243 -62.2398652 -13.9413349
244 -39.8664466 -62.2398652
245 14.3993051 -39.8664466
246 246.5654994 14.3993051
247 -75.1309458 246.5654994
248 -76.9463277 -75.1309458
249 -94.8212632 -76.9463277
250 8.1797032 -94.8212632
251 9.3274750 8.1797032
252 -79.7241323 9.3274750
253 -10.6484316 -79.7241323
254 -58.3959220 -10.6484316
255 -79.8152172 -58.3959220
256 -7.5142844 -79.8152172
257 -69.6473553 -7.5142844
258 -11.5347536 -69.6473553
259 -4.2082769 -11.5347536
260 -23.3179041 -4.2082769
261 36.6283743 -23.3179041
262 60.6880479 36.6283743
263 58.3681575 60.6880479
264 -52.3375583 58.3681575
265 18.4566316 -52.3375583
266 -40.6072596 18.4566316
267 -154.0317411 -40.6072596
268 -95.0878150 -154.0317411
269 -70.0988083 -95.0878150
270 153.4052178 -70.0988083
271 -66.3304476 153.4052178
272 -18.5824444 -66.3304476
273 19.4762366 -18.5824444
274 52.8606925 19.4762366
275 108.9521865 52.8606925
276 76.4732404 108.9521865
277 -44.4606989 76.4732404
278 125.9367620 -44.4606989
279 -32.0720174 125.9367620
280 1.0663252 -32.0720174
281 -11.4004737 1.0663252
282 37.6900412 -11.4004737
283 -30.8012814 37.6900412
284 -69.0982104 -30.8012814
285 387.6947786 -69.0982104
286 132.8329310 387.6947786
287 78.8827456 132.8329310
288 33.5277500 78.8827456
289 NA 33.5277500
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -211.1919006 57.6798828
[2,] -73.3155276 -211.1919006
[3,] -399.4575428 -73.3155276
[4,] 4.3621656 -399.4575428
[5,] -80.6359710 4.3621656
[6,] -419.3535238 -80.6359710
[7,] -67.3008317 -419.3535238
[8,] 18.2084336 -67.3008317
[9,] -92.3784247 18.2084336
[10,] 49.2937272 -92.3784247
[11,] -120.5057620 49.2937272
[12,] -68.2207169 -120.5057620
[13,] -74.4534012 -68.2207169
[14,] -106.0886503 -74.4534012
[15,] -6.8405877 -106.0886503
[16,] 313.9228077 -6.8405877
[17,] -21.3807140 313.9228077
[18,] -231.3479483 -21.3807140
[19,] -133.5868430 -231.3479483
[20,] 172.7165836 -133.5868430
[21,] 106.4582983 172.7165836
[22,] -217.2850490 106.4582983
[23,] 44.6556044 -217.2850490
[24,] -10.2219703 44.6556044
[25,] -92.3505370 -10.2219703
[26,] 3.2342002 -92.3505370
[27,] -82.0178130 3.2342002
[28,] 27.6983108 -82.0178130
[29,] -44.3871727 27.6983108
[30,] -99.3004364 -44.3871727
[31,] -96.5503859 -99.3004364
[32,] 41.1996790 -96.5503859
[33,] -121.9158838 41.1996790
[34,] -46.5602033 -121.9158838
[35,] -69.0985607 -46.5602033
[36,] 35.8793400 -69.0985607
[37,] -79.3153985 35.8793400
[38,] 199.3785887 -79.3153985
[39,] -93.0496558 199.3785887
[40,] 4.0429352 -93.0496558
[41,] 59.4621346 4.0429352
[42,] 259.1423884 59.4621346
[43,] -40.8009629 259.1423884
[44,] -216.9445208 -40.8009629
[45,] -206.2461204 -216.9445208
[46,] 306.2998277 -206.2461204
[47,] -149.3446683 306.2998277
[48,] 131.9711728 -149.3446683
[49,] 60.0315105 131.9711728
[50,] -447.8370309 60.0315105
[51,] -54.0687155 -447.8370309
[52,] 180.4846784 -54.0687155
[53,] 369.1989524 180.4846784
[54,] -152.8529938 369.1989524
[55,] 48.3962509 -152.8529938
[56,] -113.8718793 48.3962509
[57,] -475.1624331 -113.8718793
[58,] 10.6041186 -475.1624331
[59,] -166.3948585 10.6041186
[60,] 187.0054782 -166.3948585
[61,] 385.3468704 187.0054782
[62,] 1193.6078568 385.3468704
[63,] 4.9697952 1193.6078568
[64,] 162.5580897 4.9697952
[65,] -286.6329361 162.5580897
[66,] -119.8652769 -286.6329361
[67,] 304.6951656 -119.8652769
[68,] -76.7227921 304.6951656
[69,] -125.9335690 -76.7227921
[70,] 72.2437938 -125.9335690
[71,] -198.2108275 72.2437938
[72,] 152.5138856 -198.2108275
[73,] -40.4217227 152.5138856
[74,] 128.3736714 -40.4217227
[75,] -86.3211290 128.3736714
[76,] -182.2405238 -86.3211290
[77,] 134.1089792 -182.2405238
[78,] -161.9208793 134.1089792
[79,] 108.9432629 -161.9208793
[80,] -259.8205232 108.9432629
[81,] -18.0831195 -259.8205232
[82,] -352.7294299 -18.0831195
[83,] -163.5651040 -352.7294299
[84,] 45.4086461 -163.5651040
[85,] 69.7278337 45.4086461
[86,] -75.2276623 69.7278337
[87,] 70.8305166 -75.2276623
[88,] 287.2641839 70.8305166
[89,] -326.1184885 287.2641839
[90,] 179.3462745 -326.1184885
[91,] -243.2747568 179.3462745
[92,] -190.2532591 -243.2747568
[93,] -21.2362904 -190.2532591
[94,] 74.5793076 -21.2362904
[95,] -245.0863518 74.5793076
[96,] 31.3524865 -245.0863518
[97,] 140.9810244 31.3524865
[98,] 110.7659733 140.9810244
[99,] 6.0500566 110.7659733
[100,] 89.6989880 6.0500566
[101,] 145.9166551 89.6989880
[102,] -130.0656520 145.9166551
[103,] 19.0925394 -130.0656520
[104,] -22.7588475 19.0925394
[105,] -131.7652288 -22.7588475
[106,] 222.4838210 -131.7652288
[107,] 247.3932436 222.4838210
[108,] -76.2894734 247.3932436
[109,] -2.1722051 -76.2894734
[110,] -46.3320695 -2.1722051
[111,] -218.6129482 -46.3320695
[112,] -55.5131295 -218.6129482
[113,] 64.2742346 -55.5131295
[114,] -203.0774446 64.2742346
[115,] -208.9161228 -203.0774446
[116,] -84.4101044 -208.9161228
[117,] 179.6351448 -84.4101044
[118,] -22.4733925 179.6351448
[119,] 101.6573247 -22.4733925
[120,] 137.3088693 101.6573247
[121,] -78.0482568 137.3088693
[122,] 32.7228342 -78.0482568
[123,] -80.0508839 32.7228342
[124,] 25.8886129 -80.0508839
[125,] 39.4164839 25.8886129
[126,] -31.6304327 39.4164839
[127,] 202.7034093 -31.6304327
[128,] 104.8668642 202.7034093
[129,] -47.9225275 104.8668642
[130,] 30.3299155 -47.9225275
[131,] -55.7631372 30.3299155
[132,] -105.6237845 -55.7631372
[133,] 278.3161756 -105.6237845
[134,] 85.6132949 278.3161756
[135,] -131.2276168 85.6132949
[136,] -36.3568089 -131.2276168
[137,] -42.1562115 -36.3568089
[138,] 46.9932911 -42.1562115
[139,] -136.1759841 46.9932911
[140,] -32.8317664 -136.1759841
[141,] 206.5058036 -32.8317664
[142,] -52.7614988 206.5058036
[143,] 78.2307490 -52.7614988
[144,] 63.4080808 78.2307490
[145,] 225.1535720 63.4080808
[146,] -64.6304226 225.1535720
[147,] 16.8944862 -64.6304226
[148,] -247.2992277 16.8944862
[149,] 29.4479437 -247.2992277
[150,] -56.2313634 29.4479437
[151,] -97.3560742 -56.2313634
[152,] 121.4436705 -97.3560742
[153,] -277.0805184 121.4436705
[154,] -150.5065774 -277.0805184
[155,] 146.9757689 -150.5065774
[156,] -141.3153230 146.9757689
[157,] -97.7445120 -141.3153230
[158,] -33.4574105 -97.7445120
[159,] -423.0688184 -33.4574105
[160,] 240.5327911 -423.0688184
[161,] -31.4694389 240.5327911
[162,] -96.1529741 -31.4694389
[163,] -198.0591179 -96.1529741
[164,] -42.8357032 -198.0591179
[165,] -26.4077259 -42.8357032
[166,] -85.5701983 -26.4077259
[167,] -130.6938423 -85.5701983
[168,] 22.0197279 -130.6938423
[169,] 146.2038038 22.0197279
[170,] 41.7153381 146.2038038
[171,] -38.2645734 41.7153381
[172,] 248.0990391 -38.2645734
[173,] 157.4655504 248.0990391
[174,] -190.4823536 157.4655504
[175,] -13.2958764 -190.4823536
[176,] 33.8023816 -13.2958764
[177,] 16.8567896 33.8023816
[178,] 32.6271117 16.8567896
[179,] 0.3407809 32.6271117
[180,] 54.2810268 0.3407809
[181,] 115.8269403 54.2810268
[182,] -84.1160307 115.8269403
[183,] 75.6920271 -84.1160307
[184,] 71.3046863 75.6920271
[185,] -106.7989518 71.3046863
[186,] -190.5496774 -106.7989518
[187,] -105.3081391 -190.5496774
[188,] 264.2853478 -105.3081391
[189,] 28.5845417 264.2853478
[190,] 80.1620898 28.5845417
[191,] -152.3570334 80.1620898
[192,] 82.2350536 -152.3570334
[193,] 161.9106251 82.2350536
[194,] -14.4063869 161.9106251
[195,] 83.9525917 -14.4063869
[196,] -87.8651558 83.9525917
[197,] -47.3584557 -87.8651558
[198,] -29.8901543 -47.3584557
[199,] -35.8332720 -29.8901543
[200,] -19.3865537 -35.8332720
[201,] -15.2952793 -19.3865537
[202,] -48.0166510 -15.2952793
[203,] 15.8056306 -48.0166510
[204,] 23.1596475 15.8056306
[205,] -5.1066091 23.1596475
[206,] 154.8063703 -5.1066091
[207,] -42.8699293 154.8063703
[208,] 22.1512730 -42.8699293
[209,] -5.4918744 22.1512730
[210,] 94.3460670 -5.4918744
[211,] 243.2504973 94.3460670
[212,] 3.1748268 243.2504973
[213,] -94.3311176 3.1748268
[214,] 79.1887566 -94.3311176
[215,] 38.7525424 79.1887566
[216,] 1.1770079 38.7525424
[217,] -70.1923666 1.1770079
[218,] -33.7169081 -70.1923666
[219,] -24.3987473 -33.7169081
[220,] 78.7078792 -24.3987473
[221,] 419.8967425 78.7078792
[222,] 296.3011019 419.8967425
[223,] 68.2510590 296.3011019
[224,] -94.4860759 68.2510590
[225,] 83.3828141 -94.4860759
[226,] -23.3027836 83.3828141
[227,] -81.6298584 -23.3027836
[228,] 133.1884317 -81.6298584
[229,] 334.4529979 133.1884317
[230,] 53.5503181 334.4529979
[231,] 187.0763910 53.5503181
[232,] 118.2669256 187.0763910
[233,] 25.6759390 118.2669256
[234,] -83.5856812 25.6759390
[235,] -23.4616002 -83.5856812
[236,] 55.0293154 -23.4616002
[237,] 25.0989118 55.0293154
[238,] -4.6636791 25.0989118
[239,] -61.0082732 -4.6636791
[240,] 109.7380326 -61.0082732
[241,] 227.1399328 109.7380326
[242,] -13.9413349 227.1399328
[243,] -62.2398652 -13.9413349
[244,] -39.8664466 -62.2398652
[245,] 14.3993051 -39.8664466
[246,] 246.5654994 14.3993051
[247,] -75.1309458 246.5654994
[248,] -76.9463277 -75.1309458
[249,] -94.8212632 -76.9463277
[250,] 8.1797032 -94.8212632
[251,] 9.3274750 8.1797032
[252,] -79.7241323 9.3274750
[253,] -10.6484316 -79.7241323
[254,] -58.3959220 -10.6484316
[255,] -79.8152172 -58.3959220
[256,] -7.5142844 -79.8152172
[257,] -69.6473553 -7.5142844
[258,] -11.5347536 -69.6473553
[259,] -4.2082769 -11.5347536
[260,] -23.3179041 -4.2082769
[261,] 36.6283743 -23.3179041
[262,] 60.6880479 36.6283743
[263,] 58.3681575 60.6880479
[264,] -52.3375583 58.3681575
[265,] 18.4566316 -52.3375583
[266,] -40.6072596 18.4566316
[267,] -154.0317411 -40.6072596
[268,] -95.0878150 -154.0317411
[269,] -70.0988083 -95.0878150
[270,] 153.4052178 -70.0988083
[271,] -66.3304476 153.4052178
[272,] -18.5824444 -66.3304476
[273,] 19.4762366 -18.5824444
[274,] 52.8606925 19.4762366
[275,] 108.9521865 52.8606925
[276,] 76.4732404 108.9521865
[277,] -44.4606989 76.4732404
[278,] 125.9367620 -44.4606989
[279,] -32.0720174 125.9367620
[280,] 1.0663252 -32.0720174
[281,] -11.4004737 1.0663252
[282,] 37.6900412 -11.4004737
[283,] -30.8012814 37.6900412
[284,] -69.0982104 -30.8012814
[285,] 387.6947786 -69.0982104
[286,] 132.8329310 387.6947786
[287,] 78.8827456 132.8329310
[288,] 33.5277500 78.8827456
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -211.1919006 57.6798828
2 -73.3155276 -211.1919006
3 -399.4575428 -73.3155276
4 4.3621656 -399.4575428
5 -80.6359710 4.3621656
6 -419.3535238 -80.6359710
7 -67.3008317 -419.3535238
8 18.2084336 -67.3008317
9 -92.3784247 18.2084336
10 49.2937272 -92.3784247
11 -120.5057620 49.2937272
12 -68.2207169 -120.5057620
13 -74.4534012 -68.2207169
14 -106.0886503 -74.4534012
15 -6.8405877 -106.0886503
16 313.9228077 -6.8405877
17 -21.3807140 313.9228077
18 -231.3479483 -21.3807140
19 -133.5868430 -231.3479483
20 172.7165836 -133.5868430
21 106.4582983 172.7165836
22 -217.2850490 106.4582983
23 44.6556044 -217.2850490
24 -10.2219703 44.6556044
25 -92.3505370 -10.2219703
26 3.2342002 -92.3505370
27 -82.0178130 3.2342002
28 27.6983108 -82.0178130
29 -44.3871727 27.6983108
30 -99.3004364 -44.3871727
31 -96.5503859 -99.3004364
32 41.1996790 -96.5503859
33 -121.9158838 41.1996790
34 -46.5602033 -121.9158838
35 -69.0985607 -46.5602033
36 35.8793400 -69.0985607
37 -79.3153985 35.8793400
38 199.3785887 -79.3153985
39 -93.0496558 199.3785887
40 4.0429352 -93.0496558
41 59.4621346 4.0429352
42 259.1423884 59.4621346
43 -40.8009629 259.1423884
44 -216.9445208 -40.8009629
45 -206.2461204 -216.9445208
46 306.2998277 -206.2461204
47 -149.3446683 306.2998277
48 131.9711728 -149.3446683
49 60.0315105 131.9711728
50 -447.8370309 60.0315105
51 -54.0687155 -447.8370309
52 180.4846784 -54.0687155
53 369.1989524 180.4846784
54 -152.8529938 369.1989524
55 48.3962509 -152.8529938
56 -113.8718793 48.3962509
57 -475.1624331 -113.8718793
58 10.6041186 -475.1624331
59 -166.3948585 10.6041186
60 187.0054782 -166.3948585
61 385.3468704 187.0054782
62 1193.6078568 385.3468704
63 4.9697952 1193.6078568
64 162.5580897 4.9697952
65 -286.6329361 162.5580897
66 -119.8652769 -286.6329361
67 304.6951656 -119.8652769
68 -76.7227921 304.6951656
69 -125.9335690 -76.7227921
70 72.2437938 -125.9335690
71 -198.2108275 72.2437938
72 152.5138856 -198.2108275
73 -40.4217227 152.5138856
74 128.3736714 -40.4217227
75 -86.3211290 128.3736714
76 -182.2405238 -86.3211290
77 134.1089792 -182.2405238
78 -161.9208793 134.1089792
79 108.9432629 -161.9208793
80 -259.8205232 108.9432629
81 -18.0831195 -259.8205232
82 -352.7294299 -18.0831195
83 -163.5651040 -352.7294299
84 45.4086461 -163.5651040
85 69.7278337 45.4086461
86 -75.2276623 69.7278337
87 70.8305166 -75.2276623
88 287.2641839 70.8305166
89 -326.1184885 287.2641839
90 179.3462745 -326.1184885
91 -243.2747568 179.3462745
92 -190.2532591 -243.2747568
93 -21.2362904 -190.2532591
94 74.5793076 -21.2362904
95 -245.0863518 74.5793076
96 31.3524865 -245.0863518
97 140.9810244 31.3524865
98 110.7659733 140.9810244
99 6.0500566 110.7659733
100 89.6989880 6.0500566
101 145.9166551 89.6989880
102 -130.0656520 145.9166551
103 19.0925394 -130.0656520
104 -22.7588475 19.0925394
105 -131.7652288 -22.7588475
106 222.4838210 -131.7652288
107 247.3932436 222.4838210
108 -76.2894734 247.3932436
109 -2.1722051 -76.2894734
110 -46.3320695 -2.1722051
111 -218.6129482 -46.3320695
112 -55.5131295 -218.6129482
113 64.2742346 -55.5131295
114 -203.0774446 64.2742346
115 -208.9161228 -203.0774446
116 -84.4101044 -208.9161228
117 179.6351448 -84.4101044
118 -22.4733925 179.6351448
119 101.6573247 -22.4733925
120 137.3088693 101.6573247
121 -78.0482568 137.3088693
122 32.7228342 -78.0482568
123 -80.0508839 32.7228342
124 25.8886129 -80.0508839
125 39.4164839 25.8886129
126 -31.6304327 39.4164839
127 202.7034093 -31.6304327
128 104.8668642 202.7034093
129 -47.9225275 104.8668642
130 30.3299155 -47.9225275
131 -55.7631372 30.3299155
132 -105.6237845 -55.7631372
133 278.3161756 -105.6237845
134 85.6132949 278.3161756
135 -131.2276168 85.6132949
136 -36.3568089 -131.2276168
137 -42.1562115 -36.3568089
138 46.9932911 -42.1562115
139 -136.1759841 46.9932911
140 -32.8317664 -136.1759841
141 206.5058036 -32.8317664
142 -52.7614988 206.5058036
143 78.2307490 -52.7614988
144 63.4080808 78.2307490
145 225.1535720 63.4080808
146 -64.6304226 225.1535720
147 16.8944862 -64.6304226
148 -247.2992277 16.8944862
149 29.4479437 -247.2992277
150 -56.2313634 29.4479437
151 -97.3560742 -56.2313634
152 121.4436705 -97.3560742
153 -277.0805184 121.4436705
154 -150.5065774 -277.0805184
155 146.9757689 -150.5065774
156 -141.3153230 146.9757689
157 -97.7445120 -141.3153230
158 -33.4574105 -97.7445120
159 -423.0688184 -33.4574105
160 240.5327911 -423.0688184
161 -31.4694389 240.5327911
162 -96.1529741 -31.4694389
163 -198.0591179 -96.1529741
164 -42.8357032 -198.0591179
165 -26.4077259 -42.8357032
166 -85.5701983 -26.4077259
167 -130.6938423 -85.5701983
168 22.0197279 -130.6938423
169 146.2038038 22.0197279
170 41.7153381 146.2038038
171 -38.2645734 41.7153381
172 248.0990391 -38.2645734
173 157.4655504 248.0990391
174 -190.4823536 157.4655504
175 -13.2958764 -190.4823536
176 33.8023816 -13.2958764
177 16.8567896 33.8023816
178 32.6271117 16.8567896
179 0.3407809 32.6271117
180 54.2810268 0.3407809
181 115.8269403 54.2810268
182 -84.1160307 115.8269403
183 75.6920271 -84.1160307
184 71.3046863 75.6920271
185 -106.7989518 71.3046863
186 -190.5496774 -106.7989518
187 -105.3081391 -190.5496774
188 264.2853478 -105.3081391
189 28.5845417 264.2853478
190 80.1620898 28.5845417
191 -152.3570334 80.1620898
192 82.2350536 -152.3570334
193 161.9106251 82.2350536
194 -14.4063869 161.9106251
195 83.9525917 -14.4063869
196 -87.8651558 83.9525917
197 -47.3584557 -87.8651558
198 -29.8901543 -47.3584557
199 -35.8332720 -29.8901543
200 -19.3865537 -35.8332720
201 -15.2952793 -19.3865537
202 -48.0166510 -15.2952793
203 15.8056306 -48.0166510
204 23.1596475 15.8056306
205 -5.1066091 23.1596475
206 154.8063703 -5.1066091
207 -42.8699293 154.8063703
208 22.1512730 -42.8699293
209 -5.4918744 22.1512730
210 94.3460670 -5.4918744
211 243.2504973 94.3460670
212 3.1748268 243.2504973
213 -94.3311176 3.1748268
214 79.1887566 -94.3311176
215 38.7525424 79.1887566
216 1.1770079 38.7525424
217 -70.1923666 1.1770079
218 -33.7169081 -70.1923666
219 -24.3987473 -33.7169081
220 78.7078792 -24.3987473
221 419.8967425 78.7078792
222 296.3011019 419.8967425
223 68.2510590 296.3011019
224 -94.4860759 68.2510590
225 83.3828141 -94.4860759
226 -23.3027836 83.3828141
227 -81.6298584 -23.3027836
228 133.1884317 -81.6298584
229 334.4529979 133.1884317
230 53.5503181 334.4529979
231 187.0763910 53.5503181
232 118.2669256 187.0763910
233 25.6759390 118.2669256
234 -83.5856812 25.6759390
235 -23.4616002 -83.5856812
236 55.0293154 -23.4616002
237 25.0989118 55.0293154
238 -4.6636791 25.0989118
239 -61.0082732 -4.6636791
240 109.7380326 -61.0082732
241 227.1399328 109.7380326
242 -13.9413349 227.1399328
243 -62.2398652 -13.9413349
244 -39.8664466 -62.2398652
245 14.3993051 -39.8664466
246 246.5654994 14.3993051
247 -75.1309458 246.5654994
248 -76.9463277 -75.1309458
249 -94.8212632 -76.9463277
250 8.1797032 -94.8212632
251 9.3274750 8.1797032
252 -79.7241323 9.3274750
253 -10.6484316 -79.7241323
254 -58.3959220 -10.6484316
255 -79.8152172 -58.3959220
256 -7.5142844 -79.8152172
257 -69.6473553 -7.5142844
258 -11.5347536 -69.6473553
259 -4.2082769 -11.5347536
260 -23.3179041 -4.2082769
261 36.6283743 -23.3179041
262 60.6880479 36.6283743
263 58.3681575 60.6880479
264 -52.3375583 58.3681575
265 18.4566316 -52.3375583
266 -40.6072596 18.4566316
267 -154.0317411 -40.6072596
268 -95.0878150 -154.0317411
269 -70.0988083 -95.0878150
270 153.4052178 -70.0988083
271 -66.3304476 153.4052178
272 -18.5824444 -66.3304476
273 19.4762366 -18.5824444
274 52.8606925 19.4762366
275 108.9521865 52.8606925
276 76.4732404 108.9521865
277 -44.4606989 76.4732404
278 125.9367620 -44.4606989
279 -32.0720174 125.9367620
280 1.0663252 -32.0720174
281 -11.4004737 1.0663252
282 37.6900412 -11.4004737
283 -30.8012814 37.6900412
284 -69.0982104 -30.8012814
285 387.6947786 -69.0982104
286 132.8329310 387.6947786
287 78.8827456 132.8329310
288 33.5277500 78.8827456
> 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/74pf91355757840.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/8pdmh1355757840.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/93vph1355757840.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10oqmr1355757840.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11zuot1355757840.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/12q7d71355757840.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/13chxf1355757840.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/14vwqd1355757841.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/151mem1355757841.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/1641z11355757841.tab")
+ }
>
> try(system("convert tmp/13jr21355757840.ps tmp/13jr21355757840.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jqdy1355757840.ps tmp/2jqdy1355757840.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vzhn1355757840.ps tmp/3vzhn1355757840.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ox301355757840.ps tmp/4ox301355757840.png",intern=TRUE))
character(0)
> try(system("convert tmp/5tlns1355757840.ps tmp/5tlns1355757840.png",intern=TRUE))
character(0)
> try(system("convert tmp/61ph51355757840.ps tmp/61ph51355757840.png",intern=TRUE))
character(0)
> try(system("convert tmp/74pf91355757840.ps tmp/74pf91355757840.png",intern=TRUE))
character(0)
> try(system("convert tmp/8pdmh1355757840.ps tmp/8pdmh1355757840.png",intern=TRUE))
character(0)
> try(system("convert tmp/93vph1355757840.ps tmp/93vph1355757840.png",intern=TRUE))
character(0)
> try(system("convert tmp/10oqmr1355757840.ps tmp/10oqmr1355757840.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
13.319 1.671 15.019