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)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(305687
+ ,3615
+ ,93
+ ,1415
+ ,2
+ ,26
+ ,86997
+ ,305115
+ ,2637
+ ,78
+ ,1264
+ ,0
+ ,20
+ ,91256
+ ,280379
+ ,1883
+ ,55
+ ,809
+ ,1
+ ,25
+ ,55709
+ ,280039
+ ,2900
+ ,113
+ ,1008
+ ,4
+ ,29
+ ,92046
+ ,274949
+ ,2460
+ ,65
+ ,846
+ ,0
+ ,30
+ ,75741
+ ,264528
+ ,2057
+ ,83
+ ,749
+ ,0
+ ,30
+ ,59635
+ ,257662
+ ,1736
+ ,198
+ ,591
+ ,7
+ ,31
+ ,84607
+ ,254599
+ ,2145
+ ,71
+ ,799
+ ,3
+ ,35
+ ,162365
+ ,253056
+ ,2597
+ ,85
+ ,1170
+ ,0
+ ,27
+ ,104911
+ ,245478
+ ,3018
+ ,119
+ ,1120
+ ,0
+ ,35
+ ,70817
+ ,245107
+ ,2367
+ ,86
+ ,824
+ ,6
+ ,31
+ ,109104
+ ,244909
+ ,2692
+ ,79
+ ,1100
+ ,9
+ ,21
+ ,73586
+ ,243180
+ ,2193
+ ,71
+ ,904
+ ,8
+ ,22
+ ,120087
+ ,242153
+ ,2207
+ ,49
+ ,1013
+ ,2
+ ,31
+ ,72631
+ ,236316
+ ,1836
+ ,63
+ ,786
+ ,1
+ ,22
+ ,58233
+ ,234863
+ ,1912
+ ,55
+ ,798
+ ,1
+ ,27
+ ,85224
+ ,220835
+ ,2310
+ ,106
+ ,904
+ ,1
+ ,23
+ ,67271
+ ,213487
+ ,2703
+ ,67
+ ,1008
+ ,6
+ ,26
+ ,117986
+ ,213310
+ ,2144
+ ,54
+ ,1040
+ ,8
+ ,22
+ ,55071
+ ,209631
+ ,2000
+ ,107
+ ,767
+ ,2
+ ,24
+ ,63717
+ ,208823
+ ,1633
+ ,74
+ ,682
+ ,0
+ ,26
+ ,81493
+ ,201748
+ ,1565
+ ,65
+ ,569
+ ,0
+ ,33
+ ,86281
+ ,201603
+ ,2219
+ ,92
+ ,709
+ ,7
+ ,40
+ ,83038
+ ,201409
+ ,2156
+ ,75
+ ,806
+ ,6
+ ,21
+ ,114425
+ ,197067
+ ,2451
+ ,113
+ ,751
+ ,5
+ ,24
+ ,101653
+ ,197033
+ ,1740
+ ,68
+ ,563
+ ,7
+ ,30
+ ,63958
+ ,193662
+ ,1541
+ ,47
+ ,601
+ ,0
+ ,33
+ ,65196
+ ,192887
+ ,1701
+ ,41
+ ,690
+ ,3
+ ,36
+ ,62932
+ ,191467
+ ,1416
+ ,55
+ ,611
+ ,3
+ ,20
+ ,79194
+ ,190729
+ ,1313
+ ,61
+ ,506
+ ,1
+ ,30
+ ,64664
+ ,189764
+ ,1474
+ ,54
+ ,555
+ ,0
+ ,24
+ ,123328
+ ,189066
+ ,1328
+ ,44
+ ,601
+ ,3
+ ,25
+ ,72369
+ ,187289
+ ,1543
+ ,37
+ ,566
+ ,0
+ ,30
+ ,54628
+ ,185366
+ ,1557
+ ,67
+ ,537
+ ,1
+ ,29
+ ,111436
+ ,185288
+ ,1717
+ ,71
+ ,582
+ ,1
+ ,27
+ ,38885
+ ,185279
+ ,1809
+ ,100
+ ,730
+ ,3
+ ,22
+ ,73795
+ ,183260
+ ,1793
+ ,190
+ ,600
+ ,4
+ ,24
+ ,70111
+ ,183059
+ ,2061
+ ,73
+ ,740
+ ,1
+ ,23
+ ,57637
+ ,182557
+ ,1589
+ ,40
+ ,603
+ ,0
+ ,26
+ ,103646
+ ,181853
+ ,1458
+ ,52
+ ,572
+ ,3
+ ,25
+ ,96750
+ ,179571
+ ,1792
+ ,57
+ ,476
+ ,5
+ ,35
+ ,101773
+ ,176577
+ ,1354
+ ,50
+ ,555
+ ,4
+ ,20
+ ,76168
+ ,175663
+ ,1583
+ ,62
+ ,608
+ ,0
+ ,24
+ ,74482
+ ,173587
+ ,1612
+ ,27
+ ,654
+ ,1
+ ,20
+ ,71170
+ ,173260
+ ,2035
+ ,63
+ ,716
+ ,3
+ ,21
+ ,37238
+ ,170635
+ ,1637
+ ,59
+ ,584
+ ,6
+ ,26
+ ,70027
+ ,170588
+ ,1167
+ ,46
+ ,333
+ ,2
+ ,26
+ ,95556
+ ,169613
+ ,1970
+ ,51
+ ,735
+ ,1
+ ,24
+ ,48204
+ ,169569
+ ,1285
+ ,42
+ ,472
+ ,4
+ ,20
+ ,105965
+ ,169093
+ ,1445
+ ,35
+ ,585
+ ,5
+ ,17
+ ,85903
+ ,168059
+ ,1109
+ ,33
+ ,391
+ ,0
+ ,26
+ ,60029
+ ,167255
+ ,1557
+ ,37
+ ,669
+ ,0
+ ,25
+ ,37048
+ ,167226
+ ,1358
+ ,53
+ ,531
+ ,0
+ ,30
+ ,43460
+ ,166142
+ ,1191
+ ,40
+ ,393
+ ,4
+ ,23
+ ,90257
+ ,161729
+ ,1772
+ ,79
+ ,690
+ ,4
+ ,21
+ ,65911
+ ,160905
+ ,1285
+ ,54
+ ,387
+ ,0
+ ,27
+ ,56316
+ ,157566
+ ,1566
+ ,54
+ ,472
+ ,0
+ ,30
+ ,61704
+ ,156990
+ ,1339
+ ,62
+ ,512
+ ,0
+ ,26
+ ,52295
+ ,155012
+ ,1593
+ ,49
+ ,472
+ ,5
+ ,28
+ ,74349
+ ,154730
+ ,1297
+ ,45
+ ,423
+ ,0
+ ,27
+ ,82204
+ ,152366
+ ,1281
+ ,54
+ ,446
+ ,0
+ ,24
+ ,83042
+ ,152193
+ ,1356
+ ,49
+ ,450
+ ,2
+ ,25
+ ,76013
+ ,148857
+ ,1263
+ ,61
+ ,411
+ ,6
+ ,31
+ ,91939
+ ,145908
+ ,1143
+ ,37
+ ,527
+ ,2
+ ,24
+ ,65724
+ ,145120
+ ,1850
+ ,89
+ ,703
+ ,0
+ ,24
+ ,56699
+ ,144530
+ ,1787
+ ,72
+ ,833
+ ,2
+ ,25
+ ,79774
+ ,143937
+ ,1407
+ ,48
+ ,546
+ ,2
+ ,20
+ ,68608
+ ,142339
+ ,1145
+ ,29
+ ,397
+ ,2
+ ,20
+ ,125410
+ ,142286
+ ,1899
+ ,99
+ ,627
+ ,8
+ ,28
+ ,57231
+ ,141933
+ ,1323
+ ,55
+ ,427
+ ,0
+ ,27
+ ,51370
+ ,141150
+ ,1569
+ ,60
+ ,684
+ ,5
+ ,31
+ ,36311
+ ,139409
+ ,1667
+ ,49
+ ,678
+ ,2
+ ,24
+ ,99518
+ ,139144
+ ,828
+ ,23
+ ,344
+ ,0
+ ,21
+ ,56530
+ ,137544
+ ,1128
+ ,35
+ ,388
+ ,7
+ ,31
+ ,94137
+ ,135306
+ ,1233
+ ,28
+ ,571
+ ,0
+ ,22
+ ,71181
+ ,134088
+ ,1192
+ ,50
+ ,453
+ ,9
+ ,20
+ ,55901
+ ,132798
+ ,1176
+ ,53
+ ,570
+ ,5
+ ,22
+ ,38417
+ ,131337
+ ,1110
+ ,45
+ ,439
+ ,3
+ ,20
+ ,54506
+ ,131108
+ ,1496
+ ,39
+ ,646
+ ,3
+ ,30
+ ,56733
+ ,130539
+ ,1158
+ ,24
+ ,420
+ ,0
+ ,20
+ ,48821
+ ,130533
+ ,1030
+ ,27
+ ,387
+ ,0
+ ,20
+ ,85168
+ ,130413
+ ,1935
+ ,75
+ ,756
+ ,0
+ ,24
+ ,55027
+ ,129796
+ ,1154
+ ,55
+ ,385
+ ,4
+ ,28
+ ,38439
+ ,129340
+ ,1213
+ ,47
+ ,392
+ ,4
+ ,33
+ ,53009
+ ,129100
+ ,897
+ ,37
+ ,363
+ ,2
+ ,19
+ ,73713
+ ,128873
+ ,1275
+ ,56
+ ,447
+ ,2
+ ,20
+ ,42564
+ ,128768
+ ,1405
+ ,50
+ ,503
+ ,1
+ ,26
+ ,38650
+ ,128734
+ ,1107
+ ,53
+ ,342
+ ,0
+ ,18
+ ,55064
+ ,128274
+ ,1155
+ ,74
+ ,358
+ ,7
+ ,37
+ ,63262
+ ,128075
+ ,1223
+ ,56
+ ,329
+ ,2
+ ,25
+ ,64102
+ ,127930
+ ,1171
+ ,91
+ ,441
+ ,0
+ ,21
+ ,66477
+ ,127394
+ ,1372
+ ,44
+ ,504
+ ,4
+ ,15
+ ,34497
+ ,127185
+ ,800
+ ,38
+ ,286
+ ,0
+ ,33
+ ,73087
+ ,126630
+ ,1310
+ ,44
+ ,449
+ ,5
+ ,25
+ ,58425
+ ,125927
+ ,1264
+ ,53
+ ,474
+ ,0
+ ,24
+ ,51360
+ ,121976
+ ,1105
+ ,48
+ ,366
+ ,2
+ ,20
+ ,42051
+ ,121630
+ ,1108
+ ,47
+ ,420
+ ,1
+ ,21
+ ,28340
+ ,120362
+ ,1113
+ ,42
+ ,438
+ ,0
+ ,25
+ ,49319
+ ,118807
+ ,1348
+ ,33
+ ,468
+ ,11
+ ,25
+ ,55827
+ ,117805
+ ,1978
+ ,70
+ ,727
+ ,1
+ ,27
+ ,99501
+ ,115911
+ ,1025
+ ,40
+ ,445
+ ,5
+ ,25
+ ,40001
+ ,115885
+ ,1355
+ ,36
+ ,575
+ ,5
+ ,19
+ ,77411
+ ,113450
+ ,1253
+ ,85
+ ,413
+ ,4
+ ,19
+ ,89041
+ ,113337
+ ,1053
+ ,37
+ ,371
+ ,9
+ ,24
+ ,63016
+ ,112004
+ ,1196
+ ,42
+ ,403
+ ,4
+ ,21
+ ,37361
+ ,109237
+ ,1473
+ ,39
+ ,641
+ ,0
+ ,21
+ ,15430
+ ,108715
+ ,1075
+ ,32
+ ,304
+ ,0
+ ,15
+ ,40671
+ ,107434
+ ,853
+ ,35
+ ,320
+ ,0
+ ,19
+ ,82043
+ ,106888
+ ,1035
+ ,34
+ ,406
+ ,0
+ ,21
+ ,26982
+ ,106351
+ ,995
+ ,108
+ ,341
+ ,0
+ ,20
+ ,29467
+ ,106193
+ ,956
+ ,58
+ ,271
+ ,6
+ ,23
+ ,202316
+ ,105477
+ ,1020
+ ,33
+ ,341
+ ,2
+ ,16
+ ,49288
+ ,102350
+ ,1119
+ ,43
+ ,435
+ ,6
+ ,23
+ ,50466
+ ,101324
+ ,860
+ ,31
+ ,297
+ ,5
+ ,26
+ ,70780
+ ,98791
+ ,1209
+ ,30
+ ,447
+ ,1
+ ,18
+ ,36252
+ ,98466
+ ,1277
+ ,47
+ ,495
+ ,4
+ ,24
+ ,43448
+ ,98066
+ ,1101
+ ,58
+ ,434
+ ,3
+ ,14
+ ,31701
+ ,96981
+ ,983
+ ,33
+ ,334
+ ,0
+ ,22
+ ,56979
+ ,96634
+ ,810
+ ,35
+ ,242
+ ,5
+ ,22
+ ,72571
+ ,93125
+ ,1735
+ ,49
+ ,836
+ ,1
+ ,21
+ ,50838
+ ,91185
+ ,973
+ ,31
+ ,287
+ ,0
+ ,27
+ ,21067
+ ,90961
+ ,901
+ ,25
+ ,298
+ ,1
+ ,22
+ ,63785
+ ,90938
+ ,767
+ ,17
+ ,262
+ ,3
+ ,15
+ ,37137
+ ,89882
+ ,993
+ ,34
+ ,382
+ ,5
+ ,17
+ ,59155
+ ,89318
+ ,911
+ ,36
+ ,292
+ ,1
+ ,22
+ ,44970
+ ,89059
+ ,1069
+ ,64
+ ,345
+ ,0
+ ,20
+ ,46765
+ ,86621
+ ,669
+ ,48
+ ,223
+ ,4
+ ,20
+ ,54565
+ ,81530
+ ,668
+ ,30
+ ,178
+ ,1
+ ,15
+ ,31258
+ ,81106
+ ,1020
+ ,31
+ ,300
+ ,4
+ ,21
+ ,35838
+ ,80964
+ ,686
+ ,26
+ ,216
+ ,1
+ ,8
+ ,26998
+ ,80953
+ ,870
+ ,25
+ ,437
+ ,0
+ ,8
+ ,56622
+ ,78800
+ ,918
+ ,42
+ ,330
+ ,2
+ ,26
+ ,33032
+ ,76470
+ ,809
+ ,29
+ ,312
+ ,0
+ ,20
+ ,35606
+ ,75746
+ ,672
+ ,72
+ ,238
+ ,0
+ ,12
+ ,47261
+ ,75032
+ ,777
+ ,45
+ ,240
+ ,5
+ ,23
+ ,62147
+ ,74112
+ ,668
+ ,32
+ ,215
+ ,0
+ ,19
+ ,174949
+ ,73567
+ ,705
+ ,27
+ ,187
+ ,0
+ ,23
+ ,23238
+ ,71908
+ ,938
+ ,28
+ ,349
+ ,2
+ ,17
+ ,62832
+ ,69471
+ ,837
+ ,28
+ ,364
+ ,6
+ ,20
+ ,22618
+ ,67507
+ ,1101
+ ,39
+ ,368
+ ,5
+ ,32
+ ,78956
+ ,65029
+ ,744
+ ,17
+ ,255
+ ,5
+ ,18
+ ,32551
+ ,62731
+ ,547
+ ,25
+ ,168
+ ,4
+ ,20
+ ,36990
+ ,61857
+ ,530
+ ,25
+ ,192
+ ,4
+ ,11
+ ,25162
+ ,50999
+ ,588
+ ,15
+ ,225
+ ,8
+ ,20
+ ,63989
+ ,46660
+ ,474
+ ,20
+ ,259
+ ,0
+ ,5
+ ,6179
+ ,43287
+ ,602
+ ,14
+ ,214
+ ,4
+ ,19
+ ,43750
+ ,38214
+ ,568
+ ,34
+ ,276
+ ,0
+ ,8
+ ,8773
+ ,35523
+ ,308
+ ,17
+ ,106
+ ,2
+ ,16
+ ,52491
+ ,32750
+ ,345
+ ,16
+ ,102
+ ,0
+ ,18
+ ,22807
+ ,31414
+ ,449
+ ,19
+ ,200
+ ,0
+ ,8
+ ,14116
+ ,24188
+ ,496
+ ,24
+ ,218
+ ,0
+ ,4
+ ,5950
+ ,22938
+ ,391
+ ,10
+ ,154
+ ,0
+ ,1
+ ,1168
+ ,21054
+ ,387
+ ,16
+ ,146
+ ,0
+ ,0
+ ,855
+ ,17547
+ ,141
+ ,5
+ ,69
+ ,0
+ ,1
+ ,3926
+ ,14688
+ ,207
+ ,10
+ ,85
+ ,0
+ ,0
+ ,6023
+ ,7199
+ ,151
+ ,5
+ ,74
+ ,0
+ ,0
+ ,1644
+ ,969
+ ,29
+ ,2
+ ,0
+ ,0
+ ,0
+ ,0
+ ,455
+ ,8
+ ,2
+ ,0
+ ,0
+ ,0
+ ,0
+ ,203
+ ,4
+ ,4
+ ,0
+ ,0
+ ,0
+ ,0
+ ,98
+ ,5
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,9
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0)
+ ,dim=c(7
+ ,164)
+ ,dimnames=list(c('Time_RFC'
+ ,'#_pageviews'
+ ,'Logins'
+ ,'Compendiums_views'
+ ,'shared_compendiums'
+ ,'reviewed_compendiums'
+ ,'Compendium_writing')
+ ,1:164))
> y <- array(NA,dim=c(7,164),dimnames=list(c('Time_RFC','#_pageviews','Logins','Compendiums_views','shared_compendiums','reviewed_compendiums','Compendium_writing'),1:164))
> 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'
> 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
Time_RFC #_pageviews Logins Compendiums_views shared_compendiums
1 305687 3615 93 1415 2
2 305115 2637 78 1264 0
3 280379 1883 55 809 1
4 280039 2900 113 1008 4
5 274949 2460 65 846 0
6 264528 2057 83 749 0
7 257662 1736 198 591 7
8 254599 2145 71 799 3
9 253056 2597 85 1170 0
10 245478 3018 119 1120 0
11 245107 2367 86 824 6
12 244909 2692 79 1100 9
13 243180 2193 71 904 8
14 242153 2207 49 1013 2
15 236316 1836 63 786 1
16 234863 1912 55 798 1
17 220835 2310 106 904 1
18 213487 2703 67 1008 6
19 213310 2144 54 1040 8
20 209631 2000 107 767 2
21 208823 1633 74 682 0
22 201748 1565 65 569 0
23 201603 2219 92 709 7
24 201409 2156 75 806 6
25 197067 2451 113 751 5
26 197033 1740 68 563 7
27 193662 1541 47 601 0
28 192887 1701 41 690 3
29 191467 1416 55 611 3
30 190729 1313 61 506 1
31 189764 1474 54 555 0
32 189066 1328 44 601 3
33 187289 1543 37 566 0
34 185366 1557 67 537 1
35 185288 1717 71 582 1
36 185279 1809 100 730 3
37 183260 1793 190 600 4
38 183059 2061 73 740 1
39 182557 1589 40 603 0
40 181853 1458 52 572 3
41 179571 1792 57 476 5
42 176577 1354 50 555 4
43 175663 1583 62 608 0
44 173587 1612 27 654 1
45 173260 2035 63 716 3
46 170635 1637 59 584 6
47 170588 1167 46 333 2
48 169613 1970 51 735 1
49 169569 1285 42 472 4
50 169093 1445 35 585 5
51 168059 1109 33 391 0
52 167255 1557 37 669 0
53 167226 1358 53 531 0
54 166142 1191 40 393 4
55 161729 1772 79 690 4
56 160905 1285 54 387 0
57 157566 1566 54 472 0
58 156990 1339 62 512 0
59 155012 1593 49 472 5
60 154730 1297 45 423 0
61 152366 1281 54 446 0
62 152193 1356 49 450 2
63 148857 1263 61 411 6
64 145908 1143 37 527 2
65 145120 1850 89 703 0
66 144530 1787 72 833 2
67 143937 1407 48 546 2
68 142339 1145 29 397 2
69 142286 1899 99 627 8
70 141933 1323 55 427 0
71 141150 1569 60 684 5
72 139409 1667 49 678 2
73 139144 828 23 344 0
74 137544 1128 35 388 7
75 135306 1233 28 571 0
76 134088 1192 50 453 9
77 132798 1176 53 570 5
78 131337 1110 45 439 3
79 131108 1496 39 646 3
80 130539 1158 24 420 0
81 130533 1030 27 387 0
82 130413 1935 75 756 0
83 129796 1154 55 385 4
84 129340 1213 47 392 4
85 129100 897 37 363 2
86 128873 1275 56 447 2
87 128768 1405 50 503 1
88 128734 1107 53 342 0
89 128274 1155 74 358 7
90 128075 1223 56 329 2
91 127930 1171 91 441 0
92 127394 1372 44 504 4
93 127185 800 38 286 0
94 126630 1310 44 449 5
95 125927 1264 53 474 0
96 121976 1105 48 366 2
97 121630 1108 47 420 1
98 120362 1113 42 438 0
99 118807 1348 33 468 11
100 117805 1978 70 727 1
101 115911 1025 40 445 5
102 115885 1355 36 575 5
103 113450 1253 85 413 4
104 113337 1053 37 371 9
105 112004 1196 42 403 4
106 109237 1473 39 641 0
107 108715 1075 32 304 0
108 107434 853 35 320 0
109 106888 1035 34 406 0
110 106351 995 108 341 0
111 106193 956 58 271 6
112 105477 1020 33 341 2
113 102350 1119 43 435 6
114 101324 860 31 297 5
115 98791 1209 30 447 1
116 98466 1277 47 495 4
117 98066 1101 58 434 3
118 96981 983 33 334 0
119 96634 810 35 242 5
120 93125 1735 49 836 1
121 91185 973 31 287 0
122 90961 901 25 298 1
123 90938 767 17 262 3
124 89882 993 34 382 5
125 89318 911 36 292 1
126 89059 1069 64 345 0
127 86621 669 48 223 4
128 81530 668 30 178 1
129 81106 1020 31 300 4
130 80964 686 26 216 1
131 80953 870 25 437 0
132 78800 918 42 330 2
133 76470 809 29 312 0
134 75746 672 72 238 0
135 75032 777 45 240 5
136 74112 668 32 215 0
137 73567 705 27 187 0
138 71908 938 28 349 2
139 69471 837 28 364 6
140 67507 1101 39 368 5
141 65029 744 17 255 5
142 62731 547 25 168 4
143 61857 530 25 192 4
144 50999 588 15 225 8
145 46660 474 20 259 0
146 43287 602 14 214 4
147 38214 568 34 276 0
148 35523 308 17 106 2
149 32750 345 16 102 0
150 31414 449 19 200 0
151 24188 496 24 218 0
152 22938 391 10 154 0
153 21054 387 16 146 0
154 17547 141 5 69 0
155 14688 207 10 85 0
156 7199 151 5 74 0
157 969 29 2 0 0
158 455 8 2 0 0
159 203 4 4 0 0
160 98 5 1 0 0
161 0 0 0 0 9
162 0 0 0 0 1
163 0 0 0 0 0
164 0 0 0 0 0
reviewed_compendiums Compendium_writing
1 26 86997
2 20 91256
3 25 55709
4 29 92046
5 30 75741
6 30 59635
7 31 84607
8 35 162365
9 27 104911
10 35 70817
11 31 109104
12 21 73586
13 22 120087
14 31 72631
15 22 58233
16 27 85224
17 23 67271
18 26 117986
19 22 55071
20 24 63717
21 26 81493
22 33 86281
23 40 83038
24 21 114425
25 24 101653
26 30 63958
27 33 65196
28 36 62932
29 20 79194
30 30 64664
31 24 123328
32 25 72369
33 30 54628
34 29 111436
35 27 38885
36 22 73795
37 24 70111
38 23 57637
39 26 103646
40 25 96750
41 35 101773
42 20 76168
43 24 74482
44 20 71170
45 21 37238
46 26 70027
47 26 95556
48 24 48204
49 20 105965
50 17 85903
51 26 60029
52 25 37048
53 30 43460
54 23 90257
55 21 65911
56 27 56316
57 30 61704
58 26 52295
59 28 74349
60 27 82204
61 24 83042
62 25 76013
63 31 91939
64 24 65724
65 24 56699
66 25 79774
67 20 68608
68 20 125410
69 28 57231
70 27 51370
71 31 36311
72 24 99518
73 21 56530
74 31 94137
75 22 71181
76 20 55901
77 22 38417
78 20 54506
79 30 56733
80 20 48821
81 20 85168
82 24 55027
83 28 38439
84 33 53009
85 19 73713
86 20 42564
87 26 38650
88 18 55064
89 37 63262
90 25 64102
91 21 66477
92 15 34497
93 33 73087
94 25 58425
95 24 51360
96 20 42051
97 21 28340
98 25 49319
99 25 55827
100 27 99501
101 25 40001
102 19 77411
103 19 89041
104 24 63016
105 21 37361
106 21 15430
107 15 40671
108 19 82043
109 21 26982
110 20 29467
111 23 202316
112 16 49288
113 23 50466
114 26 70780
115 18 36252
116 24 43448
117 14 31701
118 22 56979
119 22 72571
120 21 50838
121 27 21067
122 22 63785
123 15 37137
124 17 59155
125 22 44970
126 20 46765
127 20 54565
128 15 31258
129 21 35838
130 8 26998
131 8 56622
132 26 33032
133 20 35606
134 12 47261
135 23 62147
136 19 174949
137 23 23238
138 17 62832
139 20 22618
140 32 78956
141 18 32551
142 20 36990
143 11 25162
144 20 63989
145 5 6179
146 19 43750
147 8 8773
148 16 52491
149 18 22807
150 8 14116
151 4 5950
152 1 1168
153 0 855
154 1 3926
155 0 6023
156 0 1644
157 0 0
158 0 0
159 0 0
160 0 0
161 0 0
162 0 0
163 0 0
164 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `#_pageviews` Logins
-5725.0197 37.3450 173.3665
Compendiums_views shared_compendiums reviewed_compendiums
85.1895 -1771.3956 1378.2515
Compendium_writing
0.2814
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-87853 -13660 1948 11359 88966
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -5.725e+03 5.397e+03 -1.061 0.290398
`#_pageviews` 3.734e+01 1.520e+01 2.457 0.015092 *
Logins 1.734e+02 1.002e+02 1.730 0.085615 .
Compendiums_views 8.519e+01 3.166e+01 2.691 0.007897 **
shared_compendiums -1.771e+03 7.782e+02 -2.276 0.024182 *
reviewed_compendiums 1.378e+03 3.503e+02 3.935 0.000125 ***
Compendium_writing 2.814e-01 7.646e-02 3.681 0.000319 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 24980 on 157 degrees of freedom
Multiple R-squared: 0.8711, Adjusted R-squared: 0.8662
F-statistic: 176.8 on 6 and 157 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,] 0.1560440 3.120880e-01 8.439560e-01
[2,] 0.1949850 3.899700e-01 8.050150e-01
[3,] 0.1736924 3.473848e-01 8.263076e-01
[4,] 0.2091914 4.183827e-01 7.908086e-01
[5,] 0.2130486 4.260972e-01 7.869514e-01
[6,] 0.4614724 9.229447e-01 5.385276e-01
[7,] 0.4559252 9.118505e-01 5.440748e-01
[8,] 0.7867378 4.265244e-01 2.132622e-01
[9,] 0.8786086 2.427828e-01 1.213914e-01
[10,] 0.8587827 2.824346e-01 1.412173e-01
[11,] 0.9170069 1.659862e-01 8.299312e-02
[12,] 0.9327990 1.344020e-01 6.720099e-02
[13,] 0.9334509 1.330982e-01 6.654908e-02
[14,] 0.9200105 1.599791e-01 7.998955e-02
[15,] 0.9292502 1.414995e-01 7.074977e-02
[16,] 0.9419272 1.161456e-01 5.807282e-02
[17,] 0.9270772 1.458457e-01 7.292283e-02
[18,] 0.9247073 1.505854e-01 7.529268e-02
[19,] 0.9127083 1.745834e-01 8.729170e-02
[20,] 0.9155755 1.688489e-01 8.442445e-02
[21,] 0.9132928 1.734144e-01 8.670719e-02
[22,] 0.9037321 1.925358e-01 9.626790e-02
[23,] 0.9105946 1.788108e-01 8.940542e-02
[24,] 0.8989551 2.020897e-01 1.010449e-01
[25,] 0.8851487 2.297027e-01 1.148513e-01
[26,] 0.8754358 2.491283e-01 1.245642e-01
[27,] 0.9044986 1.910029e-01 9.550144e-02
[28,] 0.9252015 1.495970e-01 7.479850e-02
[29,] 0.9276971 1.446059e-01 7.230293e-02
[30,] 0.9172695 1.654610e-01 8.273052e-02
[31,] 0.9099532 1.800935e-01 9.004675e-02
[32,] 0.8873862 2.252276e-01 1.126138e-01
[33,] 0.8975794 2.048412e-01 1.024206e-01
[34,] 0.8951220 2.097561e-01 1.048780e-01
[35,] 0.8858867 2.282266e-01 1.141133e-01
[36,] 0.8708533 2.582934e-01 1.291467e-01
[37,] 0.8532350 2.935299e-01 1.467650e-01
[38,] 0.8615919 2.768162e-01 1.384081e-01
[39,] 0.8673810 2.652380e-01 1.326190e-01
[40,] 0.8751919 2.496163e-01 1.248081e-01
[41,] 0.8881656 2.236688e-01 1.118344e-01
[42,] 0.9067868 1.864265e-01 9.321324e-02
[43,] 0.9174479 1.651042e-01 8.255210e-02
[44,] 0.9216134 1.567732e-01 7.838661e-02
[45,] 0.9391553 1.216893e-01 6.084467e-02
[46,] 0.9476128 1.047744e-01 5.238719e-02
[47,] 0.9449446 1.101108e-01 5.505541e-02
[48,] 0.9366750 1.266499e-01 6.332495e-02
[49,] 0.9408651 1.182699e-01 5.913493e-02
[50,] 0.9279552 1.440896e-01 7.204480e-02
[51,] 0.9226726 1.546548e-01 7.732740e-02
[52,] 0.9226935 1.546131e-01 7.730653e-02
[53,] 0.9174198 1.651605e-01 8.258023e-02
[54,] 0.9141853 1.716293e-01 8.581466e-02
[55,] 0.9347789 1.304423e-01 6.522113e-02
[56,] 0.9704399 5.912010e-02 2.956005e-02
[57,] 0.9947747 1.045067e-02 5.225337e-03
[58,] 0.9946456 1.070877e-02 5.354385e-03
[59,] 0.9949502 1.009969e-02 5.049847e-03
[60,] 0.9968409 6.318280e-03 3.159140e-03
[61,] 0.9961206 7.758804e-03 3.879402e-03
[62,] 0.9969903 6.019425e-03 3.009713e-03
[63,] 0.9985071 2.985814e-03 1.492907e-03
[64,] 0.9995495 9.010129e-04 4.505065e-04
[65,] 0.9994698 1.060454e-03 5.302269e-04
[66,] 0.9996575 6.849850e-04 3.424925e-04
[67,] 0.9996796 6.408707e-04 3.204354e-04
[68,] 0.9997890 4.220931e-04 2.110465e-04
[69,] 0.9998461 3.077432e-04 1.538716e-04
[70,] 0.9998880 2.239361e-04 1.119681e-04
[71,] 0.9999082 1.836807e-04 9.184037e-05
[72,] 0.9999533 9.346935e-05 4.673468e-05
[73,] 0.9999930 1.407519e-05 7.037593e-06
[74,] 0.9999899 2.016694e-05 1.008347e-05
[75,] 0.9999847 3.052231e-05 1.526116e-05
[76,] 0.9999971 5.828454e-06 2.914227e-06
[77,] 0.9999960 8.064933e-06 4.032466e-06
[78,] 0.9999941 1.173621e-05 5.868105e-06
[79,] 0.9999943 1.143479e-05 5.717394e-06
[80,] 0.9999914 1.721034e-05 8.605168e-06
[81,] 0.9999858 2.841409e-05 1.420704e-05
[82,] 0.9999838 3.245361e-05 1.622680e-05
[83,] 0.9999825 3.498481e-05 1.749241e-05
[84,] 0.9999923 1.548111e-05 7.740556e-06
[85,] 0.9999884 2.315055e-05 1.157528e-05
[86,] 0.9999869 2.629548e-05 1.314774e-05
[87,] 0.9999869 2.625738e-05 1.312869e-05
[88,] 0.9999904 1.923869e-05 9.619346e-06
[89,] 0.9999932 1.361440e-05 6.807200e-06
[90,] 0.9999882 2.353743e-05 1.176871e-05
[91,] 1.0000000 7.515744e-08 3.757872e-08
[92,] 1.0000000 1.909519e-08 9.547597e-09
[93,] 1.0000000 2.337210e-08 1.168605e-08
[94,] 1.0000000 2.441607e-08 1.220804e-08
[95,] 1.0000000 2.761369e-08 1.380684e-08
[96,] 1.0000000 5.637593e-08 2.818797e-08
[97,] 1.0000000 7.865180e-08 3.932590e-08
[98,] 0.9999999 1.587071e-07 7.935354e-08
[99,] 1.0000000 5.144898e-08 2.572449e-08
[100,] 1.0000000 2.749472e-08 1.374736e-08
[101,] 1.0000000 5.784033e-08 2.892016e-08
[102,] 1.0000000 4.505292e-08 2.252646e-08
[103,] 1.0000000 6.623512e-08 3.311756e-08
[104,] 0.9999999 1.128256e-07 5.641278e-08
[105,] 1.0000000 7.936010e-08 3.968005e-08
[106,] 0.9999999 1.567001e-07 7.835006e-08
[107,] 0.9999999 2.420886e-07 1.210443e-07
[108,] 0.9999998 4.899761e-07 2.449881e-07
[109,] 0.9999996 7.880714e-07 3.940357e-07
[110,] 0.9999995 1.053802e-06 5.269009e-07
[111,] 1.0000000 8.067650e-08 4.033825e-08
[112,] 0.9999999 1.751972e-07 8.759860e-08
[113,] 0.9999999 2.938076e-07 1.469038e-07
[114,] 1.0000000 7.399498e-08 3.699749e-08
[115,] 0.9999999 1.585503e-07 7.927517e-08
[116,] 0.9999999 2.971753e-07 1.485877e-07
[117,] 0.9999998 3.258815e-07 1.629407e-07
[118,] 0.9999998 3.067236e-07 1.533618e-07
[119,] 0.9999999 1.826618e-07 9.133091e-08
[120,] 0.9999998 4.309242e-07 2.154621e-07
[121,] 1.0000000 6.487742e-08 3.243871e-08
[122,] 1.0000000 4.475412e-08 2.237706e-08
[123,] 0.9999999 1.159799e-07 5.798996e-08
[124,] 0.9999999 1.617660e-07 8.088302e-08
[125,] 0.9999998 4.684562e-07 2.342281e-07
[126,] 0.9999994 1.289049e-06 6.445243e-07
[127,] 0.9999995 9.163390e-07 4.581695e-07
[128,] 0.9999994 1.103630e-06 5.518148e-07
[129,] 0.9999991 1.827392e-06 9.136962e-07
[130,] 0.9999974 5.180445e-06 2.590222e-06
[131,] 0.9999998 4.075690e-07 2.037845e-07
[132,] 0.9999994 1.121506e-06 5.607531e-07
[133,] 0.9999992 1.583982e-06 7.919908e-07
[134,] 1.0000000 1.475943e-09 7.379713e-10
[135,] 1.0000000 9.181809e-09 4.590905e-09
[136,] 1.0000000 2.602449e-09 1.301225e-09
[137,] 1.0000000 5.273975e-09 2.636988e-09
[138,] 1.0000000 1.766613e-08 8.833063e-09
[139,] 1.0000000 2.683209e-08 1.341605e-08
[140,] 0.9999999 2.755719e-07 1.377860e-07
[141,] 0.9999987 2.561969e-06 1.280985e-06
[142,] 1.0000000 8.232369e-08 4.116184e-08
[143,] 1.0000000 2.800662e-08 1.400331e-08
[144,] 1.0000000 5.244387e-10 2.622194e-10
[145,] 0.9999999 1.651966e-07 8.259831e-08
> postscript(file="/var/wessaorg/rcomp/tmp/1rvjn1321784320.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/27qmi1321784320.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3emv41321784320.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4z76m1321784320.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/58f4u1321784320.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 164
Frequency = 1
1 2 3 4 5 6
-17033.31129 37910.22433 88965.80691 13212.16552 42801.44218 57106.27064
7 8 9 10 11 12
59743.98941 11221.53518 -19351.66743 -45717.18624 14526.14691 8985.47714
13 14 15 16 17 18
27738.41020 11040.77701 50654.82628 32240.42547 -3956.80457 -37631.24895
19 20 21 22 23 24
9358.43681 9307.15291 23864.63935 19520.47820 -17990.82278 -5566.69318
25 26 27 28 29 30
-25139.45086 31078.44806 18659.63562 7184.40075 38185.66717 35963.04728
31 32 33 34 35 36
16011.98878 36859.58244 24036.34929 6021.12929 18616.82651 -1854.91918
37 38 39 40 41 42
-7752.99400 -10030.24791 5631.31992 19013.29865 -84.00094 33871.56231
43 44 45 46 47 48
5686.05259 12892.71631 -3039.49773 10331.79694 37202.59049 -14561.18975
49 50 51 52 53 54
29511.70246 26200.22707 40608.60782 6544.12238 14233.15978 36958.07967
55 56 57 58 59 60
-11606.28784 23248.72085 -3476.52967 7791.42364 1882.55015 7832.91141
61 62 63 64 65 66
6445.67342 8140.71711 3853.51549 9605.07802 -42596.95639 -53291.52270
67 68 69 70 71 72
-1049.32147 7137.41827 -34011.69188 668.70874 -24479.39328 -40917.98837
73 74 75 76 77 78
35801.16693 5201.74747 -8868.16545 20682.88169 4581.88928 12817.90355
79 80 81 82 83 84
-32829.59613 11772.49170 8607.98768 -62095.61220 7767.71537 -5092.99847
85 86 87 88 89 90
20597.79171 3193.09927 -14436.47761 14488.66017 -8861.95361 1436.30450
91 92 93 94 95 96
-11074.03919 8020.72566 6029.35823 -4488.08490 -12653.54422 11076.41402
97 98 99 100 101 102
6900.80655 -8409.41192 -2082.18666 -87852.62638 1655.86953 -23334.63627
103 104 105 106 107 108
-21699.34492 6846.62738 -921.25900 -34700.96072 10728.24464 -1302.40482
109 110 111 112 113 114
-3057.78007 -8713.93016 -34938.39427 5958.13483 -13501.22490 -2641.81955
115 116 117 118 119 120
-17154.99139 -32036.40575 -7256.86142 -14536.69628 3536.31960 -87137.11232
121 122 123 124 125 126
-12392.47565 -13184.79683 16940.78305 -11135.80788 -11301.68310 -26350.59076
127 128 129 130 131 132
4206.67155 14243.93911 -14136.34167 21308.72466 -14336.30700 -26740.17512
133 134 135 136 137 138
-17210.12745 -6222.87165 -16841.01199 -44398.85720 -5887.62011 -29553.45376
139 140 141 142 143 144
-15227.44717 -63464.98276 -6814.19503 -1507.92521 11941.62912 -18406.46018
145 146 147 148 149 150
521.74856 -25541.92851 -20174.86514 -15514.31343 -17099.72314 -14959.69025
151 152 153 154 155 156
-18529.83239 -2498.70550 -3125.66331 8778.24745 2012.66712 -348.63260
157 158 159 160 161 162
5264.28236 5534.52691 5085.17382 5462.92835 21667.57999 7496.41532
163 164
5725.01974 5725.01974
> postscript(file="/var/wessaorg/rcomp/tmp/6dpgh1321784320.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 = 164
Frequency = 1
lag(myerror, k = 1) myerror
0 -17033.31129 NA
1 37910.22433 -17033.31129
2 88965.80691 37910.22433
3 13212.16552 88965.80691
4 42801.44218 13212.16552
5 57106.27064 42801.44218
6 59743.98941 57106.27064
7 11221.53518 59743.98941
8 -19351.66743 11221.53518
9 -45717.18624 -19351.66743
10 14526.14691 -45717.18624
11 8985.47714 14526.14691
12 27738.41020 8985.47714
13 11040.77701 27738.41020
14 50654.82628 11040.77701
15 32240.42547 50654.82628
16 -3956.80457 32240.42547
17 -37631.24895 -3956.80457
18 9358.43681 -37631.24895
19 9307.15291 9358.43681
20 23864.63935 9307.15291
21 19520.47820 23864.63935
22 -17990.82278 19520.47820
23 -5566.69318 -17990.82278
24 -25139.45086 -5566.69318
25 31078.44806 -25139.45086
26 18659.63562 31078.44806
27 7184.40075 18659.63562
28 38185.66717 7184.40075
29 35963.04728 38185.66717
30 16011.98878 35963.04728
31 36859.58244 16011.98878
32 24036.34929 36859.58244
33 6021.12929 24036.34929
34 18616.82651 6021.12929
35 -1854.91918 18616.82651
36 -7752.99400 -1854.91918
37 -10030.24791 -7752.99400
38 5631.31992 -10030.24791
39 19013.29865 5631.31992
40 -84.00094 19013.29865
41 33871.56231 -84.00094
42 5686.05259 33871.56231
43 12892.71631 5686.05259
44 -3039.49773 12892.71631
45 10331.79694 -3039.49773
46 37202.59049 10331.79694
47 -14561.18975 37202.59049
48 29511.70246 -14561.18975
49 26200.22707 29511.70246
50 40608.60782 26200.22707
51 6544.12238 40608.60782
52 14233.15978 6544.12238
53 36958.07967 14233.15978
54 -11606.28784 36958.07967
55 23248.72085 -11606.28784
56 -3476.52967 23248.72085
57 7791.42364 -3476.52967
58 1882.55015 7791.42364
59 7832.91141 1882.55015
60 6445.67342 7832.91141
61 8140.71711 6445.67342
62 3853.51549 8140.71711
63 9605.07802 3853.51549
64 -42596.95639 9605.07802
65 -53291.52270 -42596.95639
66 -1049.32147 -53291.52270
67 7137.41827 -1049.32147
68 -34011.69188 7137.41827
69 668.70874 -34011.69188
70 -24479.39328 668.70874
71 -40917.98837 -24479.39328
72 35801.16693 -40917.98837
73 5201.74747 35801.16693
74 -8868.16545 5201.74747
75 20682.88169 -8868.16545
76 4581.88928 20682.88169
77 12817.90355 4581.88928
78 -32829.59613 12817.90355
79 11772.49170 -32829.59613
80 8607.98768 11772.49170
81 -62095.61220 8607.98768
82 7767.71537 -62095.61220
83 -5092.99847 7767.71537
84 20597.79171 -5092.99847
85 3193.09927 20597.79171
86 -14436.47761 3193.09927
87 14488.66017 -14436.47761
88 -8861.95361 14488.66017
89 1436.30450 -8861.95361
90 -11074.03919 1436.30450
91 8020.72566 -11074.03919
92 6029.35823 8020.72566
93 -4488.08490 6029.35823
94 -12653.54422 -4488.08490
95 11076.41402 -12653.54422
96 6900.80655 11076.41402
97 -8409.41192 6900.80655
98 -2082.18666 -8409.41192
99 -87852.62638 -2082.18666
100 1655.86953 -87852.62638
101 -23334.63627 1655.86953
102 -21699.34492 -23334.63627
103 6846.62738 -21699.34492
104 -921.25900 6846.62738
105 -34700.96072 -921.25900
106 10728.24464 -34700.96072
107 -1302.40482 10728.24464
108 -3057.78007 -1302.40482
109 -8713.93016 -3057.78007
110 -34938.39427 -8713.93016
111 5958.13483 -34938.39427
112 -13501.22490 5958.13483
113 -2641.81955 -13501.22490
114 -17154.99139 -2641.81955
115 -32036.40575 -17154.99139
116 -7256.86142 -32036.40575
117 -14536.69628 -7256.86142
118 3536.31960 -14536.69628
119 -87137.11232 3536.31960
120 -12392.47565 -87137.11232
121 -13184.79683 -12392.47565
122 16940.78305 -13184.79683
123 -11135.80788 16940.78305
124 -11301.68310 -11135.80788
125 -26350.59076 -11301.68310
126 4206.67155 -26350.59076
127 14243.93911 4206.67155
128 -14136.34167 14243.93911
129 21308.72466 -14136.34167
130 -14336.30700 21308.72466
131 -26740.17512 -14336.30700
132 -17210.12745 -26740.17512
133 -6222.87165 -17210.12745
134 -16841.01199 -6222.87165
135 -44398.85720 -16841.01199
136 -5887.62011 -44398.85720
137 -29553.45376 -5887.62011
138 -15227.44717 -29553.45376
139 -63464.98276 -15227.44717
140 -6814.19503 -63464.98276
141 -1507.92521 -6814.19503
142 11941.62912 -1507.92521
143 -18406.46018 11941.62912
144 521.74856 -18406.46018
145 -25541.92851 521.74856
146 -20174.86514 -25541.92851
147 -15514.31343 -20174.86514
148 -17099.72314 -15514.31343
149 -14959.69025 -17099.72314
150 -18529.83239 -14959.69025
151 -2498.70550 -18529.83239
152 -3125.66331 -2498.70550
153 8778.24745 -3125.66331
154 2012.66712 8778.24745
155 -348.63260 2012.66712
156 5264.28236 -348.63260
157 5534.52691 5264.28236
158 5085.17382 5534.52691
159 5462.92835 5085.17382
160 21667.57999 5462.92835
161 7496.41532 21667.57999
162 5725.01974 7496.41532
163 5725.01974 5725.01974
164 NA 5725.01974
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 37910.22433 -17033.31129
[2,] 88965.80691 37910.22433
[3,] 13212.16552 88965.80691
[4,] 42801.44218 13212.16552
[5,] 57106.27064 42801.44218
[6,] 59743.98941 57106.27064
[7,] 11221.53518 59743.98941
[8,] -19351.66743 11221.53518
[9,] -45717.18624 -19351.66743
[10,] 14526.14691 -45717.18624
[11,] 8985.47714 14526.14691
[12,] 27738.41020 8985.47714
[13,] 11040.77701 27738.41020
[14,] 50654.82628 11040.77701
[15,] 32240.42547 50654.82628
[16,] -3956.80457 32240.42547
[17,] -37631.24895 -3956.80457
[18,] 9358.43681 -37631.24895
[19,] 9307.15291 9358.43681
[20,] 23864.63935 9307.15291
[21,] 19520.47820 23864.63935
[22,] -17990.82278 19520.47820
[23,] -5566.69318 -17990.82278
[24,] -25139.45086 -5566.69318
[25,] 31078.44806 -25139.45086
[26,] 18659.63562 31078.44806
[27,] 7184.40075 18659.63562
[28,] 38185.66717 7184.40075
[29,] 35963.04728 38185.66717
[30,] 16011.98878 35963.04728
[31,] 36859.58244 16011.98878
[32,] 24036.34929 36859.58244
[33,] 6021.12929 24036.34929
[34,] 18616.82651 6021.12929
[35,] -1854.91918 18616.82651
[36,] -7752.99400 -1854.91918
[37,] -10030.24791 -7752.99400
[38,] 5631.31992 -10030.24791
[39,] 19013.29865 5631.31992
[40,] -84.00094 19013.29865
[41,] 33871.56231 -84.00094
[42,] 5686.05259 33871.56231
[43,] 12892.71631 5686.05259
[44,] -3039.49773 12892.71631
[45,] 10331.79694 -3039.49773
[46,] 37202.59049 10331.79694
[47,] -14561.18975 37202.59049
[48,] 29511.70246 -14561.18975
[49,] 26200.22707 29511.70246
[50,] 40608.60782 26200.22707
[51,] 6544.12238 40608.60782
[52,] 14233.15978 6544.12238
[53,] 36958.07967 14233.15978
[54,] -11606.28784 36958.07967
[55,] 23248.72085 -11606.28784
[56,] -3476.52967 23248.72085
[57,] 7791.42364 -3476.52967
[58,] 1882.55015 7791.42364
[59,] 7832.91141 1882.55015
[60,] 6445.67342 7832.91141
[61,] 8140.71711 6445.67342
[62,] 3853.51549 8140.71711
[63,] 9605.07802 3853.51549
[64,] -42596.95639 9605.07802
[65,] -53291.52270 -42596.95639
[66,] -1049.32147 -53291.52270
[67,] 7137.41827 -1049.32147
[68,] -34011.69188 7137.41827
[69,] 668.70874 -34011.69188
[70,] -24479.39328 668.70874
[71,] -40917.98837 -24479.39328
[72,] 35801.16693 -40917.98837
[73,] 5201.74747 35801.16693
[74,] -8868.16545 5201.74747
[75,] 20682.88169 -8868.16545
[76,] 4581.88928 20682.88169
[77,] 12817.90355 4581.88928
[78,] -32829.59613 12817.90355
[79,] 11772.49170 -32829.59613
[80,] 8607.98768 11772.49170
[81,] -62095.61220 8607.98768
[82,] 7767.71537 -62095.61220
[83,] -5092.99847 7767.71537
[84,] 20597.79171 -5092.99847
[85,] 3193.09927 20597.79171
[86,] -14436.47761 3193.09927
[87,] 14488.66017 -14436.47761
[88,] -8861.95361 14488.66017
[89,] 1436.30450 -8861.95361
[90,] -11074.03919 1436.30450
[91,] 8020.72566 -11074.03919
[92,] 6029.35823 8020.72566
[93,] -4488.08490 6029.35823
[94,] -12653.54422 -4488.08490
[95,] 11076.41402 -12653.54422
[96,] 6900.80655 11076.41402
[97,] -8409.41192 6900.80655
[98,] -2082.18666 -8409.41192
[99,] -87852.62638 -2082.18666
[100,] 1655.86953 -87852.62638
[101,] -23334.63627 1655.86953
[102,] -21699.34492 -23334.63627
[103,] 6846.62738 -21699.34492
[104,] -921.25900 6846.62738
[105,] -34700.96072 -921.25900
[106,] 10728.24464 -34700.96072
[107,] -1302.40482 10728.24464
[108,] -3057.78007 -1302.40482
[109,] -8713.93016 -3057.78007
[110,] -34938.39427 -8713.93016
[111,] 5958.13483 -34938.39427
[112,] -13501.22490 5958.13483
[113,] -2641.81955 -13501.22490
[114,] -17154.99139 -2641.81955
[115,] -32036.40575 -17154.99139
[116,] -7256.86142 -32036.40575
[117,] -14536.69628 -7256.86142
[118,] 3536.31960 -14536.69628
[119,] -87137.11232 3536.31960
[120,] -12392.47565 -87137.11232
[121,] -13184.79683 -12392.47565
[122,] 16940.78305 -13184.79683
[123,] -11135.80788 16940.78305
[124,] -11301.68310 -11135.80788
[125,] -26350.59076 -11301.68310
[126,] 4206.67155 -26350.59076
[127,] 14243.93911 4206.67155
[128,] -14136.34167 14243.93911
[129,] 21308.72466 -14136.34167
[130,] -14336.30700 21308.72466
[131,] -26740.17512 -14336.30700
[132,] -17210.12745 -26740.17512
[133,] -6222.87165 -17210.12745
[134,] -16841.01199 -6222.87165
[135,] -44398.85720 -16841.01199
[136,] -5887.62011 -44398.85720
[137,] -29553.45376 -5887.62011
[138,] -15227.44717 -29553.45376
[139,] -63464.98276 -15227.44717
[140,] -6814.19503 -63464.98276
[141,] -1507.92521 -6814.19503
[142,] 11941.62912 -1507.92521
[143,] -18406.46018 11941.62912
[144,] 521.74856 -18406.46018
[145,] -25541.92851 521.74856
[146,] -20174.86514 -25541.92851
[147,] -15514.31343 -20174.86514
[148,] -17099.72314 -15514.31343
[149,] -14959.69025 -17099.72314
[150,] -18529.83239 -14959.69025
[151,] -2498.70550 -18529.83239
[152,] -3125.66331 -2498.70550
[153,] 8778.24745 -3125.66331
[154,] 2012.66712 8778.24745
[155,] -348.63260 2012.66712
[156,] 5264.28236 -348.63260
[157,] 5534.52691 5264.28236
[158,] 5085.17382 5534.52691
[159,] 5462.92835 5085.17382
[160,] 21667.57999 5462.92835
[161,] 7496.41532 21667.57999
[162,] 5725.01974 7496.41532
[163,] 5725.01974 5725.01974
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 37910.22433 -17033.31129
2 88965.80691 37910.22433
3 13212.16552 88965.80691
4 42801.44218 13212.16552
5 57106.27064 42801.44218
6 59743.98941 57106.27064
7 11221.53518 59743.98941
8 -19351.66743 11221.53518
9 -45717.18624 -19351.66743
10 14526.14691 -45717.18624
11 8985.47714 14526.14691
12 27738.41020 8985.47714
13 11040.77701 27738.41020
14 50654.82628 11040.77701
15 32240.42547 50654.82628
16 -3956.80457 32240.42547
17 -37631.24895 -3956.80457
18 9358.43681 -37631.24895
19 9307.15291 9358.43681
20 23864.63935 9307.15291
21 19520.47820 23864.63935
22 -17990.82278 19520.47820
23 -5566.69318 -17990.82278
24 -25139.45086 -5566.69318
25 31078.44806 -25139.45086
26 18659.63562 31078.44806
27 7184.40075 18659.63562
28 38185.66717 7184.40075
29 35963.04728 38185.66717
30 16011.98878 35963.04728
31 36859.58244 16011.98878
32 24036.34929 36859.58244
33 6021.12929 24036.34929
34 18616.82651 6021.12929
35 -1854.91918 18616.82651
36 -7752.99400 -1854.91918
37 -10030.24791 -7752.99400
38 5631.31992 -10030.24791
39 19013.29865 5631.31992
40 -84.00094 19013.29865
41 33871.56231 -84.00094
42 5686.05259 33871.56231
43 12892.71631 5686.05259
44 -3039.49773 12892.71631
45 10331.79694 -3039.49773
46 37202.59049 10331.79694
47 -14561.18975 37202.59049
48 29511.70246 -14561.18975
49 26200.22707 29511.70246
50 40608.60782 26200.22707
51 6544.12238 40608.60782
52 14233.15978 6544.12238
53 36958.07967 14233.15978
54 -11606.28784 36958.07967
55 23248.72085 -11606.28784
56 -3476.52967 23248.72085
57 7791.42364 -3476.52967
58 1882.55015 7791.42364
59 7832.91141 1882.55015
60 6445.67342 7832.91141
61 8140.71711 6445.67342
62 3853.51549 8140.71711
63 9605.07802 3853.51549
64 -42596.95639 9605.07802
65 -53291.52270 -42596.95639
66 -1049.32147 -53291.52270
67 7137.41827 -1049.32147
68 -34011.69188 7137.41827
69 668.70874 -34011.69188
70 -24479.39328 668.70874
71 -40917.98837 -24479.39328
72 35801.16693 -40917.98837
73 5201.74747 35801.16693
74 -8868.16545 5201.74747
75 20682.88169 -8868.16545
76 4581.88928 20682.88169
77 12817.90355 4581.88928
78 -32829.59613 12817.90355
79 11772.49170 -32829.59613
80 8607.98768 11772.49170
81 -62095.61220 8607.98768
82 7767.71537 -62095.61220
83 -5092.99847 7767.71537
84 20597.79171 -5092.99847
85 3193.09927 20597.79171
86 -14436.47761 3193.09927
87 14488.66017 -14436.47761
88 -8861.95361 14488.66017
89 1436.30450 -8861.95361
90 -11074.03919 1436.30450
91 8020.72566 -11074.03919
92 6029.35823 8020.72566
93 -4488.08490 6029.35823
94 -12653.54422 -4488.08490
95 11076.41402 -12653.54422
96 6900.80655 11076.41402
97 -8409.41192 6900.80655
98 -2082.18666 -8409.41192
99 -87852.62638 -2082.18666
100 1655.86953 -87852.62638
101 -23334.63627 1655.86953
102 -21699.34492 -23334.63627
103 6846.62738 -21699.34492
104 -921.25900 6846.62738
105 -34700.96072 -921.25900
106 10728.24464 -34700.96072
107 -1302.40482 10728.24464
108 -3057.78007 -1302.40482
109 -8713.93016 -3057.78007
110 -34938.39427 -8713.93016
111 5958.13483 -34938.39427
112 -13501.22490 5958.13483
113 -2641.81955 -13501.22490
114 -17154.99139 -2641.81955
115 -32036.40575 -17154.99139
116 -7256.86142 -32036.40575
117 -14536.69628 -7256.86142
118 3536.31960 -14536.69628
119 -87137.11232 3536.31960
120 -12392.47565 -87137.11232
121 -13184.79683 -12392.47565
122 16940.78305 -13184.79683
123 -11135.80788 16940.78305
124 -11301.68310 -11135.80788
125 -26350.59076 -11301.68310
126 4206.67155 -26350.59076
127 14243.93911 4206.67155
128 -14136.34167 14243.93911
129 21308.72466 -14136.34167
130 -14336.30700 21308.72466
131 -26740.17512 -14336.30700
132 -17210.12745 -26740.17512
133 -6222.87165 -17210.12745
134 -16841.01199 -6222.87165
135 -44398.85720 -16841.01199
136 -5887.62011 -44398.85720
137 -29553.45376 -5887.62011
138 -15227.44717 -29553.45376
139 -63464.98276 -15227.44717
140 -6814.19503 -63464.98276
141 -1507.92521 -6814.19503
142 11941.62912 -1507.92521
143 -18406.46018 11941.62912
144 521.74856 -18406.46018
145 -25541.92851 521.74856
146 -20174.86514 -25541.92851
147 -15514.31343 -20174.86514
148 -17099.72314 -15514.31343
149 -14959.69025 -17099.72314
150 -18529.83239 -14959.69025
151 -2498.70550 -18529.83239
152 -3125.66331 -2498.70550
153 8778.24745 -3125.66331
154 2012.66712 8778.24745
155 -348.63260 2012.66712
156 5264.28236 -348.63260
157 5534.52691 5264.28236
158 5085.17382 5534.52691
159 5462.92835 5085.17382
160 21667.57999 5462.92835
161 7496.41532 21667.57999
162 5725.01974 7496.41532
163 5725.01974 5725.01974
> 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/7x69f1321784320.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/8tbrk1321784320.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/97a7e1321784320.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/100uwf1321784320.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11hsjg1321784321.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12zq281321784321.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13573j1321784321.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14xj0u1321784321.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/15q99j1321784321.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/16l14s1321784321.tab")
+ }
>
> try(system("convert tmp/1rvjn1321784320.ps tmp/1rvjn1321784320.png",intern=TRUE))
character(0)
> try(system("convert tmp/27qmi1321784320.ps tmp/27qmi1321784320.png",intern=TRUE))
character(0)
> try(system("convert tmp/3emv41321784320.ps tmp/3emv41321784320.png",intern=TRUE))
character(0)
> try(system("convert tmp/4z76m1321784320.ps tmp/4z76m1321784320.png",intern=TRUE))
character(0)
> try(system("convert tmp/58f4u1321784320.ps tmp/58f4u1321784320.png",intern=TRUE))
character(0)
> try(system("convert tmp/6dpgh1321784320.ps tmp/6dpgh1321784320.png",intern=TRUE))
character(0)
> try(system("convert tmp/7x69f1321784320.ps tmp/7x69f1321784320.png",intern=TRUE))
character(0)
> try(system("convert tmp/8tbrk1321784320.ps tmp/8tbrk1321784320.png",intern=TRUE))
character(0)
> try(system("convert tmp/97a7e1321784320.ps tmp/97a7e1321784320.png",intern=TRUE))
character(0)
> try(system("convert tmp/100uwf1321784320.ps tmp/100uwf1321784320.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.935 0.508 6.012