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(9
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+ ,18475
+ ,12
+ ,11
+ ,11
+ ,947
+ ,50857
+ ,21
+ ,165
+ ,34
+ ,0
+ ,15
+ ,20
+ ,71
+ ,37
+ ,36944
+ ,1352
+ ,12645
+ ,24
+ ,24
+ ,11
+ ,819
+ ,56613
+ ,19
+ ,234
+ ,37
+ ,1
+ ,15
+ ,12
+ ,44
+ ,35
+ ,8019
+ ,3080
+ ,11017
+ ,16
+ ,16
+ ,11
+ ,757
+ ,62792
+ ,35
+ ,176
+ ,46
+ ,0
+ ,28
+ ,15
+ ,60
+ ,51
+ ,30884
+ ,10205
+ ,37623
+ ,72
+ ,72
+ ,11
+ ,894
+ ,72535
+ ,14
+ ,329
+ ,44
+ ,0
+ ,17
+ ,16
+ ,64
+ ,39
+ ,19540
+ ,6095
+ ,35873
+ ,27
+ ,21)
+ ,dim=c(16
+ ,289)
+ ,dimnames=list(c('months'
+ ,'pageviews'
+ ,'time_in_rfc'
+ ,'logins'
+ ,'compendium_views_info'
+ ,'compendium_views_pr'
+ ,'shared_compendiums'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'feedback_messages_p1'
+ ,'feedback_messages_p120'
+ ,'totsize'
+ ,'totrevisions'
+ ,'totseconds'
+ ,'tothyperlinks'
+ ,'totblogs
')
+ ,1:289))
> y <- array(NA,dim=c(16,289),dimnames=list(c('months','pageviews','time_in_rfc','logins','compendium_views_info','compendium_views_pr','shared_compendiums','blogged_computations','compendiums_reviewed','feedback_messages_p1','feedback_messages_p120','totsize','totrevisions','totseconds','tothyperlinks','totblogs
'),1:289))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '3'
> 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 months pageviews logins compendium_views_info
1 210907 9 1418 56 396
2 120982 9 869 56 297
3 176508 9 1530 54 559
4 179321 9 2172 89 967
5 123185 9 901 40 270
6 52746 9 463 25 143
7 385534 9 3201 92 1562
8 33170 9 371 18 109
9 101645 9 1192 63 371
10 149061 9 1583 44 656
11 165446 9 1439 33 511
12 237213 9 1764 84 655
13 173326 9 1495 88 465
14 133131 9 1373 55 525
15 258873 9 2187 60 885
16 180083 9 1491 66 497
17 324799 9 4041 154 1436
18 230964 9 1706 53 612
19 236785 9 2152 119 865
20 135473 9 1036 41 385
21 202925 9 1882 61 567
22 215147 9 1929 58 639
23 344297 9 2242 75 963
24 153935 9 1220 33 398
25 132943 9 1289 40 410
26 174724 9 2515 92 966
27 174415 9 2147 100 801
28 225548 9 2352 112 892
29 223632 9 1638 73 513
30 124817 9 1222 40 469
31 221698 9 1812 45 683
32 210767 9 1677 60 643
33 170266 9 1579 62 535
34 260561 9 1731 75 625
35 84853 9 807 31 264
36 294424 9 2452 77 992
37 101011 9 829 34 238
38 215641 9 1940 46 818
39 325107 9 2662 99 937
40 7176 9 186 17 70
41 167542 9 1499 66 507
42 106408 9 865 30 260
43 96560 9 1793 76 503
44 265769 9 2527 146 927
45 269651 9 2747 67 1269
46 149112 9 1324 56 537
47 175824 9 2702 107 910
48 152871 9 1383 58 532
49 111665 9 1179 34 345
50 116408 9 2099 61 918
51 362301 9 4308 119 1635
52 78800 9 918 42 330
53 183167 9 1831 66 557
54 277965 9 3373 89 1178
55 150629 9 1713 44 740
56 168809 9 1438 66 452
57 24188 9 496 24 218
58 329267 9 2253 259 764
59 65029 9 744 17 255
60 101097 9 1161 64 454
61 218946 9 2352 41 866
62 244052 9 2144 68 574
63 341570 9 4691 168 1276
64 103597 9 1112 43 379
65 233328 9 2694 132 825
66 256462 9 1973 105 798
67 206161 9 1769 71 663
68 311473 9 3148 112 1069
69 235800 9 2474 94 921
70 177939 9 2084 82 858
71 207176 9 1954 70 711
72 196553 9 1226 57 503
73 174184 9 1389 53 382
74 143246 9 1496 103 464
75 187559 9 2269 121 717
76 187681 9 1833 62 690
77 119016 9 1268 52 462
78 182192 9 1943 52 657
79 73566 9 893 32 385
80 194979 9 1762 62 577
81 167488 9 1403 45 619
82 143756 9 1425 46 479
83 275541 9 1857 63 817
84 243199 9 1840 75 752
85 182999 9 1502 88 430
86 135649 9 1441 46 451
87 152299 9 1420 53 537
88 120221 9 1416 37 519
89 346485 9 2970 90 1000
90 145790 10 1317 63 637
91 193339 10 1644 78 465
92 80953 10 870 25 437
93 122774 10 1654 45 711
94 130585 10 1054 46 299
95 112611 10 937 41 248
96 286468 10 3004 144 1162
97 241066 10 2008 82 714
98 148446 10 2547 91 905
99 204713 10 1885 71 649
100 182079 10 1626 63 512
101 140344 10 1468 53 472
102 220516 10 2445 62 905
103 243060 10 1964 63 786
104 162765 10 1381 32 489
105 182613 10 1369 39 479
106 232138 10 1659 62 617
107 265318 10 2888 117 925
108 85574 10 1290 34 351
109 310839 10 2845 92 1144
110 225060 10 1982 93 669
111 232317 10 1904 54 707
112 144966 10 1391 144 458
113 43287 10 602 14 214
114 155754 10 1743 61 599
115 164709 10 1559 109 572
116 201940 10 2014 38 897
117 235454 10 2143 73 819
118 220801 10 2146 75 720
119 99466 10 874 50 273
120 92661 10 1590 61 508
121 133328 10 1590 55 506
122 61361 10 1210 77 451
123 125930 10 2072 75 699
124 100750 10 1281 72 407
125 224549 10 1401 50 465
126 82316 10 834 32 245
127 102010 10 1105 53 370
128 101523 10 1272 42 316
129 243511 10 1944 71 603
130 22938 10 391 10 154
131 41566 10 761 35 229
132 152474 10 1605 65 577
133 61857 10 530 25 192
134 99923 10 1988 66 617
135 132487 10 1386 41 411
136 317394 10 2395 86 975
137 21054 10 387 16 146
138 209641 10 1742 42 705
139 22648 10 620 19 184
140 31414 10 449 19 200
141 46698 10 800 45 274
142 131698 10 1684 65 502
143 91735 10 1050 35 382
144 244749 10 2699 95 964
145 184510 10 1606 49 537
146 79863 10 1502 37 438
147 128423 10 1204 64 369
148 97839 10 1138 38 417
149 38214 10 568 34 276
150 151101 10 1459 32 514
151 272458 10 2158 65 822
152 172494 10 1111 52 389
153 108043 10 1421 62 466
154 328107 10 2833 65 1255
155 250579 10 1955 83 694
156 351067 10 2922 95 1024
157 158015 10 1002 29 400
158 98866 10 1060 18 397
159 85439 10 956 33 350
160 229242 10 2186 247 719
161 351619 10 3604 139 1277
162 84207 10 1035 29 356
163 120445 10 1417 118 457
164 324598 10 3261 110 1402
165 131069 10 1587 67 600
166 204271 10 1424 42 480
167 165543 10 1701 65 595
168 141722 10 1249 94 436
169 116048 10 946 64 230
170 250047 10 1926 81 651
171 299775 10 3352 95 1367
172 195838 10 1641 67 564
173 173260 10 2035 63 716
174 254488 10 2312 83 747
175 104389 10 1369 45 467
176 136084 10 1577 30 671
177 199476 10 2201 70 861
178 92499 10 961 32 319
179 224330 10 1900 83 612
180 135781 10 1254 31 433
181 74408 10 1335 67 434
182 81240 10 1597 66 503
183 14688 10 207 10 85
184 181633 10 1645 70 564
185 271856 10 2429 103 824
186 7199 10 151 5 74
187 46660 10 474 20 259
188 17547 10 141 5 69
189 133368 10 1639 36 535
190 95227 10 872 34 239
191 152601 10 1318 48 438
192 98146 10 1018 40 459
193 79619 10 1383 43 426
194 59194 10 1314 31 288
195 139942 10 1335 42 498
196 118612 11 1403 46 454
197 72880 11 910 33 376
198 65475 11 616 18 225
199 99643 11 1407 55 555
200 71965 11 771 35 252
201 77272 11 766 59 208
202 49289 11 473 19 130
203 135131 11 1376 66 481
204 108446 11 1232 60 389
205 89746 11 1521 36 565
206 44296 11 572 25 173
207 77648 11 1059 47 278
208 181528 11 1544 54 609
209 134019 11 1230 53 422
210 124064 11 1206 40 445
211 92630 11 1205 40 387
212 121848 11 1255 39 339
213 52915 11 613 14 181
214 81872 11 721 45 245
215 58981 11 1109 36 384
216 53515 11 740 28 212
217 60812 11 1126 44 399
218 56375 11 728 30 229
219 65490 11 689 22 224
220 80949 11 592 17 203
221 76302 11 995 31 333
222 104011 11 1613 55 384
223 98104 11 2048 54 636
224 67989 11 705 21 185
225 30989 11 301 14 93
226 135458 11 1803 81 581
227 73504 11 799 35 248
228 63123 11 861 43 304
229 61254 11 1186 46 344
230 74914 11 1451 30 407
231 31774 11 628 23 170
232 81437 11 1161 38 312
233 87186 11 1463 54 507
234 50090 11 742 20 224
235 65745 11 979 53 340
236 56653 11 675 45 168
237 158399 11 1241 39 443
238 46455 11 676 20 204
239 73624 11 1049 24 367
240 38395 11 620 31 210
241 91899 11 1081 35 335
242 139526 11 1688 151 364
243 52164 11 736 52 178
244 51567 11 617 30 206
245 70551 11 812 31 279
246 84856 11 1051 29 387
247 102538 11 1656 57 490
248 86678 11 705 40 238
249 85709 11 945 44 343
250 34662 11 554 25 232
251 150580 11 1597 77 530
252 99611 11 982 35 291
253 19349 11 222 11 67
254 99373 11 1212 63 397
255 86230 11 1143 44 467
256 30837 11 435 19 178
257 31706 11 532 13 175
258 89806 11 882 42 299
259 62088 11 608 38 154
260 40151 11 459 29 106
261 27634 11 578 20 189
262 76990 11 826 27 194
263 37460 11 509 20 135
264 54157 11 717 19 201
265 49862 11 637 37 207
266 84337 11 857 26 280
267 64175 11 830 42 260
268 59382 11 652 49 227
269 119308 11 707 30 239
270 76702 11 954 49 333
271 103425 11 1461 67 428
272 70344 11 672 28 230
273 43410 11 778 19 292
274 104838 11 1141 49 350
275 62215 11 680 27 186
276 69304 11 1090 30 326
277 53117 11 616 22 155
278 19764 11 285 12 75
279 86680 11 1145 31 361
280 84105 11 733 20 261
281 77945 11 888 20 299
282 89113 11 849 39 300
283 91005 11 1182 29 450
284 40248 11 528 16 183
285 64187 11 642 27 238
286 50857 11 947 21 165
287 56613 11 819 19 234
288 62792 11 757 35 176
289 72535 11 894 14 329
compendium_views_pr shared_compendiums blogged_computations
1 81 3 79
2 55 4 58
3 50 12 60
4 125 2 108
5 40 1 49
6 37 3 0
7 63 0 121
8 44 0 1
9 88 0 20
10 66 5 43
11 57 0 69
12 74 0 78
13 49 7 86
14 52 7 44
15 88 3 104
16 36 9 63
17 108 0 158
18 43 4 102
19 75 3 77
20 32 0 82
21 44 7 115
22 85 0 101
23 86 1 80
24 56 5 50
25 50 7 83
26 135 0 123
27 63 0 73
28 81 5 81
29 52 0 105
30 44 0 47
31 113 0 105
32 39 3 94
33 73 4 44
34 48 1 114
35 33 4 38
36 59 2 107
37 41 0 30
38 69 0 71
39 64 0 84
40 1 0 0
41 59 2 59
42 32 1 33
43 129 0 42
44 37 2 96
45 31 10 106
46 65 6 56
47 107 0 57
48 74 5 59
49 54 4 39
50 76 1 34
51 715 2 76
52 57 2 20
53 66 0 91
54 106 8 115
55 54 3 85
56 32 0 76
57 20 0 8
58 71 8 79
59 21 5 21
60 70 3 30
61 112 1 76
62 66 5 101
63 190 1 94
64 66 1 27
65 165 5 92
66 56 0 123
67 61 12 75
68 53 8 128
69 127 8 105
70 63 8 55
71 38 8 56
72 50 2 41
73 52 0 72
74 42 5 67
75 76 8 75
76 67 2 114
77 50 5 118
78 53 12 77
79 39 6 22
80 50 7 66
81 77 2 69
82 57 0 105
83 73 4 116
84 34 3 88
85 39 6 73
86 46 2 99
87 63 0 62
88 35 1 53
89 106 0 118
90 43 5 30
91 47 2 100
92 31 0 49
93 162 0 24
94 57 5 67
95 36 0 46
96 263 1 57
97 78 0 75
98 63 1 135
99 54 1 68
100 63 2 124
101 77 6 33
102 79 1 98
103 110 4 58
104 56 2 68
105 56 3 81
106 43 0 131
107 111 10 110
108 71 0 37
109 62 9 130
110 56 7 93
111 74 0 118
112 60 0 39
113 43 4 13
114 68 4 74
115 53 0 81
116 87 0 109
117 46 0 151
118 105 1 51
119 32 0 28
120 133 1 40
121 79 0 56
122 51 0 27
123 207 4 37
124 67 0 83
125 47 4 54
126 34 4 27
127 66 3 28
128 76 0 59
129 65 0 133
130 9 0 12
131 42 5 0
132 45 0 106
133 25 4 23
134 115 0 44
135 97 0 71
136 53 1 116
137 2 0 4
138 52 5 62
139 44 0 12
140 22 0 18
141 35 0 14
142 74 0 60
143 103 0 7
144 144 2 98
145 60 7 64
146 134 1 29
147 89 8 32
148 42 2 25
149 52 0 16
150 98 2 48
151 99 0 100
152 52 0 46
153 29 1 45
154 125 3 129
155 106 0 130
156 95 3 136
157 40 0 59
158 140 0 25
159 43 0 32
160 128 4 63
161 142 4 95
162 73 11 14
163 72 0 36
164 128 0 113
165 61 4 47
166 73 0 92
167 148 1 70
168 64 0 19
169 45 0 50
170 58 0 41
171 97 9 91
172 50 1 111
173 37 3 41
174 50 10 120
175 105 5 135
176 69 0 27
177 46 2 87
178 57 0 25
179 52 1 131
180 98 2 45
181 61 4 29
182 89 0 58
183 0 0 4
184 48 2 47
185 91 1 109
186 0 0 7
187 7 0 12
188 3 0 0
189 54 1 37
190 70 0 37
191 36 2 46
192 37 0 15
193 123 3 42
194 247 6 7
195 46 0 54
196 72 2 54
197 41 0 14
198 24 2 16
199 45 1 33
200 33 1 32
201 27 2 21
202 36 1 15
203 87 0 38
204 90 1 22
205 114 3 28
206 31 0 10
207 45 0 31
208 69 0 32
209 51 0 32
210 34 1 43
211 60 4 27
212 45 0 37
213 54 0 20
214 25 0 32
215 38 7 0
216 52 2 5
217 67 0 26
218 74 7 10
219 38 3 27
220 30 0 11
221 26 0 29
222 67 6 25
223 132 2 55
224 42 0 23
225 35 0 5
226 118 3 43
227 68 0 23
228 43 1 34
229 76 1 36
230 64 0 35
231 48 1 0
232 64 0 37
233 56 0 28
234 71 0 16
235 75 0 26
236 39 0 38
237 42 0 23
238 39 0 22
239 93 0 30
240 38 0 16
241 60 0 18
242 71 0 28
243 52 0 32
244 27 2 21
245 59 0 23
246 40 1 29
247 79 1 50
248 44 0 12
249 65 0 21
250 10 0 18
251 124 0 27
252 81 0 41
253 15 0 13
254 92 1 12
255 42 0 21
256 10 0 8
257 24 0 26
258 64 0 27
259 45 1 13
260 22 0 16
261 56 0 2
262 94 0 42
263 19 0 5
264 35 0 37
265 32 0 17
266 35 0 38
267 48 0 37
268 49 0 29
269 48 0 32
270 62 0 35
271 96 1 17
272 45 0 20
273 63 0 7
274 71 1 46
275 26 0 24
276 48 6 40
277 29 3 3
278 19 1 10
279 45 2 37
280 45 0 17
281 67 0 28
282 30 0 19
283 36 3 29
284 34 1 8
285 36 0 10
286 34 0 15
287 37 1 15
288 46 0 28
289 44 0 17
compendiums_reviewed feedback_messages_p1 feedback_messages_p120 totsize
1 30 115 94 112285
2 28 109 103 84786
3 38 146 93 83123
4 30 116 103 101193
5 22 68 51 38361
6 26 101 70 68504
7 25 96 91 119182
8 18 67 22 22807
9 11 44 38 17140
10 26 100 93 116174
11 25 93 60 57635
12 38 140 123 66198
13 44 166 148 71701
14 30 99 90 57793
15 40 139 124 80444
16 34 130 70 53855
17 47 181 168 97668
18 30 116 115 133824
19 31 116 71 101481
20 23 88 66 99645
21 36 139 134 114789
22 36 135 117 99052
23 30 108 108 67654
24 25 89 84 65553
25 39 156 156 97500
26 34 129 120 69112
27 31 118 114 82753
28 31 118 94 85323
29 33 125 120 72654
30 25 95 81 30727
31 33 126 110 77873
32 35 135 133 117478
33 42 154 122 74007
34 43 165 158 90183
35 30 113 109 61542
36 33 127 124 101494
37 13 52 39 27570
38 32 121 92 55813
39 36 136 126 79215
40 0 0 0 1423
41 28 108 70 55461
42 14 46 37 31081
43 17 54 38 22996
44 32 124 120 83122
45 30 115 93 70106
46 35 128 95 60578
47 20 80 77 39992
48 28 97 90 79892
49 28 104 80 49810
50 39 59 31 71570
51 34 125 110 100708
52 26 82 66 33032
53 39 149 138 82875
54 39 149 133 139077
55 33 122 113 71595
56 28 118 100 72260
57 4 12 7 5950
58 39 144 140 115762
59 18 67 61 32551
60 14 52 41 31701
61 29 108 96 80670
62 44 166 164 143558
63 21 80 78 117105
64 16 60 49 23789
65 28 107 102 120733
66 35 127 124 105195
67 28 107 99 73107
68 38 146 129 132068
69 23 84 62 149193
70 36 141 73 46821
71 32 123 114 87011
72 29 111 99 95260
73 25 98 70 55183
74 27 105 104 106671
75 36 135 116 73511
76 28 107 91 92945
77 23 85 74 78664
78 40 155 138 70054
79 23 88 67 22618
80 40 155 151 74011
81 28 104 72 83737
82 34 132 120 69094
83 33 127 115 93133
84 28 108 105 95536
85 34 129 104 225920
86 30 116 108 62133
87 33 122 98 61370
88 22 85 69 43836
89 38 147 111 106117
90 26 99 99 38692
91 35 87 71 84651
92 8 28 27 56622
93 24 90 69 15986
94 29 109 107 95364
95 20 78 73 26706
96 29 111 107 89691
97 45 158 93 67267
98 37 141 129 126846
99 33 122 69 41140
100 33 124 118 102860
101 25 93 73 51715
102 32 124 119 55801
103 29 112 104 111813
104 28 108 107 120293
105 28 99 99 138599
106 31 117 90 161647
107 52 199 197 115929
108 21 78 36 24266
109 24 91 85 162901
110 41 158 139 109825
111 33 126 106 129838
112 32 122 50 37510
113 19 71 64 43750
114 20 75 31 40652
115 31 115 63 87771
116 31 119 92 85872
117 32 124 106 89275
118 18 72 63 44418
119 23 91 69 192565
120 17 45 41 35232
121 20 78 56 40909
122 12 39 25 13294
123 17 68 65 32387
124 30 119 93 140867
125 31 117 114 120662
126 10 39 38 21233
127 13 50 44 44332
128 22 88 87 61056
129 42 155 110 101338
130 1 0 0 1168
131 9 36 27 13497
132 32 123 83 65567
133 11 32 30 25162
134 25 99 80 32334
135 36 136 98 40735
136 31 117 82 91413
137 0 0 0 855
138 24 88 60 97068
139 13 39 28 44339
140 8 25 9 14116
141 13 52 33 10288
142 19 75 59 65622
143 18 71 49 16563
144 33 124 115 76643
145 40 151 140 110681
146 22 71 49 29011
147 38 145 120 92696
148 24 87 66 94785
149 8 27 21 8773
150 35 131 124 83209
151 43 162 152 93815
152 43 165 139 86687
153 14 54 38 34553
154 41 159 144 105547
155 38 147 120 103487
156 45 170 160 213688
157 31 119 114 71220
158 13 49 39 23517
159 28 104 78 56926
160 31 120 119 91721
161 40 150 141 115168
162 30 112 101 111194
163 16 59 56 51009
164 37 136 133 135777
165 30 107 83 51513
166 35 130 116 74163
167 32 115 90 51633
168 27 107 36 75345
169 20 75 50 33416
170 18 71 61 83305
171 31 120 97 98952
172 31 116 98 102372
173 21 79 78 37238
174 39 150 117 103772
175 41 156 148 123969
176 13 51 41 27142
177 32 118 105 135400
178 18 71 55 21399
179 39 144 132 130115
180 14 47 44 24874
181 7 28 21 34988
182 17 68 50 45549
183 0 0 0 6023
184 30 110 73 64466
185 37 147 86 54990
186 0 0 0 1644
187 5 15 13 6179
188 1 4 4 3926
189 16 64 57 32755
190 32 111 48 34777
191 24 85 46 73224
192 17 68 48 27114
193 11 40 32 20760
194 24 80 68 37636
195 22 88 87 65461
196 12 48 43 30080
197 19 76 67 24094
198 13 51 46 69008
199 17 67 46 54968
200 15 59 56 46090
201 16 61 48 27507
202 24 76 44 10672
203 15 60 60 34029
204 17 68 65 46300
205 18 71 55 24760
206 20 76 38 18779
207 16 62 52 21280
208 16 61 60 40662
209 18 67 54 28987
210 22 88 86 22827
211 8 30 24 18513
212 17 64 52 30594
213 18 68 49 24006
214 16 64 61 27913
215 23 91 61 42744
216 22 88 81 12934
217 13 52 43 22574
218 13 49 40 41385
219 16 62 40 18653
220 16 61 56 18472
221 20 76 68 30976
222 22 88 79 63339
223 17 66 47 25568
224 18 71 57 33747
225 17 68 41 4154
226 12 48 29 19474
227 7 25 3 35130
228 17 68 60 39067
229 14 41 30 13310
230 23 90 79 65892
231 17 66 47 4143
232 14 54 40 28579
233 15 59 48 51776
234 17 60 36 21152
235 21 77 42 38084
236 18 68 49 27717
237 18 72 57 32928
238 17 67 12 11342
239 17 64 40 19499
240 16 63 43 16380
241 15 59 33 36874
242 21 84 77 48259
243 16 64 43 16734
244 14 56 45 28207
245 15 54 47 30143
246 17 67 43 41369
247 15 58 45 45833
248 15 59 50 29156
249 10 40 35 35944
250 6 22 7 36278
251 22 83 71 45588
252 21 81 67 45097
253 1 2 0 3895
254 18 72 62 28394
255 17 61 54 18632
256 4 15 4 2325
257 10 32 25 25139
258 16 62 40 27975
259 16 58 38 14483
260 9 36 19 13127
261 16 59 17 5839
262 17 68 67 24069
263 7 21 14 3738
264 15 55 30 18625
265 14 54 54 36341
266 14 55 35 24548
267 18 72 59 21792
268 12 41 24 26263
269 16 61 58 23686
270 21 67 42 49303
271 19 76 46 25659
272 16 64 61 28904
273 1 3 3 2781
274 16 63 52 29236
275 10 40 25 19546
276 19 69 40 22818
277 12 48 32 32689
278 2 8 4 5752
279 14 52 49 22197
280 17 66 63 20055
281 19 76 67 25272
282 14 43 32 82206
283 11 39 23 32073
284 4 14 7 5444
285 16 61 54 20154
286 20 71 37 36944
287 12 44 35 8019
288 15 60 51 30884
289 16 64 39 19540
totrevisions totseconds tothyperlinks totblogs\r
1 24188 146283 144 145
2 18273 98364 103 101
3 14130 86146 98 98
4 32287 96933 135 132
5 8654 79234 61 60
6 9245 42551 39 38
7 33251 195663 150 144
8 1271 6853 5 5
9 5279 21529 28 28
10 27101 95757 84 84
11 16373 85584 80 79
12 19716 143983 130 127
13 17753 75851 82 78
14 9028 59238 60 60
15 18653 93163 131 131
16 8828 96037 84 84
17 29498 151511 140 133
18 27563 136368 151 150
19 18293 112642 91 91
20 22530 94728 138 132
21 15977 105499 150 136
22 35082 121527 124 124
23 16116 127766 119 118
24 15849 98958 73 70
25 16026 77900 110 107
26 26569 85646 123 119
27 24785 98579 90 89
28 17569 130767 116 112
29 23825 131741 113 108
30 7869 53907 56 52
31 14975 178812 115 112
32 37791 146761 119 116
33 9605 82036 129 123
34 27295 163253 127 125
35 2746 27032 27 27
36 34461 171975 175 162
37 8098 65990 35 32
38 4787 86572 64 64
39 24919 159676 96 92
40 603 1929 0 0
41 16329 85371 84 83
42 12558 58391 41 41
43 7784 31580 47 47
44 28522 136815 126 120
45 22265 120642 105 105
46 14459 69107 80 79
47 14526 50495 70 65
48 22240 108016 73 70
49 11802 46341 57 55
50 7623 78348 40 39
51 11912 79336 68 67
52 7935 56968 21 21
53 18220 93176 127 127
54 19199 161632 154 152
55 19918 87850 116 113
56 21884 127969 102 99
57 2694 15049 7 7
58 15808 155135 148 141
59 3597 25109 21 21
60 5296 45824 35 35
61 25239 102996 112 109
62 29801 160604 137 133
63 18450 158051 135 123
64 7132 44547 26 26
65 34861 162647 230 230
66 35940 174141 181 166
67 16688 60622 71 68
68 24683 179566 147 147
69 46230 184301 190 179
70 10387 75661 64 61
71 21436 96144 105 101
72 30546 129847 107 108
73 19746 117286 94 90
74 15977 71180 116 114
75 22583 109377 106 103
76 17274 85298 143 142
77 16469 73631 81 79
78 14251 86767 89 88
79 3007 23824 26 25
80 16851 93487 84 83
81 21113 82981 113 113
82 17401 73815 120 118
83 23958 94552 110 110
84 23567 132190 134 129
85 13065 128754 54 51
86 15358 66363 96 93
87 14587 67808 78 76
88 12770 61724 51 49
89 24021 131722 121 118
90 9648 68580 38 38
91 20537 106175 145 141
92 7905 55792 59 58
93 4527 25157 27 27
94 30495 76669 91 91
95 7117 57283 48 48
96 17719 105805 68 63
97 27056 129484 58 56
98 33473 72413 150 144
99 9758 87831 74 73
100 21115 96971 181 168
101 7236 71299 65 64
102 13790 77494 97 97
103 32902 120336 121 117
104 25131 93913 99 100
105 30910 136048 152 149
106 35947 181248 188 187
107 29848 146123 138 127
108 6943 32036 40 37
109 42705 186646 254 245
110 31808 102255 87 87
111 26675 168237 178 177
112 8435 64219 51 49
113 7409 19630 49 49
114 14993 76825 73 73
115 36867 115338 176 177
116 33835 109427 94 94
117 24164 118168 120 117
118 12607 84845 66 60
119 22609 153197 56 55
120 5892 29877 39 39
121 17014 63506 66 64
122 5394 22445 27 26
123 9178 47695 65 64
124 6440 68370 58 58
125 21916 146304 98 95
126 4011 38233 25 25
127 5818 42071 26 26
128 18647 50517 77 76
129 20556 103950 130 129
130 238 5841 11 11
131 70 2341 2 2
132 22392 84396 101 101
133 3913 24610 31 28
134 12237 35753 36 36
135 8388 55515 120 89
136 22120 209056 195 193
137 338 6622 4 4
138 11727 115814 89 84
139 3704 11609 24 23
140 3988 13155 39 39
141 3030 18274 14 14
142 13520 72875 78 78
143 1421 10112 15 14
144 20923 142775 106 101
145 20237 68847 83 82
146 3219 17659 24 24
147 3769 20112 37 36
148 12252 61023 77 75
149 1888 13983 16 16
150 14497 65176 56 55
151 28864 132432 132 131
152 21721 112494 144 131
153 4821 45109 40 39
154 33644 170875 153 144
155 15923 180759 143 139
156 42935 214921 220 211
157 18864 100226 79 78
158 4977 32043 50 50
159 7785 54454 39 39
160 17939 78876 95 90
161 23436 170745 169 166
162 325 6940 12 12
163 13539 49025 63 57
164 34538 122037 134 133
165 12198 53782 69 69
166 26924 127748 119 119
167 12716 86839 119 119
168 8172 44830 75 65
169 10855 77395 63 61
170 11932 89324 55 49
171 14300 103300 103 101
172 25515 112283 197 196
173 2805 10901 16 15
174 29402 120691 140 136
175 16440 58106 89 89
176 11221 57140 40 40
177 28732 122422 125 123
178 5250 25899 21 21
179 28608 139296 167 163
180 8092 52678 32 29
181 4473 23853 36 35
182 1572 17306 13 13
183 2065 7953 5 5
184 14817 89455 96 96
185 16714 147866 151 151
186 556 4245 6 6
187 2089 21509 13 13
188 2658 7670 3 3
189 10695 66675 57 56
190 1669 14336 23 23
191 16267 53608 61 57
192 7768 30059 21 14
193 7252 29668 43 43
194 6387 22097 20 20
195 18715 96841 82 72
196 7936 41907 90 87
197 8643 27080 25 21
198 7294 35885 60 56
199 4570 41247 61 59
200 7185 28313 85 82
201 10058 36845 43 43
202 2342 16548 25 25
203 8509 36134 41 38
204 13275 55764 26 25
205 6816 28910 38 38
206 1930 13339 12 12
207 8086 25319 29 29
208 10737 66956 49 47
209 8033 47487 46 45
210 7058 52785 41 40
211 6782 44683 31 30
212 5401 35619 41 41
213 6521 21920 26 25
214 10856 45608 23 23
215 2154 7721 14 14
216 6117 20634 16 16
217 5238 29788 25 26
218 4820 31931 21 21
219 5615 37754 32 27
220 4272 32505 9 9
221 8702 40557 35 33
222 15340 94238 42 42
223 8030 44197 68 68
224 9526 43228 32 32
225 1278 4103 6 6
226 4236 44144 68 67
227 3023 32868 33 33
228 7196 27640 84 77
229 3394 14063 46 46
230 6371 28990 30 30
231 1574 4694 0 0
232 9620 42648 36 36
233 6978 64329 47 46
234 4911 21928 20 18
235 8645 25836 50 48
236 8987 22779 30 29
237 5544 40820 30 28
238 3083 27530 34 34
239 6909 32378 33 33
240 3189 10824 34 34
241 6745 39613 37 33
242 16724 60865 83 80
243 4850 19787 32 32
244 7025 20107 30 30
245 6047 36605 43 41
246 7377 40961 41 41
247 9078 48231 51 51
248 4605 39725 19 18
249 3238 21455 37 34
250 8100 23430 33 31
251 9653 62991 41 39
252 8914 49363 54 54
253 786 9604 14 14
254 6700 24552 25 24
255 5788 31493 25 24
256 593 3439 8 8
257 4506 19555 26 26
258 6382 21228 20 19
259 5621 23177 11 11
260 3997 22094 14 14
261 520 2342 3 1
262 8891 38798 40 39
263 999 3255 5 5
264 7067 24261 38 37
265 4639 18511 32 32
266 5654 40798 41 38
267 6928 28893 46 47
268 1514 21425 47 47
269 9238 50276 37 37
270 8204 37643 51 51
271 5926 30377 49 45
272 5785 27126 21 21
273 4 13 1 1
274 5930 42097 44 42
275 3710 24451 26 26
276 705 14335 21 21
277 443 5084 4 4
278 2416 9927 10 10
279 7747 43527 43 43
280 5432 27184 34 34
281 4913 21610 32 31
282 2650 20484 20 19
283 2370 20156 34 34
284 775 6012 6 6
285 5576 18475 12 11
286 1352 12645 24 24
287 3080 11017 16 16
288 10205 37623 72 72
289 6095 35873 27 21
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) months pageviews
-1.095e+04 5.115e+02 5.888e+00
logins compendium_views_info compendium_views_pr
1.731e+02 1.121e+02 1.486e+01
shared_compendiums blogged_computations compendiums_reviewed
-1.846e+02 3.881e+01 -8.980e+02
feedback_messages_p1 feedback_messages_p120 totsize
3.720e+02 1.878e+02 -9.884e-02
totrevisions totseconds tothyperlinks
-8.133e-01 8.609e-01 1.014e+02
`totblogs\\r`
-9.130e+01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-61954 -11767 592 10144 87279
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.095e+04 2.263e+04 -0.484 0.62883
months 5.115e+02 2.069e+03 0.247 0.80496
pageviews 5.888e+00 8.171e+00 0.721 0.47177
logins 1.731e+02 6.113e+01 2.833 0.00496 **
compendium_views_info 1.121e+02 1.748e+01 6.413 6.27e-10 ***
compendium_views_pr 1.486e+01 3.317e+01 0.448 0.65444
shared_compendiums -1.846e+02 5.642e+02 -0.327 0.74379
blogged_computations 3.881e+01 9.242e+01 0.420 0.67483
compendiums_reviewed -8.980e+02 7.012e+02 -1.281 0.20139
feedback_messages_p1 3.720e+02 2.110e+02 1.763 0.07905 .
feedback_messages_p120 1.878e+02 1.042e+02 1.802 0.07262 .
totsize -9.884e-02 6.485e-02 -1.524 0.12867
totrevisions -8.134e-01 3.191e-01 -2.549 0.01136 *
totseconds 8.609e-01 7.204e-02 11.951 < 2e-16 ***
tothyperlinks 1.014e+02 4.375e+02 0.232 0.81694
`totblogs\\r` -9.130e+01 4.534e+02 -0.201 0.84057
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 21570 on 273 degrees of freedom
Multiple R-squared: 0.9349, Adjusted R-squared: 0.9314
F-statistic: 261.5 on 15 and 273 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,] 0.7589582 4.820835e-01 2.410418e-01
[2,] 0.7285023 5.429953e-01 2.714977e-01
[3,] 0.6975363 6.049273e-01 3.024637e-01
[4,] 0.7630755 4.738490e-01 2.369245e-01
[5,] 0.9562850 8.743009e-02 4.371504e-02
[6,] 0.9300171 1.399658e-01 6.998290e-02
[7,] 0.9613308 7.733848e-02 3.866924e-02
[8,] 0.9720063 5.598732e-02 2.799366e-02
[9,] 0.9735433 5.291345e-02 2.645673e-02
[10,] 0.9739149 5.217022e-02 2.608511e-02
[11,] 0.9694971 6.100583e-02 3.050292e-02
[12,] 0.9589368 8.212644e-02 4.106322e-02
[13,] 0.9845742 3.085153e-02 1.542576e-02
[14,] 0.9775947 4.481052e-02 2.240526e-02
[15,] 0.9682872 6.342553e-02 3.171276e-02
[16,] 0.9557343 8.853146e-02 4.426573e-02
[17,] 0.9385968 1.228063e-01 6.140317e-02
[18,] 0.9219336 1.561327e-01 7.806637e-02
[19,] 0.8967184 2.065632e-01 1.032816e-01
[20,] 0.8671092 2.657817e-01 1.328908e-01
[21,] 0.9113405 1.773191e-01 8.865953e-02
[22,] 0.9284571 1.430859e-01 7.154295e-02
[23,] 0.9089143 1.821713e-01 9.108565e-02
[24,] 0.8889319 2.221361e-01 1.110681e-01
[25,] 0.8621206 2.757589e-01 1.378794e-01
[26,] 0.8328766 3.342469e-01 1.671234e-01
[27,] 0.8606837 2.786327e-01 1.393163e-01
[28,] 0.8314398 3.371204e-01 1.685602e-01
[29,] 0.7997034 4.005931e-01 2.002966e-01
[30,] 0.7637799 4.724402e-01 2.362201e-01
[31,] 0.7283524 5.432952e-01 2.716476e-01
[32,] 0.8917677 2.164646e-01 1.082323e-01
[33,] 0.9882208 2.355834e-02 1.177917e-02
[34,] 0.9880335 2.393300e-02 1.196650e-02
[35,] 0.9857599 2.848022e-02 1.424011e-02
[36,] 0.9960387 7.922568e-03 3.961284e-03
[37,] 0.9981113 3.777369e-03 1.888684e-03
[38,] 0.9982954 3.409191e-03 1.704596e-03
[39,] 0.9980789 3.842135e-03 1.921068e-03
[40,] 0.9983460 3.307990e-03 1.653995e-03
[41,] 0.9976585 4.682929e-03 2.341464e-03
[42,] 0.9971384 5.723101e-03 2.861551e-03
[43,] 0.9963006 7.398708e-03 3.699354e-03
[44,] 0.9951916 9.616764e-03 4.808382e-03
[45,] 0.9934736 1.305289e-02 6.526447e-03
[46,] 0.9912174 1.756528e-02 8.782638e-03
[47,] 0.9966249 6.750251e-03 3.375126e-03
[48,] 0.9958910 8.218075e-03 4.109038e-03
[49,] 0.9988805 2.239045e-03 1.119523e-03
[50,] 0.9985849 2.830276e-03 1.415138e-03
[51,] 0.9985339 2.932279e-03 1.466139e-03
[52,] 0.9986042 2.791555e-03 1.395778e-03
[53,] 0.9982294 3.541208e-03 1.770604e-03
[54,] 0.9977896 4.420799e-03 2.210399e-03
[55,] 0.9971509 5.698143e-03 2.849071e-03
[56,] 0.9961512 7.697640e-03 3.848820e-03
[57,] 0.9973905 5.219002e-03 2.609501e-03
[58,] 0.9967229 6.554188e-03 3.277094e-03
[59,] 0.9959801 8.039709e-03 4.019855e-03
[60,] 0.9952373 9.525468e-03 4.762734e-03
[61,] 0.9948643 1.027134e-02 5.135668e-03
[62,] 0.9932507 1.349854e-02 6.749269e-03
[63,] 0.9920480 1.590395e-02 7.951975e-03
[64,] 0.9899901 2.001980e-02 1.000990e-02
[65,] 0.9993834 1.233148e-03 6.165738e-04
[66,] 0.9992298 1.540497e-03 7.702484e-04
[67,] 0.9989407 2.118531e-03 1.059266e-03
[68,] 0.9985742 2.851613e-03 1.425806e-03
[69,] 0.9980915 3.817033e-03 1.908517e-03
[70,] 0.9977865 4.426908e-03 2.213454e-03
[71,] 0.9999466 1.067855e-04 5.339273e-05
[72,] 0.9999389 1.221696e-04 6.108482e-05
[73,] 0.9999685 6.296546e-05 3.148273e-05
[74,] 0.9999719 5.624288e-05 2.812144e-05
[75,] 0.9999618 7.634950e-05 3.817475e-05
[76,] 0.9999571 8.576029e-05 4.288014e-05
[77,] 0.9999396 1.208703e-04 6.043513e-05
[78,] 0.9999281 1.437704e-04 7.188521e-05
[79,] 0.9999038 1.924965e-04 9.624826e-05
[80,] 0.9999852 2.956592e-05 1.478296e-05
[81,] 0.9999810 3.796678e-05 1.898339e-05
[82,] 0.9999735 5.299414e-05 2.649707e-05
[83,] 0.9999619 7.626812e-05 3.813406e-05
[84,] 0.9999445 1.109990e-04 5.549951e-05
[85,] 0.9999683 6.335046e-05 3.167523e-05
[86,] 0.9999582 8.362544e-05 4.181272e-05
[87,] 0.9999399 1.202584e-04 6.012921e-05
[88,] 0.9999236 1.527816e-04 7.639079e-05
[89,] 0.9999643 7.139468e-05 3.569734e-05
[90,] 0.9999483 1.033190e-04 5.165951e-05
[91,] 0.9999308 1.384335e-04 6.921673e-05
[92,] 0.9999262 1.475822e-04 7.379112e-05
[93,] 0.9999252 1.496264e-04 7.481318e-05
[94,] 0.9999000 2.000814e-04 1.000407e-04
[95,] 0.9998692 2.615225e-04 1.307613e-04
[96,] 0.9998164 3.671178e-04 1.835589e-04
[97,] 0.9997852 4.296190e-04 2.148095e-04
[98,] 0.9997190 5.620362e-04 2.810181e-04
[99,] 0.9996111 7.777940e-04 3.888970e-04
[100,] 0.9997741 4.517441e-04 2.258721e-04
[101,] 0.9999749 5.027314e-05 2.513657e-05
[102,] 0.9999684 6.310173e-05 3.155086e-05
[103,] 0.9999542 9.150986e-05 4.575493e-05
[104,] 0.9999734 5.316235e-05 2.658117e-05
[105,] 0.9999760 4.801834e-05 2.400917e-05
[106,] 0.9999870 2.607171e-05 1.303586e-05
[107,] 0.9999872 2.568942e-05 1.284471e-05
[108,] 0.9999820 3.592488e-05 1.796244e-05
[109,] 0.9999747 5.069403e-05 2.534701e-05
[110,] 0.9999635 7.309023e-05 3.654511e-05
[111,] 0.9999900 2.004359e-05 1.002179e-05
[112,] 0.9999853 2.941650e-05 1.470825e-05
[113,] 0.9999785 4.303642e-05 2.151821e-05
[114,] 0.9999741 5.186658e-05 2.593329e-05
[115,] 0.9999656 6.874835e-05 3.437418e-05
[116,] 0.9999836 3.287148e-05 1.643574e-05
[117,] 0.9999791 4.184266e-05 2.092133e-05
[118,] 0.9999725 5.509243e-05 2.754622e-05
[119,] 0.9999606 7.888071e-05 3.944036e-05
[120,] 0.9999489 1.021913e-04 5.109564e-05
[121,] 0.9999444 1.111363e-04 5.556813e-05
[122,] 0.9999238 1.524186e-04 7.620932e-05
[123,] 0.9999221 1.557847e-04 7.789237e-05
[124,] 0.9999012 1.975595e-04 9.877975e-05
[125,] 0.9998913 2.174151e-04 1.087075e-04
[126,] 0.9999421 1.158863e-04 5.794316e-05
[127,] 0.9999595 8.106057e-05 4.053028e-05
[128,] 0.9999498 1.004173e-04 5.020864e-05
[129,] 0.9999661 6.771118e-05 3.385559e-05
[130,] 0.9999639 7.214111e-05 3.607055e-05
[131,] 0.9999594 8.116705e-05 4.058353e-05
[132,] 0.9999426 1.148004e-04 5.740018e-05
[133,] 0.9999517 9.663994e-05 4.831997e-05
[134,] 0.9999365 1.270885e-04 6.354423e-05
[135,] 0.9999242 1.516495e-04 7.582476e-05
[136,] 0.9998918 2.163483e-04 1.081741e-04
[137,] 0.9999312 1.376406e-04 6.882030e-05
[138,] 0.9999154 1.691656e-04 8.458279e-05
[139,] 0.9998799 2.402013e-04 1.201006e-04
[140,] 0.9998810 2.379769e-04 1.189884e-04
[141,] 0.9999184 1.632436e-04 8.162182e-05
[142,] 0.9998932 2.135996e-04 1.067998e-04
[143,] 0.9998542 2.915247e-04 1.457624e-04
[144,] 0.9998305 3.389865e-04 1.694933e-04
[145,] 0.9998335 3.329322e-04 1.664661e-04
[146,] 0.9998490 3.020804e-04 1.510402e-04
[147,] 0.9998483 3.033300e-04 1.516650e-04
[148,] 0.9998423 3.153601e-04 1.576800e-04
[149,] 0.9997962 4.075355e-04 2.037677e-04
[150,] 0.9997845 4.309662e-04 2.154831e-04
[151,] 0.9997367 5.266020e-04 2.633010e-04
[152,] 0.9999906 1.878525e-05 9.392627e-06
[153,] 0.9999877 2.453239e-05 1.226620e-05
[154,] 0.9999862 2.768411e-05 1.384206e-05
[155,] 0.9999953 9.330452e-06 4.665226e-06
[156,] 0.9999991 1.836853e-06 9.184267e-07
[157,] 0.9999993 1.427576e-06 7.137882e-07
[158,] 0.9999989 2.169114e-06 1.084557e-06
[159,] 0.9999989 2.274418e-06 1.137209e-06
[160,] 0.9999985 2.943957e-06 1.471979e-06
[161,] 0.9999978 4.365645e-06 2.182822e-06
[162,] 0.9999982 3.630824e-06 1.815412e-06
[163,] 0.9999974 5.107474e-06 2.553737e-06
[164,] 0.9999988 2.377639e-06 1.188819e-06
[165,] 0.9999982 3.613660e-06 1.806830e-06
[166,] 0.9999978 4.453446e-06 2.226723e-06
[167,] 0.9999970 5.924200e-06 2.962100e-06
[168,] 0.9999960 7.939471e-06 3.969736e-06
[169,] 0.9999958 8.370330e-06 4.185165e-06
[170,] 0.9999939 1.214116e-05 6.070582e-06
[171,] 0.9999906 1.879367e-05 9.396836e-06
[172,] 0.9999905 1.897637e-05 9.488187e-06
[173,] 0.9999997 5.888575e-07 2.944287e-07
[174,] 0.9999995 9.337537e-07 4.668769e-07
[175,] 0.9999993 1.433337e-06 7.166686e-07
[176,] 0.9999991 1.841954e-06 9.209768e-07
[177,] 0.9999986 2.798607e-06 1.399304e-06
[178,] 0.9999986 2.710124e-06 1.355062e-06
[179,] 0.9999984 3.267919e-06 1.633960e-06
[180,] 0.9999975 5.065442e-06 2.532721e-06
[181,] 0.9999976 4.707151e-06 2.353575e-06
[182,] 0.9999966 6.853623e-06 3.426811e-06
[183,] 0.9999951 9.747627e-06 4.873814e-06
[184,] 0.9999923 1.543726e-05 7.718631e-06
[185,] 0.9999913 1.741402e-05 8.707009e-06
[186,] 0.9999861 2.787413e-05 1.393706e-05
[187,] 0.9999806 3.885779e-05 1.942890e-05
[188,] 0.9999701 5.976719e-05 2.988360e-05
[189,] 0.9999540 9.205721e-05 4.602861e-05
[190,] 0.9999883 2.347738e-05 1.173869e-05
[191,] 0.9999930 1.403001e-05 7.015007e-06
[192,] 0.9999885 2.300933e-05 1.150466e-05
[193,] 0.9999829 3.428991e-05 1.714495e-05
[194,] 0.9999944 1.125294e-05 5.626470e-06
[195,] 0.9999908 1.844330e-05 9.221648e-06
[196,] 0.9999852 2.955182e-05 1.477591e-05
[197,] 0.9999772 4.564883e-05 2.282442e-05
[198,] 0.9999676 6.484099e-05 3.242049e-05
[199,] 0.9999866 2.679903e-05 1.339951e-05
[200,] 0.9999779 4.417239e-05 2.208620e-05
[201,] 0.9999654 6.925854e-05 3.462927e-05
[202,] 0.9999495 1.009976e-04 5.049881e-05
[203,] 0.9999371 1.258518e-04 6.292589e-05
[204,] 0.9999823 3.547393e-05 1.773696e-05
[205,] 0.9999853 2.942998e-05 1.471499e-05
[206,] 0.9999750 5.002741e-05 2.501370e-05
[207,] 0.9999575 8.500480e-05 4.250240e-05
[208,] 0.9999393 1.214587e-04 6.072937e-05
[209,] 0.9999147 1.705483e-04 8.527413e-05
[210,] 0.9999003 1.994324e-04 9.971619e-05
[211,] 0.9998348 3.303146e-04 1.651573e-04
[212,] 0.9999073 1.854216e-04 9.271079e-05
[213,] 0.9999127 1.745128e-04 8.725638e-05
[214,] 0.9998525 2.949247e-04 1.474623e-04
[215,] 0.9999993 1.366537e-06 6.832684e-07
[216,] 0.9999987 2.609316e-06 1.304658e-06
[217,] 0.9999974 5.109893e-06 2.554947e-06
[218,] 0.9999951 9.840565e-06 4.920282e-06
[219,] 1.0000000 4.689406e-08 2.344703e-08
[220,] 0.9999999 1.093255e-07 5.466273e-08
[221,] 0.9999999 2.430081e-07 1.215040e-07
[222,] 0.9999998 4.573941e-07 2.286970e-07
[223,] 0.9999995 1.002119e-06 5.010597e-07
[224,] 0.9999991 1.840410e-06 9.202051e-07
[225,] 0.9999982 3.550913e-06 1.775456e-06
[226,] 0.9999962 7.589773e-06 3.794887e-06
[227,] 0.9999944 1.128780e-05 5.643899e-06
[228,] 0.9999893 2.141866e-05 1.070933e-05
[229,] 0.9999920 1.598951e-05 7.994755e-06
[230,] 0.9999848 3.034303e-05 1.517151e-05
[231,] 0.9999736 5.274978e-05 2.637489e-05
[232,] 0.9999644 7.123886e-05 3.561943e-05
[233,] 0.9999431 1.138623e-04 5.693113e-05
[234,] 0.9999037 1.926978e-04 9.634891e-05
[235,] 0.9997923 4.153425e-04 2.076712e-04
[236,] 0.9995741 8.517297e-04 4.258648e-04
[237,] 0.9996017 7.965238e-04 3.982619e-04
[238,] 0.9991597 1.680700e-03 8.403499e-04
[239,] 0.9988486 2.302852e-03 1.151426e-03
[240,] 0.9992040 1.591961e-03 7.959806e-04
[241,] 0.9983391 3.321759e-03 1.660879e-03
[242,] 0.9970983 5.803421e-03 2.901710e-03
[243,] 0.9948534 1.029318e-02 5.146591e-03
[244,] 0.9895579 2.088426e-02 1.044213e-02
[245,] 0.9855411 2.891786e-02 1.445893e-02
[246,] 0.9860509 2.789818e-02 1.394909e-02
[247,] 0.9786234 4.275323e-02 2.137661e-02
[248,] 0.9586665 8.266701e-02 4.133351e-02
[249,] 0.9251428 1.497144e-01 7.485722e-02
[250,] 0.8815591 2.368819e-01 1.184409e-01
[251,] 0.9982998 3.400309e-03 1.700155e-03
[252,] 0.9973915 5.216949e-03 2.608474e-03
> postscript(file="/var/fisher/rcomp/tmp/1vxvz1353429302.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/20upe1353429302.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3dtnw1353429302.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/49dm91353429302.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5x5qv1353429302.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
21074.72649 -20519.78306 7870.05886 -41007.02331 11510.43376 -14185.53638
7 8 9 10 11 12
14303.02797 5749.60678 19930.70456 -17884.44716 17810.13091 -2952.13157
13 14 15 16 17 18
5727.38507 -3516.21548 40462.66907 7184.84360 -43569.80202 24436.37982
19 20 21 22 23 24
7692.55220 2003.65638 6415.14513 15853.09209 87278.95998 7645.22409
25 26 27 28 29 30
-21944.95667 -51641.54955 -37765.03823 -29882.44908 17474.97272 -4020.25906
31 32 33 34 35 36
-46142.39895 -8154.99380 -5284.08699 5370.10016 -535.91563 3275.98014
37 38 39 40 41 42
5010.73158 7787.34075 36742.07241 592.21407 10143.91916 22859.65611
43 44 45 46 47 48
-11767.45811 -4000.11469 -9972.74551 -942.50469 -13221.56247 -16939.78913
49 50 51 52 53 54
10228.15378 -52775.29333 40094.54391 -24870.76464 -4462.64703 -44503.80506
55 56 57 58 59 60
-38010.91926 -22903.90947 -14024.04538 32974.09462 -641.73360 -9860.03080
61 62 63 64 65 66
9086.82787 3045.30259 4359.67114 3999.42948 -32511.76643 -14651.02108
67 68 69 70 71 72
48230.81497 -11599.60183 -27922.54325 -26788.28188 12332.29850 15095.14885
73 74 75 76 77 78
8855.73144 -4810.07169 -32905.58683 6608.76977 -15386.28681 -11953.62267
79 80 81 82 83 84
-15222.08154 3015.45390 10733.61154 -9942.20061 70572.43420 16295.12550
85 86 87 88 89 90
-946.58346 -5408.98896 1990.16647 -12695.78743 75212.84685 -19160.72888
91 92 93 94 95 96
37213.24270 -19015.81798 -13529.06478 18909.96930 9569.54230 9165.42606
97 98 99 100 101 102
17338.17757 -52017.66619 17976.79326 6842.24045 -2864.69254 4259.80765
103 104 105 106 107 108
32626.46428 12447.76718 6140.80072 -2829.91707 -30676.85455 -1047.73817
109 110 111 112 113 114
9927.28142 24722.25238 -16694.35110 -7530.89671 -9654.42486 4035.68225
115 116 117 118 119 120
-14661.89109 -9611.55676 5625.96356 34869.15564 -61954.04444 -8741.19467
121 122 123 124 125 126
987.26448 -28043.58188 -28943.31007 -38348.96348 24726.80830 8946.32089
127 128 129 130 131 132
6608.33252 1274.80004 47112.75269 2942.14333 460.31419 -13459.42815
133 134 135 136 137 138
14428.02725 -37363.25820 -4865.15717 -6372.61483 -95.25976 12267.43481
139 140 141 142 143 144
-11229.78463 -3018.10992 -18011.02225 -11309.11922 15092.46372 -33353.23684
145 146 147 148 149 150
30773.81146 -7408.13295 25729.12934 -14950.36984 -14120.03859 4888.42826
151 152 153 154 155 156
23939.92426 -5505.88811 -6108.88646 -2061.46418 -31240.42272 17399.27575
157 158 159 160 161 162
2569.19977 12186.46850 -24696.36681 10405.67748 -956.95996 10886.13974
163 164 165 166 167 168
-1630.75098 21371.82835 -13737.94785 15313.15411 -12792.74064 24867.23933
169 170 171 172 173 174
2189.38153 73306.63096 9085.89572 10720.75105 45489.29495 30772.78831
175 176 177 178 179 180
-38165.23566 -2649.90852 -24957.27142 12853.39845 1142.67774 27401.65851
181 182 183 184 185 186
-11137.75102 -22393.18989 3265.99110 13013.04412 369.42035 -388.47114
187 188 189 190 191 192
-3236.44100 8481.71350 -4992.98571 31420.87798 45935.99045 1692.85001
193 194 195 196 197 198
-9836.54639 -14486.97726 -20706.78599 11026.11854 -14487.28688 3174.47025
199 200 201 202 203 204
-22284.74306 2789.03224 5111.08554 6510.38756 22600.62992 -4717.97840
205 206 207 208 209 210
-23549.93755 -3947.58888 3688.04044 32703.67295 22671.31358 -3601.13189
211 212 213 214 215 216
-667.53534 30949.13834 452.95791 -2725.69812 -16247.18926 -14593.68144
217 218 219 220 221 222
-29911.11985 -7408.49278 -6303.89826 14597.34014 -16840.21416 -44230.57296
223 224 225 226 227 228
-40804.23915 -4138.77127 1104.92515 2194.38172 12078.70842 -16788.51807
229 230 231 232 233 234
-6088.08174 -22667.52215 -10632.96748 -5480.21525 -46863.34021 -6199.51171
235 236 237 238 239 240
-13921.87209 1032.88504 49290.61603 -12296.25933 -11791.85535 -12619.52198
241 242 243 244 245 246
5262.00574 3826.29011 -7093.55220 -1700.11613 -6999.60203 -9275.68322
247 248 249 250 251 252
-16305.87397 7398.89194 12209.34851 -9086.29257 3933.23897 2482.21618
253 254 255 256 257 258
5991.31193 5006.55000 -15065.76846 4825.97374 -7905.33660 20322.68858
259 260 261 262 263 264
10593.39544 1427.36402 -8009.11909 1100.94393 14886.81373 1082.48925
265 266 267 268 269 270
-5863.87532 3478.86790 -13116.53143 1004.54850 33506.51510 -7018.75133
271 272 273 274 275 276
-845.59658 2734.25136 6392.50846 5074.45962 9731.21520 -533.99111
277 278 279 280 281 282
19718.69755 4393.22603 -7700.43938 12597.97671 2656.97565 30786.60221
283 284 285 286 287 288
11241.61444 11546.00142 5394.89705 5605.94311 8129.93347 -4093.56006
289
-9607.95091
> postscript(file="/var/fisher/rcomp/tmp/6dans1353429302.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 21074.72649 NA
1 -20519.78306 21074.72649
2 7870.05886 -20519.78306
3 -41007.02331 7870.05886
4 11510.43376 -41007.02331
5 -14185.53638 11510.43376
6 14303.02797 -14185.53638
7 5749.60678 14303.02797
8 19930.70456 5749.60678
9 -17884.44716 19930.70456
10 17810.13091 -17884.44716
11 -2952.13157 17810.13091
12 5727.38507 -2952.13157
13 -3516.21548 5727.38507
14 40462.66907 -3516.21548
15 7184.84360 40462.66907
16 -43569.80202 7184.84360
17 24436.37982 -43569.80202
18 7692.55220 24436.37982
19 2003.65638 7692.55220
20 6415.14513 2003.65638
21 15853.09209 6415.14513
22 87278.95998 15853.09209
23 7645.22409 87278.95998
24 -21944.95667 7645.22409
25 -51641.54955 -21944.95667
26 -37765.03823 -51641.54955
27 -29882.44908 -37765.03823
28 17474.97272 -29882.44908
29 -4020.25906 17474.97272
30 -46142.39895 -4020.25906
31 -8154.99380 -46142.39895
32 -5284.08699 -8154.99380
33 5370.10016 -5284.08699
34 -535.91563 5370.10016
35 3275.98014 -535.91563
36 5010.73158 3275.98014
37 7787.34075 5010.73158
38 36742.07241 7787.34075
39 592.21407 36742.07241
40 10143.91916 592.21407
41 22859.65611 10143.91916
42 -11767.45811 22859.65611
43 -4000.11469 -11767.45811
44 -9972.74551 -4000.11469
45 -942.50469 -9972.74551
46 -13221.56247 -942.50469
47 -16939.78913 -13221.56247
48 10228.15378 -16939.78913
49 -52775.29333 10228.15378
50 40094.54391 -52775.29333
51 -24870.76464 40094.54391
52 -4462.64703 -24870.76464
53 -44503.80506 -4462.64703
54 -38010.91926 -44503.80506
55 -22903.90947 -38010.91926
56 -14024.04538 -22903.90947
57 32974.09462 -14024.04538
58 -641.73360 32974.09462
59 -9860.03080 -641.73360
60 9086.82787 -9860.03080
61 3045.30259 9086.82787
62 4359.67114 3045.30259
63 3999.42948 4359.67114
64 -32511.76643 3999.42948
65 -14651.02108 -32511.76643
66 48230.81497 -14651.02108
67 -11599.60183 48230.81497
68 -27922.54325 -11599.60183
69 -26788.28188 -27922.54325
70 12332.29850 -26788.28188
71 15095.14885 12332.29850
72 8855.73144 15095.14885
73 -4810.07169 8855.73144
74 -32905.58683 -4810.07169
75 6608.76977 -32905.58683
76 -15386.28681 6608.76977
77 -11953.62267 -15386.28681
78 -15222.08154 -11953.62267
79 3015.45390 -15222.08154
80 10733.61154 3015.45390
81 -9942.20061 10733.61154
82 70572.43420 -9942.20061
83 16295.12550 70572.43420
84 -946.58346 16295.12550
85 -5408.98896 -946.58346
86 1990.16647 -5408.98896
87 -12695.78743 1990.16647
88 75212.84685 -12695.78743
89 -19160.72888 75212.84685
90 37213.24270 -19160.72888
91 -19015.81798 37213.24270
92 -13529.06478 -19015.81798
93 18909.96930 -13529.06478
94 9569.54230 18909.96930
95 9165.42606 9569.54230
96 17338.17757 9165.42606
97 -52017.66619 17338.17757
98 17976.79326 -52017.66619
99 6842.24045 17976.79326
100 -2864.69254 6842.24045
101 4259.80765 -2864.69254
102 32626.46428 4259.80765
103 12447.76718 32626.46428
104 6140.80072 12447.76718
105 -2829.91707 6140.80072
106 -30676.85455 -2829.91707
107 -1047.73817 -30676.85455
108 9927.28142 -1047.73817
109 24722.25238 9927.28142
110 -16694.35110 24722.25238
111 -7530.89671 -16694.35110
112 -9654.42486 -7530.89671
113 4035.68225 -9654.42486
114 -14661.89109 4035.68225
115 -9611.55676 -14661.89109
116 5625.96356 -9611.55676
117 34869.15564 5625.96356
118 -61954.04444 34869.15564
119 -8741.19467 -61954.04444
120 987.26448 -8741.19467
121 -28043.58188 987.26448
122 -28943.31007 -28043.58188
123 -38348.96348 -28943.31007
124 24726.80830 -38348.96348
125 8946.32089 24726.80830
126 6608.33252 8946.32089
127 1274.80004 6608.33252
128 47112.75269 1274.80004
129 2942.14333 47112.75269
130 460.31419 2942.14333
131 -13459.42815 460.31419
132 14428.02725 -13459.42815
133 -37363.25820 14428.02725
134 -4865.15717 -37363.25820
135 -6372.61483 -4865.15717
136 -95.25976 -6372.61483
137 12267.43481 -95.25976
138 -11229.78463 12267.43481
139 -3018.10992 -11229.78463
140 -18011.02225 -3018.10992
141 -11309.11922 -18011.02225
142 15092.46372 -11309.11922
143 -33353.23684 15092.46372
144 30773.81146 -33353.23684
145 -7408.13295 30773.81146
146 25729.12934 -7408.13295
147 -14950.36984 25729.12934
148 -14120.03859 -14950.36984
149 4888.42826 -14120.03859
150 23939.92426 4888.42826
151 -5505.88811 23939.92426
152 -6108.88646 -5505.88811
153 -2061.46418 -6108.88646
154 -31240.42272 -2061.46418
155 17399.27575 -31240.42272
156 2569.19977 17399.27575
157 12186.46850 2569.19977
158 -24696.36681 12186.46850
159 10405.67748 -24696.36681
160 -956.95996 10405.67748
161 10886.13974 -956.95996
162 -1630.75098 10886.13974
163 21371.82835 -1630.75098
164 -13737.94785 21371.82835
165 15313.15411 -13737.94785
166 -12792.74064 15313.15411
167 24867.23933 -12792.74064
168 2189.38153 24867.23933
169 73306.63096 2189.38153
170 9085.89572 73306.63096
171 10720.75105 9085.89572
172 45489.29495 10720.75105
173 30772.78831 45489.29495
174 -38165.23566 30772.78831
175 -2649.90852 -38165.23566
176 -24957.27142 -2649.90852
177 12853.39845 -24957.27142
178 1142.67774 12853.39845
179 27401.65851 1142.67774
180 -11137.75102 27401.65851
181 -22393.18989 -11137.75102
182 3265.99110 -22393.18989
183 13013.04412 3265.99110
184 369.42035 13013.04412
185 -388.47114 369.42035
186 -3236.44100 -388.47114
187 8481.71350 -3236.44100
188 -4992.98571 8481.71350
189 31420.87798 -4992.98571
190 45935.99045 31420.87798
191 1692.85001 45935.99045
192 -9836.54639 1692.85001
193 -14486.97726 -9836.54639
194 -20706.78599 -14486.97726
195 11026.11854 -20706.78599
196 -14487.28688 11026.11854
197 3174.47025 -14487.28688
198 -22284.74306 3174.47025
199 2789.03224 -22284.74306
200 5111.08554 2789.03224
201 6510.38756 5111.08554
202 22600.62992 6510.38756
203 -4717.97840 22600.62992
204 -23549.93755 -4717.97840
205 -3947.58888 -23549.93755
206 3688.04044 -3947.58888
207 32703.67295 3688.04044
208 22671.31358 32703.67295
209 -3601.13189 22671.31358
210 -667.53534 -3601.13189
211 30949.13834 -667.53534
212 452.95791 30949.13834
213 -2725.69812 452.95791
214 -16247.18926 -2725.69812
215 -14593.68144 -16247.18926
216 -29911.11985 -14593.68144
217 -7408.49278 -29911.11985
218 -6303.89826 -7408.49278
219 14597.34014 -6303.89826
220 -16840.21416 14597.34014
221 -44230.57296 -16840.21416
222 -40804.23915 -44230.57296
223 -4138.77127 -40804.23915
224 1104.92515 -4138.77127
225 2194.38172 1104.92515
226 12078.70842 2194.38172
227 -16788.51807 12078.70842
228 -6088.08174 -16788.51807
229 -22667.52215 -6088.08174
230 -10632.96748 -22667.52215
231 -5480.21525 -10632.96748
232 -46863.34021 -5480.21525
233 -6199.51171 -46863.34021
234 -13921.87209 -6199.51171
235 1032.88504 -13921.87209
236 49290.61603 1032.88504
237 -12296.25933 49290.61603
238 -11791.85535 -12296.25933
239 -12619.52198 -11791.85535
240 5262.00574 -12619.52198
241 3826.29011 5262.00574
242 -7093.55220 3826.29011
243 -1700.11613 -7093.55220
244 -6999.60203 -1700.11613
245 -9275.68322 -6999.60203
246 -16305.87397 -9275.68322
247 7398.89194 -16305.87397
248 12209.34851 7398.89194
249 -9086.29257 12209.34851
250 3933.23897 -9086.29257
251 2482.21618 3933.23897
252 5991.31193 2482.21618
253 5006.55000 5991.31193
254 -15065.76846 5006.55000
255 4825.97374 -15065.76846
256 -7905.33660 4825.97374
257 20322.68858 -7905.33660
258 10593.39544 20322.68858
259 1427.36402 10593.39544
260 -8009.11909 1427.36402
261 1100.94393 -8009.11909
262 14886.81373 1100.94393
263 1082.48925 14886.81373
264 -5863.87532 1082.48925
265 3478.86790 -5863.87532
266 -13116.53143 3478.86790
267 1004.54850 -13116.53143
268 33506.51510 1004.54850
269 -7018.75133 33506.51510
270 -845.59658 -7018.75133
271 2734.25136 -845.59658
272 6392.50846 2734.25136
273 5074.45962 6392.50846
274 9731.21520 5074.45962
275 -533.99111 9731.21520
276 19718.69755 -533.99111
277 4393.22603 19718.69755
278 -7700.43938 4393.22603
279 12597.97671 -7700.43938
280 2656.97565 12597.97671
281 30786.60221 2656.97565
282 11241.61444 30786.60221
283 11546.00142 11241.61444
284 5394.89705 11546.00142
285 5605.94311 5394.89705
286 8129.93347 5605.94311
287 -4093.56006 8129.93347
288 -9607.95091 -4093.56006
289 NA -9607.95091
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -20519.78306 21074.72649
[2,] 7870.05886 -20519.78306
[3,] -41007.02331 7870.05886
[4,] 11510.43376 -41007.02331
[5,] -14185.53638 11510.43376
[6,] 14303.02797 -14185.53638
[7,] 5749.60678 14303.02797
[8,] 19930.70456 5749.60678
[9,] -17884.44716 19930.70456
[10,] 17810.13091 -17884.44716
[11,] -2952.13157 17810.13091
[12,] 5727.38507 -2952.13157
[13,] -3516.21548 5727.38507
[14,] 40462.66907 -3516.21548
[15,] 7184.84360 40462.66907
[16,] -43569.80202 7184.84360
[17,] 24436.37982 -43569.80202
[18,] 7692.55220 24436.37982
[19,] 2003.65638 7692.55220
[20,] 6415.14513 2003.65638
[21,] 15853.09209 6415.14513
[22,] 87278.95998 15853.09209
[23,] 7645.22409 87278.95998
[24,] -21944.95667 7645.22409
[25,] -51641.54955 -21944.95667
[26,] -37765.03823 -51641.54955
[27,] -29882.44908 -37765.03823
[28,] 17474.97272 -29882.44908
[29,] -4020.25906 17474.97272
[30,] -46142.39895 -4020.25906
[31,] -8154.99380 -46142.39895
[32,] -5284.08699 -8154.99380
[33,] 5370.10016 -5284.08699
[34,] -535.91563 5370.10016
[35,] 3275.98014 -535.91563
[36,] 5010.73158 3275.98014
[37,] 7787.34075 5010.73158
[38,] 36742.07241 7787.34075
[39,] 592.21407 36742.07241
[40,] 10143.91916 592.21407
[41,] 22859.65611 10143.91916
[42,] -11767.45811 22859.65611
[43,] -4000.11469 -11767.45811
[44,] -9972.74551 -4000.11469
[45,] -942.50469 -9972.74551
[46,] -13221.56247 -942.50469
[47,] -16939.78913 -13221.56247
[48,] 10228.15378 -16939.78913
[49,] -52775.29333 10228.15378
[50,] 40094.54391 -52775.29333
[51,] -24870.76464 40094.54391
[52,] -4462.64703 -24870.76464
[53,] -44503.80506 -4462.64703
[54,] -38010.91926 -44503.80506
[55,] -22903.90947 -38010.91926
[56,] -14024.04538 -22903.90947
[57,] 32974.09462 -14024.04538
[58,] -641.73360 32974.09462
[59,] -9860.03080 -641.73360
[60,] 9086.82787 -9860.03080
[61,] 3045.30259 9086.82787
[62,] 4359.67114 3045.30259
[63,] 3999.42948 4359.67114
[64,] -32511.76643 3999.42948
[65,] -14651.02108 -32511.76643
[66,] 48230.81497 -14651.02108
[67,] -11599.60183 48230.81497
[68,] -27922.54325 -11599.60183
[69,] -26788.28188 -27922.54325
[70,] 12332.29850 -26788.28188
[71,] 15095.14885 12332.29850
[72,] 8855.73144 15095.14885
[73,] -4810.07169 8855.73144
[74,] -32905.58683 -4810.07169
[75,] 6608.76977 -32905.58683
[76,] -15386.28681 6608.76977
[77,] -11953.62267 -15386.28681
[78,] -15222.08154 -11953.62267
[79,] 3015.45390 -15222.08154
[80,] 10733.61154 3015.45390
[81,] -9942.20061 10733.61154
[82,] 70572.43420 -9942.20061
[83,] 16295.12550 70572.43420
[84,] -946.58346 16295.12550
[85,] -5408.98896 -946.58346
[86,] 1990.16647 -5408.98896
[87,] -12695.78743 1990.16647
[88,] 75212.84685 -12695.78743
[89,] -19160.72888 75212.84685
[90,] 37213.24270 -19160.72888
[91,] -19015.81798 37213.24270
[92,] -13529.06478 -19015.81798
[93,] 18909.96930 -13529.06478
[94,] 9569.54230 18909.96930
[95,] 9165.42606 9569.54230
[96,] 17338.17757 9165.42606
[97,] -52017.66619 17338.17757
[98,] 17976.79326 -52017.66619
[99,] 6842.24045 17976.79326
[100,] -2864.69254 6842.24045
[101,] 4259.80765 -2864.69254
[102,] 32626.46428 4259.80765
[103,] 12447.76718 32626.46428
[104,] 6140.80072 12447.76718
[105,] -2829.91707 6140.80072
[106,] -30676.85455 -2829.91707
[107,] -1047.73817 -30676.85455
[108,] 9927.28142 -1047.73817
[109,] 24722.25238 9927.28142
[110,] -16694.35110 24722.25238
[111,] -7530.89671 -16694.35110
[112,] -9654.42486 -7530.89671
[113,] 4035.68225 -9654.42486
[114,] -14661.89109 4035.68225
[115,] -9611.55676 -14661.89109
[116,] 5625.96356 -9611.55676
[117,] 34869.15564 5625.96356
[118,] -61954.04444 34869.15564
[119,] -8741.19467 -61954.04444
[120,] 987.26448 -8741.19467
[121,] -28043.58188 987.26448
[122,] -28943.31007 -28043.58188
[123,] -38348.96348 -28943.31007
[124,] 24726.80830 -38348.96348
[125,] 8946.32089 24726.80830
[126,] 6608.33252 8946.32089
[127,] 1274.80004 6608.33252
[128,] 47112.75269 1274.80004
[129,] 2942.14333 47112.75269
[130,] 460.31419 2942.14333
[131,] -13459.42815 460.31419
[132,] 14428.02725 -13459.42815
[133,] -37363.25820 14428.02725
[134,] -4865.15717 -37363.25820
[135,] -6372.61483 -4865.15717
[136,] -95.25976 -6372.61483
[137,] 12267.43481 -95.25976
[138,] -11229.78463 12267.43481
[139,] -3018.10992 -11229.78463
[140,] -18011.02225 -3018.10992
[141,] -11309.11922 -18011.02225
[142,] 15092.46372 -11309.11922
[143,] -33353.23684 15092.46372
[144,] 30773.81146 -33353.23684
[145,] -7408.13295 30773.81146
[146,] 25729.12934 -7408.13295
[147,] -14950.36984 25729.12934
[148,] -14120.03859 -14950.36984
[149,] 4888.42826 -14120.03859
[150,] 23939.92426 4888.42826
[151,] -5505.88811 23939.92426
[152,] -6108.88646 -5505.88811
[153,] -2061.46418 -6108.88646
[154,] -31240.42272 -2061.46418
[155,] 17399.27575 -31240.42272
[156,] 2569.19977 17399.27575
[157,] 12186.46850 2569.19977
[158,] -24696.36681 12186.46850
[159,] 10405.67748 -24696.36681
[160,] -956.95996 10405.67748
[161,] 10886.13974 -956.95996
[162,] -1630.75098 10886.13974
[163,] 21371.82835 -1630.75098
[164,] -13737.94785 21371.82835
[165,] 15313.15411 -13737.94785
[166,] -12792.74064 15313.15411
[167,] 24867.23933 -12792.74064
[168,] 2189.38153 24867.23933
[169,] 73306.63096 2189.38153
[170,] 9085.89572 73306.63096
[171,] 10720.75105 9085.89572
[172,] 45489.29495 10720.75105
[173,] 30772.78831 45489.29495
[174,] -38165.23566 30772.78831
[175,] -2649.90852 -38165.23566
[176,] -24957.27142 -2649.90852
[177,] 12853.39845 -24957.27142
[178,] 1142.67774 12853.39845
[179,] 27401.65851 1142.67774
[180,] -11137.75102 27401.65851
[181,] -22393.18989 -11137.75102
[182,] 3265.99110 -22393.18989
[183,] 13013.04412 3265.99110
[184,] 369.42035 13013.04412
[185,] -388.47114 369.42035
[186,] -3236.44100 -388.47114
[187,] 8481.71350 -3236.44100
[188,] -4992.98571 8481.71350
[189,] 31420.87798 -4992.98571
[190,] 45935.99045 31420.87798
[191,] 1692.85001 45935.99045
[192,] -9836.54639 1692.85001
[193,] -14486.97726 -9836.54639
[194,] -20706.78599 -14486.97726
[195,] 11026.11854 -20706.78599
[196,] -14487.28688 11026.11854
[197,] 3174.47025 -14487.28688
[198,] -22284.74306 3174.47025
[199,] 2789.03224 -22284.74306
[200,] 5111.08554 2789.03224
[201,] 6510.38756 5111.08554
[202,] 22600.62992 6510.38756
[203,] -4717.97840 22600.62992
[204,] -23549.93755 -4717.97840
[205,] -3947.58888 -23549.93755
[206,] 3688.04044 -3947.58888
[207,] 32703.67295 3688.04044
[208,] 22671.31358 32703.67295
[209,] -3601.13189 22671.31358
[210,] -667.53534 -3601.13189
[211,] 30949.13834 -667.53534
[212,] 452.95791 30949.13834
[213,] -2725.69812 452.95791
[214,] -16247.18926 -2725.69812
[215,] -14593.68144 -16247.18926
[216,] -29911.11985 -14593.68144
[217,] -7408.49278 -29911.11985
[218,] -6303.89826 -7408.49278
[219,] 14597.34014 -6303.89826
[220,] -16840.21416 14597.34014
[221,] -44230.57296 -16840.21416
[222,] -40804.23915 -44230.57296
[223,] -4138.77127 -40804.23915
[224,] 1104.92515 -4138.77127
[225,] 2194.38172 1104.92515
[226,] 12078.70842 2194.38172
[227,] -16788.51807 12078.70842
[228,] -6088.08174 -16788.51807
[229,] -22667.52215 -6088.08174
[230,] -10632.96748 -22667.52215
[231,] -5480.21525 -10632.96748
[232,] -46863.34021 -5480.21525
[233,] -6199.51171 -46863.34021
[234,] -13921.87209 -6199.51171
[235,] 1032.88504 -13921.87209
[236,] 49290.61603 1032.88504
[237,] -12296.25933 49290.61603
[238,] -11791.85535 -12296.25933
[239,] -12619.52198 -11791.85535
[240,] 5262.00574 -12619.52198
[241,] 3826.29011 5262.00574
[242,] -7093.55220 3826.29011
[243,] -1700.11613 -7093.55220
[244,] -6999.60203 -1700.11613
[245,] -9275.68322 -6999.60203
[246,] -16305.87397 -9275.68322
[247,] 7398.89194 -16305.87397
[248,] 12209.34851 7398.89194
[249,] -9086.29257 12209.34851
[250,] 3933.23897 -9086.29257
[251,] 2482.21618 3933.23897
[252,] 5991.31193 2482.21618
[253,] 5006.55000 5991.31193
[254,] -15065.76846 5006.55000
[255,] 4825.97374 -15065.76846
[256,] -7905.33660 4825.97374
[257,] 20322.68858 -7905.33660
[258,] 10593.39544 20322.68858
[259,] 1427.36402 10593.39544
[260,] -8009.11909 1427.36402
[261,] 1100.94393 -8009.11909
[262,] 14886.81373 1100.94393
[263,] 1082.48925 14886.81373
[264,] -5863.87532 1082.48925
[265,] 3478.86790 -5863.87532
[266,] -13116.53143 3478.86790
[267,] 1004.54850 -13116.53143
[268,] 33506.51510 1004.54850
[269,] -7018.75133 33506.51510
[270,] -845.59658 -7018.75133
[271,] 2734.25136 -845.59658
[272,] 6392.50846 2734.25136
[273,] 5074.45962 6392.50846
[274,] 9731.21520 5074.45962
[275,] -533.99111 9731.21520
[276,] 19718.69755 -533.99111
[277,] 4393.22603 19718.69755
[278,] -7700.43938 4393.22603
[279,] 12597.97671 -7700.43938
[280,] 2656.97565 12597.97671
[281,] 30786.60221 2656.97565
[282,] 11241.61444 30786.60221
[283,] 11546.00142 11241.61444
[284,] 5394.89705 11546.00142
[285,] 5605.94311 5394.89705
[286,] 8129.93347 5605.94311
[287,] -4093.56006 8129.93347
[288,] -9607.95091 -4093.56006
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -20519.78306 21074.72649
2 7870.05886 -20519.78306
3 -41007.02331 7870.05886
4 11510.43376 -41007.02331
5 -14185.53638 11510.43376
6 14303.02797 -14185.53638
7 5749.60678 14303.02797
8 19930.70456 5749.60678
9 -17884.44716 19930.70456
10 17810.13091 -17884.44716
11 -2952.13157 17810.13091
12 5727.38507 -2952.13157
13 -3516.21548 5727.38507
14 40462.66907 -3516.21548
15 7184.84360 40462.66907
16 -43569.80202 7184.84360
17 24436.37982 -43569.80202
18 7692.55220 24436.37982
19 2003.65638 7692.55220
20 6415.14513 2003.65638
21 15853.09209 6415.14513
22 87278.95998 15853.09209
23 7645.22409 87278.95998
24 -21944.95667 7645.22409
25 -51641.54955 -21944.95667
26 -37765.03823 -51641.54955
27 -29882.44908 -37765.03823
28 17474.97272 -29882.44908
29 -4020.25906 17474.97272
30 -46142.39895 -4020.25906
31 -8154.99380 -46142.39895
32 -5284.08699 -8154.99380
33 5370.10016 -5284.08699
34 -535.91563 5370.10016
35 3275.98014 -535.91563
36 5010.73158 3275.98014
37 7787.34075 5010.73158
38 36742.07241 7787.34075
39 592.21407 36742.07241
40 10143.91916 592.21407
41 22859.65611 10143.91916
42 -11767.45811 22859.65611
43 -4000.11469 -11767.45811
44 -9972.74551 -4000.11469
45 -942.50469 -9972.74551
46 -13221.56247 -942.50469
47 -16939.78913 -13221.56247
48 10228.15378 -16939.78913
49 -52775.29333 10228.15378
50 40094.54391 -52775.29333
51 -24870.76464 40094.54391
52 -4462.64703 -24870.76464
53 -44503.80506 -4462.64703
54 -38010.91926 -44503.80506
55 -22903.90947 -38010.91926
56 -14024.04538 -22903.90947
57 32974.09462 -14024.04538
58 -641.73360 32974.09462
59 -9860.03080 -641.73360
60 9086.82787 -9860.03080
61 3045.30259 9086.82787
62 4359.67114 3045.30259
63 3999.42948 4359.67114
64 -32511.76643 3999.42948
65 -14651.02108 -32511.76643
66 48230.81497 -14651.02108
67 -11599.60183 48230.81497
68 -27922.54325 -11599.60183
69 -26788.28188 -27922.54325
70 12332.29850 -26788.28188
71 15095.14885 12332.29850
72 8855.73144 15095.14885
73 -4810.07169 8855.73144
74 -32905.58683 -4810.07169
75 6608.76977 -32905.58683
76 -15386.28681 6608.76977
77 -11953.62267 -15386.28681
78 -15222.08154 -11953.62267
79 3015.45390 -15222.08154
80 10733.61154 3015.45390
81 -9942.20061 10733.61154
82 70572.43420 -9942.20061
83 16295.12550 70572.43420
84 -946.58346 16295.12550
85 -5408.98896 -946.58346
86 1990.16647 -5408.98896
87 -12695.78743 1990.16647
88 75212.84685 -12695.78743
89 -19160.72888 75212.84685
90 37213.24270 -19160.72888
91 -19015.81798 37213.24270
92 -13529.06478 -19015.81798
93 18909.96930 -13529.06478
94 9569.54230 18909.96930
95 9165.42606 9569.54230
96 17338.17757 9165.42606
97 -52017.66619 17338.17757
98 17976.79326 -52017.66619
99 6842.24045 17976.79326
100 -2864.69254 6842.24045
101 4259.80765 -2864.69254
102 32626.46428 4259.80765
103 12447.76718 32626.46428
104 6140.80072 12447.76718
105 -2829.91707 6140.80072
106 -30676.85455 -2829.91707
107 -1047.73817 -30676.85455
108 9927.28142 -1047.73817
109 24722.25238 9927.28142
110 -16694.35110 24722.25238
111 -7530.89671 -16694.35110
112 -9654.42486 -7530.89671
113 4035.68225 -9654.42486
114 -14661.89109 4035.68225
115 -9611.55676 -14661.89109
116 5625.96356 -9611.55676
117 34869.15564 5625.96356
118 -61954.04444 34869.15564
119 -8741.19467 -61954.04444
120 987.26448 -8741.19467
121 -28043.58188 987.26448
122 -28943.31007 -28043.58188
123 -38348.96348 -28943.31007
124 24726.80830 -38348.96348
125 8946.32089 24726.80830
126 6608.33252 8946.32089
127 1274.80004 6608.33252
128 47112.75269 1274.80004
129 2942.14333 47112.75269
130 460.31419 2942.14333
131 -13459.42815 460.31419
132 14428.02725 -13459.42815
133 -37363.25820 14428.02725
134 -4865.15717 -37363.25820
135 -6372.61483 -4865.15717
136 -95.25976 -6372.61483
137 12267.43481 -95.25976
138 -11229.78463 12267.43481
139 -3018.10992 -11229.78463
140 -18011.02225 -3018.10992
141 -11309.11922 -18011.02225
142 15092.46372 -11309.11922
143 -33353.23684 15092.46372
144 30773.81146 -33353.23684
145 -7408.13295 30773.81146
146 25729.12934 -7408.13295
147 -14950.36984 25729.12934
148 -14120.03859 -14950.36984
149 4888.42826 -14120.03859
150 23939.92426 4888.42826
151 -5505.88811 23939.92426
152 -6108.88646 -5505.88811
153 -2061.46418 -6108.88646
154 -31240.42272 -2061.46418
155 17399.27575 -31240.42272
156 2569.19977 17399.27575
157 12186.46850 2569.19977
158 -24696.36681 12186.46850
159 10405.67748 -24696.36681
160 -956.95996 10405.67748
161 10886.13974 -956.95996
162 -1630.75098 10886.13974
163 21371.82835 -1630.75098
164 -13737.94785 21371.82835
165 15313.15411 -13737.94785
166 -12792.74064 15313.15411
167 24867.23933 -12792.74064
168 2189.38153 24867.23933
169 73306.63096 2189.38153
170 9085.89572 73306.63096
171 10720.75105 9085.89572
172 45489.29495 10720.75105
173 30772.78831 45489.29495
174 -38165.23566 30772.78831
175 -2649.90852 -38165.23566
176 -24957.27142 -2649.90852
177 12853.39845 -24957.27142
178 1142.67774 12853.39845
179 27401.65851 1142.67774
180 -11137.75102 27401.65851
181 -22393.18989 -11137.75102
182 3265.99110 -22393.18989
183 13013.04412 3265.99110
184 369.42035 13013.04412
185 -388.47114 369.42035
186 -3236.44100 -388.47114
187 8481.71350 -3236.44100
188 -4992.98571 8481.71350
189 31420.87798 -4992.98571
190 45935.99045 31420.87798
191 1692.85001 45935.99045
192 -9836.54639 1692.85001
193 -14486.97726 -9836.54639
194 -20706.78599 -14486.97726
195 11026.11854 -20706.78599
196 -14487.28688 11026.11854
197 3174.47025 -14487.28688
198 -22284.74306 3174.47025
199 2789.03224 -22284.74306
200 5111.08554 2789.03224
201 6510.38756 5111.08554
202 22600.62992 6510.38756
203 -4717.97840 22600.62992
204 -23549.93755 -4717.97840
205 -3947.58888 -23549.93755
206 3688.04044 -3947.58888
207 32703.67295 3688.04044
208 22671.31358 32703.67295
209 -3601.13189 22671.31358
210 -667.53534 -3601.13189
211 30949.13834 -667.53534
212 452.95791 30949.13834
213 -2725.69812 452.95791
214 -16247.18926 -2725.69812
215 -14593.68144 -16247.18926
216 -29911.11985 -14593.68144
217 -7408.49278 -29911.11985
218 -6303.89826 -7408.49278
219 14597.34014 -6303.89826
220 -16840.21416 14597.34014
221 -44230.57296 -16840.21416
222 -40804.23915 -44230.57296
223 -4138.77127 -40804.23915
224 1104.92515 -4138.77127
225 2194.38172 1104.92515
226 12078.70842 2194.38172
227 -16788.51807 12078.70842
228 -6088.08174 -16788.51807
229 -22667.52215 -6088.08174
230 -10632.96748 -22667.52215
231 -5480.21525 -10632.96748
232 -46863.34021 -5480.21525
233 -6199.51171 -46863.34021
234 -13921.87209 -6199.51171
235 1032.88504 -13921.87209
236 49290.61603 1032.88504
237 -12296.25933 49290.61603
238 -11791.85535 -12296.25933
239 -12619.52198 -11791.85535
240 5262.00574 -12619.52198
241 3826.29011 5262.00574
242 -7093.55220 3826.29011
243 -1700.11613 -7093.55220
244 -6999.60203 -1700.11613
245 -9275.68322 -6999.60203
246 -16305.87397 -9275.68322
247 7398.89194 -16305.87397
248 12209.34851 7398.89194
249 -9086.29257 12209.34851
250 3933.23897 -9086.29257
251 2482.21618 3933.23897
252 5991.31193 2482.21618
253 5006.55000 5991.31193
254 -15065.76846 5006.55000
255 4825.97374 -15065.76846
256 -7905.33660 4825.97374
257 20322.68858 -7905.33660
258 10593.39544 20322.68858
259 1427.36402 10593.39544
260 -8009.11909 1427.36402
261 1100.94393 -8009.11909
262 14886.81373 1100.94393
263 1082.48925 14886.81373
264 -5863.87532 1082.48925
265 3478.86790 -5863.87532
266 -13116.53143 3478.86790
267 1004.54850 -13116.53143
268 33506.51510 1004.54850
269 -7018.75133 33506.51510
270 -845.59658 -7018.75133
271 2734.25136 -845.59658
272 6392.50846 2734.25136
273 5074.45962 6392.50846
274 9731.21520 5074.45962
275 -533.99111 9731.21520
276 19718.69755 -533.99111
277 4393.22603 19718.69755
278 -7700.43938 4393.22603
279 12597.97671 -7700.43938
280 2656.97565 12597.97671
281 30786.60221 2656.97565
282 11241.61444 30786.60221
283 11546.00142 11241.61444
284 5394.89705 11546.00142
285 5605.94311 5394.89705
286 8129.93347 5605.94311
287 -4093.56006 8129.93347
288 -9607.95091 -4093.56006
> 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/7pulp1353429302.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/8ipml1353429302.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/9muby1353429302.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/10lyom1353429302.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/11tykz1353429302.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/12zt0i1353429302.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/13g0631353429302.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14lor61353429302.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/15704u1353429302.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/168pdy1353429302.tab")
+ }
>
> try(system("convert tmp/1vxvz1353429302.ps tmp/1vxvz1353429302.png",intern=TRUE))
character(0)
> try(system("convert tmp/20upe1353429302.ps tmp/20upe1353429302.png",intern=TRUE))
character(0)
> try(system("convert tmp/3dtnw1353429302.ps tmp/3dtnw1353429302.png",intern=TRUE))
character(0)
> try(system("convert tmp/49dm91353429302.ps tmp/49dm91353429302.png",intern=TRUE))
character(0)
> try(system("convert tmp/5x5qv1353429302.ps tmp/5x5qv1353429302.png",intern=TRUE))
character(0)
> try(system("convert tmp/6dans1353429302.ps tmp/6dans1353429302.png",intern=TRUE))
character(0)
> try(system("convert tmp/7pulp1353429302.ps tmp/7pulp1353429302.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ipml1353429302.ps tmp/8ipml1353429302.png",intern=TRUE))
character(0)
> try(system("convert tmp/9muby1353429302.ps tmp/9muby1353429302.png",intern=TRUE))
character(0)
> try(system("convert tmp/10lyom1353429302.ps tmp/10lyom1353429302.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
18.345 1.483 19.833