R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(1418
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+ ,18475
+ ,0
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+ ,50857
+ ,21
+ ,165
+ ,34
+ ,0
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+ ,20
+ ,36944
+ ,1352
+ ,12645
+ ,0
+ ,819
+ ,56613
+ ,19
+ ,234
+ ,37
+ ,1
+ ,15
+ ,12
+ ,8019
+ ,3080
+ ,11017
+ ,0
+ ,757
+ ,62792
+ ,35
+ ,176
+ ,46
+ ,0
+ ,28
+ ,15
+ ,30884
+ ,10205
+ ,37623
+ ,0
+ ,894
+ ,72535
+ ,14
+ ,329
+ ,44
+ ,0
+ ,17
+ ,16
+ ,19540
+ ,6095
+ ,35873
+ ,0)
+ ,dim=c(12
+ ,289)
+ ,dimnames=list(c('pageviews'
+ ,'timerfc'
+ ,'logins'
+ ,'compendiumviewsinfo'
+ ,'compendiumviewspr'
+ ,'sharedcompendiums'
+ ,'bloggedcomputations'
+ ,'compendiumsreviewed'
+ ,'totalsize'
+ ,'totalsizerevisions'
+ ,'totalseconds'
+ ,'course')
+ ,1:289))
> y <- array(NA,dim=c(12,289),dimnames=list(c('pageviews','timerfc','logins','compendiumviewsinfo','compendiumviewspr','sharedcompendiums','bloggedcomputations','compendiumsreviewed','totalsize','totalsizerevisions','totalseconds','course'),1:289))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> 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 timerfc logins compendiumviewsinfo compendiumviewspr
1 1418 210907 56 396 81
2 869 120982 56 297 55
3 1530 176508 54 559 50
4 2172 179321 89 967 125
5 901 123185 40 270 40
6 463 52746 25 143 37
7 3201 385534 92 1562 63
8 371 33170 18 109 44
9 1192 101645 63 371 88
10 1583 149061 44 656 66
11 1439 165446 33 511 57
12 1764 237213 84 655 74
13 1495 173326 88 465 49
14 1373 133131 55 525 52
15 2187 258873 60 885 88
16 1491 180083 66 497 36
17 4041 324799 154 1436 108
18 1706 230964 53 612 43
19 2152 236785 119 865 75
20 1036 135473 41 385 32
21 1882 202925 61 567 44
22 1929 215147 58 639 85
23 2242 344297 75 963 86
24 1220 153935 33 398 56
25 1289 132943 40 410 50
26 2515 174724 92 966 135
27 2147 174415 100 801 63
28 2352 225548 112 892 81
29 1638 223632 73 513 52
30 1222 124817 40 469 44
31 1812 221698 45 683 113
32 1677 210767 60 643 39
33 1579 170266 62 535 73
34 1731 260561 75 625 48
35 807 84853 31 264 33
36 2452 294424 77 992 59
37 829 101011 34 238 41
38 1940 215641 46 818 69
39 2662 325107 99 937 64
40 186 7176 17 70 1
41 1499 167542 66 507 59
42 865 106408 30 260 32
43 1793 96560 76 503 129
44 2527 265769 146 927 37
45 2747 269651 67 1269 31
46 1324 149112 56 537 65
47 2702 175824 107 910 107
48 1383 152871 58 532 74
49 1179 111665 34 345 54
50 2099 116408 61 918 76
51 4308 362301 119 1635 715
52 918 78800 42 330 57
53 1831 183167 66 557 66
54 3373 277965 89 1178 106
55 1713 150629 44 740 54
56 1438 168809 66 452 32
57 496 24188 24 218 20
58 2253 329267 259 764 71
59 744 65029 17 255 21
60 1161 101097 64 454 70
61 2352 218946 41 866 112
62 2144 244052 68 574 66
63 4691 341570 168 1276 190
64 1112 103597 43 379 66
65 2694 233328 132 825 165
66 1973 256462 105 798 56
67 1769 206161 71 663 61
68 3148 311473 112 1069 53
69 2474 235800 94 921 127
70 2084 177939 82 858 63
71 1954 207176 70 711 38
72 1226 196553 57 503 50
73 1389 174184 53 382 52
74 1496 143246 103 464 42
75 2269 187559 121 717 76
76 1833 187681 62 690 67
77 1268 119016 52 462 50
78 1943 182192 52 657 53
79 893 73566 32 385 39
80 1762 194979 62 577 50
81 1403 167488 45 619 77
82 1425 143756 46 479 57
83 1857 275541 63 817 73
84 1840 243199 75 752 34
85 1502 182999 88 430 39
86 1441 135649 46 451 46
87 1420 152299 53 537 63
88 1416 120221 37 519 35
89 2970 346485 90 1000 106
90 1317 145790 63 637 43
91 1644 193339 78 465 47
92 870 80953 25 437 31
93 1654 122774 45 711 162
94 1054 130585 46 299 57
95 937 112611 41 248 36
96 3004 286468 144 1162 263
97 2008 241066 82 714 78
98 2547 148446 91 905 63
99 1885 204713 71 649 54
100 1626 182079 63 512 63
101 1468 140344 53 472 77
102 2445 220516 62 905 79
103 1964 243060 63 786 110
104 1381 162765 32 489 56
105 1369 182613 39 479 56
106 1659 232138 62 617 43
107 2888 265318 117 925 111
108 1290 85574 34 351 71
109 2845 310839 92 1144 62
110 1982 225060 93 669 56
111 1904 232317 54 707 74
112 1391 144966 144 458 60
113 602 43287 14 214 43
114 1743 155754 61 599 68
115 1559 164709 109 572 53
116 2014 201940 38 897 87
117 2143 235454 73 819 46
118 2146 220801 75 720 105
119 874 99466 50 273 32
120 1590 92661 61 508 133
121 1590 133328 55 506 79
122 1210 61361 77 451 51
123 2072 125930 75 699 207
124 1281 100750 72 407 67
125 1401 224549 50 465 47
126 834 82316 32 245 34
127 1105 102010 53 370 66
128 1272 101523 42 316 76
129 1944 243511 71 603 65
130 391 22938 10 154 9
131 761 41566 35 229 42
132 1605 152474 65 577 45
133 530 61857 25 192 25
134 1988 99923 66 617 115
135 1386 132487 41 411 97
136 2395 317394 86 975 53
137 387 21054 16 146 2
138 1742 209641 42 705 52
139 620 22648 19 184 44
140 449 31414 19 200 22
141 800 46698 45 274 35
142 1684 131698 65 502 74
143 1050 91735 35 382 103
144 2699 244749 95 964 144
145 1606 184510 49 537 60
146 1502 79863 37 438 134
147 1204 128423 64 369 89
148 1138 97839 38 417 42
149 568 38214 34 276 52
150 1459 151101 32 514 98
151 2158 272458 65 822 99
152 1111 172494 52 389 52
153 1421 108043 62 466 29
154 2833 328107 65 1255 125
155 1955 250579 83 694 106
156 2922 351067 95 1024 95
157 1002 158015 29 400 40
158 1060 98866 18 397 140
159 956 85439 33 350 43
160 2186 229242 247 719 128
161 3604 351619 139 1277 142
162 1035 84207 29 356 73
163 1417 120445 118 457 72
164 3261 324598 110 1402 128
165 1587 131069 67 600 61
166 1424 204271 42 480 73
167 1701 165543 65 595 148
168 1249 141722 94 436 64
169 946 116048 64 230 45
170 1926 250047 81 651 58
171 3352 299775 95 1367 97
172 1641 195838 67 564 50
173 2035 173260 63 716 37
174 2312 254488 83 747 50
175 1369 104389 45 467 105
176 1577 136084 30 671 69
177 2201 199476 70 861 46
178 961 92499 32 319 57
179 1900 224330 83 612 52
180 1254 135781 31 433 98
181 1335 74408 67 434 61
182 1597 81240 66 503 89
183 207 14688 10 85 0
184 1645 181633 70 564 48
185 2429 271856 103 824 91
186 151 7199 5 74 0
187 474 46660 20 259 7
188 141 17547 5 69 3
189 1639 133368 36 535 54
190 872 95227 34 239 70
191 1318 152601 48 438 36
192 1018 98146 40 459 37
193 1383 79619 43 426 123
194 1314 59194 31 288 247
195 1335 139942 42 498 46
196 1403 118612 46 454 72
197 910 72880 33 376 41
198 616 65475 18 225 24
199 1407 99643 55 555 45
200 771 71965 35 252 33
201 766 77272 59 208 27
202 473 49289 19 130 36
203 1376 135131 66 481 87
204 1232 108446 60 389 90
205 1521 89746 36 565 114
206 572 44296 25 173 31
207 1059 77648 47 278 45
208 1544 181528 54 609 69
209 1230 134019 53 422 51
210 1206 124064 40 445 34
211 1205 92630 40 387 60
212 1255 121848 39 339 45
213 613 52915 14 181 54
214 721 81872 45 245 25
215 1109 58981 36 384 38
216 740 53515 28 212 52
217 1126 60812 44 399 67
218 728 56375 30 229 74
219 689 65490 22 224 38
220 592 80949 17 203 30
221 995 76302 31 333 26
222 1613 104011 55 384 67
223 2048 98104 54 636 132
224 705 67989 21 185 42
225 301 30989 14 93 35
226 1803 135458 81 581 118
227 799 73504 35 248 68
228 861 63123 43 304 43
229 1186 61254 46 344 76
230 1451 74914 30 407 64
231 628 31774 23 170 48
232 1161 81437 38 312 64
233 1463 87186 54 507 56
234 742 50090 20 224 71
235 979 65745 53 340 75
236 675 56653 45 168 39
237 1241 158399 39 443 42
238 676 46455 20 204 39
239 1049 73624 24 367 93
240 620 38395 31 210 38
241 1081 91899 35 335 60
242 1688 139526 151 364 71
243 736 52164 52 178 52
244 617 51567 30 206 27
245 812 70551 31 279 59
246 1051 84856 29 387 40
247 1656 102538 57 490 79
248 705 86678 40 238 44
249 945 85709 44 343 65
250 554 34662 25 232 10
251 1597 150580 77 530 124
252 982 99611 35 291 81
253 222 19349 11 67 15
254 1212 99373 63 397 92
255 1143 86230 44 467 42
256 435 30837 19 178 10
257 532 31706 13 175 24
258 882 89806 42 299 64
259 608 62088 38 154 45
260 459 40151 29 106 22
261 578 27634 20 189 56
262 826 76990 27 194 94
263 509 37460 20 135 19
264 717 54157 19 201 35
265 637 49862 37 207 32
266 857 84337 26 280 35
267 830 64175 42 260 48
268 652 59382 49 227 49
269 707 119308 30 239 48
270 954 76702 49 333 62
271 1461 103425 67 428 96
272 672 70344 28 230 45
273 778 43410 19 292 63
274 1141 104838 49 350 71
275 680 62215 27 186 26
276 1090 69304 30 326 48
277 616 53117 22 155 29
278 285 19764 12 75 19
279 1145 86680 31 361 45
280 733 84105 20 261 45
281 888 77945 20 299 67
282 849 89113 39 300 30
283 1182 91005 29 450 36
284 528 40248 16 183 34
285 642 64187 27 238 36
286 947 50857 21 165 34
287 819 56613 19 234 37
288 757 62792 35 176 46
289 894 72535 14 329 44
sharedcompendiums bloggedcomputations compendiumsreviewed totalsize
1 3 79 30 112285
2 4 58 28 84786
3 12 60 38 83123
4 2 108 30 101193
5 1 49 22 38361
6 3 0 26 68504
7 0 121 25 119182
8 0 1 18 22807
9 0 20 11 17140
10 5 43 26 116174
11 0 69 25 57635
12 0 78 38 66198
13 7 86 44 71701
14 7 44 30 57793
15 3 104 40 80444
16 9 63 34 53855
17 0 158 47 97668
18 4 102 30 133824
19 3 77 31 101481
20 0 82 23 99645
21 7 115 36 114789
22 0 101 36 99052
23 1 80 30 67654
24 5 50 25 65553
25 7 83 39 97500
26 0 123 34 69112
27 0 73 31 82753
28 5 81 31 85323
29 0 105 33 72654
30 0 47 25 30727
31 0 105 33 77873
32 3 94 35 117478
33 4 44 42 74007
34 1 114 43 90183
35 4 38 30 61542
36 2 107 33 101494
37 0 30 13 27570
38 0 71 32 55813
39 0 84 36 79215
40 0 0 0 1423
41 2 59 28 55461
42 1 33 14 31081
43 0 42 17 22996
44 2 96 32 83122
45 10 106 30 70106
46 6 56 35 60578
47 0 57 20 39992
48 5 59 28 79892
49 4 39 28 49810
50 1 34 39 71570
51 2 76 34 100708
52 2 20 26 33032
53 0 91 39 82875
54 8 115 39 139077
55 3 85 33 71595
56 0 76 28 72260
57 0 8 4 5950
58 8 79 39 115762
59 5 21 18 32551
60 3 30 14 31701
61 1 76 29 80670
62 5 101 44 143558
63 1 94 21 117105
64 1 27 16 23789
65 5 92 28 120733
66 0 123 35 105195
67 12 75 28 73107
68 8 128 38 132068
69 8 105 23 149193
70 8 55 36 46821
71 8 56 32 87011
72 2 41 29 95260
73 0 72 25 55183
74 5 67 27 106671
75 8 75 36 73511
76 2 114 28 92945
77 5 118 23 78664
78 12 77 40 70054
79 6 22 23 22618
80 7 66 40 74011
81 2 69 28 83737
82 0 105 34 69094
83 4 116 33 93133
84 3 88 28 95536
85 6 73 34 225920
86 2 99 30 62133
87 0 62 33 61370
88 1 53 22 43836
89 0 118 38 106117
90 5 30 26 38692
91 2 100 35 84651
92 0 49 8 56622
93 0 24 24 15986
94 5 67 29 95364
95 0 46 20 26706
96 1 57 29 89691
97 0 75 45 67267
98 1 135 37 126846
99 1 68 33 41140
100 2 124 33 102860
101 6 33 25 51715
102 1 98 32 55801
103 4 58 29 111813
104 2 68 28 120293
105 3 81 28 138599
106 0 131 31 161647
107 10 110 52 115929
108 0 37 21 24266
109 9 130 24 162901
110 7 93 41 109825
111 0 118 33 129838
112 0 39 32 37510
113 4 13 19 43750
114 4 74 20 40652
115 0 81 31 87771
116 0 109 31 85872
117 0 151 32 89275
118 1 51 18 44418
119 0 28 23 192565
120 1 40 17 35232
121 0 56 20 40909
122 0 27 12 13294
123 4 37 17 32387
124 0 83 30 140867
125 4 54 31 120662
126 4 27 10 21233
127 3 28 13 44332
128 0 59 22 61056
129 0 133 42 101338
130 0 12 1 1168
131 5 0 9 13497
132 0 106 32 65567
133 4 23 11 25162
134 0 44 25 32334
135 0 71 36 40735
136 1 116 31 91413
137 0 4 0 855
138 5 62 24 97068
139 0 12 13 44339
140 0 18 8 14116
141 0 14 13 10288
142 0 60 19 65622
143 0 7 18 16563
144 2 98 33 76643
145 7 64 40 110681
146 1 29 22 29011
147 8 32 38 92696
148 2 25 24 94785
149 0 16 8 8773
150 2 48 35 83209
151 0 100 43 93815
152 0 46 43 86687
153 1 45 14 34553
154 3 129 41 105547
155 0 130 38 103487
156 3 136 45 213688
157 0 59 31 71220
158 0 25 13 23517
159 0 32 28 56926
160 4 63 31 91721
161 4 95 40 115168
162 11 14 30 111194
163 0 36 16 51009
164 0 113 37 135777
165 4 47 30 51513
166 0 92 35 74163
167 1 70 32 51633
168 0 19 27 75345
169 0 50 20 33416
170 0 41 18 83305
171 9 91 31 98952
172 1 111 31 102372
173 3 41 21 37238
174 10 120 39 103772
175 5 135 41 123969
176 0 27 13 27142
177 2 87 32 135400
178 0 25 18 21399
179 1 131 39 130115
180 2 45 14 24874
181 4 29 7 34988
182 0 58 17 45549
183 0 4 0 6023
184 2 47 30 64466
185 1 109 37 54990
186 0 7 0 1644
187 0 12 5 6179
188 0 0 1 3926
189 1 37 16 32755
190 0 37 32 34777
191 2 46 24 73224
192 0 15 17 27114
193 3 42 11 20760
194 6 7 24 37636
195 0 54 22 65461
196 2 54 12 30080
197 0 14 19 24094
198 2 16 13 69008
199 1 33 17 54968
200 1 32 15 46090
201 2 21 16 27507
202 1 15 24 10672
203 0 38 15 34029
204 1 22 17 46300
205 3 28 18 24760
206 0 10 20 18779
207 0 31 16 21280
208 0 32 16 40662
209 0 32 18 28987
210 1 43 22 22827
211 4 27 8 18513
212 0 37 17 30594
213 0 20 18 24006
214 0 32 16 27913
215 7 0 23 42744
216 2 5 22 12934
217 0 26 13 22574
218 7 10 13 41385
219 3 27 16 18653
220 0 11 16 18472
221 0 29 20 30976
222 6 25 22 63339
223 2 55 17 25568
224 0 23 18 33747
225 0 5 17 4154
226 3 43 12 19474
227 0 23 7 35130
228 1 34 17 39067
229 1 36 14 13310
230 0 35 23 65892
231 1 0 17 4143
232 0 37 14 28579
233 0 28 15 51776
234 0 16 17 21152
235 0 26 21 38084
236 0 38 18 27717
237 0 23 18 32928
238 0 22 17 11342
239 0 30 17 19499
240 0 16 16 16380
241 0 18 15 36874
242 0 28 21 48259
243 0 32 16 16734
244 2 21 14 28207
245 0 23 15 30143
246 1 29 17 41369
247 1 50 15 45833
248 0 12 15 29156
249 0 21 10 35944
250 0 18 6 36278
251 0 27 22 45588
252 0 41 21 45097
253 0 13 1 3895
254 1 12 18 28394
255 0 21 17 18632
256 0 8 4 2325
257 0 26 10 25139
258 0 27 16 27975
259 1 13 16 14483
260 0 16 9 13127
261 0 2 16 5839
262 0 42 17 24069
263 0 5 7 3738
264 0 37 15 18625
265 0 17 14 36341
266 0 38 14 24548
267 0 37 18 21792
268 0 29 12 26263
269 0 32 16 23686
270 0 35 21 49303
271 1 17 19 25659
272 0 20 16 28904
273 0 7 1 2781
274 1 46 16 29236
275 0 24 10 19546
276 6 40 19 22818
277 3 3 12 32689
278 1 10 2 5752
279 2 37 14 22197
280 0 17 17 20055
281 0 28 19 25272
282 0 19 14 82206
283 3 29 11 32073
284 1 8 4 5444
285 0 10 16 20154
286 0 15 20 36944
287 1 15 12 8019
288 0 28 15 30884
289 0 17 16 19540
totalsizerevisions totalseconds course
1 24188 146283 1
2 18273 98364 1
3 14130 86146 1
4 32287 96933 1
5 8654 79234 1
6 9245 42551 1
7 33251 195663 1
8 1271 6853 1
9 5279 21529 0
10 27101 95757 1
11 16373 85584 1
12 19716 143983 1
13 17753 75851 1
14 9028 59238 1
15 18653 93163 1
16 8828 96037 1
17 29498 151511 1
18 27563 136368 1
19 18293 112642 1
20 22530 94728 1
21 15977 105499 1
22 35082 121527 1
23 16116 127766 1
24 15849 98958 1
25 16026 77900 1
26 26569 85646 1
27 24785 98579 1
28 17569 130767 1
29 23825 131741 1
30 7869 53907 1
31 14975 178812 1
32 37791 146761 1
33 9605 82036 1
34 27295 163253 1
35 2746 27032 1
36 34461 171975 1
37 8098 65990 0
38 4787 86572 1
39 24919 159676 1
40 603 1929 0
41 16329 85371 1
42 12558 58391 1
43 7784 31580 0
44 28522 136815 1
45 22265 120642 1
46 14459 69107 1
47 14526 50495 0
48 22240 108016 1
49 11802 46341 1
50 7623 78348 1
51 11912 79336 1
52 7935 56968 1
53 18220 93176 1
54 19199 161632 1
55 19918 87850 1
56 21884 127969 1
57 2694 15049 1
58 15808 155135 1
59 3597 25109 1
60 5296 45824 1
61 25239 102996 1
62 29801 160604 1
63 18450 158051 0
64 7132 44547 0
65 34861 162647 1
66 35940 174141 1
67 16688 60622 1
68 24683 179566 1
69 46230 184301 1
70 10387 75661 1
71 21436 96144 1
72 30546 129847 1
73 19746 117286 1
74 15977 71180 1
75 22583 109377 1
76 17274 85298 1
77 16469 73631 1
78 14251 86767 1
79 3007 23824 1
80 16851 93487 1
81 21113 82981 1
82 17401 73815 1
83 23958 94552 1
84 23567 132190 1
85 13065 128754 1
86 15358 66363 1
87 14587 67808 1
88 12770 61724 1
89 24021 131722 1
90 9648 68580 1
91 20537 106175 1
92 7905 55792 1
93 4527 25157 1
94 30495 76669 1
95 7117 57283 0
96 17719 105805 1
97 27056 129484 1
98 33473 72413 1
99 9758 87831 1
100 21115 96971 1
101 7236 71299 1
102 13790 77494 1
103 32902 120336 1
104 25131 93913 1
105 30910 136048 1
106 35947 181248 1
107 29848 146123 1
108 6943 32036 0
109 42705 186646 1
110 31808 102255 1
111 26675 168237 1
112 8435 64219 1
113 7409 19630 1
114 14993 76825 1
115 36867 115338 1
116 33835 109427 1
117 24164 118168 1
118 12607 84845 0
119 22609 153197 1
120 5892 29877 0
121 17014 63506 0
122 5394 22445 0
123 9178 47695 0
124 6440 68370 1
125 21916 146304 1
126 4011 38233 0
127 5818 42071 0
128 18647 50517 0
129 20556 103950 1
130 238 5841 1
131 70 2341 0
132 22392 84396 1
133 3913 24610 1
134 12237 35753 0
135 8388 55515 1
136 22120 209056 1
137 338 6622 1
138 11727 115814 1
139 3704 11609 0
140 3988 13155 1
141 3030 18274 0
142 13520 72875 0
143 1421 10112 0
144 20923 142775 1
145 20237 68847 1
146 3219 17659 0
147 3769 20112 1
148 12252 61023 1
149 1888 13983 1
150 14497 65176 1
151 28864 132432 1
152 21721 112494 1
153 4821 45109 0
154 33644 170875 1
155 15923 180759 1
156 42935 214921 1
157 18864 100226 1
158 4977 32043 0
159 7785 54454 1
160 17939 78876 1
161 23436 170745 1
162 325 6940 1
163 13539 49025 0
164 34538 122037 1
165 12198 53782 1
166 26924 127748 1
167 12716 86839 1
168 8172 44830 1
169 10855 77395 0
170 11932 89324 0
171 14300 103300 1
172 25515 112283 1
173 2805 10901 1
174 29402 120691 1
175 16440 58106 1
176 11221 57140 0
177 28732 122422 1
178 5250 25899 0
179 28608 139296 1
180 8092 52678 0
181 4473 23853 0
182 1572 17306 0
183 2065 7953 1
184 14817 89455 1
185 16714 147866 1
186 556 4245 1
187 2089 21509 1
188 2658 7670 1
189 10695 66675 0
190 1669 14336 1
191 16267 53608 1
192 7768 30059 0
193 7252 29668 0
194 6387 22097 0
195 18715 96841 0
196 7936 41907 0
197 8643 27080 0
198 7294 35885 0
199 4570 41247 0
200 7185 28313 0
201 10058 36845 0
202 2342 16548 0
203 8509 36134 0
204 13275 55764 0
205 6816 28910 0
206 1930 13339 0
207 8086 25319 0
208 10737 66956 0
209 8033 47487 0
210 7058 52785 0
211 6782 44683 0
212 5401 35619 0
213 6521 21920 0
214 10856 45608 0
215 2154 7721 0
216 6117 20634 0
217 5238 29788 0
218 4820 31931 0
219 5615 37754 0
220 4272 32505 0
221 8702 40557 0
222 15340 94238 0
223 8030 44197 0
224 9526 43228 0
225 1278 4103 0
226 4236 44144 0
227 3023 32868 0
228 7196 27640 0
229 3394 14063 0
230 6371 28990 0
231 1574 4694 0
232 9620 42648 0
233 6978 64329 0
234 4911 21928 0
235 8645 25836 0
236 8987 22779 0
237 5544 40820 0
238 3083 27530 0
239 6909 32378 0
240 3189 10824 0
241 6745 39613 0
242 16724 60865 0
243 4850 19787 0
244 7025 20107 0
245 6047 36605 0
246 7377 40961 0
247 9078 48231 0
248 4605 39725 0
249 3238 21455 0
250 8100 23430 0
251 9653 62991 0
252 8914 49363 0
253 786 9604 0
254 6700 24552 0
255 5788 31493 0
256 593 3439 0
257 4506 19555 0
258 6382 21228 0
259 5621 23177 0
260 3997 22094 0
261 520 2342 0
262 8891 38798 0
263 999 3255 0
264 7067 24261 0
265 4639 18511 0
266 5654 40798 0
267 6928 28893 0
268 1514 21425 0
269 9238 50276 0
270 8204 37643 0
271 5926 30377 0
272 5785 27126 0
273 4 13 0
274 5930 42097 0
275 3710 24451 0
276 705 14335 0
277 443 5084 0
278 2416 9927 0
279 7747 43527 0
280 5432 27184 0
281 4913 21610 0
282 2650 20484 0
283 2370 20156 0
284 775 6012 0
285 5576 18475 0
286 1352 12645 0
287 3080 11017 0
288 10205 37623 0
289 6095 35873 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) timerfc logins
7.711e+01 4.044e-04 2.966e+00
compendiumviewsinfo compendiumviewspr sharedcompendiums
1.784e+00 1.290e+00 1.000e+01
bloggedcomputations compendiumsreviewed totalsize
2.482e+00 4.053e+00 4.104e-04
totalsizerevisions totalseconds course
-4.054e-03 6.161e-04 -1.912e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-502.29 -86.92 -15.30 79.77 1056.50
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.711e+01 2.302e+01 3.350 0.000922 ***
timerfc 4.044e-04 4.011e-04 1.008 0.314215
logins 2.966e+00 3.775e-01 7.858 8.67e-14 ***
compendiumviewsinfo 1.784e+00 7.871e-02 22.669 < 2e-16 ***
compendiumviewspr 1.290e+00 2.105e-01 6.128 3.05e-09 ***
sharedcompendiums 1.000e+01 3.697e+00 2.706 0.007225 **
bloggedcomputations 2.482e+00 5.308e-01 4.676 4.58e-06 ***
compendiumsreviewed 4.053e+00 1.547e+00 2.620 0.009276 **
totalsize 4.104e-04 4.406e-04 0.931 0.352439
totalsizerevisions -4.054e-03 2.020e-03 -2.007 0.045760 *
totalseconds 6.161e-04 5.712e-04 1.079 0.281728
course -1.912e+02 2.551e+01 -7.497 8.84e-13 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 146.6 on 277 degrees of freedom
Multiple R-squared: 0.9619, Adjusted R-squared: 0.9604
F-statistic: 635.2 on 11 and 277 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,] 0.16542140 3.308428e-01 8.345786e-01
[2,] 0.09451593 1.890319e-01 9.054841e-01
[3,] 0.92359238 1.528152e-01 7.640762e-02
[4,] 0.88359468 2.328106e-01 1.164053e-01
[5,] 0.83512187 3.297563e-01 1.648781e-01
[6,] 0.82626921 3.474616e-01 1.737308e-01
[7,] 0.77330472 4.533906e-01 2.266953e-01
[8,] 0.83172960 3.365408e-01 1.682704e-01
[9,] 0.78454915 4.309017e-01 2.154508e-01
[10,] 0.79335432 4.132914e-01 2.066457e-01
[11,] 0.78635232 4.272954e-01 2.136477e-01
[12,] 0.72732345 5.453531e-01 2.726765e-01
[13,] 0.70054090 5.989182e-01 2.994591e-01
[14,] 0.64503361 7.099328e-01 3.549664e-01
[15,] 0.57789399 8.442120e-01 4.221060e-01
[16,] 0.50781863 9.843627e-01 4.921814e-01
[17,] 0.49981994 9.996399e-01 5.001801e-01
[18,] 0.45158764 9.031753e-01 5.484124e-01
[19,] 0.38669206 7.733841e-01 6.133079e-01
[20,] 0.44826960 8.965392e-01 5.517304e-01
[21,] 0.40161204 8.032241e-01 5.983880e-01
[22,] 0.35785384 7.157077e-01 6.421462e-01
[23,] 0.30527585 6.105517e-01 6.947242e-01
[24,] 0.25708150 5.141630e-01 7.429185e-01
[25,] 0.37750896 7.550179e-01 6.224910e-01
[26,] 0.33327282 6.665456e-01 6.667272e-01
[27,] 0.29286263 5.857253e-01 7.071374e-01
[28,] 0.30969932 6.193986e-01 6.903007e-01
[29,] 0.36576098 7.315220e-01 6.342390e-01
[30,] 0.31590031 6.318006e-01 6.840997e-01
[31,] 0.29565001 5.913000e-01 7.043500e-01
[32,] 0.31742726 6.348545e-01 6.825727e-01
[33,] 0.39855235 7.971047e-01 6.014477e-01
[34,] 0.35694546 7.138909e-01 6.430545e-01
[35,] 0.39417329 7.883466e-01 6.058267e-01
[36,] 0.35351955 7.070391e-01 6.464805e-01
[37,] 0.37494576 7.498915e-01 6.250542e-01
[38,] 0.32905574 6.581115e-01 6.709443e-01
[39,] 0.32136195 6.427239e-01 6.786380e-01
[40,] 0.68313218 6.337356e-01 3.168678e-01
[41,] 0.65986312 6.802738e-01 3.401369e-01
[42,] 0.63659534 7.268093e-01 3.634047e-01
[43,] 0.60924631 7.815074e-01 3.907537e-01
[44,] 0.86126168 2.774766e-01 1.387383e-01
[45,] 0.85126489 2.974702e-01 1.487351e-01
[46,] 0.82602121 3.479576e-01 1.739788e-01
[47,] 0.87521246 2.495751e-01 1.247875e-01
[48,] 0.94079732 1.184054e-01 5.920268e-02
[49,] 0.99999999 1.442853e-08 7.214265e-09
[50,] 1.00000000 9.797525e-09 4.898762e-09
[51,] 1.00000000 3.232613e-09 1.616306e-09
[52,] 1.00000000 7.213439e-10 3.606720e-10
[53,] 1.00000000 9.647187e-10 4.823593e-10
[54,] 1.00000000 6.089725e-10 3.044862e-10
[55,] 1.00000000 1.119997e-09 5.599984e-10
[56,] 1.00000000 1.477811e-09 7.389056e-10
[57,] 1.00000000 1.771053e-09 8.855265e-10
[58,] 1.00000000 2.395584e-09 1.197792e-09
[59,] 1.00000000 9.255575e-10 4.627787e-10
[60,] 1.00000000 1.622882e-09 8.114408e-10
[61,] 1.00000000 1.080603e-09 5.403013e-10
[62,] 1.00000000 1.561927e-09 7.809633e-10
[63,] 1.00000000 1.455404e-09 7.277020e-10
[64,] 1.00000000 1.866277e-09 9.331384e-10
[65,] 1.00000000 2.690761e-09 1.345380e-09
[66,] 1.00000000 3.739033e-09 1.869517e-09
[67,] 1.00000000 2.390649e-09 1.195324e-09
[68,] 1.00000000 4.197755e-09 2.098877e-09
[69,] 1.00000000 3.948111e-10 1.974055e-10
[70,] 1.00000000 4.305743e-10 2.152871e-10
[71,] 1.00000000 4.847356e-10 2.423678e-10
[72,] 1.00000000 6.319746e-10 3.159873e-10
[73,] 1.00000000 1.099610e-09 5.498049e-10
[74,] 1.00000000 8.910137e-10 4.455068e-10
[75,] 1.00000000 1.618797e-10 8.093986e-11
[76,] 1.00000000 4.159068e-11 2.079534e-11
[77,] 1.00000000 4.870224e-11 2.435112e-11
[78,] 1.00000000 6.274418e-11 3.137209e-11
[79,] 1.00000000 9.113601e-11 4.556801e-11
[80,] 1.00000000 1.473495e-10 7.367473e-11
[81,] 1.00000000 1.343209e-10 6.716045e-11
[82,] 1.00000000 1.361508e-10 6.807538e-11
[83,] 1.00000000 2.398031e-10 1.199016e-10
[84,] 1.00000000 1.826614e-10 9.133072e-11
[85,] 1.00000000 1.962103e-10 9.810515e-11
[86,] 1.00000000 3.388660e-10 1.694330e-10
[87,] 1.00000000 3.338866e-10 1.669433e-10
[88,] 1.00000000 2.562656e-10 1.281328e-10
[89,] 1.00000000 3.911512e-10 1.955756e-10
[90,] 1.00000000 6.055752e-10 3.027876e-10
[91,] 1.00000000 1.037983e-09 5.189917e-10
[92,] 1.00000000 9.628480e-10 4.814240e-10
[93,] 1.00000000 1.015912e-09 5.079561e-10
[94,] 1.00000000 8.740939e-10 4.370470e-10
[95,] 1.00000000 1.239787e-09 6.198936e-10
[96,] 1.00000000 2.138803e-09 1.069402e-09
[97,] 1.00000000 3.128835e-09 1.564418e-09
[98,] 1.00000000 3.909197e-09 1.954598e-09
[99,] 1.00000000 5.897578e-09 2.948789e-09
[100,] 1.00000000 5.320913e-09 2.660456e-09
[101,] 1.00000000 7.311032e-09 3.655516e-09
[102,] 1.00000000 6.158250e-09 3.079125e-09
[103,] 1.00000000 8.915561e-09 4.457781e-09
[104,] 0.99999999 1.153510e-08 5.767552e-09
[105,] 0.99999999 1.755484e-08 8.777418e-09
[106,] 0.99999999 2.389184e-08 1.194592e-08
[107,] 0.99999998 3.163966e-08 1.581983e-08
[108,] 0.99999999 2.820980e-08 1.410490e-08
[109,] 0.99999998 4.119191e-08 2.059596e-08
[110,] 0.99999997 6.090301e-08 3.045151e-08
[111,] 0.99999995 9.565945e-08 4.782972e-08
[112,] 0.99999993 1.356231e-07 6.781157e-08
[113,] 0.99999993 1.464342e-07 7.321711e-08
[114,] 0.99999993 1.415533e-07 7.077664e-08
[115,] 0.99999991 1.744554e-07 8.722769e-08
[116,] 0.99999992 1.657935e-07 8.289675e-08
[117,] 0.99999987 2.543696e-07 1.271848e-07
[118,] 0.99999980 4.023402e-07 2.011701e-07
[119,] 0.99999970 6.045059e-07 3.022530e-07
[120,] 0.99999983 3.421093e-07 1.710547e-07
[121,] 0.99999983 3.493630e-07 1.746815e-07
[122,] 0.99999987 2.597339e-07 1.298670e-07
[123,] 0.99999989 2.271001e-07 1.135501e-07
[124,] 0.99999985 3.025095e-07 1.512547e-07
[125,] 0.99999979 4.208798e-07 2.104399e-07
[126,] 0.99999967 6.515686e-07 3.257843e-07
[127,] 0.99999958 8.389122e-07 4.194561e-07
[128,] 0.99999960 7.947754e-07 3.973877e-07
[129,] 0.99999955 9.081637e-07 4.540819e-07
[130,] 0.99999940 1.190677e-06 5.953384e-07
[131,] 0.99999913 1.744450e-06 8.722248e-07
[132,] 0.99999919 1.611223e-06 8.056115e-07
[133,] 0.99999890 2.198571e-06 1.099286e-06
[134,] 0.99999855 2.898356e-06 1.449178e-06
[135,] 0.99999817 3.666810e-06 1.833405e-06
[136,] 0.99999749 5.027473e-06 2.513737e-06
[137,] 0.99999635 7.299597e-06 3.649798e-06
[138,] 0.99999505 9.892679e-06 4.946340e-06
[139,] 0.99999328 1.343772e-05 6.718862e-06
[140,] 0.99999928 1.437914e-06 7.189572e-07
[141,] 0.99999969 6.113325e-07 3.056663e-07
[142,] 0.99999956 8.723324e-07 4.361662e-07
[143,] 0.99999951 9.753103e-07 4.876551e-07
[144,] 0.99999959 8.142874e-07 4.071437e-07
[145,] 0.99999936 1.278208e-06 6.391041e-07
[146,] 0.99999996 7.850155e-08 3.925077e-08
[147,] 0.99999996 7.731347e-08 3.865673e-08
[148,] 0.99999995 1.041049e-07 5.205243e-08
[149,] 0.99999995 9.072004e-08 4.536002e-08
[150,] 0.99999997 5.044923e-08 2.522462e-08
[151,] 0.99999996 7.306220e-08 3.653110e-08
[152,] 0.99999994 1.211796e-07 6.058979e-08
[153,] 0.99999993 1.378460e-07 6.892300e-08
[154,] 0.99999993 1.484641e-07 7.423204e-08
[155,] 0.99999990 2.094337e-07 1.047169e-07
[156,] 0.99999984 3.196908e-07 1.598454e-07
[157,] 0.99999988 2.493200e-07 1.246600e-07
[158,] 0.99999980 3.983229e-07 1.991615e-07
[159,] 0.99999996 8.285689e-08 4.142845e-08
[160,] 0.99999994 1.160750e-07 5.803751e-08
[161,] 0.99999999 2.017487e-08 1.008743e-08
[162,] 0.99999998 3.095522e-08 1.547761e-08
[163,] 0.99999998 4.742188e-08 2.371094e-08
[164,] 0.99999996 7.515272e-08 3.757636e-08
[165,] 0.99999996 7.848621e-08 3.924311e-08
[166,] 0.99999995 1.063277e-07 5.316387e-08
[167,] 0.99999991 1.776181e-07 8.880904e-08
[168,] 0.99999986 2.899496e-07 1.449748e-07
[169,] 0.99999980 4.058728e-07 2.029364e-07
[170,] 0.99999969 6.184547e-07 3.092274e-07
[171,] 0.99999970 6.043853e-07 3.021926e-07
[172,] 0.99999954 9.282504e-07 4.641252e-07
[173,] 0.99999946 1.073485e-06 5.367425e-07
[174,] 0.99999916 1.676219e-06 8.381095e-07
[175,] 0.99999960 8.080067e-07 4.040033e-07
[176,] 0.99999942 1.166857e-06 5.834285e-07
[177,] 0.99999914 1.725766e-06 8.628829e-07
[178,] 0.99999935 1.302253e-06 6.511265e-07
[179,] 0.99999893 2.142713e-06 1.071357e-06
[180,] 0.99999834 3.311733e-06 1.655867e-06
[181,] 0.99999829 3.420689e-06 1.710344e-06
[182,] 0.99999725 5.506743e-06 2.753371e-06
[183,] 0.99999684 6.313474e-06 3.156737e-06
[184,] 0.99999607 7.869536e-06 3.934768e-06
[185,] 0.99999618 7.648473e-06 3.824236e-06
[186,] 0.99999494 1.012435e-05 5.062173e-06
[187,] 0.99999265 1.469232e-05 7.346158e-06
[188,] 0.99999031 1.938371e-05 9.691856e-06
[189,] 0.99998720 2.559229e-05 1.279615e-05
[190,] 0.99998096 3.808477e-05 1.904238e-05
[191,] 0.99997468 5.064856e-05 2.532428e-05
[192,] 0.99996176 7.647951e-05 3.823975e-05
[193,] 0.99996466 7.068049e-05 3.534025e-05
[194,] 0.99996106 7.788318e-05 3.894159e-05
[195,] 0.99994152 1.169605e-04 5.848025e-05
[196,] 0.99993340 1.332075e-04 6.660377e-05
[197,] 0.99989859 2.028140e-04 1.014070e-04
[198,] 0.99995276 9.447447e-05 4.723724e-05
[199,] 0.99992721 1.455785e-04 7.278923e-05
[200,] 0.99992709 1.458163e-04 7.290814e-05
[201,] 0.99989509 2.098156e-04 1.049078e-04
[202,] 0.99983805 3.238993e-04 1.619497e-04
[203,] 0.99976889 4.622176e-04 2.311088e-04
[204,] 0.99991530 1.693954e-04 8.469771e-05
[205,] 0.99991820 1.636055e-04 8.180274e-05
[206,] 0.99987478 2.504433e-04 1.252216e-04
[207,] 0.99980849 3.830115e-04 1.915057e-04
[208,] 0.99983259 3.348180e-04 1.674090e-04
[209,] 0.99987575 2.484901e-04 1.242451e-04
[210,] 0.99981539 3.692127e-04 1.846064e-04
[211,] 0.99975966 4.806812e-04 2.403406e-04
[212,] 0.99962632 7.473661e-04 3.736830e-04
[213,] 0.99943824 1.123515e-03 5.617576e-04
[214,] 0.99948318 1.033632e-03 5.168162e-04
[215,] 0.99933943 1.321148e-03 6.605738e-04
[216,] 0.99989008 2.198424e-04 1.099212e-04
[217,] 0.99982958 3.408471e-04 1.704235e-04
[218,] 0.99990069 1.986199e-04 9.930993e-05
[219,] 0.99985773 2.845372e-04 1.422686e-04
[220,] 0.99977182 4.563599e-04 2.281800e-04
[221,] 0.99975420 4.915986e-04 2.457993e-04
[222,] 0.99962932 7.413651e-04 3.706825e-04
[223,] 0.99943940 1.121197e-03 5.605985e-04
[224,] 0.99912245 1.755092e-03 8.775458e-04
[225,] 0.99862643 2.747130e-03 1.373565e-03
[226,] 0.99813524 3.729519e-03 1.864759e-03
[227,] 0.99799795 4.004095e-03 2.002048e-03
[228,] 0.99929839 1.403214e-03 7.016071e-04
[229,] 0.99885898 2.282037e-03 1.141019e-03
[230,] 0.99852613 2.947739e-03 1.473869e-03
[231,] 0.99794071 4.118582e-03 2.059291e-03
[232,] 0.99684598 6.308033e-03 3.154016e-03
[233,] 0.99941671 1.166570e-03 5.832852e-04
[234,] 0.99923131 1.537375e-03 7.686875e-04
[235,] 0.99873270 2.534599e-03 1.267299e-03
[236,] 0.99790810 4.183797e-03 2.091899e-03
[237,] 0.99656530 6.869394e-03 3.434697e-03
[238,] 0.99464605 1.070790e-02 5.353951e-03
[239,] 0.99194303 1.611394e-02 8.056972e-03
[240,] 0.98728720 2.542559e-02 1.271280e-02
[241,] 0.98139023 3.721955e-02 1.860977e-02
[242,] 0.97286546 5.426907e-02 2.713454e-02
[243,] 0.96008493 7.983014e-02 3.991507e-02
[244,] 0.94411202 1.117760e-01 5.588798e-02
[245,] 0.92381631 1.523674e-01 7.618369e-02
[246,] 0.89277664 2.144467e-01 1.072234e-01
[247,] 0.89655348 2.068930e-01 1.034465e-01
[248,] 0.85642083 2.871583e-01 1.435792e-01
[249,] 0.81280154 3.743969e-01 1.871985e-01
[250,] 0.77214499 4.557100e-01 2.278550e-01
[251,] 0.71239285 5.752143e-01 2.876072e-01
[252,] 0.63654808 7.269038e-01 3.634519e-01
[253,] 0.54870219 9.025956e-01 4.512978e-01
[254,] 0.70342796 5.931441e-01 2.965720e-01
[255,] 0.61203555 7.759289e-01 3.879644e-01
[256,] 0.75090526 4.981895e-01 2.490947e-01
[257,] 0.65464141 6.907172e-01 3.453586e-01
[258,] 0.61549669 7.690066e-01 3.845033e-01
[259,] 0.50243686 9.951263e-01 4.975631e-01
[260,] 0.34126517 6.825303e-01 6.587348e-01
> postscript(file="/var/wessaorg/rcomp/tmp/19wfr1323962018.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/21ede1323962018.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3t40d1323962018.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4d4go1323962018.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5re3k1323962018.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
83.8321273 -151.5664679 -102.2296174 -317.0486022 63.0431868 26.5248295
7 8 9 10 11 12
-418.2880012 83.2140133 18.2982604 -8.2174239 120.4569203 -114.6835847
13 14 15 16 17 18
-80.9013069 -58.1222342 -139.1900986 -26.3866165 268.9351931 -19.9000639
19 20 21 22 23 24
-206.4279477 -59.1615873 115.9693560 164.3903029 -206.0733717 92.5465260
25 26 27 28 29 30
-22.4775311 -28.6993991 82.4443540 -74.4410306 53.9830923 41.5201821
31 32 33 34 35 36
-137.2108595 -60.2784230 30.1829823 -153.9710055 -5.4592529 -54.6790958
37 38 39 40 41 42
-13.6476329 -80.8206268 212.3093998 -69.9534779 79.7710030 195.4468977
43 44 45 46 47 48
217.0141317 8.0586955 -248.4499517 -179.9816864 263.5007372 -100.5489320
49 50 51 52 53 54
210.4398703 -50.0813983 -305.4038708 21.8290240 194.8183124 269.7451267
55 56 57 58 59 60
-131.8099312 118.4208874 77.5249670 -502.2899358 109.9838950 -36.9512076
61 62 63 64 65 66
255.8977468 332.3282021 1056.5048136 -46.0941245 237.0507713 -276.0389192
67 68 69 70 71 72
-91.9046952 211.6684849 -14.4366164 -115.4155686 102.3052318 -104.9862721
73 74 75 76 77 78
231.9175064 15.9694431 152.8882102 -67.3717252 -156.0900964 90.8479043
79 80 81 82 83 84
-74.4139837 103.7263795 -192.5275215 14.6459797 -340.1275640 -139.3492702
85 86 87 88 89 90
-34.5592940 108.3332807 -19.5559881 165.6098858 281.8143632 -255.6327457
91 92 93 94 95 96
131.2881610 -122.0894445 -53.1485500 75.2445397 -8.8372122 -136.6558947
97 98 99 100 101 102
40.5891234 179.1164651 134.1162368 6.9128758 147.5784078 171.6889978
103 104 105 106 107 108
-39.5294339 82.0249923 6.7613125 -144.0874653 153.7108737 181.0680023
109 110 111 112 113 114
-79.3588626 17.1764669 -68.3602775 -122.5106767 70.4922217 148.7148679
115 116 117 118 119 120
-90.0910153 -140.6433559 -91.2508598 108.0633493 26.7348349 29.3228287
121 122 123 124 125 126
84.0830884 -103.8972432 1.0254872 -73.2491503 35.1949684 -15.8968068
127 128 129 130 131 132
-88.6258386 151.1911959 66.6451461 142.8521840 7.2853582 -3.8330556
133 134 135 136 137 138
18.8130563 229.2387838 127.4226621 -182.5629383 169.0818250 -43.0506567
139 140 141 142 143 144
-0.4961412 34.0014955 -54.1510592 126.7085444 -80.0816574 94.9600876
145 146 147 148 149 150
67.8155376 147.5858169 -45.4866216 95.4688480 -70.4177945 77.0390730
151 152 153 154 155 156
-50.7965873 -65.3058507 46.5397262 -307.4366819 -219.3984489 66.7115454
157 158 159 160 161 162
-85.6801298 -123.3940124 39.4706937 -308.8411717 206.5357347 -15.2971211
163 164 165 166 167 168
-117.5963841 -170.4228851 17.0423113 10.1303234 -33.7734177 -15.5254964
169 170 171 172 173 174
-58.8682749 55.5526623 11.0417304 -12.5451924 339.3991524 125.9547324
175 176 177 178 179 180
-232.5743076 -50.9357501 51.0729352 -29.6056441 1.6920557 -67.2832789
181 182 183 184 185 186
24.6981053 43.1152822 124.9356846 130.0323964 63.6122065 96.9411193
187 188 189 190 191 192
-18.5886234 106.6048978 199.0795565 92.1566563 171.4993184 -188.4428079
193 194 195 196 197 198
51.1280958 110.6541866 -105.0399394 29.8672955 -121.5271906 -106.6667396
199 200 201 202 203 204
-112.1275700 -88.6922144 -53.5220491 -108.3762207 -78.8445625 -10.1758529
205 206 207 208 209 210
-27.1648358 -59.8238055 123.6546568 -101.0123997 -38.2372997 -96.9611485
211 212 213 214 215 216
56.7763317 176.6727399 -39.1579645 -131.9127519 -9.7395274 -1.9530383
217 218 219 220 221 222
-28.1759505 -129.6116842 -98.5721917 -71.6106024 11.9233969 325.9856349
223 224 225 226 227 228
235.3677841 21.9355270 -121.6127589 38.5571261 -49.7460186 -134.2581246
229 230 231 232 233 234
79.3716240 246.6886646 27.4590835 151.4052193 50.7036835 -16.8481931
235 236 237 238 239 240
-131.4578247 -64.8172742 -6.6871280 -26.1400482 -47.1703609 -93.3280981
241 242 243 244 245 246
70.1127999 221.3599775 -44.8038516 -96.6967642 -87.8039809 -51.7467809
247 248 249 250 251 252
185.5163650 -115.5789273 -100.6396811 -103.6123919 -49.6012380 -62.5819589
253 254 255 256 257 258
-75.1063607 -31.5704343 -111.5362963 -78.1740648 -48.8561916 -102.6175396
259 260 261 262 263 264
-44.3172219 -16.8652126 -50.6156390 -0.6249174 51.7616171 11.2750079
265 266 267 268 269 270
-87.0978735 -39.4289420 -86.9224258 -201.1700929 -143.2211000 -155.7679509
271 272 273 274 275 276
121.3855094 -104.6517004 2.1386918 -42.8611474 24.0842271 0.6311219
277 278 279 280 281 282
37.3347495 -35.6387510 65.6074280 -75.2381880 -50.1498243 -93.3283282
283 284 285 286 287 288
-29.8420866 -32.0950797 -98.9642735 313.0109340 103.9287812 52.5328211
289
-10.2008801
> postscript(file="/var/wessaorg/rcomp/tmp/6lqxs1323962018.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 83.8321273 NA
1 -151.5664679 83.8321273
2 -102.2296174 -151.5664679
3 -317.0486022 -102.2296174
4 63.0431868 -317.0486022
5 26.5248295 63.0431868
6 -418.2880012 26.5248295
7 83.2140133 -418.2880012
8 18.2982604 83.2140133
9 -8.2174239 18.2982604
10 120.4569203 -8.2174239
11 -114.6835847 120.4569203
12 -80.9013069 -114.6835847
13 -58.1222342 -80.9013069
14 -139.1900986 -58.1222342
15 -26.3866165 -139.1900986
16 268.9351931 -26.3866165
17 -19.9000639 268.9351931
18 -206.4279477 -19.9000639
19 -59.1615873 -206.4279477
20 115.9693560 -59.1615873
21 164.3903029 115.9693560
22 -206.0733717 164.3903029
23 92.5465260 -206.0733717
24 -22.4775311 92.5465260
25 -28.6993991 -22.4775311
26 82.4443540 -28.6993991
27 -74.4410306 82.4443540
28 53.9830923 -74.4410306
29 41.5201821 53.9830923
30 -137.2108595 41.5201821
31 -60.2784230 -137.2108595
32 30.1829823 -60.2784230
33 -153.9710055 30.1829823
34 -5.4592529 -153.9710055
35 -54.6790958 -5.4592529
36 -13.6476329 -54.6790958
37 -80.8206268 -13.6476329
38 212.3093998 -80.8206268
39 -69.9534779 212.3093998
40 79.7710030 -69.9534779
41 195.4468977 79.7710030
42 217.0141317 195.4468977
43 8.0586955 217.0141317
44 -248.4499517 8.0586955
45 -179.9816864 -248.4499517
46 263.5007372 -179.9816864
47 -100.5489320 263.5007372
48 210.4398703 -100.5489320
49 -50.0813983 210.4398703
50 -305.4038708 -50.0813983
51 21.8290240 -305.4038708
52 194.8183124 21.8290240
53 269.7451267 194.8183124
54 -131.8099312 269.7451267
55 118.4208874 -131.8099312
56 77.5249670 118.4208874
57 -502.2899358 77.5249670
58 109.9838950 -502.2899358
59 -36.9512076 109.9838950
60 255.8977468 -36.9512076
61 332.3282021 255.8977468
62 1056.5048136 332.3282021
63 -46.0941245 1056.5048136
64 237.0507713 -46.0941245
65 -276.0389192 237.0507713
66 -91.9046952 -276.0389192
67 211.6684849 -91.9046952
68 -14.4366164 211.6684849
69 -115.4155686 -14.4366164
70 102.3052318 -115.4155686
71 -104.9862721 102.3052318
72 231.9175064 -104.9862721
73 15.9694431 231.9175064
74 152.8882102 15.9694431
75 -67.3717252 152.8882102
76 -156.0900964 -67.3717252
77 90.8479043 -156.0900964
78 -74.4139837 90.8479043
79 103.7263795 -74.4139837
80 -192.5275215 103.7263795
81 14.6459797 -192.5275215
82 -340.1275640 14.6459797
83 -139.3492702 -340.1275640
84 -34.5592940 -139.3492702
85 108.3332807 -34.5592940
86 -19.5559881 108.3332807
87 165.6098858 -19.5559881
88 281.8143632 165.6098858
89 -255.6327457 281.8143632
90 131.2881610 -255.6327457
91 -122.0894445 131.2881610
92 -53.1485500 -122.0894445
93 75.2445397 -53.1485500
94 -8.8372122 75.2445397
95 -136.6558947 -8.8372122
96 40.5891234 -136.6558947
97 179.1164651 40.5891234
98 134.1162368 179.1164651
99 6.9128758 134.1162368
100 147.5784078 6.9128758
101 171.6889978 147.5784078
102 -39.5294339 171.6889978
103 82.0249923 -39.5294339
104 6.7613125 82.0249923
105 -144.0874653 6.7613125
106 153.7108737 -144.0874653
107 181.0680023 153.7108737
108 -79.3588626 181.0680023
109 17.1764669 -79.3588626
110 -68.3602775 17.1764669
111 -122.5106767 -68.3602775
112 70.4922217 -122.5106767
113 148.7148679 70.4922217
114 -90.0910153 148.7148679
115 -140.6433559 -90.0910153
116 -91.2508598 -140.6433559
117 108.0633493 -91.2508598
118 26.7348349 108.0633493
119 29.3228287 26.7348349
120 84.0830884 29.3228287
121 -103.8972432 84.0830884
122 1.0254872 -103.8972432
123 -73.2491503 1.0254872
124 35.1949684 -73.2491503
125 -15.8968068 35.1949684
126 -88.6258386 -15.8968068
127 151.1911959 -88.6258386
128 66.6451461 151.1911959
129 142.8521840 66.6451461
130 7.2853582 142.8521840
131 -3.8330556 7.2853582
132 18.8130563 -3.8330556
133 229.2387838 18.8130563
134 127.4226621 229.2387838
135 -182.5629383 127.4226621
136 169.0818250 -182.5629383
137 -43.0506567 169.0818250
138 -0.4961412 -43.0506567
139 34.0014955 -0.4961412
140 -54.1510592 34.0014955
141 126.7085444 -54.1510592
142 -80.0816574 126.7085444
143 94.9600876 -80.0816574
144 67.8155376 94.9600876
145 147.5858169 67.8155376
146 -45.4866216 147.5858169
147 95.4688480 -45.4866216
148 -70.4177945 95.4688480
149 77.0390730 -70.4177945
150 -50.7965873 77.0390730
151 -65.3058507 -50.7965873
152 46.5397262 -65.3058507
153 -307.4366819 46.5397262
154 -219.3984489 -307.4366819
155 66.7115454 -219.3984489
156 -85.6801298 66.7115454
157 -123.3940124 -85.6801298
158 39.4706937 -123.3940124
159 -308.8411717 39.4706937
160 206.5357347 -308.8411717
161 -15.2971211 206.5357347
162 -117.5963841 -15.2971211
163 -170.4228851 -117.5963841
164 17.0423113 -170.4228851
165 10.1303234 17.0423113
166 -33.7734177 10.1303234
167 -15.5254964 -33.7734177
168 -58.8682749 -15.5254964
169 55.5526623 -58.8682749
170 11.0417304 55.5526623
171 -12.5451924 11.0417304
172 339.3991524 -12.5451924
173 125.9547324 339.3991524
174 -232.5743076 125.9547324
175 -50.9357501 -232.5743076
176 51.0729352 -50.9357501
177 -29.6056441 51.0729352
178 1.6920557 -29.6056441
179 -67.2832789 1.6920557
180 24.6981053 -67.2832789
181 43.1152822 24.6981053
182 124.9356846 43.1152822
183 130.0323964 124.9356846
184 63.6122065 130.0323964
185 96.9411193 63.6122065
186 -18.5886234 96.9411193
187 106.6048978 -18.5886234
188 199.0795565 106.6048978
189 92.1566563 199.0795565
190 171.4993184 92.1566563
191 -188.4428079 171.4993184
192 51.1280958 -188.4428079
193 110.6541866 51.1280958
194 -105.0399394 110.6541866
195 29.8672955 -105.0399394
196 -121.5271906 29.8672955
197 -106.6667396 -121.5271906
198 -112.1275700 -106.6667396
199 -88.6922144 -112.1275700
200 -53.5220491 -88.6922144
201 -108.3762207 -53.5220491
202 -78.8445625 -108.3762207
203 -10.1758529 -78.8445625
204 -27.1648358 -10.1758529
205 -59.8238055 -27.1648358
206 123.6546568 -59.8238055
207 -101.0123997 123.6546568
208 -38.2372997 -101.0123997
209 -96.9611485 -38.2372997
210 56.7763317 -96.9611485
211 176.6727399 56.7763317
212 -39.1579645 176.6727399
213 -131.9127519 -39.1579645
214 -9.7395274 -131.9127519
215 -1.9530383 -9.7395274
216 -28.1759505 -1.9530383
217 -129.6116842 -28.1759505
218 -98.5721917 -129.6116842
219 -71.6106024 -98.5721917
220 11.9233969 -71.6106024
221 325.9856349 11.9233969
222 235.3677841 325.9856349
223 21.9355270 235.3677841
224 -121.6127589 21.9355270
225 38.5571261 -121.6127589
226 -49.7460186 38.5571261
227 -134.2581246 -49.7460186
228 79.3716240 -134.2581246
229 246.6886646 79.3716240
230 27.4590835 246.6886646
231 151.4052193 27.4590835
232 50.7036835 151.4052193
233 -16.8481931 50.7036835
234 -131.4578247 -16.8481931
235 -64.8172742 -131.4578247
236 -6.6871280 -64.8172742
237 -26.1400482 -6.6871280
238 -47.1703609 -26.1400482
239 -93.3280981 -47.1703609
240 70.1127999 -93.3280981
241 221.3599775 70.1127999
242 -44.8038516 221.3599775
243 -96.6967642 -44.8038516
244 -87.8039809 -96.6967642
245 -51.7467809 -87.8039809
246 185.5163650 -51.7467809
247 -115.5789273 185.5163650
248 -100.6396811 -115.5789273
249 -103.6123919 -100.6396811
250 -49.6012380 -103.6123919
251 -62.5819589 -49.6012380
252 -75.1063607 -62.5819589
253 -31.5704343 -75.1063607
254 -111.5362963 -31.5704343
255 -78.1740648 -111.5362963
256 -48.8561916 -78.1740648
257 -102.6175396 -48.8561916
258 -44.3172219 -102.6175396
259 -16.8652126 -44.3172219
260 -50.6156390 -16.8652126
261 -0.6249174 -50.6156390
262 51.7616171 -0.6249174
263 11.2750079 51.7616171
264 -87.0978735 11.2750079
265 -39.4289420 -87.0978735
266 -86.9224258 -39.4289420
267 -201.1700929 -86.9224258
268 -143.2211000 -201.1700929
269 -155.7679509 -143.2211000
270 121.3855094 -155.7679509
271 -104.6517004 121.3855094
272 2.1386918 -104.6517004
273 -42.8611474 2.1386918
274 24.0842271 -42.8611474
275 0.6311219 24.0842271
276 37.3347495 0.6311219
277 -35.6387510 37.3347495
278 65.6074280 -35.6387510
279 -75.2381880 65.6074280
280 -50.1498243 -75.2381880
281 -93.3283282 -50.1498243
282 -29.8420866 -93.3283282
283 -32.0950797 -29.8420866
284 -98.9642735 -32.0950797
285 313.0109340 -98.9642735
286 103.9287812 313.0109340
287 52.5328211 103.9287812
288 -10.2008801 52.5328211
289 NA -10.2008801
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -151.5664679 83.8321273
[2,] -102.2296174 -151.5664679
[3,] -317.0486022 -102.2296174
[4,] 63.0431868 -317.0486022
[5,] 26.5248295 63.0431868
[6,] -418.2880012 26.5248295
[7,] 83.2140133 -418.2880012
[8,] 18.2982604 83.2140133
[9,] -8.2174239 18.2982604
[10,] 120.4569203 -8.2174239
[11,] -114.6835847 120.4569203
[12,] -80.9013069 -114.6835847
[13,] -58.1222342 -80.9013069
[14,] -139.1900986 -58.1222342
[15,] -26.3866165 -139.1900986
[16,] 268.9351931 -26.3866165
[17,] -19.9000639 268.9351931
[18,] -206.4279477 -19.9000639
[19,] -59.1615873 -206.4279477
[20,] 115.9693560 -59.1615873
[21,] 164.3903029 115.9693560
[22,] -206.0733717 164.3903029
[23,] 92.5465260 -206.0733717
[24,] -22.4775311 92.5465260
[25,] -28.6993991 -22.4775311
[26,] 82.4443540 -28.6993991
[27,] -74.4410306 82.4443540
[28,] 53.9830923 -74.4410306
[29,] 41.5201821 53.9830923
[30,] -137.2108595 41.5201821
[31,] -60.2784230 -137.2108595
[32,] 30.1829823 -60.2784230
[33,] -153.9710055 30.1829823
[34,] -5.4592529 -153.9710055
[35,] -54.6790958 -5.4592529
[36,] -13.6476329 -54.6790958
[37,] -80.8206268 -13.6476329
[38,] 212.3093998 -80.8206268
[39,] -69.9534779 212.3093998
[40,] 79.7710030 -69.9534779
[41,] 195.4468977 79.7710030
[42,] 217.0141317 195.4468977
[43,] 8.0586955 217.0141317
[44,] -248.4499517 8.0586955
[45,] -179.9816864 -248.4499517
[46,] 263.5007372 -179.9816864
[47,] -100.5489320 263.5007372
[48,] 210.4398703 -100.5489320
[49,] -50.0813983 210.4398703
[50,] -305.4038708 -50.0813983
[51,] 21.8290240 -305.4038708
[52,] 194.8183124 21.8290240
[53,] 269.7451267 194.8183124
[54,] -131.8099312 269.7451267
[55,] 118.4208874 -131.8099312
[56,] 77.5249670 118.4208874
[57,] -502.2899358 77.5249670
[58,] 109.9838950 -502.2899358
[59,] -36.9512076 109.9838950
[60,] 255.8977468 -36.9512076
[61,] 332.3282021 255.8977468
[62,] 1056.5048136 332.3282021
[63,] -46.0941245 1056.5048136
[64,] 237.0507713 -46.0941245
[65,] -276.0389192 237.0507713
[66,] -91.9046952 -276.0389192
[67,] 211.6684849 -91.9046952
[68,] -14.4366164 211.6684849
[69,] -115.4155686 -14.4366164
[70,] 102.3052318 -115.4155686
[71,] -104.9862721 102.3052318
[72,] 231.9175064 -104.9862721
[73,] 15.9694431 231.9175064
[74,] 152.8882102 15.9694431
[75,] -67.3717252 152.8882102
[76,] -156.0900964 -67.3717252
[77,] 90.8479043 -156.0900964
[78,] -74.4139837 90.8479043
[79,] 103.7263795 -74.4139837
[80,] -192.5275215 103.7263795
[81,] 14.6459797 -192.5275215
[82,] -340.1275640 14.6459797
[83,] -139.3492702 -340.1275640
[84,] -34.5592940 -139.3492702
[85,] 108.3332807 -34.5592940
[86,] -19.5559881 108.3332807
[87,] 165.6098858 -19.5559881
[88,] 281.8143632 165.6098858
[89,] -255.6327457 281.8143632
[90,] 131.2881610 -255.6327457
[91,] -122.0894445 131.2881610
[92,] -53.1485500 -122.0894445
[93,] 75.2445397 -53.1485500
[94,] -8.8372122 75.2445397
[95,] -136.6558947 -8.8372122
[96,] 40.5891234 -136.6558947
[97,] 179.1164651 40.5891234
[98,] 134.1162368 179.1164651
[99,] 6.9128758 134.1162368
[100,] 147.5784078 6.9128758
[101,] 171.6889978 147.5784078
[102,] -39.5294339 171.6889978
[103,] 82.0249923 -39.5294339
[104,] 6.7613125 82.0249923
[105,] -144.0874653 6.7613125
[106,] 153.7108737 -144.0874653
[107,] 181.0680023 153.7108737
[108,] -79.3588626 181.0680023
[109,] 17.1764669 -79.3588626
[110,] -68.3602775 17.1764669
[111,] -122.5106767 -68.3602775
[112,] 70.4922217 -122.5106767
[113,] 148.7148679 70.4922217
[114,] -90.0910153 148.7148679
[115,] -140.6433559 -90.0910153
[116,] -91.2508598 -140.6433559
[117,] 108.0633493 -91.2508598
[118,] 26.7348349 108.0633493
[119,] 29.3228287 26.7348349
[120,] 84.0830884 29.3228287
[121,] -103.8972432 84.0830884
[122,] 1.0254872 -103.8972432
[123,] -73.2491503 1.0254872
[124,] 35.1949684 -73.2491503
[125,] -15.8968068 35.1949684
[126,] -88.6258386 -15.8968068
[127,] 151.1911959 -88.6258386
[128,] 66.6451461 151.1911959
[129,] 142.8521840 66.6451461
[130,] 7.2853582 142.8521840
[131,] -3.8330556 7.2853582
[132,] 18.8130563 -3.8330556
[133,] 229.2387838 18.8130563
[134,] 127.4226621 229.2387838
[135,] -182.5629383 127.4226621
[136,] 169.0818250 -182.5629383
[137,] -43.0506567 169.0818250
[138,] -0.4961412 -43.0506567
[139,] 34.0014955 -0.4961412
[140,] -54.1510592 34.0014955
[141,] 126.7085444 -54.1510592
[142,] -80.0816574 126.7085444
[143,] 94.9600876 -80.0816574
[144,] 67.8155376 94.9600876
[145,] 147.5858169 67.8155376
[146,] -45.4866216 147.5858169
[147,] 95.4688480 -45.4866216
[148,] -70.4177945 95.4688480
[149,] 77.0390730 -70.4177945
[150,] -50.7965873 77.0390730
[151,] -65.3058507 -50.7965873
[152,] 46.5397262 -65.3058507
[153,] -307.4366819 46.5397262
[154,] -219.3984489 -307.4366819
[155,] 66.7115454 -219.3984489
[156,] -85.6801298 66.7115454
[157,] -123.3940124 -85.6801298
[158,] 39.4706937 -123.3940124
[159,] -308.8411717 39.4706937
[160,] 206.5357347 -308.8411717
[161,] -15.2971211 206.5357347
[162,] -117.5963841 -15.2971211
[163,] -170.4228851 -117.5963841
[164,] 17.0423113 -170.4228851
[165,] 10.1303234 17.0423113
[166,] -33.7734177 10.1303234
[167,] -15.5254964 -33.7734177
[168,] -58.8682749 -15.5254964
[169,] 55.5526623 -58.8682749
[170,] 11.0417304 55.5526623
[171,] -12.5451924 11.0417304
[172,] 339.3991524 -12.5451924
[173,] 125.9547324 339.3991524
[174,] -232.5743076 125.9547324
[175,] -50.9357501 -232.5743076
[176,] 51.0729352 -50.9357501
[177,] -29.6056441 51.0729352
[178,] 1.6920557 -29.6056441
[179,] -67.2832789 1.6920557
[180,] 24.6981053 -67.2832789
[181,] 43.1152822 24.6981053
[182,] 124.9356846 43.1152822
[183,] 130.0323964 124.9356846
[184,] 63.6122065 130.0323964
[185,] 96.9411193 63.6122065
[186,] -18.5886234 96.9411193
[187,] 106.6048978 -18.5886234
[188,] 199.0795565 106.6048978
[189,] 92.1566563 199.0795565
[190,] 171.4993184 92.1566563
[191,] -188.4428079 171.4993184
[192,] 51.1280958 -188.4428079
[193,] 110.6541866 51.1280958
[194,] -105.0399394 110.6541866
[195,] 29.8672955 -105.0399394
[196,] -121.5271906 29.8672955
[197,] -106.6667396 -121.5271906
[198,] -112.1275700 -106.6667396
[199,] -88.6922144 -112.1275700
[200,] -53.5220491 -88.6922144
[201,] -108.3762207 -53.5220491
[202,] -78.8445625 -108.3762207
[203,] -10.1758529 -78.8445625
[204,] -27.1648358 -10.1758529
[205,] -59.8238055 -27.1648358
[206,] 123.6546568 -59.8238055
[207,] -101.0123997 123.6546568
[208,] -38.2372997 -101.0123997
[209,] -96.9611485 -38.2372997
[210,] 56.7763317 -96.9611485
[211,] 176.6727399 56.7763317
[212,] -39.1579645 176.6727399
[213,] -131.9127519 -39.1579645
[214,] -9.7395274 -131.9127519
[215,] -1.9530383 -9.7395274
[216,] -28.1759505 -1.9530383
[217,] -129.6116842 -28.1759505
[218,] -98.5721917 -129.6116842
[219,] -71.6106024 -98.5721917
[220,] 11.9233969 -71.6106024
[221,] 325.9856349 11.9233969
[222,] 235.3677841 325.9856349
[223,] 21.9355270 235.3677841
[224,] -121.6127589 21.9355270
[225,] 38.5571261 -121.6127589
[226,] -49.7460186 38.5571261
[227,] -134.2581246 -49.7460186
[228,] 79.3716240 -134.2581246
[229,] 246.6886646 79.3716240
[230,] 27.4590835 246.6886646
[231,] 151.4052193 27.4590835
[232,] 50.7036835 151.4052193
[233,] -16.8481931 50.7036835
[234,] -131.4578247 -16.8481931
[235,] -64.8172742 -131.4578247
[236,] -6.6871280 -64.8172742
[237,] -26.1400482 -6.6871280
[238,] -47.1703609 -26.1400482
[239,] -93.3280981 -47.1703609
[240,] 70.1127999 -93.3280981
[241,] 221.3599775 70.1127999
[242,] -44.8038516 221.3599775
[243,] -96.6967642 -44.8038516
[244,] -87.8039809 -96.6967642
[245,] -51.7467809 -87.8039809
[246,] 185.5163650 -51.7467809
[247,] -115.5789273 185.5163650
[248,] -100.6396811 -115.5789273
[249,] -103.6123919 -100.6396811
[250,] -49.6012380 -103.6123919
[251,] -62.5819589 -49.6012380
[252,] -75.1063607 -62.5819589
[253,] -31.5704343 -75.1063607
[254,] -111.5362963 -31.5704343
[255,] -78.1740648 -111.5362963
[256,] -48.8561916 -78.1740648
[257,] -102.6175396 -48.8561916
[258,] -44.3172219 -102.6175396
[259,] -16.8652126 -44.3172219
[260,] -50.6156390 -16.8652126
[261,] -0.6249174 -50.6156390
[262,] 51.7616171 -0.6249174
[263,] 11.2750079 51.7616171
[264,] -87.0978735 11.2750079
[265,] -39.4289420 -87.0978735
[266,] -86.9224258 -39.4289420
[267,] -201.1700929 -86.9224258
[268,] -143.2211000 -201.1700929
[269,] -155.7679509 -143.2211000
[270,] 121.3855094 -155.7679509
[271,] -104.6517004 121.3855094
[272,] 2.1386918 -104.6517004
[273,] -42.8611474 2.1386918
[274,] 24.0842271 -42.8611474
[275,] 0.6311219 24.0842271
[276,] 37.3347495 0.6311219
[277,] -35.6387510 37.3347495
[278,] 65.6074280 -35.6387510
[279,] -75.2381880 65.6074280
[280,] -50.1498243 -75.2381880
[281,] -93.3283282 -50.1498243
[282,] -29.8420866 -93.3283282
[283,] -32.0950797 -29.8420866
[284,] -98.9642735 -32.0950797
[285,] 313.0109340 -98.9642735
[286,] 103.9287812 313.0109340
[287,] 52.5328211 103.9287812
[288,] -10.2008801 52.5328211
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -151.5664679 83.8321273
2 -102.2296174 -151.5664679
3 -317.0486022 -102.2296174
4 63.0431868 -317.0486022
5 26.5248295 63.0431868
6 -418.2880012 26.5248295
7 83.2140133 -418.2880012
8 18.2982604 83.2140133
9 -8.2174239 18.2982604
10 120.4569203 -8.2174239
11 -114.6835847 120.4569203
12 -80.9013069 -114.6835847
13 -58.1222342 -80.9013069
14 -139.1900986 -58.1222342
15 -26.3866165 -139.1900986
16 268.9351931 -26.3866165
17 -19.9000639 268.9351931
18 -206.4279477 -19.9000639
19 -59.1615873 -206.4279477
20 115.9693560 -59.1615873
21 164.3903029 115.9693560
22 -206.0733717 164.3903029
23 92.5465260 -206.0733717
24 -22.4775311 92.5465260
25 -28.6993991 -22.4775311
26 82.4443540 -28.6993991
27 -74.4410306 82.4443540
28 53.9830923 -74.4410306
29 41.5201821 53.9830923
30 -137.2108595 41.5201821
31 -60.2784230 -137.2108595
32 30.1829823 -60.2784230
33 -153.9710055 30.1829823
34 -5.4592529 -153.9710055
35 -54.6790958 -5.4592529
36 -13.6476329 -54.6790958
37 -80.8206268 -13.6476329
38 212.3093998 -80.8206268
39 -69.9534779 212.3093998
40 79.7710030 -69.9534779
41 195.4468977 79.7710030
42 217.0141317 195.4468977
43 8.0586955 217.0141317
44 -248.4499517 8.0586955
45 -179.9816864 -248.4499517
46 263.5007372 -179.9816864
47 -100.5489320 263.5007372
48 210.4398703 -100.5489320
49 -50.0813983 210.4398703
50 -305.4038708 -50.0813983
51 21.8290240 -305.4038708
52 194.8183124 21.8290240
53 269.7451267 194.8183124
54 -131.8099312 269.7451267
55 118.4208874 -131.8099312
56 77.5249670 118.4208874
57 -502.2899358 77.5249670
58 109.9838950 -502.2899358
59 -36.9512076 109.9838950
60 255.8977468 -36.9512076
61 332.3282021 255.8977468
62 1056.5048136 332.3282021
63 -46.0941245 1056.5048136
64 237.0507713 -46.0941245
65 -276.0389192 237.0507713
66 -91.9046952 -276.0389192
67 211.6684849 -91.9046952
68 -14.4366164 211.6684849
69 -115.4155686 -14.4366164
70 102.3052318 -115.4155686
71 -104.9862721 102.3052318
72 231.9175064 -104.9862721
73 15.9694431 231.9175064
74 152.8882102 15.9694431
75 -67.3717252 152.8882102
76 -156.0900964 -67.3717252
77 90.8479043 -156.0900964
78 -74.4139837 90.8479043
79 103.7263795 -74.4139837
80 -192.5275215 103.7263795
81 14.6459797 -192.5275215
82 -340.1275640 14.6459797
83 -139.3492702 -340.1275640
84 -34.5592940 -139.3492702
85 108.3332807 -34.5592940
86 -19.5559881 108.3332807
87 165.6098858 -19.5559881
88 281.8143632 165.6098858
89 -255.6327457 281.8143632
90 131.2881610 -255.6327457
91 -122.0894445 131.2881610
92 -53.1485500 -122.0894445
93 75.2445397 -53.1485500
94 -8.8372122 75.2445397
95 -136.6558947 -8.8372122
96 40.5891234 -136.6558947
97 179.1164651 40.5891234
98 134.1162368 179.1164651
99 6.9128758 134.1162368
100 147.5784078 6.9128758
101 171.6889978 147.5784078
102 -39.5294339 171.6889978
103 82.0249923 -39.5294339
104 6.7613125 82.0249923
105 -144.0874653 6.7613125
106 153.7108737 -144.0874653
107 181.0680023 153.7108737
108 -79.3588626 181.0680023
109 17.1764669 -79.3588626
110 -68.3602775 17.1764669
111 -122.5106767 -68.3602775
112 70.4922217 -122.5106767
113 148.7148679 70.4922217
114 -90.0910153 148.7148679
115 -140.6433559 -90.0910153
116 -91.2508598 -140.6433559
117 108.0633493 -91.2508598
118 26.7348349 108.0633493
119 29.3228287 26.7348349
120 84.0830884 29.3228287
121 -103.8972432 84.0830884
122 1.0254872 -103.8972432
123 -73.2491503 1.0254872
124 35.1949684 -73.2491503
125 -15.8968068 35.1949684
126 -88.6258386 -15.8968068
127 151.1911959 -88.6258386
128 66.6451461 151.1911959
129 142.8521840 66.6451461
130 7.2853582 142.8521840
131 -3.8330556 7.2853582
132 18.8130563 -3.8330556
133 229.2387838 18.8130563
134 127.4226621 229.2387838
135 -182.5629383 127.4226621
136 169.0818250 -182.5629383
137 -43.0506567 169.0818250
138 -0.4961412 -43.0506567
139 34.0014955 -0.4961412
140 -54.1510592 34.0014955
141 126.7085444 -54.1510592
142 -80.0816574 126.7085444
143 94.9600876 -80.0816574
144 67.8155376 94.9600876
145 147.5858169 67.8155376
146 -45.4866216 147.5858169
147 95.4688480 -45.4866216
148 -70.4177945 95.4688480
149 77.0390730 -70.4177945
150 -50.7965873 77.0390730
151 -65.3058507 -50.7965873
152 46.5397262 -65.3058507
153 -307.4366819 46.5397262
154 -219.3984489 -307.4366819
155 66.7115454 -219.3984489
156 -85.6801298 66.7115454
157 -123.3940124 -85.6801298
158 39.4706937 -123.3940124
159 -308.8411717 39.4706937
160 206.5357347 -308.8411717
161 -15.2971211 206.5357347
162 -117.5963841 -15.2971211
163 -170.4228851 -117.5963841
164 17.0423113 -170.4228851
165 10.1303234 17.0423113
166 -33.7734177 10.1303234
167 -15.5254964 -33.7734177
168 -58.8682749 -15.5254964
169 55.5526623 -58.8682749
170 11.0417304 55.5526623
171 -12.5451924 11.0417304
172 339.3991524 -12.5451924
173 125.9547324 339.3991524
174 -232.5743076 125.9547324
175 -50.9357501 -232.5743076
176 51.0729352 -50.9357501
177 -29.6056441 51.0729352
178 1.6920557 -29.6056441
179 -67.2832789 1.6920557
180 24.6981053 -67.2832789
181 43.1152822 24.6981053
182 124.9356846 43.1152822
183 130.0323964 124.9356846
184 63.6122065 130.0323964
185 96.9411193 63.6122065
186 -18.5886234 96.9411193
187 106.6048978 -18.5886234
188 199.0795565 106.6048978
189 92.1566563 199.0795565
190 171.4993184 92.1566563
191 -188.4428079 171.4993184
192 51.1280958 -188.4428079
193 110.6541866 51.1280958
194 -105.0399394 110.6541866
195 29.8672955 -105.0399394
196 -121.5271906 29.8672955
197 -106.6667396 -121.5271906
198 -112.1275700 -106.6667396
199 -88.6922144 -112.1275700
200 -53.5220491 -88.6922144
201 -108.3762207 -53.5220491
202 -78.8445625 -108.3762207
203 -10.1758529 -78.8445625
204 -27.1648358 -10.1758529
205 -59.8238055 -27.1648358
206 123.6546568 -59.8238055
207 -101.0123997 123.6546568
208 -38.2372997 -101.0123997
209 -96.9611485 -38.2372997
210 56.7763317 -96.9611485
211 176.6727399 56.7763317
212 -39.1579645 176.6727399
213 -131.9127519 -39.1579645
214 -9.7395274 -131.9127519
215 -1.9530383 -9.7395274
216 -28.1759505 -1.9530383
217 -129.6116842 -28.1759505
218 -98.5721917 -129.6116842
219 -71.6106024 -98.5721917
220 11.9233969 -71.6106024
221 325.9856349 11.9233969
222 235.3677841 325.9856349
223 21.9355270 235.3677841
224 -121.6127589 21.9355270
225 38.5571261 -121.6127589
226 -49.7460186 38.5571261
227 -134.2581246 -49.7460186
228 79.3716240 -134.2581246
229 246.6886646 79.3716240
230 27.4590835 246.6886646
231 151.4052193 27.4590835
232 50.7036835 151.4052193
233 -16.8481931 50.7036835
234 -131.4578247 -16.8481931
235 -64.8172742 -131.4578247
236 -6.6871280 -64.8172742
237 -26.1400482 -6.6871280
238 -47.1703609 -26.1400482
239 -93.3280981 -47.1703609
240 70.1127999 -93.3280981
241 221.3599775 70.1127999
242 -44.8038516 221.3599775
243 -96.6967642 -44.8038516
244 -87.8039809 -96.6967642
245 -51.7467809 -87.8039809
246 185.5163650 -51.7467809
247 -115.5789273 185.5163650
248 -100.6396811 -115.5789273
249 -103.6123919 -100.6396811
250 -49.6012380 -103.6123919
251 -62.5819589 -49.6012380
252 -75.1063607 -62.5819589
253 -31.5704343 -75.1063607
254 -111.5362963 -31.5704343
255 -78.1740648 -111.5362963
256 -48.8561916 -78.1740648
257 -102.6175396 -48.8561916
258 -44.3172219 -102.6175396
259 -16.8652126 -44.3172219
260 -50.6156390 -16.8652126
261 -0.6249174 -50.6156390
262 51.7616171 -0.6249174
263 11.2750079 51.7616171
264 -87.0978735 11.2750079
265 -39.4289420 -87.0978735
266 -86.9224258 -39.4289420
267 -201.1700929 -86.9224258
268 -143.2211000 -201.1700929
269 -155.7679509 -143.2211000
270 121.3855094 -155.7679509
271 -104.6517004 121.3855094
272 2.1386918 -104.6517004
273 -42.8611474 2.1386918
274 24.0842271 -42.8611474
275 0.6311219 24.0842271
276 37.3347495 0.6311219
277 -35.6387510 37.3347495
278 65.6074280 -35.6387510
279 -75.2381880 65.6074280
280 -50.1498243 -75.2381880
281 -93.3283282 -50.1498243
282 -29.8420866 -93.3283282
283 -32.0950797 -29.8420866
284 -98.9642735 -32.0950797
285 313.0109340 -98.9642735
286 103.9287812 313.0109340
287 52.5328211 103.9287812
288 -10.2008801 52.5328211
> 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/700bh1323962018.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/86smg1323962018.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9o18q1323962018.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10gl4a1323962018.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11q4n31323962018.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/1284s01323962018.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/13jvk41323962018.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/14miwn1323962018.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/15i84p1323962018.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/161q6p1323962018.tab")
+ }
>
> try(system("convert tmp/19wfr1323962018.ps tmp/19wfr1323962018.png",intern=TRUE))
character(0)
> try(system("convert tmp/21ede1323962018.ps tmp/21ede1323962018.png",intern=TRUE))
character(0)
> try(system("convert tmp/3t40d1323962018.ps tmp/3t40d1323962018.png",intern=TRUE))
character(0)
> try(system("convert tmp/4d4go1323962018.ps tmp/4d4go1323962018.png",intern=TRUE))
character(0)
> try(system("convert tmp/5re3k1323962018.ps tmp/5re3k1323962018.png",intern=TRUE))
character(0)
> try(system("convert tmp/6lqxs1323962018.ps tmp/6lqxs1323962018.png",intern=TRUE))
character(0)
> try(system("convert tmp/700bh1323962018.ps tmp/700bh1323962018.png",intern=TRUE))
character(0)
> try(system("convert tmp/86smg1323962018.ps tmp/86smg1323962018.png",intern=TRUE))
character(0)
> try(system("convert tmp/9o18q1323962018.ps tmp/9o18q1323962018.png",intern=TRUE))
character(0)
> try(system("convert tmp/10gl4a1323962018.ps tmp/10gl4a1323962018.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
10.861 0.690 11.682