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 = '2'
> 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 months time_in_rfc logins compendium_views_info
1 1418 9 210907 56 396
2 869 9 120982 56 297
3 1530 9 176508 54 559
4 2172 9 179321 89 967
5 901 9 123185 40 270
6 463 9 52746 25 143
7 3201 9 385534 92 1562
8 371 9 33170 18 109
9 1192 9 101645 63 371
10 1583 9 149061 44 656
11 1439 9 165446 33 511
12 1764 9 237213 84 655
13 1495 9 173326 88 465
14 1373 9 133131 55 525
15 2187 9 258873 60 885
16 1491 9 180083 66 497
17 4041 9 324799 154 1436
18 1706 9 230964 53 612
19 2152 9 236785 119 865
20 1036 9 135473 41 385
21 1882 9 202925 61 567
22 1929 9 215147 58 639
23 2242 9 344297 75 963
24 1220 9 153935 33 398
25 1289 9 132943 40 410
26 2515 9 174724 92 966
27 2147 9 174415 100 801
28 2352 9 225548 112 892
29 1638 9 223632 73 513
30 1222 9 124817 40 469
31 1812 9 221698 45 683
32 1677 9 210767 60 643
33 1579 9 170266 62 535
34 1731 9 260561 75 625
35 807 9 84853 31 264
36 2452 9 294424 77 992
37 829 9 101011 34 238
38 1940 9 215641 46 818
39 2662 9 325107 99 937
40 186 9 7176 17 70
41 1499 9 167542 66 507
42 865 9 106408 30 260
43 1793 9 96560 76 503
44 2527 9 265769 146 927
45 2747 9 269651 67 1269
46 1324 9 149112 56 537
47 2702 9 175824 107 910
48 1383 9 152871 58 532
49 1179 9 111665 34 345
50 2099 9 116408 61 918
51 4308 9 362301 119 1635
52 918 9 78800 42 330
53 1831 9 183167 66 557
54 3373 9 277965 89 1178
55 1713 9 150629 44 740
56 1438 9 168809 66 452
57 496 9 24188 24 218
58 2253 9 329267 259 764
59 744 9 65029 17 255
60 1161 9 101097 64 454
61 2352 9 218946 41 866
62 2144 9 244052 68 574
63 4691 9 341570 168 1276
64 1112 9 103597 43 379
65 2694 9 233328 132 825
66 1973 9 256462 105 798
67 1769 9 206161 71 663
68 3148 9 311473 112 1069
69 2474 9 235800 94 921
70 2084 9 177939 82 858
71 1954 9 207176 70 711
72 1226 9 196553 57 503
73 1389 9 174184 53 382
74 1496 9 143246 103 464
75 2269 9 187559 121 717
76 1833 9 187681 62 690
77 1268 9 119016 52 462
78 1943 9 182192 52 657
79 893 9 73566 32 385
80 1762 9 194979 62 577
81 1403 9 167488 45 619
82 1425 9 143756 46 479
83 1857 9 275541 63 817
84 1840 9 243199 75 752
85 1502 9 182999 88 430
86 1441 9 135649 46 451
87 1420 9 152299 53 537
88 1416 9 120221 37 519
89 2970 9 346485 90 1000
90 1317 10 145790 63 637
91 1644 10 193339 78 465
92 870 10 80953 25 437
93 1654 10 122774 45 711
94 1054 10 130585 46 299
95 937 10 112611 41 248
96 3004 10 286468 144 1162
97 2008 10 241066 82 714
98 2547 10 148446 91 905
99 1885 10 204713 71 649
100 1626 10 182079 63 512
101 1468 10 140344 53 472
102 2445 10 220516 62 905
103 1964 10 243060 63 786
104 1381 10 162765 32 489
105 1369 10 182613 39 479
106 1659 10 232138 62 617
107 2888 10 265318 117 925
108 1290 10 85574 34 351
109 2845 10 310839 92 1144
110 1982 10 225060 93 669
111 1904 10 232317 54 707
112 1391 10 144966 144 458
113 602 10 43287 14 214
114 1743 10 155754 61 599
115 1559 10 164709 109 572
116 2014 10 201940 38 897
117 2143 10 235454 73 819
118 2146 10 220801 75 720
119 874 10 99466 50 273
120 1590 10 92661 61 508
121 1590 10 133328 55 506
122 1210 10 61361 77 451
123 2072 10 125930 75 699
124 1281 10 100750 72 407
125 1401 10 224549 50 465
126 834 10 82316 32 245
127 1105 10 102010 53 370
128 1272 10 101523 42 316
129 1944 10 243511 71 603
130 391 10 22938 10 154
131 761 10 41566 35 229
132 1605 10 152474 65 577
133 530 10 61857 25 192
134 1988 10 99923 66 617
135 1386 10 132487 41 411
136 2395 10 317394 86 975
137 387 10 21054 16 146
138 1742 10 209641 42 705
139 620 10 22648 19 184
140 449 10 31414 19 200
141 800 10 46698 45 274
142 1684 10 131698 65 502
143 1050 10 91735 35 382
144 2699 10 244749 95 964
145 1606 10 184510 49 537
146 1502 10 79863 37 438
147 1204 10 128423 64 369
148 1138 10 97839 38 417
149 568 10 38214 34 276
150 1459 10 151101 32 514
151 2158 10 272458 65 822
152 1111 10 172494 52 389
153 1421 10 108043 62 466
154 2833 10 328107 65 1255
155 1955 10 250579 83 694
156 2922 10 351067 95 1024
157 1002 10 158015 29 400
158 1060 10 98866 18 397
159 956 10 85439 33 350
160 2186 10 229242 247 719
161 3604 10 351619 139 1277
162 1035 10 84207 29 356
163 1417 10 120445 118 457
164 3261 10 324598 110 1402
165 1587 10 131069 67 600
166 1424 10 204271 42 480
167 1701 10 165543 65 595
168 1249 10 141722 94 436
169 946 10 116048 64 230
170 1926 10 250047 81 651
171 3352 10 299775 95 1367
172 1641 10 195838 67 564
173 2035 10 173260 63 716
174 2312 10 254488 83 747
175 1369 10 104389 45 467
176 1577 10 136084 30 671
177 2201 10 199476 70 861
178 961 10 92499 32 319
179 1900 10 224330 83 612
180 1254 10 135781 31 433
181 1335 10 74408 67 434
182 1597 10 81240 66 503
183 207 10 14688 10 85
184 1645 10 181633 70 564
185 2429 10 271856 103 824
186 151 10 7199 5 74
187 474 10 46660 20 259
188 141 10 17547 5 69
189 1639 10 133368 36 535
190 872 10 95227 34 239
191 1318 10 152601 48 438
192 1018 10 98146 40 459
193 1383 10 79619 43 426
194 1314 10 59194 31 288
195 1335 10 139942 42 498
196 1403 11 118612 46 454
197 910 11 72880 33 376
198 616 11 65475 18 225
199 1407 11 99643 55 555
200 771 11 71965 35 252
201 766 11 77272 59 208
202 473 11 49289 19 130
203 1376 11 135131 66 481
204 1232 11 108446 60 389
205 1521 11 89746 36 565
206 572 11 44296 25 173
207 1059 11 77648 47 278
208 1544 11 181528 54 609
209 1230 11 134019 53 422
210 1206 11 124064 40 445
211 1205 11 92630 40 387
212 1255 11 121848 39 339
213 613 11 52915 14 181
214 721 11 81872 45 245
215 1109 11 58981 36 384
216 740 11 53515 28 212
217 1126 11 60812 44 399
218 728 11 56375 30 229
219 689 11 65490 22 224
220 592 11 80949 17 203
221 995 11 76302 31 333
222 1613 11 104011 55 384
223 2048 11 98104 54 636
224 705 11 67989 21 185
225 301 11 30989 14 93
226 1803 11 135458 81 581
227 799 11 73504 35 248
228 861 11 63123 43 304
229 1186 11 61254 46 344
230 1451 11 74914 30 407
231 628 11 31774 23 170
232 1161 11 81437 38 312
233 1463 11 87186 54 507
234 742 11 50090 20 224
235 979 11 65745 53 340
236 675 11 56653 45 168
237 1241 11 158399 39 443
238 676 11 46455 20 204
239 1049 11 73624 24 367
240 620 11 38395 31 210
241 1081 11 91899 35 335
242 1688 11 139526 151 364
243 736 11 52164 52 178
244 617 11 51567 30 206
245 812 11 70551 31 279
246 1051 11 84856 29 387
247 1656 11 102538 57 490
248 705 11 86678 40 238
249 945 11 85709 44 343
250 554 11 34662 25 232
251 1597 11 150580 77 530
252 982 11 99611 35 291
253 222 11 19349 11 67
254 1212 11 99373 63 397
255 1143 11 86230 44 467
256 435 11 30837 19 178
257 532 11 31706 13 175
258 882 11 89806 42 299
259 608 11 62088 38 154
260 459 11 40151 29 106
261 578 11 27634 20 189
262 826 11 76990 27 194
263 509 11 37460 20 135
264 717 11 54157 19 201
265 637 11 49862 37 207
266 857 11 84337 26 280
267 830 11 64175 42 260
268 652 11 59382 49 227
269 707 11 119308 30 239
270 954 11 76702 49 333
271 1461 11 103425 67 428
272 672 11 70344 28 230
273 778 11 43410 19 292
274 1141 11 104838 49 350
275 680 11 62215 27 186
276 1090 11 69304 30 326
277 616 11 53117 22 155
278 285 11 19764 12 75
279 1145 11 86680 31 361
280 733 11 84105 20 261
281 888 11 77945 20 299
282 849 11 89113 39 300
283 1182 11 91005 29 450
284 528 11 40248 16 183
285 642 11 64187 27 238
286 947 11 50857 21 165
287 819 11 56613 19 234
288 757 11 62792 35 176
289 894 11 72535 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 time_in_rfc
-2.777e+02 3.468e+01 3.224e-04
logins compendium_views_info compendium_views_pr
3.243e+00 1.773e+00 1.497e+00
shared_compendiums blogged_computations compendiums_reviewed
7.674e+00 2.389e+00 -2.458e+00
feedback_messages_p1 feedback_messages_p120 totsize
6.863e-01 4.003e-01 -1.212e-05
totrevisions totseconds tothyperlinks
-4.167e-03 6.420e-04 3.367e+00
`totblogs\\r`
-3.627e+00
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-516.14 -83.05 -15.34 67.50 1157.36
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.777e+02 1.667e+02 -1.666 0.096790 .
months 3.468e+01 1.517e+01 2.286 0.022999 *
time_in_rfc 3.224e-04 4.474e-04 0.721 0.471766
logins 3.243e+00 4.148e-01 7.816 1.18e-13 ***
compendium_views_info 1.773e+00 8.804e-02 20.133 < 2e-16 ***
compendium_views_pr 1.497e+00 2.282e-01 6.558 2.72e-10 ***
shared_compendiums 7.674e+00 4.150e+00 1.849 0.065497 .
blogged_computations 2.389e+00 6.686e-01 3.572 0.000418 ***
compendiums_reviewed -2.458e+00 5.202e+00 -0.472 0.636958
feedback_messages_p1 6.863e-01 1.570e+00 0.437 0.662324
feedback_messages_p120 4.003e-01 7.751e-01 0.516 0.605991
totsize -1.212e-05 4.819e-04 -0.025 0.979952
totrevisions -4.167e-03 2.376e-03 -1.754 0.080565 .
totseconds 6.420e-04 6.567e-04 0.978 0.329168
tothyperlinks 3.367e+00 3.231e+00 1.042 0.298311
`totblogs\\r` -3.627e+00 3.348e+00 -1.083 0.279626
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 159.6 on 273 degrees of freedom
Multiple R-squared: 0.9554, Adjusted R-squared: 0.953
F-statistic: 390.2 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,] 0.6097349 7.805302e-01 3.902651e-01
[2,] 0.9101512 1.796977e-01 8.984884e-02
[3,] 0.8478361 3.043278e-01 1.521639e-01
[4,] 0.8502499 2.995002e-01 1.497501e-01
[5,] 0.7954621 4.090759e-01 2.045379e-01
[6,] 0.7143188 5.713624e-01 2.856812e-01
[7,] 0.7279996 5.440009e-01 2.720004e-01
[8,] 0.6636186 6.727627e-01 3.363814e-01
[9,] 0.6786037 6.427925e-01 3.213963e-01
[10,] 0.6174743 7.650514e-01 3.825257e-01
[11,] 0.5822042 8.355917e-01 4.177958e-01
[12,] 0.5027401 9.945199e-01 4.972599e-01
[13,] 0.5486956 9.026087e-01 4.513044e-01
[14,] 0.4899689 9.799378e-01 5.100311e-01
[15,] 0.4603040 9.206080e-01 5.396960e-01
[16,] 0.4645092 9.290185e-01 5.354908e-01
[17,] 0.4116551 8.233101e-01 5.883449e-01
[18,] 0.3486221 6.972441e-01 6.513779e-01
[19,] 0.3038441 6.076881e-01 6.961559e-01
[20,] 0.2513633 5.027266e-01 7.486367e-01
[21,] 0.2644878 5.289756e-01 7.355122e-01
[22,] 0.2241040 4.482080e-01 7.758960e-01
[23,] 0.1832962 3.665924e-01 8.167038e-01
[24,] 0.1667141 3.334282e-01 8.332859e-01
[25,] 0.2293552 4.587104e-01 7.706448e-01
[26,] 0.1868771 3.737543e-01 8.131229e-01
[27,] 0.1765146 3.530291e-01 8.234854e-01
[28,] 0.1896128 3.792255e-01 8.103872e-01
[29,] 0.2870334 5.740668e-01 7.129666e-01
[30,] 0.2736486 5.472971e-01 7.263514e-01
[31,] 0.2593177 5.186353e-01 7.406823e-01
[32,] 0.2446405 4.892809e-01 7.553595e-01
[33,] 0.4080926 8.161853e-01 5.919074e-01
[34,] 0.3660701 7.321401e-01 6.339299e-01
[35,] 0.3869354 7.738708e-01 6.130646e-01
[36,] 0.7802244 4.395512e-01 2.197756e-01
[37,] 0.7570846 4.858308e-01 2.429154e-01
[38,] 0.7245043 5.509914e-01 2.754957e-01
[39,] 0.6934705 6.130590e-01 3.065295e-01
[40,] 0.9122813 1.754374e-01 8.771869e-02
[41,] 0.8931892 2.136216e-01 1.068108e-01
[42,] 0.8809375 2.381251e-01 1.190625e-01
[43,] 0.9046410 1.907180e-01 9.535899e-02
[44,] 0.9663054 6.738925e-02 3.369462e-02
[45,] 1.0000000 4.464266e-10 2.232133e-10
[46,] 1.0000000 7.877215e-10 3.938607e-10
[47,] 1.0000000 1.637595e-10 8.187976e-11
[48,] 1.0000000 2.058589e-11 1.029294e-11
[49,] 1.0000000 3.132699e-11 1.566350e-11
[50,] 1.0000000 1.064441e-11 5.322207e-12
[51,] 1.0000000 2.090824e-11 1.045412e-11
[52,] 1.0000000 3.211621e-11 1.605811e-11
[53,] 1.0000000 4.126106e-11 2.063053e-11
[54,] 1.0000000 6.816033e-11 3.408016e-11
[55,] 1.0000000 5.294187e-11 2.647094e-11
[56,] 1.0000000 8.175996e-11 4.087998e-11
[57,] 1.0000000 6.017201e-11 3.008600e-11
[58,] 1.0000000 9.117766e-11 4.558883e-11
[59,] 1.0000000 8.422334e-11 4.211167e-11
[60,] 1.0000000 8.272856e-11 4.136428e-11
[61,] 1.0000000 1.076685e-10 5.383426e-11
[62,] 1.0000000 1.310359e-10 6.551793e-11
[63,] 1.0000000 1.118021e-10 5.590106e-11
[64,] 1.0000000 2.045747e-10 1.022873e-10
[65,] 1.0000000 4.678581e-11 2.339291e-11
[66,] 1.0000000 5.180773e-11 2.590386e-11
[67,] 1.0000000 7.483066e-11 3.741533e-11
[68,] 1.0000000 1.147820e-10 5.739098e-11
[69,] 1.0000000 2.055731e-10 1.027865e-10
[70,] 1.0000000 2.840358e-10 1.420179e-10
[71,] 1.0000000 4.984468e-11 2.492234e-11
[72,] 1.0000000 1.944452e-11 9.722258e-12
[73,] 1.0000000 7.800032e-12 3.900016e-12
[74,] 1.0000000 6.120714e-12 3.060357e-12
[75,] 1.0000000 5.180554e-12 2.590277e-12
[76,] 1.0000000 6.042695e-12 3.021347e-12
[77,] 1.0000000 7.960512e-12 3.980256e-12
[78,] 1.0000000 2.811468e-12 1.405734e-12
[79,] 1.0000000 4.392336e-12 2.196168e-12
[80,] 1.0000000 3.272222e-12 1.636111e-12
[81,] 1.0000000 4.740292e-12 2.370146e-12
[82,] 1.0000000 7.689542e-12 3.844771e-12
[83,] 1.0000000 1.096843e-11 5.484216e-12
[84,] 1.0000000 1.211924e-11 6.059621e-12
[85,] 1.0000000 1.542121e-11 7.710603e-12
[86,] 1.0000000 2.613224e-11 1.306612e-11
[87,] 1.0000000 4.780014e-11 2.390007e-11
[88,] 1.0000000 6.413740e-11 3.206870e-11
[89,] 1.0000000 5.072961e-11 2.536480e-11
[90,] 1.0000000 1.968802e-11 9.844010e-12
[91,] 1.0000000 3.240643e-11 1.620322e-11
[92,] 1.0000000 5.668520e-11 2.834260e-11
[93,] 1.0000000 9.594527e-11 4.797264e-11
[94,] 1.0000000 6.260631e-11 3.130315e-11
[95,] 1.0000000 1.106160e-10 5.530798e-11
[96,] 1.0000000 1.694096e-10 8.470480e-11
[97,] 1.0000000 2.044849e-10 1.022424e-10
[98,] 1.0000000 1.072827e-10 5.364133e-11
[99,] 1.0000000 1.556419e-10 7.782095e-11
[100,] 1.0000000 1.481815e-10 7.409077e-11
[101,] 1.0000000 2.619159e-10 1.309580e-10
[102,] 1.0000000 3.323541e-10 1.661770e-10
[103,] 1.0000000 3.583804e-10 1.791902e-10
[104,] 1.0000000 6.086696e-10 3.043348e-10
[105,] 1.0000000 9.553623e-10 4.776811e-10
[106,] 1.0000000 1.388479e-09 6.942396e-10
[107,] 1.0000000 2.365891e-09 1.182945e-09
[108,] 1.0000000 3.778064e-09 1.889032e-09
[109,] 1.0000000 6.365876e-09 3.182938e-09
[110,] 1.0000000 3.057211e-09 1.528606e-09
[111,] 1.0000000 4.077629e-09 2.038815e-09
[112,] 1.0000000 6.827284e-09 3.413642e-09
[113,] 1.0000000 1.109225e-08 5.546127e-09
[114,] 1.0000000 1.789567e-08 8.947837e-09
[115,] 1.0000000 2.527687e-08 1.263844e-08
[116,] 1.0000000 6.541074e-09 3.270537e-09
[117,] 1.0000000 2.523520e-09 1.261760e-09
[118,] 1.0000000 1.681513e-09 8.407567e-10
[119,] 1.0000000 2.875134e-09 1.437567e-09
[120,] 1.0000000 3.694434e-09 1.847217e-09
[121,] 1.0000000 5.087482e-09 2.543741e-09
[122,] 1.0000000 7.085132e-09 3.542566e-09
[123,] 1.0000000 1.201559e-08 6.007797e-09
[124,] 1.0000000 6.806396e-09 3.403198e-09
[125,] 1.0000000 1.129048e-08 5.645240e-09
[126,] 1.0000000 1.755158e-08 8.775789e-09
[127,] 1.0000000 2.741305e-08 1.370653e-08
[128,] 1.0000000 1.124507e-08 5.622537e-09
[129,] 1.0000000 1.568767e-08 7.843836e-09
[130,] 1.0000000 2.614919e-08 1.307459e-08
[131,] 1.0000000 1.667986e-08 8.339932e-09
[132,] 1.0000000 2.708228e-08 1.354114e-08
[133,] 1.0000000 4.246049e-08 2.123025e-08
[134,] 1.0000000 5.901858e-08 2.950929e-08
[135,] 1.0000000 5.957352e-08 2.978676e-08
[136,] 1.0000000 8.089025e-09 4.044512e-09
[137,] 1.0000000 3.557244e-09 1.778622e-09
[138,] 1.0000000 4.976770e-09 2.488385e-09
[139,] 1.0000000 5.156626e-09 2.578313e-09
[140,] 1.0000000 6.596172e-09 3.298086e-09
[141,] 1.0000000 1.118738e-08 5.593691e-09
[142,] 1.0000000 1.682036e-10 8.410178e-11
[143,] 1.0000000 1.830309e-10 9.151547e-11
[144,] 1.0000000 2.330736e-10 1.165368e-10
[145,] 1.0000000 3.766885e-10 1.883442e-10
[146,] 1.0000000 1.063943e-10 5.319716e-11
[147,] 1.0000000 1.566978e-10 7.834891e-11
[148,] 1.0000000 2.612713e-10 1.306357e-10
[149,] 1.0000000 2.565339e-10 1.282669e-10
[150,] 1.0000000 2.900884e-10 1.450442e-10
[151,] 1.0000000 5.297642e-10 2.648821e-10
[152,] 1.0000000 6.747149e-10 3.373574e-10
[153,] 1.0000000 3.918369e-10 1.959185e-10
[154,] 1.0000000 6.890399e-10 3.445200e-10
[155,] 1.0000000 2.267126e-10 1.133563e-10
[156,] 1.0000000 3.460791e-10 1.730395e-10
[157,] 1.0000000 3.566051e-11 1.783025e-11
[158,] 1.0000000 6.688828e-11 3.344414e-11
[159,] 1.0000000 7.273523e-11 3.636761e-11
[160,] 1.0000000 1.367916e-10 6.839580e-11
[161,] 1.0000000 1.463100e-10 7.315499e-11
[162,] 1.0000000 2.789224e-10 1.394612e-10
[163,] 1.0000000 5.124843e-10 2.562421e-10
[164,] 1.0000000 8.849331e-10 4.424665e-10
[165,] 1.0000000 1.570018e-09 7.850089e-10
[166,] 1.0000000 2.644514e-09 1.322257e-09
[167,] 1.0000000 1.092648e-09 5.463239e-10
[168,] 1.0000000 1.950290e-09 9.751449e-10
[169,] 1.0000000 1.818763e-09 9.093814e-10
[170,] 1.0000000 3.289485e-09 1.644743e-09
[171,] 1.0000000 1.334196e-09 6.670981e-10
[172,] 1.0000000 2.312351e-09 1.156175e-09
[173,] 1.0000000 4.171154e-09 2.085577e-09
[174,] 1.0000000 6.172942e-09 3.086471e-09
[175,] 1.0000000 1.070938e-08 5.354691e-09
[176,] 1.0000000 1.553813e-08 7.769064e-09
[177,] 1.0000000 2.839478e-08 1.419739e-08
[178,] 1.0000000 4.646764e-08 2.323382e-08
[179,] 1.0000000 7.476820e-08 3.738410e-08
[180,] 0.9999999 1.301588e-07 6.507941e-08
[181,] 0.9999999 1.431393e-07 7.156966e-08
[182,] 0.9999999 2.508505e-07 1.254253e-07
[183,] 0.9999998 3.961372e-07 1.980686e-07
[184,] 0.9999997 6.851003e-07 3.425502e-07
[185,] 0.9999995 1.081917e-06 5.409584e-07
[186,] 0.9999992 1.667482e-06 8.337410e-07
[187,] 0.9999989 2.201441e-06 1.100721e-06
[188,] 0.9999982 3.665106e-06 1.832553e-06
[189,] 0.9999982 3.670764e-06 1.835382e-06
[190,] 0.9999978 4.483223e-06 2.241612e-06
[191,] 0.9999963 7.368357e-06 3.684179e-06
[192,] 0.9999950 1.002403e-05 5.012013e-06
[193,] 0.9999919 1.612064e-05 8.060318e-06
[194,] 0.9999962 7.535755e-06 3.767878e-06
[195,] 0.9999936 1.284292e-05 6.421461e-06
[196,] 0.9999940 1.192416e-05 5.962079e-06
[197,] 0.9999917 1.663729e-05 8.318646e-06
[198,] 0.9999860 2.790396e-05 1.395198e-05
[199,] 0.9999813 3.740891e-05 1.870445e-05
[200,] 0.9999921 1.574948e-05 7.874739e-06
[201,] 0.9999886 2.272116e-05 1.136058e-05
[202,] 0.9999807 3.852335e-05 1.926167e-05
[203,] 0.9999697 6.066795e-05 3.033398e-05
[204,] 0.9999752 4.951349e-05 2.475675e-05
[205,] 0.9999793 4.141686e-05 2.070843e-05
[206,] 0.9999664 6.716732e-05 3.358366e-05
[207,] 0.9999548 9.038075e-05 4.519037e-05
[208,] 0.9999249 1.501685e-04 7.508423e-05
[209,] 0.9998819 2.362444e-04 1.181222e-04
[210,] 0.9998439 3.121392e-04 1.560696e-04
[211,] 0.9998614 2.772734e-04 1.386367e-04
[212,] 0.9999751 4.988785e-05 2.494392e-05
[213,] 0.9999612 7.759488e-05 3.879744e-05
[214,] 0.9999765 4.695636e-05 2.347818e-05
[215,] 0.9999697 6.054508e-05 3.027254e-05
[216,] 0.9999479 1.041855e-04 5.209273e-05
[217,] 0.9999549 9.015362e-05 4.507681e-05
[218,] 0.9999232 1.536825e-04 7.684125e-05
[219,] 0.9998640 2.719033e-04 1.359516e-04
[220,] 0.9997863 4.274370e-04 2.137185e-04
[221,] 0.9996379 7.242203e-04 3.621101e-04
[222,] 0.9994932 1.013532e-03 5.067662e-04
[223,] 0.9992382 1.523546e-03 7.617729e-04
[224,] 0.9997743 4.513654e-04 2.256827e-04
[225,] 0.9995976 8.048772e-04 4.024386e-04
[226,] 0.9994135 1.173037e-03 5.865186e-04
[227,] 0.9990196 1.960752e-03 9.803759e-04
[228,] 0.9988675 2.264952e-03 1.132476e-03
[229,] 0.9997719 4.562169e-04 2.281085e-04
[230,] 0.9996268 7.464467e-04 3.732233e-04
[231,] 0.9993582 1.283582e-03 6.417910e-04
[232,] 0.9988928 2.214495e-03 1.107248e-03
[233,] 0.9982364 3.527188e-03 1.763594e-03
[234,] 0.9970127 5.974543e-03 2.987271e-03
[235,] 0.9950614 9.877233e-03 4.938616e-03
[236,] 0.9917513 1.649731e-02 8.248654e-03
[237,] 0.9870704 2.585927e-02 1.292963e-02
[238,] 0.9799643 4.007149e-02 2.003575e-02
[239,] 0.9676784 6.464322e-02 3.232161e-02
[240,] 0.9530895 9.382110e-02 4.691055e-02
[241,] 0.9279188 1.441623e-01 7.208117e-02
[242,] 0.8945530 2.108941e-01 1.054470e-01
[243,] 0.9176724 1.646553e-01 8.232763e-02
[244,] 0.8903886 2.192227e-01 1.096114e-01
[245,] 0.8691393 2.617215e-01 1.308607e-01
[246,] 0.8051688 3.896624e-01 1.948312e-01
[247,] 0.7336359 5.327282e-01 2.663641e-01
[248,] 0.6318553 7.362894e-01 3.681447e-01
[249,] 0.5360341 9.279318e-01 4.639659e-01
[250,] 0.6835450 6.329100e-01 3.164550e-01
[251,] 0.6200321 7.599358e-01 3.799679e-01
[252,] 0.8081901 3.836198e-01 1.918099e-01
> postscript(file="/var/wessaorg/rcomp/tmp/1c36m1353427870.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2wddc1353427870.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/35w5i1353427870.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/46c7a1353427870.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/53fx61353427870.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
105.6808027 -177.6187608 -51.4256973 -332.5376745 18.9165649 -16.2110445
7 8 9 10 11 12
-417.1943801 -1.9806992 80.7650012 -11.9885096 93.1523219 -115.7573631
13 14 15 16 17 18
-69.3631220 -64.2092847 -90.9690874 -5.8686726 280.0889154 14.5034816
19 20 21 22 23 24
-200.0382358 -83.0523596 113.0445466 186.7055068 -211.3261299 60.0557338
25 26 27 28 29 30
-9.4576723 -61.0741959 54.0400416 -88.8884432 31.0074014 -29.3277900
31 32 33 34 35 36
-152.1458672 -40.6466281 44.0883818 -125.2084757 -39.6642700 -67.4371191
37 38 39 40 41 42
67.5003000 -95.3793057 201.9687512 -30.1204839 52.1516941 117.6901676
43 44 45 46 47 48
310.2530448 -21.0786789 -216.1579233 -175.0269666 346.7883940 -123.1464855
49 50 51 52 53 54
175.1942819 31.5435632 -426.3858299 -27.7873321 208.6230401 328.7461444
55 56 57 58 59 60
-132.2487972 77.9477970 -57.2197956 -516.1371803 40.1245596 -133.2351527
61 62 63 64 65 66
239.2567582 387.1340508 1157.3614171 48.7476409 245.6914938 -295.4583208
67 68 69 70 71 72
-104.9425757 277.7284330 -16.2350665 -117.9915038 103.6153171 -104.2578616
73 74 75 76 77 78
183.4590997 -4.5024704 147.4826621 -63.0152947 -182.6393573 122.1270774
79 80 81 82 83 84
-138.3005892 115.5814826 -190.1536654 4.8217677 -318.8914295 -149.1331949
85 86 87 88 89 90
13.3874383 80.7776193 -40.3880730 104.5288315 304.5510752 -343.9816472
91 92 93 94 95 96
150.4586313 -245.1012339 -181.0916117 36.2914691 67.4265498 -262.6514283
97 98 99 100 101 102
37.0591244 160.7757287 88.5770963 -43.7140233 71.7668488 119.2089778
103 104 105 106 107 108
-83.8232852 54.4813089 -1.6978959 -116.3047704 149.1710938 258.1453008
109 110 111 112 113 114
-66.6767250 20.8806113 -61.2319775 -211.2124528 -27.9530205 72.8613926
115 116 117 118 119 120
-101.1723568 -169.9788850 -122.5394589 163.3092809 -12.3470020 100.9695558
121 122 123 124 125 126
164.4549031 -64.4208053 41.6549876 -119.3917507 6.8977566 35.8050413
127 128 129 130 131 132
-28.7803986 240.4862692 85.5684628 -30.4310584 43.9649551 -40.0723458
133 134 135 136 137 138
-112.4034063 301.1145099 -27.4989943 -181.9119312 -13.8811685 -89.4816704
139 140 141 142 143 144
66.4622339 -104.8498891 -13.8308555 220.0761902 -34.3209297 25.1915789
145 146 147 148 149 150
68.3988872 227.7394945 -83.3346412 35.7670437 -233.0234071 26.6972378
151 152 153 154 155 156
-52.9443679 -113.0418196 111.9556930 -322.4172520 -244.5483824 124.6022231
157 158 159 160 161 162
-140.9129567 -76.0843818 -34.2636243 -427.0708140 198.6639732 -55.5895674
163 164 165 166 167 168
-80.7104671 -173.1350155 -37.3989388 -14.5215210 -90.7155269 -116.6096598
169 170 171 172 173 174
20.2833872 132.0391878 -7.3843172 -15.3387681 232.1712125 143.7563410
175 176 177 178 179 180
-235.0701788 10.9972162 46.1767496 32.3462897 10.7789484 -14.1988885
181 182 183 184 185 186
63.2135429 98.8717877 -54.5914636 90.3277092 43.8175521 -83.3331573
187 188 189 190 191 192
-178.0562222 -71.6573448 270.9684803 32.6061659 106.4713811 -147.8423574
193 194 195 196 197 198
95.6805298 177.3418986 -35.4003420 53.4291557 -106.8965218 -67.7080972
199 200 201 202 203 204
-65.5897471 -52.1099666 -20.5630616 -41.0900915 -74.7659883 6.5998218
205 206 207 208 209 210
3.1006781 -19.4246823 144.8476077 -71.3667334 -1.2711173 -55.4132548
211 212 213 214 215 216
64.4187803 216.6017809 -8.1509902 -109.9300355 56.0837449 25.1146266
217 218 219 220 221 222
-17.4979487 -97.6215537 -78.3086984 -49.4405156 49.9154408 387.8526348
223 224 225 226 227 228
266.6718882 58.8837795 -104.3191507 49.3031318 -38.8937717 -114.3520241
229 230 231 232 233 234
107.6803167 304.6847233 39.8366927 174.3309395 80.8397225 6.4966262
235 236 237 238 239 240
-87.2119899 -34.5666082 26.5405047 15.0475187 -19.0100573 -69.7219575
241 242 243 244 245 246
88.9369383 236.3512457 -28.7400467 -69.2491782 -65.8114949 -2.7300256
247 248 249 250 251 252
220.2165091 -101.0714860 -102.4710054 -93.8604430 -22.0593681 -13.0765436
253 254 255 256 257 258
-94.0501190 -20.4152301 -86.7175752 -89.5938503 -26.4544318 -81.5238616
259 260 261 262 263 264
-22.1545578 -14.6955339 -36.8350681 12.4975231 49.2419318 44.5992294
265 266 267 268 269 270
-66.2785016 -17.6119057 -54.3239384 -177.9119138 -114.0369371 -87.3122306
271 272 273 274 275 276
135.9146795 -84.5472238 -30.4576117 -22.1377866 36.5814218 58.1482313
277 278 279 280 281 282
59.1992581 -52.7962701 96.7174485 -47.7732362 -23.5614970 -39.4404951
283 284 285 286 287 288
8.2882370 -44.2478818 -82.6752276 369.3891855 117.0313824 84.5680337
289
-0.5065464
> postscript(file="/var/wessaorg/rcomp/tmp/6l53s1353427870.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
0 105.6808027 NA
1 -177.6187608 105.6808027
2 -51.4256973 -177.6187608
3 -332.5376745 -51.4256973
4 18.9165649 -332.5376745
5 -16.2110445 18.9165649
6 -417.1943801 -16.2110445
7 -1.9806992 -417.1943801
8 80.7650012 -1.9806992
9 -11.9885096 80.7650012
10 93.1523219 -11.9885096
11 -115.7573631 93.1523219
12 -69.3631220 -115.7573631
13 -64.2092847 -69.3631220
14 -90.9690874 -64.2092847
15 -5.8686726 -90.9690874
16 280.0889154 -5.8686726
17 14.5034816 280.0889154
18 -200.0382358 14.5034816
19 -83.0523596 -200.0382358
20 113.0445466 -83.0523596
21 186.7055068 113.0445466
22 -211.3261299 186.7055068
23 60.0557338 -211.3261299
24 -9.4576723 60.0557338
25 -61.0741959 -9.4576723
26 54.0400416 -61.0741959
27 -88.8884432 54.0400416
28 31.0074014 -88.8884432
29 -29.3277900 31.0074014
30 -152.1458672 -29.3277900
31 -40.6466281 -152.1458672
32 44.0883818 -40.6466281
33 -125.2084757 44.0883818
34 -39.6642700 -125.2084757
35 -67.4371191 -39.6642700
36 67.5003000 -67.4371191
37 -95.3793057 67.5003000
38 201.9687512 -95.3793057
39 -30.1204839 201.9687512
40 52.1516941 -30.1204839
41 117.6901676 52.1516941
42 310.2530448 117.6901676
43 -21.0786789 310.2530448
44 -216.1579233 -21.0786789
45 -175.0269666 -216.1579233
46 346.7883940 -175.0269666
47 -123.1464855 346.7883940
48 175.1942819 -123.1464855
49 31.5435632 175.1942819
50 -426.3858299 31.5435632
51 -27.7873321 -426.3858299
52 208.6230401 -27.7873321
53 328.7461444 208.6230401
54 -132.2487972 328.7461444
55 77.9477970 -132.2487972
56 -57.2197956 77.9477970
57 -516.1371803 -57.2197956
58 40.1245596 -516.1371803
59 -133.2351527 40.1245596
60 239.2567582 -133.2351527
61 387.1340508 239.2567582
62 1157.3614171 387.1340508
63 48.7476409 1157.3614171
64 245.6914938 48.7476409
65 -295.4583208 245.6914938
66 -104.9425757 -295.4583208
67 277.7284330 -104.9425757
68 -16.2350665 277.7284330
69 -117.9915038 -16.2350665
70 103.6153171 -117.9915038
71 -104.2578616 103.6153171
72 183.4590997 -104.2578616
73 -4.5024704 183.4590997
74 147.4826621 -4.5024704
75 -63.0152947 147.4826621
76 -182.6393573 -63.0152947
77 122.1270774 -182.6393573
78 -138.3005892 122.1270774
79 115.5814826 -138.3005892
80 -190.1536654 115.5814826
81 4.8217677 -190.1536654
82 -318.8914295 4.8217677
83 -149.1331949 -318.8914295
84 13.3874383 -149.1331949
85 80.7776193 13.3874383
86 -40.3880730 80.7776193
87 104.5288315 -40.3880730
88 304.5510752 104.5288315
89 -343.9816472 304.5510752
90 150.4586313 -343.9816472
91 -245.1012339 150.4586313
92 -181.0916117 -245.1012339
93 36.2914691 -181.0916117
94 67.4265498 36.2914691
95 -262.6514283 67.4265498
96 37.0591244 -262.6514283
97 160.7757287 37.0591244
98 88.5770963 160.7757287
99 -43.7140233 88.5770963
100 71.7668488 -43.7140233
101 119.2089778 71.7668488
102 -83.8232852 119.2089778
103 54.4813089 -83.8232852
104 -1.6978959 54.4813089
105 -116.3047704 -1.6978959
106 149.1710938 -116.3047704
107 258.1453008 149.1710938
108 -66.6767250 258.1453008
109 20.8806113 -66.6767250
110 -61.2319775 20.8806113
111 -211.2124528 -61.2319775
112 -27.9530205 -211.2124528
113 72.8613926 -27.9530205
114 -101.1723568 72.8613926
115 -169.9788850 -101.1723568
116 -122.5394589 -169.9788850
117 163.3092809 -122.5394589
118 -12.3470020 163.3092809
119 100.9695558 -12.3470020
120 164.4549031 100.9695558
121 -64.4208053 164.4549031
122 41.6549876 -64.4208053
123 -119.3917507 41.6549876
124 6.8977566 -119.3917507
125 35.8050413 6.8977566
126 -28.7803986 35.8050413
127 240.4862692 -28.7803986
128 85.5684628 240.4862692
129 -30.4310584 85.5684628
130 43.9649551 -30.4310584
131 -40.0723458 43.9649551
132 -112.4034063 -40.0723458
133 301.1145099 -112.4034063
134 -27.4989943 301.1145099
135 -181.9119312 -27.4989943
136 -13.8811685 -181.9119312
137 -89.4816704 -13.8811685
138 66.4622339 -89.4816704
139 -104.8498891 66.4622339
140 -13.8308555 -104.8498891
141 220.0761902 -13.8308555
142 -34.3209297 220.0761902
143 25.1915789 -34.3209297
144 68.3988872 25.1915789
145 227.7394945 68.3988872
146 -83.3346412 227.7394945
147 35.7670437 -83.3346412
148 -233.0234071 35.7670437
149 26.6972378 -233.0234071
150 -52.9443679 26.6972378
151 -113.0418196 -52.9443679
152 111.9556930 -113.0418196
153 -322.4172520 111.9556930
154 -244.5483824 -322.4172520
155 124.6022231 -244.5483824
156 -140.9129567 124.6022231
157 -76.0843818 -140.9129567
158 -34.2636243 -76.0843818
159 -427.0708140 -34.2636243
160 198.6639732 -427.0708140
161 -55.5895674 198.6639732
162 -80.7104671 -55.5895674
163 -173.1350155 -80.7104671
164 -37.3989388 -173.1350155
165 -14.5215210 -37.3989388
166 -90.7155269 -14.5215210
167 -116.6096598 -90.7155269
168 20.2833872 -116.6096598
169 132.0391878 20.2833872
170 -7.3843172 132.0391878
171 -15.3387681 -7.3843172
172 232.1712125 -15.3387681
173 143.7563410 232.1712125
174 -235.0701788 143.7563410
175 10.9972162 -235.0701788
176 46.1767496 10.9972162
177 32.3462897 46.1767496
178 10.7789484 32.3462897
179 -14.1988885 10.7789484
180 63.2135429 -14.1988885
181 98.8717877 63.2135429
182 -54.5914636 98.8717877
183 90.3277092 -54.5914636
184 43.8175521 90.3277092
185 -83.3331573 43.8175521
186 -178.0562222 -83.3331573
187 -71.6573448 -178.0562222
188 270.9684803 -71.6573448
189 32.6061659 270.9684803
190 106.4713811 32.6061659
191 -147.8423574 106.4713811
192 95.6805298 -147.8423574
193 177.3418986 95.6805298
194 -35.4003420 177.3418986
195 53.4291557 -35.4003420
196 -106.8965218 53.4291557
197 -67.7080972 -106.8965218
198 -65.5897471 -67.7080972
199 -52.1099666 -65.5897471
200 -20.5630616 -52.1099666
201 -41.0900915 -20.5630616
202 -74.7659883 -41.0900915
203 6.5998218 -74.7659883
204 3.1006781 6.5998218
205 -19.4246823 3.1006781
206 144.8476077 -19.4246823
207 -71.3667334 144.8476077
208 -1.2711173 -71.3667334
209 -55.4132548 -1.2711173
210 64.4187803 -55.4132548
211 216.6017809 64.4187803
212 -8.1509902 216.6017809
213 -109.9300355 -8.1509902
214 56.0837449 -109.9300355
215 25.1146266 56.0837449
216 -17.4979487 25.1146266
217 -97.6215537 -17.4979487
218 -78.3086984 -97.6215537
219 -49.4405156 -78.3086984
220 49.9154408 -49.4405156
221 387.8526348 49.9154408
222 266.6718882 387.8526348
223 58.8837795 266.6718882
224 -104.3191507 58.8837795
225 49.3031318 -104.3191507
226 -38.8937717 49.3031318
227 -114.3520241 -38.8937717
228 107.6803167 -114.3520241
229 304.6847233 107.6803167
230 39.8366927 304.6847233
231 174.3309395 39.8366927
232 80.8397225 174.3309395
233 6.4966262 80.8397225
234 -87.2119899 6.4966262
235 -34.5666082 -87.2119899
236 26.5405047 -34.5666082
237 15.0475187 26.5405047
238 -19.0100573 15.0475187
239 -69.7219575 -19.0100573
240 88.9369383 -69.7219575
241 236.3512457 88.9369383
242 -28.7400467 236.3512457
243 -69.2491782 -28.7400467
244 -65.8114949 -69.2491782
245 -2.7300256 -65.8114949
246 220.2165091 -2.7300256
247 -101.0714860 220.2165091
248 -102.4710054 -101.0714860
249 -93.8604430 -102.4710054
250 -22.0593681 -93.8604430
251 -13.0765436 -22.0593681
252 -94.0501190 -13.0765436
253 -20.4152301 -94.0501190
254 -86.7175752 -20.4152301
255 -89.5938503 -86.7175752
256 -26.4544318 -89.5938503
257 -81.5238616 -26.4544318
258 -22.1545578 -81.5238616
259 -14.6955339 -22.1545578
260 -36.8350681 -14.6955339
261 12.4975231 -36.8350681
262 49.2419318 12.4975231
263 44.5992294 49.2419318
264 -66.2785016 44.5992294
265 -17.6119057 -66.2785016
266 -54.3239384 -17.6119057
267 -177.9119138 -54.3239384
268 -114.0369371 -177.9119138
269 -87.3122306 -114.0369371
270 135.9146795 -87.3122306
271 -84.5472238 135.9146795
272 -30.4576117 -84.5472238
273 -22.1377866 -30.4576117
274 36.5814218 -22.1377866
275 58.1482313 36.5814218
276 59.1992581 58.1482313
277 -52.7962701 59.1992581
278 96.7174485 -52.7962701
279 -47.7732362 96.7174485
280 -23.5614970 -47.7732362
281 -39.4404951 -23.5614970
282 8.2882370 -39.4404951
283 -44.2478818 8.2882370
284 -82.6752276 -44.2478818
285 369.3891855 -82.6752276
286 117.0313824 369.3891855
287 84.5680337 117.0313824
288 -0.5065464 84.5680337
289 NA -0.5065464
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -177.6187608 105.680803
[2,] -51.4256973 -177.618761
[3,] -332.5376745 -51.425697
[4,] 18.9165649 -332.537674
[5,] -16.2110445 18.916565
[6,] -417.1943801 -16.211044
[7,] -1.9806992 -417.194380
[8,] 80.7650012 -1.980699
[9,] -11.9885096 80.765001
[10,] 93.1523219 -11.988510
[11,] -115.7573631 93.152322
[12,] -69.3631220 -115.757363
[13,] -64.2092847 -69.363122
[14,] -90.9690874 -64.209285
[15,] -5.8686726 -90.969087
[16,] 280.0889154 -5.868673
[17,] 14.5034816 280.088915
[18,] -200.0382358 14.503482
[19,] -83.0523596 -200.038236
[20,] 113.0445466 -83.052360
[21,] 186.7055068 113.044547
[22,] -211.3261299 186.705507
[23,] 60.0557338 -211.326130
[24,] -9.4576723 60.055734
[25,] -61.0741959 -9.457672
[26,] 54.0400416 -61.074196
[27,] -88.8884432 54.040042
[28,] 31.0074014 -88.888443
[29,] -29.3277900 31.007401
[30,] -152.1458672 -29.327790
[31,] -40.6466281 -152.145867
[32,] 44.0883818 -40.646628
[33,] -125.2084757 44.088382
[34,] -39.6642700 -125.208476
[35,] -67.4371191 -39.664270
[36,] 67.5003000 -67.437119
[37,] -95.3793057 67.500300
[38,] 201.9687512 -95.379306
[39,] -30.1204839 201.968751
[40,] 52.1516941 -30.120484
[41,] 117.6901676 52.151694
[42,] 310.2530448 117.690168
[43,] -21.0786789 310.253045
[44,] -216.1579233 -21.078679
[45,] -175.0269666 -216.157923
[46,] 346.7883940 -175.026967
[47,] -123.1464855 346.788394
[48,] 175.1942819 -123.146485
[49,] 31.5435632 175.194282
[50,] -426.3858299 31.543563
[51,] -27.7873321 -426.385830
[52,] 208.6230401 -27.787332
[53,] 328.7461444 208.623040
[54,] -132.2487972 328.746144
[55,] 77.9477970 -132.248797
[56,] -57.2197956 77.947797
[57,] -516.1371803 -57.219796
[58,] 40.1245596 -516.137180
[59,] -133.2351527 40.124560
[60,] 239.2567582 -133.235153
[61,] 387.1340508 239.256758
[62,] 1157.3614171 387.134051
[63,] 48.7476409 1157.361417
[64,] 245.6914938 48.747641
[65,] -295.4583208 245.691494
[66,] -104.9425757 -295.458321
[67,] 277.7284330 -104.942576
[68,] -16.2350665 277.728433
[69,] -117.9915038 -16.235067
[70,] 103.6153171 -117.991504
[71,] -104.2578616 103.615317
[72,] 183.4590997 -104.257862
[73,] -4.5024704 183.459100
[74,] 147.4826621 -4.502470
[75,] -63.0152947 147.482662
[76,] -182.6393573 -63.015295
[77,] 122.1270774 -182.639357
[78,] -138.3005892 122.127077
[79,] 115.5814826 -138.300589
[80,] -190.1536654 115.581483
[81,] 4.8217677 -190.153665
[82,] -318.8914295 4.821768
[83,] -149.1331949 -318.891429
[84,] 13.3874383 -149.133195
[85,] 80.7776193 13.387438
[86,] -40.3880730 80.777619
[87,] 104.5288315 -40.388073
[88,] 304.5510752 104.528831
[89,] -343.9816472 304.551075
[90,] 150.4586313 -343.981647
[91,] -245.1012339 150.458631
[92,] -181.0916117 -245.101234
[93,] 36.2914691 -181.091612
[94,] 67.4265498 36.291469
[95,] -262.6514283 67.426550
[96,] 37.0591244 -262.651428
[97,] 160.7757287 37.059124
[98,] 88.5770963 160.775729
[99,] -43.7140233 88.577096
[100,] 71.7668488 -43.714023
[101,] 119.2089778 71.766849
[102,] -83.8232852 119.208978
[103,] 54.4813089 -83.823285
[104,] -1.6978959 54.481309
[105,] -116.3047704 -1.697896
[106,] 149.1710938 -116.304770
[107,] 258.1453008 149.171094
[108,] -66.6767250 258.145301
[109,] 20.8806113 -66.676725
[110,] -61.2319775 20.880611
[111,] -211.2124528 -61.231978
[112,] -27.9530205 -211.212453
[113,] 72.8613926 -27.953020
[114,] -101.1723568 72.861393
[115,] -169.9788850 -101.172357
[116,] -122.5394589 -169.978885
[117,] 163.3092809 -122.539459
[118,] -12.3470020 163.309281
[119,] 100.9695558 -12.347002
[120,] 164.4549031 100.969556
[121,] -64.4208053 164.454903
[122,] 41.6549876 -64.420805
[123,] -119.3917507 41.654988
[124,] 6.8977566 -119.391751
[125,] 35.8050413 6.897757
[126,] -28.7803986 35.805041
[127,] 240.4862692 -28.780399
[128,] 85.5684628 240.486269
[129,] -30.4310584 85.568463
[130,] 43.9649551 -30.431058
[131,] -40.0723458 43.964955
[132,] -112.4034063 -40.072346
[133,] 301.1145099 -112.403406
[134,] -27.4989943 301.114510
[135,] -181.9119312 -27.498994
[136,] -13.8811685 -181.911931
[137,] -89.4816704 -13.881168
[138,] 66.4622339 -89.481670
[139,] -104.8498891 66.462234
[140,] -13.8308555 -104.849889
[141,] 220.0761902 -13.830855
[142,] -34.3209297 220.076190
[143,] 25.1915789 -34.320930
[144,] 68.3988872 25.191579
[145,] 227.7394945 68.398887
[146,] -83.3346412 227.739495
[147,] 35.7670437 -83.334641
[148,] -233.0234071 35.767044
[149,] 26.6972378 -233.023407
[150,] -52.9443679 26.697238
[151,] -113.0418196 -52.944368
[152,] 111.9556930 -113.041820
[153,] -322.4172520 111.955693
[154,] -244.5483824 -322.417252
[155,] 124.6022231 -244.548382
[156,] -140.9129567 124.602223
[157,] -76.0843818 -140.912957
[158,] -34.2636243 -76.084382
[159,] -427.0708140 -34.263624
[160,] 198.6639732 -427.070814
[161,] -55.5895674 198.663973
[162,] -80.7104671 -55.589567
[163,] -173.1350155 -80.710467
[164,] -37.3989388 -173.135015
[165,] -14.5215210 -37.398939
[166,] -90.7155269 -14.521521
[167,] -116.6096598 -90.715527
[168,] 20.2833872 -116.609660
[169,] 132.0391878 20.283387
[170,] -7.3843172 132.039188
[171,] -15.3387681 -7.384317
[172,] 232.1712125 -15.338768
[173,] 143.7563410 232.171213
[174,] -235.0701788 143.756341
[175,] 10.9972162 -235.070179
[176,] 46.1767496 10.997216
[177,] 32.3462897 46.176750
[178,] 10.7789484 32.346290
[179,] -14.1988885 10.778948
[180,] 63.2135429 -14.198888
[181,] 98.8717877 63.213543
[182,] -54.5914636 98.871788
[183,] 90.3277092 -54.591464
[184,] 43.8175521 90.327709
[185,] -83.3331573 43.817552
[186,] -178.0562222 -83.333157
[187,] -71.6573448 -178.056222
[188,] 270.9684803 -71.657345
[189,] 32.6061659 270.968480
[190,] 106.4713811 32.606166
[191,] -147.8423574 106.471381
[192,] 95.6805298 -147.842357
[193,] 177.3418986 95.680530
[194,] -35.4003420 177.341899
[195,] 53.4291557 -35.400342
[196,] -106.8965218 53.429156
[197,] -67.7080972 -106.896522
[198,] -65.5897471 -67.708097
[199,] -52.1099666 -65.589747
[200,] -20.5630616 -52.109967
[201,] -41.0900915 -20.563062
[202,] -74.7659883 -41.090092
[203,] 6.5998218 -74.765988
[204,] 3.1006781 6.599822
[205,] -19.4246823 3.100678
[206,] 144.8476077 -19.424682
[207,] -71.3667334 144.847608
[208,] -1.2711173 -71.366733
[209,] -55.4132548 -1.271117
[210,] 64.4187803 -55.413255
[211,] 216.6017809 64.418780
[212,] -8.1509902 216.601781
[213,] -109.9300355 -8.150990
[214,] 56.0837449 -109.930035
[215,] 25.1146266 56.083745
[216,] -17.4979487 25.114627
[217,] -97.6215537 -17.497949
[218,] -78.3086984 -97.621554
[219,] -49.4405156 -78.308698
[220,] 49.9154408 -49.440516
[221,] 387.8526348 49.915441
[222,] 266.6718882 387.852635
[223,] 58.8837795 266.671888
[224,] -104.3191507 58.883779
[225,] 49.3031318 -104.319151
[226,] -38.8937717 49.303132
[227,] -114.3520241 -38.893772
[228,] 107.6803167 -114.352024
[229,] 304.6847233 107.680317
[230,] 39.8366927 304.684723
[231,] 174.3309395 39.836693
[232,] 80.8397225 174.330939
[233,] 6.4966262 80.839722
[234,] -87.2119899 6.496626
[235,] -34.5666082 -87.211990
[236,] 26.5405047 -34.566608
[237,] 15.0475187 26.540505
[238,] -19.0100573 15.047519
[239,] -69.7219575 -19.010057
[240,] 88.9369383 -69.721957
[241,] 236.3512457 88.936938
[242,] -28.7400467 236.351246
[243,] -69.2491782 -28.740047
[244,] -65.8114949 -69.249178
[245,] -2.7300256 -65.811495
[246,] 220.2165091 -2.730026
[247,] -101.0714860 220.216509
[248,] -102.4710054 -101.071486
[249,] -93.8604430 -102.471005
[250,] -22.0593681 -93.860443
[251,] -13.0765436 -22.059368
[252,] -94.0501190 -13.076544
[253,] -20.4152301 -94.050119
[254,] -86.7175752 -20.415230
[255,] -89.5938503 -86.717575
[256,] -26.4544318 -89.593850
[257,] -81.5238616 -26.454432
[258,] -22.1545578 -81.523862
[259,] -14.6955339 -22.154558
[260,] -36.8350681 -14.695534
[261,] 12.4975231 -36.835068
[262,] 49.2419318 12.497523
[263,] 44.5992294 49.241932
[264,] -66.2785016 44.599229
[265,] -17.6119057 -66.278502
[266,] -54.3239384 -17.611906
[267,] -177.9119138 -54.323938
[268,] -114.0369371 -177.911914
[269,] -87.3122306 -114.036937
[270,] 135.9146795 -87.312231
[271,] -84.5472238 135.914680
[272,] -30.4576117 -84.547224
[273,] -22.1377866 -30.457612
[274,] 36.5814218 -22.137787
[275,] 58.1482313 36.581422
[276,] 59.1992581 58.148231
[277,] -52.7962701 59.199258
[278,] 96.7174485 -52.796270
[279,] -47.7732362 96.717448
[280,] -23.5614970 -47.773236
[281,] -39.4404951 -23.561497
[282,] 8.2882370 -39.440495
[283,] -44.2478818 8.288237
[284,] -82.6752276 -44.247882
[285,] 369.3891855 -82.675228
[286,] 117.0313824 369.389185
[287,] 84.5680337 117.031382
[288,] -0.5065464 84.568034
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -177.6187608 105.680803
2 -51.4256973 -177.618761
3 -332.5376745 -51.425697
4 18.9165649 -332.537674
5 -16.2110445 18.916565
6 -417.1943801 -16.211044
7 -1.9806992 -417.194380
8 80.7650012 -1.980699
9 -11.9885096 80.765001
10 93.1523219 -11.988510
11 -115.7573631 93.152322
12 -69.3631220 -115.757363
13 -64.2092847 -69.363122
14 -90.9690874 -64.209285
15 -5.8686726 -90.969087
16 280.0889154 -5.868673
17 14.5034816 280.088915
18 -200.0382358 14.503482
19 -83.0523596 -200.038236
20 113.0445466 -83.052360
21 186.7055068 113.044547
22 -211.3261299 186.705507
23 60.0557338 -211.326130
24 -9.4576723 60.055734
25 -61.0741959 -9.457672
26 54.0400416 -61.074196
27 -88.8884432 54.040042
28 31.0074014 -88.888443
29 -29.3277900 31.007401
30 -152.1458672 -29.327790
31 -40.6466281 -152.145867
32 44.0883818 -40.646628
33 -125.2084757 44.088382
34 -39.6642700 -125.208476
35 -67.4371191 -39.664270
36 67.5003000 -67.437119
37 -95.3793057 67.500300
38 201.9687512 -95.379306
39 -30.1204839 201.968751
40 52.1516941 -30.120484
41 117.6901676 52.151694
42 310.2530448 117.690168
43 -21.0786789 310.253045
44 -216.1579233 -21.078679
45 -175.0269666 -216.157923
46 346.7883940 -175.026967
47 -123.1464855 346.788394
48 175.1942819 -123.146485
49 31.5435632 175.194282
50 -426.3858299 31.543563
51 -27.7873321 -426.385830
52 208.6230401 -27.787332
53 328.7461444 208.623040
54 -132.2487972 328.746144
55 77.9477970 -132.248797
56 -57.2197956 77.947797
57 -516.1371803 -57.219796
58 40.1245596 -516.137180
59 -133.2351527 40.124560
60 239.2567582 -133.235153
61 387.1340508 239.256758
62 1157.3614171 387.134051
63 48.7476409 1157.361417
64 245.6914938 48.747641
65 -295.4583208 245.691494
66 -104.9425757 -295.458321
67 277.7284330 -104.942576
68 -16.2350665 277.728433
69 -117.9915038 -16.235067
70 103.6153171 -117.991504
71 -104.2578616 103.615317
72 183.4590997 -104.257862
73 -4.5024704 183.459100
74 147.4826621 -4.502470
75 -63.0152947 147.482662
76 -182.6393573 -63.015295
77 122.1270774 -182.639357
78 -138.3005892 122.127077
79 115.5814826 -138.300589
80 -190.1536654 115.581483
81 4.8217677 -190.153665
82 -318.8914295 4.821768
83 -149.1331949 -318.891429
84 13.3874383 -149.133195
85 80.7776193 13.387438
86 -40.3880730 80.777619
87 104.5288315 -40.388073
88 304.5510752 104.528831
89 -343.9816472 304.551075
90 150.4586313 -343.981647
91 -245.1012339 150.458631
92 -181.0916117 -245.101234
93 36.2914691 -181.091612
94 67.4265498 36.291469
95 -262.6514283 67.426550
96 37.0591244 -262.651428
97 160.7757287 37.059124
98 88.5770963 160.775729
99 -43.7140233 88.577096
100 71.7668488 -43.714023
101 119.2089778 71.766849
102 -83.8232852 119.208978
103 54.4813089 -83.823285
104 -1.6978959 54.481309
105 -116.3047704 -1.697896
106 149.1710938 -116.304770
107 258.1453008 149.171094
108 -66.6767250 258.145301
109 20.8806113 -66.676725
110 -61.2319775 20.880611
111 -211.2124528 -61.231978
112 -27.9530205 -211.212453
113 72.8613926 -27.953020
114 -101.1723568 72.861393
115 -169.9788850 -101.172357
116 -122.5394589 -169.978885
117 163.3092809 -122.539459
118 -12.3470020 163.309281
119 100.9695558 -12.347002
120 164.4549031 100.969556
121 -64.4208053 164.454903
122 41.6549876 -64.420805
123 -119.3917507 41.654988
124 6.8977566 -119.391751
125 35.8050413 6.897757
126 -28.7803986 35.805041
127 240.4862692 -28.780399
128 85.5684628 240.486269
129 -30.4310584 85.568463
130 43.9649551 -30.431058
131 -40.0723458 43.964955
132 -112.4034063 -40.072346
133 301.1145099 -112.403406
134 -27.4989943 301.114510
135 -181.9119312 -27.498994
136 -13.8811685 -181.911931
137 -89.4816704 -13.881168
138 66.4622339 -89.481670
139 -104.8498891 66.462234
140 -13.8308555 -104.849889
141 220.0761902 -13.830855
142 -34.3209297 220.076190
143 25.1915789 -34.320930
144 68.3988872 25.191579
145 227.7394945 68.398887
146 -83.3346412 227.739495
147 35.7670437 -83.334641
148 -233.0234071 35.767044
149 26.6972378 -233.023407
150 -52.9443679 26.697238
151 -113.0418196 -52.944368
152 111.9556930 -113.041820
153 -322.4172520 111.955693
154 -244.5483824 -322.417252
155 124.6022231 -244.548382
156 -140.9129567 124.602223
157 -76.0843818 -140.912957
158 -34.2636243 -76.084382
159 -427.0708140 -34.263624
160 198.6639732 -427.070814
161 -55.5895674 198.663973
162 -80.7104671 -55.589567
163 -173.1350155 -80.710467
164 -37.3989388 -173.135015
165 -14.5215210 -37.398939
166 -90.7155269 -14.521521
167 -116.6096598 -90.715527
168 20.2833872 -116.609660
169 132.0391878 20.283387
170 -7.3843172 132.039188
171 -15.3387681 -7.384317
172 232.1712125 -15.338768
173 143.7563410 232.171213
174 -235.0701788 143.756341
175 10.9972162 -235.070179
176 46.1767496 10.997216
177 32.3462897 46.176750
178 10.7789484 32.346290
179 -14.1988885 10.778948
180 63.2135429 -14.198888
181 98.8717877 63.213543
182 -54.5914636 98.871788
183 90.3277092 -54.591464
184 43.8175521 90.327709
185 -83.3331573 43.817552
186 -178.0562222 -83.333157
187 -71.6573448 -178.056222
188 270.9684803 -71.657345
189 32.6061659 270.968480
190 106.4713811 32.606166
191 -147.8423574 106.471381
192 95.6805298 -147.842357
193 177.3418986 95.680530
194 -35.4003420 177.341899
195 53.4291557 -35.400342
196 -106.8965218 53.429156
197 -67.7080972 -106.896522
198 -65.5897471 -67.708097
199 -52.1099666 -65.589747
200 -20.5630616 -52.109967
201 -41.0900915 -20.563062
202 -74.7659883 -41.090092
203 6.5998218 -74.765988
204 3.1006781 6.599822
205 -19.4246823 3.100678
206 144.8476077 -19.424682
207 -71.3667334 144.847608
208 -1.2711173 -71.366733
209 -55.4132548 -1.271117
210 64.4187803 -55.413255
211 216.6017809 64.418780
212 -8.1509902 216.601781
213 -109.9300355 -8.150990
214 56.0837449 -109.930035
215 25.1146266 56.083745
216 -17.4979487 25.114627
217 -97.6215537 -17.497949
218 -78.3086984 -97.621554
219 -49.4405156 -78.308698
220 49.9154408 -49.440516
221 387.8526348 49.915441
222 266.6718882 387.852635
223 58.8837795 266.671888
224 -104.3191507 58.883779
225 49.3031318 -104.319151
226 -38.8937717 49.303132
227 -114.3520241 -38.893772
228 107.6803167 -114.352024
229 304.6847233 107.680317
230 39.8366927 304.684723
231 174.3309395 39.836693
232 80.8397225 174.330939
233 6.4966262 80.839722
234 -87.2119899 6.496626
235 -34.5666082 -87.211990
236 26.5405047 -34.566608
237 15.0475187 26.540505
238 -19.0100573 15.047519
239 -69.7219575 -19.010057
240 88.9369383 -69.721957
241 236.3512457 88.936938
242 -28.7400467 236.351246
243 -69.2491782 -28.740047
244 -65.8114949 -69.249178
245 -2.7300256 -65.811495
246 220.2165091 -2.730026
247 -101.0714860 220.216509
248 -102.4710054 -101.071486
249 -93.8604430 -102.471005
250 -22.0593681 -93.860443
251 -13.0765436 -22.059368
252 -94.0501190 -13.076544
253 -20.4152301 -94.050119
254 -86.7175752 -20.415230
255 -89.5938503 -86.717575
256 -26.4544318 -89.593850
257 -81.5238616 -26.454432
258 -22.1545578 -81.523862
259 -14.6955339 -22.154558
260 -36.8350681 -14.695534
261 12.4975231 -36.835068
262 49.2419318 12.497523
263 44.5992294 49.241932
264 -66.2785016 44.599229
265 -17.6119057 -66.278502
266 -54.3239384 -17.611906
267 -177.9119138 -54.323938
268 -114.0369371 -177.911914
269 -87.3122306 -114.036937
270 135.9146795 -87.312231
271 -84.5472238 135.914680
272 -30.4576117 -84.547224
273 -22.1377866 -30.457612
274 36.5814218 -22.137787
275 58.1482313 36.581422
276 59.1992581 58.148231
277 -52.7962701 59.199258
278 96.7174485 -52.796270
279 -47.7732362 96.717448
280 -23.5614970 -47.773236
281 -39.4404951 -23.561497
282 8.2882370 -39.440495
283 -44.2478818 8.288237
284 -82.6752276 -44.247882
285 369.3891855 -82.675228
286 117.0313824 369.389185
287 84.5680337 117.031382
288 -0.5065464 84.568034
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/75jfj1353427870.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/81ju51353427870.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9sufk1353427870.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/105uuh1353427870.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11uhse1353427870.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12g1aq1353427870.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13szn51353427870.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14qfz91353427870.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/15pjp01353427870.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/16bs4d1353427870.tab")
+ }
>
> try(system("convert tmp/1c36m1353427870.ps tmp/1c36m1353427870.png",intern=TRUE))
character(0)
> try(system("convert tmp/2wddc1353427870.ps tmp/2wddc1353427870.png",intern=TRUE))
character(0)
> try(system("convert tmp/35w5i1353427870.ps tmp/35w5i1353427870.png",intern=TRUE))
character(0)
> try(system("convert tmp/46c7a1353427870.ps tmp/46c7a1353427870.png",intern=TRUE))
character(0)
> try(system("convert tmp/53fx61353427870.ps tmp/53fx61353427870.png",intern=TRUE))
character(0)
> try(system("convert tmp/6l53s1353427870.ps tmp/6l53s1353427870.png",intern=TRUE))
character(0)
> try(system("convert tmp/75jfj1353427870.ps tmp/75jfj1353427870.png",intern=TRUE))
character(0)
> try(system("convert tmp/81ju51353427870.ps tmp/81ju51353427870.png",intern=TRUE))
character(0)
> try(system("convert tmp/9sufk1353427870.ps tmp/9sufk1353427870.png",intern=TRUE))
character(0)
> try(system("convert tmp/105uuh1353427870.ps tmp/105uuh1353427870.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
20.804 1.256 22.516