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(30
+ ,210907
+ ,112285
+ ,1418
+ ,144
+ ,28
+ ,120982
+ ,84786
+ ,869
+ ,103
+ ,38
+ ,176508
+ ,83123
+ ,1530
+ ,98
+ ,30
+ ,179321
+ ,101193
+ ,2172
+ ,135
+ ,22
+ ,123185
+ ,38361
+ ,901
+ ,61
+ ,26
+ ,52746
+ ,68504
+ ,463
+ ,39
+ ,25
+ ,385534
+ ,119182
+ ,3201
+ ,150
+ ,18
+ ,33170
+ ,22807
+ ,371
+ ,5
+ ,11
+ ,101645
+ ,17140
+ ,1192
+ ,28
+ ,26
+ ,149061
+ ,116174
+ ,1583
+ ,84
+ ,25
+ ,165446
+ ,57635
+ ,1439
+ ,80
+ ,38
+ ,237213
+ ,66198
+ ,1764
+ ,130
+ ,44
+ ,173326
+ ,71701
+ ,1495
+ ,82
+ ,30
+ ,133131
+ ,57793
+ ,1373
+ ,60
+ ,40
+ ,258873
+ ,80444
+ ,2187
+ ,131
+ ,34
+ ,180083
+ ,53855
+ ,1491
+ ,84
+ ,47
+ ,324799
+ ,97668
+ ,4041
+ ,140
+ ,30
+ ,230964
+ ,133824
+ ,1706
+ ,151
+ ,31
+ ,236785
+ ,101481
+ ,2152
+ ,91
+ ,23
+ ,135473
+ ,99645
+ ,1036
+ ,138
+ ,36
+ ,202925
+ ,114789
+ ,1882
+ ,150
+ ,36
+ ,215147
+ ,99052
+ ,1929
+ ,124
+ ,30
+ ,344297
+ ,67654
+ ,2242
+ ,119
+ ,25
+ ,153935
+ ,65553
+ ,1220
+ ,73
+ ,39
+ ,132943
+ ,97500
+ ,1289
+ ,110
+ ,34
+ ,174724
+ ,69112
+ ,2515
+ ,123
+ ,31
+ ,174415
+ ,82753
+ ,2147
+ ,90
+ ,31
+ ,225548
+ ,85323
+ ,2352
+ ,116
+ ,33
+ ,223632
+ ,72654
+ ,1638
+ ,113
+ ,25
+ ,124817
+ ,30727
+ ,1222
+ ,56
+ ,33
+ ,221698
+ ,77873
+ ,1812
+ ,115
+ ,35
+ ,210767
+ ,117478
+ ,1677
+ ,119
+ ,42
+ ,170266
+ ,74007
+ ,1579
+ ,129
+ ,43
+ ,260561
+ ,90183
+ ,1731
+ ,127
+ ,30
+ ,84853
+ ,61542
+ ,807
+ ,27
+ ,33
+ ,294424
+ ,101494
+ ,2452
+ ,175
+ ,13
+ ,101011
+ ,27570
+ ,829
+ ,35
+ ,32
+ ,215641
+ ,55813
+ ,1940
+ ,64
+ ,36
+ ,325107
+ ,79215
+ ,2662
+ ,96
+ ,0
+ ,7176
+ ,1423
+ ,186
+ ,0
+ ,28
+ ,167542
+ ,55461
+ ,1499
+ ,84
+ ,14
+ ,106408
+ ,31081
+ ,865
+ ,41
+ ,17
+ ,96560
+ ,22996
+ ,1793
+ ,47
+ ,32
+ ,265769
+ ,83122
+ ,2527
+ ,126
+ ,30
+ ,269651
+ ,70106
+ ,2747
+ ,105
+ ,35
+ ,149112
+ ,60578
+ ,1324
+ ,80
+ ,20
+ ,175824
+ ,39992
+ ,2702
+ ,70
+ ,28
+ ,152871
+ ,79892
+ ,1383
+ ,73
+ ,28
+ ,111665
+ ,49810
+ ,1179
+ ,57
+ ,39
+ ,116408
+ ,71570
+ ,2099
+ ,40
+ ,34
+ ,362301
+ ,100708
+ ,4308
+ ,68
+ ,26
+ ,78800
+ ,33032
+ ,918
+ ,21
+ ,39
+ ,183167
+ ,82875
+ ,1831
+ ,127
+ ,39
+ ,277965
+ ,139077
+ ,3373
+ ,154
+ ,33
+ ,150629
+ ,71595
+ ,1713
+ ,116
+ ,28
+ ,168809
+ ,72260
+ ,1438
+ ,102
+ ,4
+ ,24188
+ ,5950
+ ,496
+ ,7
+ ,39
+ ,329267
+ ,115762
+ ,2253
+ ,148
+ ,18
+ ,65029
+ ,32551
+ ,744
+ ,21
+ ,14
+ ,101097
+ ,31701
+ ,1161
+ ,35
+ ,29
+ ,218946
+ ,80670
+ ,2352
+ ,112
+ ,44
+ ,244052
+ ,143558
+ ,2144
+ ,137
+ ,21
+ ,341570
+ ,117105
+ ,4691
+ ,135
+ ,16
+ ,103597
+ ,23789
+ ,1112
+ ,26
+ ,28
+ ,233328
+ ,120733
+ ,2694
+ ,230
+ ,35
+ ,256462
+ ,105195
+ ,1973
+ ,181
+ ,28
+ ,206161
+ ,73107
+ ,1769
+ ,71
+ ,38
+ ,311473
+ ,132068
+ ,3148
+ ,147
+ ,23
+ ,235800
+ ,149193
+ ,2474
+ ,190
+ ,36
+ ,177939
+ ,46821
+ ,2084
+ ,64
+ ,32
+ ,207176
+ ,87011
+ ,1954
+ ,105
+ ,29
+ ,196553
+ ,95260
+ ,1226
+ ,107
+ ,25
+ ,174184
+ ,55183
+ ,1389
+ ,94
+ ,27
+ ,143246
+ ,106671
+ ,1496
+ ,116
+ ,36
+ ,187559
+ ,73511
+ ,2269
+ ,106
+ ,28
+ ,187681
+ ,92945
+ ,1833
+ ,143
+ ,23
+ ,119016
+ ,78664
+ ,1268
+ ,81
+ ,40
+ ,182192
+ ,70054
+ ,1943
+ ,89
+ ,23
+ ,73566
+ ,22618
+ ,893
+ ,26
+ ,40
+ ,194979
+ ,74011
+ ,1762
+ ,84
+ ,28
+ ,167488
+ ,83737
+ ,1403
+ ,113
+ ,34
+ ,143756
+ ,69094
+ ,1425
+ ,120
+ ,33
+ ,275541
+ ,93133
+ ,1857
+ ,110
+ ,28
+ ,243199
+ ,95536
+ ,1840
+ ,134
+ ,34
+ ,182999
+ ,225920
+ ,1502
+ ,54
+ ,30
+ ,135649
+ ,62133
+ ,1441
+ ,96
+ ,33
+ ,152299
+ ,61370
+ ,1420
+ ,78
+ ,22
+ ,120221
+ ,43836
+ ,1416
+ ,51
+ ,38
+ ,346485
+ ,106117
+ ,2970
+ ,121
+ ,26
+ ,145790
+ ,38692
+ ,1317
+ ,38
+ ,35
+ ,193339
+ ,84651
+ ,1644
+ ,145
+ ,8
+ ,80953
+ ,56622
+ ,870
+ ,59
+ ,24
+ ,122774
+ ,15986
+ ,1654
+ ,27
+ ,29
+ ,130585
+ ,95364
+ ,1054
+ ,91
+ ,20
+ ,112611
+ ,26706
+ ,937
+ ,48
+ ,29
+ ,286468
+ ,89691
+ ,3004
+ ,68
+ ,45
+ ,241066
+ ,67267
+ ,2008
+ ,58
+ ,37
+ ,148446
+ ,126846
+ ,2547
+ ,150
+ ,33
+ ,204713
+ ,41140
+ ,1885
+ ,74
+ ,33
+ ,182079
+ ,102860
+ ,1626
+ ,181
+ ,25
+ ,140344
+ ,51715
+ ,1468
+ ,65
+ ,32
+ ,220516
+ ,55801
+ ,2445
+ ,97
+ ,29
+ ,243060
+ ,111813
+ ,1964
+ ,121
+ ,28
+ ,162765
+ ,120293
+ ,1381
+ ,99
+ ,28
+ ,182613
+ ,138599
+ ,1369
+ ,152
+ ,31
+ ,232138
+ ,161647
+ ,1659
+ ,188
+ ,52
+ ,265318
+ ,115929
+ ,2888
+ ,138
+ ,21
+ ,85574
+ ,24266
+ ,1290
+ ,40
+ ,24
+ ,310839
+ ,162901
+ ,2845
+ ,254
+ ,41
+ ,225060
+ ,109825
+ ,1982
+ ,87
+ ,33
+ ,232317
+ ,129838
+ ,1904
+ ,178
+ ,32
+ ,144966
+ ,37510
+ ,1391
+ ,51
+ ,19
+ ,43287
+ ,43750
+ ,602
+ ,49
+ ,20
+ ,155754
+ ,40652
+ ,1743
+ ,73
+ ,31
+ ,164709
+ ,87771
+ ,1559
+ ,176
+ ,31
+ ,201940
+ ,85872
+ ,2014
+ ,94
+ ,32
+ ,235454
+ ,89275
+ ,2143
+ ,120
+ ,18
+ ,220801
+ ,44418
+ ,2146
+ ,66
+ ,23
+ ,99466
+ ,192565
+ ,874
+ ,56
+ ,17
+ ,92661
+ ,35232
+ ,1590
+ ,39
+ ,20
+ ,133328
+ ,40909
+ ,1590
+ ,66
+ ,12
+ ,61361
+ ,13294
+ ,1210
+ ,27
+ ,17
+ ,125930
+ ,32387
+ ,2072
+ ,65
+ ,30
+ ,100750
+ ,140867
+ ,1281
+ ,58
+ ,31
+ ,224549
+ ,120662
+ ,1401
+ ,98
+ ,10
+ ,82316
+ ,21233
+ ,834
+ ,25
+ ,13
+ ,102010
+ ,44332
+ ,1105
+ ,26
+ ,22
+ ,101523
+ ,61056
+ ,1272
+ ,77
+ ,42
+ ,243511
+ ,101338
+ ,1944
+ ,130
+ ,1
+ ,22938
+ ,1168
+ ,391
+ ,11
+ ,9
+ ,41566
+ ,13497
+ ,761
+ ,2
+ ,32
+ ,152474
+ ,65567
+ ,1605
+ ,101
+ ,11
+ ,61857
+ ,25162
+ ,530
+ ,31
+ ,25
+ ,99923
+ ,32334
+ ,1988
+ ,36
+ ,36
+ ,132487
+ ,40735
+ ,1386
+ ,120
+ ,31
+ ,317394
+ ,91413
+ ,2395
+ ,195
+ ,0
+ ,21054
+ ,855
+ ,387
+ ,4
+ ,24
+ ,209641
+ ,97068
+ ,1742
+ ,89
+ ,13
+ ,22648
+ ,44339
+ ,620
+ ,24
+ ,8
+ ,31414
+ ,14116
+ ,449
+ ,39
+ ,13
+ ,46698
+ ,10288
+ ,800
+ ,14
+ ,19
+ ,131698
+ ,65622
+ ,1684
+ ,78
+ ,18
+ ,91735
+ ,16563
+ ,1050
+ ,15
+ ,33
+ ,244749
+ ,76643
+ ,2699
+ ,106
+ ,40
+ ,184510
+ ,110681
+ ,1606
+ ,83
+ ,22
+ ,79863
+ ,29011
+ ,1502
+ ,24
+ ,38
+ ,128423
+ ,92696
+ ,1204
+ ,37
+ ,24
+ ,97839
+ ,94785
+ ,1138
+ ,77
+ ,8
+ ,38214
+ ,8773
+ ,568
+ ,16
+ ,35
+ ,151101
+ ,83209
+ ,1459
+ ,56
+ ,43
+ ,272458
+ ,93815
+ ,2158
+ ,132
+ ,43
+ ,172494
+ ,86687
+ ,1111
+ ,144
+ ,14
+ ,108043
+ ,34553
+ ,1421
+ ,40
+ ,41
+ ,328107
+ ,105547
+ ,2833
+ ,153
+ ,38
+ ,250579
+ ,103487
+ ,1955
+ ,143
+ ,45
+ ,351067
+ ,213688
+ ,2922
+ ,220
+ ,31
+ ,158015
+ ,71220
+ ,1002
+ ,79
+ ,13
+ ,98866
+ ,23517
+ ,1060
+ ,50
+ ,28
+ ,85439
+ ,56926
+ ,956
+ ,39
+ ,31
+ ,229242
+ ,91721
+ ,2186
+ ,95
+ ,40
+ ,351619
+ ,115168
+ ,3604
+ ,169
+ ,30
+ ,84207
+ ,111194
+ ,1035
+ ,12
+ ,16
+ ,120445
+ ,51009
+ ,1417
+ ,63
+ ,37
+ ,324598
+ ,135777
+ ,3261
+ ,134
+ ,30
+ ,131069
+ ,51513
+ ,1587
+ ,69
+ ,35
+ ,204271
+ ,74163
+ ,1424
+ ,119
+ ,32
+ ,165543
+ ,51633
+ ,1701
+ ,119
+ ,27
+ ,141722
+ ,75345
+ ,1249
+ ,75
+ ,20
+ ,116048
+ ,33416
+ ,946
+ ,63
+ ,18
+ ,250047
+ ,83305
+ ,1926
+ ,55
+ ,31
+ ,299775
+ ,98952
+ ,3352
+ ,103
+ ,31
+ ,195838
+ ,102372
+ ,1641
+ ,197
+ ,21
+ ,173260
+ ,37238
+ ,2035
+ ,16
+ ,39
+ ,254488
+ ,103772
+ ,2312
+ ,140
+ ,41
+ ,104389
+ ,123969
+ ,1369
+ ,89
+ ,13
+ ,136084
+ ,27142
+ ,1577
+ ,40
+ ,32
+ ,199476
+ ,135400
+ ,2201
+ ,125
+ ,18
+ ,92499
+ ,21399
+ ,961
+ ,21
+ ,39
+ ,224330
+ ,130115
+ ,1900
+ ,167
+ ,14
+ ,135781
+ ,24874
+ ,1254
+ ,32
+ ,7
+ ,74408
+ ,34988
+ ,1335
+ ,36
+ ,17
+ ,81240
+ ,45549
+ ,1597
+ ,13
+ ,0
+ ,14688
+ ,6023
+ ,207
+ ,5
+ ,30
+ ,181633
+ ,64466
+ ,1645
+ ,96
+ ,37
+ ,271856
+ ,54990
+ ,2429
+ ,151
+ ,0
+ ,7199
+ ,1644
+ ,151
+ ,6
+ ,5
+ ,46660
+ ,6179
+ ,474
+ ,13
+ ,1
+ ,17547
+ ,3926
+ ,141
+ ,3
+ ,16
+ ,133368
+ ,32755
+ ,1639
+ ,57
+ ,32
+ ,95227
+ ,34777
+ ,872
+ ,23
+ ,24
+ ,152601
+ ,73224
+ ,1318
+ ,61
+ ,17
+ ,98146
+ ,27114
+ ,1018
+ ,21
+ ,11
+ ,79619
+ ,20760
+ ,1383
+ ,43
+ ,24
+ ,59194
+ ,37636
+ ,1314
+ ,20
+ ,22
+ ,139942
+ ,65461
+ ,1335
+ ,82
+ ,12
+ ,118612
+ ,30080
+ ,1403
+ ,90
+ ,19
+ ,72880
+ ,24094
+ ,910
+ ,25
+ ,13
+ ,65475
+ ,69008
+ ,616
+ ,60
+ ,17
+ ,99643
+ ,54968
+ ,1407
+ ,61
+ ,15
+ ,71965
+ ,46090
+ ,771
+ ,85
+ ,16
+ ,77272
+ ,27507
+ ,766
+ ,43
+ ,24
+ ,49289
+ ,10672
+ ,473
+ ,25
+ ,15
+ ,135131
+ ,34029
+ ,1376
+ ,41
+ ,17
+ ,108446
+ ,46300
+ ,1232
+ ,26
+ ,18
+ ,89746
+ ,24760
+ ,1521
+ ,38
+ ,20
+ ,44296
+ ,18779
+ ,572
+ ,12
+ ,16
+ ,77648
+ ,21280
+ ,1059
+ ,29
+ ,16
+ ,181528
+ ,40662
+ ,1544
+ ,49
+ ,18
+ ,134019
+ ,28987
+ ,1230
+ ,46
+ ,22
+ ,124064
+ ,22827
+ ,1206
+ ,41
+ ,8
+ ,92630
+ ,18513
+ ,1205
+ ,31
+ ,17
+ ,121848
+ ,30594
+ ,1255
+ ,41
+ ,18
+ ,52915
+ ,24006
+ ,613
+ ,26
+ ,16
+ ,81872
+ ,27913
+ ,721
+ ,23
+ ,23
+ ,58981
+ ,42744
+ ,1109
+ ,14
+ ,22
+ ,53515
+ ,12934
+ ,740
+ ,16
+ ,13
+ ,60812
+ ,22574
+ ,1126
+ ,25
+ ,13
+ ,56375
+ ,41385
+ ,728
+ ,21
+ ,16
+ ,65490
+ ,18653
+ ,689
+ ,32
+ ,16
+ ,80949
+ ,18472
+ ,592
+ ,9
+ ,20
+ ,76302
+ ,30976
+ ,995
+ ,35
+ ,22
+ ,104011
+ ,63339
+ ,1613
+ ,42
+ ,17
+ ,98104
+ ,25568
+ ,2048
+ ,68
+ ,18
+ ,67989
+ ,33747
+ ,705
+ ,32
+ ,17
+ ,30989
+ ,4154
+ ,301
+ ,6
+ ,12
+ ,135458
+ ,19474
+ ,1803
+ ,68
+ ,7
+ ,73504
+ ,35130
+ ,799
+ ,33
+ ,17
+ ,63123
+ ,39067
+ ,861
+ ,84
+ ,14
+ ,61254
+ ,13310
+ ,1186
+ ,46
+ ,23
+ ,74914
+ ,65892
+ ,1451
+ ,30
+ ,17
+ ,31774
+ ,4143
+ ,628
+ ,0
+ ,14
+ ,81437
+ ,28579
+ ,1161
+ ,36
+ ,15
+ ,87186
+ ,51776
+ ,1463
+ ,47
+ ,17
+ ,50090
+ ,21152
+ ,742
+ ,20
+ ,21
+ ,65745
+ ,38084
+ ,979
+ ,50
+ ,18
+ ,56653
+ ,27717
+ ,675
+ ,30
+ ,18
+ ,158399
+ ,32928
+ ,1241
+ ,30
+ ,17
+ ,46455
+ ,11342
+ ,676
+ ,34
+ ,17
+ ,73624
+ ,19499
+ ,1049
+ ,33
+ ,16
+ ,38395
+ ,16380
+ ,620
+ ,34
+ ,15
+ ,91899
+ ,36874
+ ,1081
+ ,37
+ ,21
+ ,139526
+ ,48259
+ ,1688
+ ,83
+ ,16
+ ,52164
+ ,16734
+ ,736
+ ,32
+ ,14
+ ,51567
+ ,28207
+ ,617
+ ,30
+ ,15
+ ,70551
+ ,30143
+ ,812
+ ,43
+ ,17
+ ,84856
+ ,41369
+ ,1051
+ ,41
+ ,15
+ ,102538
+ ,45833
+ ,1656
+ ,51
+ ,15
+ ,86678
+ ,29156
+ ,705
+ ,19
+ ,10
+ ,85709
+ ,35944
+ ,945
+ ,37
+ ,6
+ ,34662
+ ,36278
+ ,554
+ ,33
+ ,22
+ ,150580
+ ,45588
+ ,1597
+ ,41
+ ,21
+ ,99611
+ ,45097
+ ,982
+ ,54
+ ,1
+ ,19349
+ ,3895
+ ,222
+ ,14
+ ,18
+ ,99373
+ ,28394
+ ,1212
+ ,25
+ ,17
+ ,86230
+ ,18632
+ ,1143
+ ,25
+ ,4
+ ,30837
+ ,2325
+ ,435
+ ,8
+ ,10
+ ,31706
+ ,25139
+ ,532
+ ,26
+ ,16
+ ,89806
+ ,27975
+ ,882
+ ,20
+ ,16
+ ,62088
+ ,14483
+ ,608
+ ,11
+ ,9
+ ,40151
+ ,13127
+ ,459
+ ,14
+ ,16
+ ,27634
+ ,5839
+ ,578
+ ,3
+ ,17
+ ,76990
+ ,24069
+ ,826
+ ,40
+ ,7
+ ,37460
+ ,3738
+ ,509
+ ,5
+ ,15
+ ,54157
+ ,18625
+ ,717
+ ,38
+ ,14
+ ,49862
+ ,36341
+ ,637
+ ,32
+ ,14
+ ,84337
+ ,24548
+ ,857
+ ,41
+ ,18
+ ,64175
+ ,21792
+ ,830
+ ,46
+ ,12
+ ,59382
+ ,26263
+ ,652
+ ,47
+ ,16
+ ,119308
+ ,23686
+ ,707
+ ,37
+ ,21
+ ,76702
+ ,49303
+ ,954
+ ,51
+ ,19
+ ,103425
+ ,25659
+ ,1461
+ ,49
+ ,16
+ ,70344
+ ,28904
+ ,672
+ ,21
+ ,1
+ ,43410
+ ,2781
+ ,778
+ ,1
+ ,16
+ ,104838
+ ,29236
+ ,1141
+ ,44
+ ,10
+ ,62215
+ ,19546
+ ,680
+ ,26
+ ,19
+ ,69304
+ ,22818
+ ,1090
+ ,21
+ ,12
+ ,53117
+ ,32689
+ ,616
+ ,4
+ ,2
+ ,19764
+ ,5752
+ ,285
+ ,10
+ ,14
+ ,86680
+ ,22197
+ ,1145
+ ,43
+ ,17
+ ,84105
+ ,20055
+ ,733
+ ,34
+ ,19
+ ,77945
+ ,25272
+ ,888
+ ,32
+ ,14
+ ,89113
+ ,82206
+ ,849
+ ,20
+ ,11
+ ,91005
+ ,32073
+ ,1182
+ ,34
+ ,4
+ ,40248
+ ,5444
+ ,528
+ ,6
+ ,16
+ ,64187
+ ,20154
+ ,642
+ ,12
+ ,20
+ ,50857
+ ,36944
+ ,947
+ ,24
+ ,12
+ ,56613
+ ,8019
+ ,819
+ ,16
+ ,15
+ ,62792
+ ,30884
+ ,757
+ ,72
+ ,16
+ ,72535
+ ,19540
+ ,894
+ ,27)
+ ,dim=c(5
+ ,289)
+ ,dimnames=list(c('compendiums_reviewed'
+ ,'time_in_rfc'
+ ,'totsize'
+ ,'pageviews'
+ ,'tothyperlinks')
+ ,1:289))
> y <- array(NA,dim=c(5,289),dimnames=list(c('compendiums_reviewed','time_in_rfc','totsize','pageviews','tothyperlinks'),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
compendiums_reviewed time_in_rfc totsize pageviews tothyperlinks
1 30 210907 112285 1418 144
2 28 120982 84786 869 103
3 38 176508 83123 1530 98
4 30 179321 101193 2172 135
5 22 123185 38361 901 61
6 26 52746 68504 463 39
7 25 385534 119182 3201 150
8 18 33170 22807 371 5
9 11 101645 17140 1192 28
10 26 149061 116174 1583 84
11 25 165446 57635 1439 80
12 38 237213 66198 1764 130
13 44 173326 71701 1495 82
14 30 133131 57793 1373 60
15 40 258873 80444 2187 131
16 34 180083 53855 1491 84
17 47 324799 97668 4041 140
18 30 230964 133824 1706 151
19 31 236785 101481 2152 91
20 23 135473 99645 1036 138
21 36 202925 114789 1882 150
22 36 215147 99052 1929 124
23 30 344297 67654 2242 119
24 25 153935 65553 1220 73
25 39 132943 97500 1289 110
26 34 174724 69112 2515 123
27 31 174415 82753 2147 90
28 31 225548 85323 2352 116
29 33 223632 72654 1638 113
30 25 124817 30727 1222 56
31 33 221698 77873 1812 115
32 35 210767 117478 1677 119
33 42 170266 74007 1579 129
34 43 260561 90183 1731 127
35 30 84853 61542 807 27
36 33 294424 101494 2452 175
37 13 101011 27570 829 35
38 32 215641 55813 1940 64
39 36 325107 79215 2662 96
40 0 7176 1423 186 0
41 28 167542 55461 1499 84
42 14 106408 31081 865 41
43 17 96560 22996 1793 47
44 32 265769 83122 2527 126
45 30 269651 70106 2747 105
46 35 149112 60578 1324 80
47 20 175824 39992 2702 70
48 28 152871 79892 1383 73
49 28 111665 49810 1179 57
50 39 116408 71570 2099 40
51 34 362301 100708 4308 68
52 26 78800 33032 918 21
53 39 183167 82875 1831 127
54 39 277965 139077 3373 154
55 33 150629 71595 1713 116
56 28 168809 72260 1438 102
57 4 24188 5950 496 7
58 39 329267 115762 2253 148
59 18 65029 32551 744 21
60 14 101097 31701 1161 35
61 29 218946 80670 2352 112
62 44 244052 143558 2144 137
63 21 341570 117105 4691 135
64 16 103597 23789 1112 26
65 28 233328 120733 2694 230
66 35 256462 105195 1973 181
67 28 206161 73107 1769 71
68 38 311473 132068 3148 147
69 23 235800 149193 2474 190
70 36 177939 46821 2084 64
71 32 207176 87011 1954 105
72 29 196553 95260 1226 107
73 25 174184 55183 1389 94
74 27 143246 106671 1496 116
75 36 187559 73511 2269 106
76 28 187681 92945 1833 143
77 23 119016 78664 1268 81
78 40 182192 70054 1943 89
79 23 73566 22618 893 26
80 40 194979 74011 1762 84
81 28 167488 83737 1403 113
82 34 143756 69094 1425 120
83 33 275541 93133 1857 110
84 28 243199 95536 1840 134
85 34 182999 225920 1502 54
86 30 135649 62133 1441 96
87 33 152299 61370 1420 78
88 22 120221 43836 1416 51
89 38 346485 106117 2970 121
90 26 145790 38692 1317 38
91 35 193339 84651 1644 145
92 8 80953 56622 870 59
93 24 122774 15986 1654 27
94 29 130585 95364 1054 91
95 20 112611 26706 937 48
96 29 286468 89691 3004 68
97 45 241066 67267 2008 58
98 37 148446 126846 2547 150
99 33 204713 41140 1885 74
100 33 182079 102860 1626 181
101 25 140344 51715 1468 65
102 32 220516 55801 2445 97
103 29 243060 111813 1964 121
104 28 162765 120293 1381 99
105 28 182613 138599 1369 152
106 31 232138 161647 1659 188
107 52 265318 115929 2888 138
108 21 85574 24266 1290 40
109 24 310839 162901 2845 254
110 41 225060 109825 1982 87
111 33 232317 129838 1904 178
112 32 144966 37510 1391 51
113 19 43287 43750 602 49
114 20 155754 40652 1743 73
115 31 164709 87771 1559 176
116 31 201940 85872 2014 94
117 32 235454 89275 2143 120
118 18 220801 44418 2146 66
119 23 99466 192565 874 56
120 17 92661 35232 1590 39
121 20 133328 40909 1590 66
122 12 61361 13294 1210 27
123 17 125930 32387 2072 65
124 30 100750 140867 1281 58
125 31 224549 120662 1401 98
126 10 82316 21233 834 25
127 13 102010 44332 1105 26
128 22 101523 61056 1272 77
129 42 243511 101338 1944 130
130 1 22938 1168 391 11
131 9 41566 13497 761 2
132 32 152474 65567 1605 101
133 11 61857 25162 530 31
134 25 99923 32334 1988 36
135 36 132487 40735 1386 120
136 31 317394 91413 2395 195
137 0 21054 855 387 4
138 24 209641 97068 1742 89
139 13 22648 44339 620 24
140 8 31414 14116 449 39
141 13 46698 10288 800 14
142 19 131698 65622 1684 78
143 18 91735 16563 1050 15
144 33 244749 76643 2699 106
145 40 184510 110681 1606 83
146 22 79863 29011 1502 24
147 38 128423 92696 1204 37
148 24 97839 94785 1138 77
149 8 38214 8773 568 16
150 35 151101 83209 1459 56
151 43 272458 93815 2158 132
152 43 172494 86687 1111 144
153 14 108043 34553 1421 40
154 41 328107 105547 2833 153
155 38 250579 103487 1955 143
156 45 351067 213688 2922 220
157 31 158015 71220 1002 79
158 13 98866 23517 1060 50
159 28 85439 56926 956 39
160 31 229242 91721 2186 95
161 40 351619 115168 3604 169
162 30 84207 111194 1035 12
163 16 120445 51009 1417 63
164 37 324598 135777 3261 134
165 30 131069 51513 1587 69
166 35 204271 74163 1424 119
167 32 165543 51633 1701 119
168 27 141722 75345 1249 75
169 20 116048 33416 946 63
170 18 250047 83305 1926 55
171 31 299775 98952 3352 103
172 31 195838 102372 1641 197
173 21 173260 37238 2035 16
174 39 254488 103772 2312 140
175 41 104389 123969 1369 89
176 13 136084 27142 1577 40
177 32 199476 135400 2201 125
178 18 92499 21399 961 21
179 39 224330 130115 1900 167
180 14 135781 24874 1254 32
181 7 74408 34988 1335 36
182 17 81240 45549 1597 13
183 0 14688 6023 207 5
184 30 181633 64466 1645 96
185 37 271856 54990 2429 151
186 0 7199 1644 151 6
187 5 46660 6179 474 13
188 1 17547 3926 141 3
189 16 133368 32755 1639 57
190 32 95227 34777 872 23
191 24 152601 73224 1318 61
192 17 98146 27114 1018 21
193 11 79619 20760 1383 43
194 24 59194 37636 1314 20
195 22 139942 65461 1335 82
196 12 118612 30080 1403 90
197 19 72880 24094 910 25
198 13 65475 69008 616 60
199 17 99643 54968 1407 61
200 15 71965 46090 771 85
201 16 77272 27507 766 43
202 24 49289 10672 473 25
203 15 135131 34029 1376 41
204 17 108446 46300 1232 26
205 18 89746 24760 1521 38
206 20 44296 18779 572 12
207 16 77648 21280 1059 29
208 16 181528 40662 1544 49
209 18 134019 28987 1230 46
210 22 124064 22827 1206 41
211 8 92630 18513 1205 31
212 17 121848 30594 1255 41
213 18 52915 24006 613 26
214 16 81872 27913 721 23
215 23 58981 42744 1109 14
216 22 53515 12934 740 16
217 13 60812 22574 1126 25
218 13 56375 41385 728 21
219 16 65490 18653 689 32
220 16 80949 18472 592 9
221 20 76302 30976 995 35
222 22 104011 63339 1613 42
223 17 98104 25568 2048 68
224 18 67989 33747 705 32
225 17 30989 4154 301 6
226 12 135458 19474 1803 68
227 7 73504 35130 799 33
228 17 63123 39067 861 84
229 14 61254 13310 1186 46
230 23 74914 65892 1451 30
231 17 31774 4143 628 0
232 14 81437 28579 1161 36
233 15 87186 51776 1463 47
234 17 50090 21152 742 20
235 21 65745 38084 979 50
236 18 56653 27717 675 30
237 18 158399 32928 1241 30
238 17 46455 11342 676 34
239 17 73624 19499 1049 33
240 16 38395 16380 620 34
241 15 91899 36874 1081 37
242 21 139526 48259 1688 83
243 16 52164 16734 736 32
244 14 51567 28207 617 30
245 15 70551 30143 812 43
246 17 84856 41369 1051 41
247 15 102538 45833 1656 51
248 15 86678 29156 705 19
249 10 85709 35944 945 37
250 6 34662 36278 554 33
251 22 150580 45588 1597 41
252 21 99611 45097 982 54
253 1 19349 3895 222 14
254 18 99373 28394 1212 25
255 17 86230 18632 1143 25
256 4 30837 2325 435 8
257 10 31706 25139 532 26
258 16 89806 27975 882 20
259 16 62088 14483 608 11
260 9 40151 13127 459 14
261 16 27634 5839 578 3
262 17 76990 24069 826 40
263 7 37460 3738 509 5
264 15 54157 18625 717 38
265 14 49862 36341 637 32
266 14 84337 24548 857 41
267 18 64175 21792 830 46
268 12 59382 26263 652 47
269 16 119308 23686 707 37
270 21 76702 49303 954 51
271 19 103425 25659 1461 49
272 16 70344 28904 672 21
273 1 43410 2781 778 1
274 16 104838 29236 1141 44
275 10 62215 19546 680 26
276 19 69304 22818 1090 21
277 12 53117 32689 616 4
278 2 19764 5752 285 10
279 14 86680 22197 1145 43
280 17 84105 20055 733 34
281 19 77945 25272 888 32
282 14 89113 82206 849 20
283 11 91005 32073 1182 34
284 4 40248 5444 528 6
285 16 64187 20154 642 12
286 20 50857 36944 947 24
287 12 56613 8019 819 16
288 15 62792 30884 757 72
289 16 72535 19540 894 27
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time_in_rfc totsize pageviews tothyperlinks
9.235e+00 5.420e-05 8.669e-05 -9.650e-05 2.479e-02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-22.2275 -4.1642 -0.4548 3.6285 17.2657
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.235e+00 8.258e-01 11.184 < 2e-16 ***
time_in_rfc 5.420e-05 1.276e-05 4.249 2.91e-05 ***
totsize 8.669e-05 1.604e-05 5.404 1.38e-07 ***
pageviews -9.650e-05 1.139e-03 -0.085 0.9325
tothyperlinks 2.479e-02 1.491e-02 1.663 0.0975 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.38 on 284 degrees of freedom
Multiple R-squared: 0.6424, Adjusted R-squared: 0.6374
F-statistic: 127.6 on 4 and 284 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,] 0.6530595 6.938810e-01 3.469405e-01
[2,] 0.6007975 7.984050e-01 3.992025e-01
[3,] 0.5233959 9.532083e-01 4.766041e-01
[4,] 0.4081917 8.163833e-01 5.918083e-01
[5,] 0.5175094 9.649812e-01 4.824906e-01
[6,] 0.9390630 1.218740e-01 6.093700e-02
[7,] 0.9302694 1.394612e-01 6.973061e-02
[8,] 0.9346160 1.307681e-01 6.538404e-02
[9,] 0.9240847 1.518307e-01 7.591534e-02
[10,] 0.9475871 1.048258e-01 5.241292e-02
[11,] 0.9333568 1.332863e-01 6.664316e-02
[12,] 0.9095976 1.808047e-01 9.040236e-02
[13,] 0.9254345 1.491309e-01 7.456547e-02
[14,] 0.8995269 2.009463e-01 1.004731e-01
[15,] 0.8743722 2.512556e-01 1.256278e-01
[16,] 0.8419292 3.161417e-01 1.580708e-01
[17,] 0.8007849 3.984301e-01 1.992151e-01
[18,] 0.8306436 3.387129e-01 1.693564e-01
[19,] 0.8064861 3.870277e-01 1.935139e-01
[20,] 0.7634631 4.730739e-01 2.365369e-01
[21,] 0.7233163 5.533673e-01 2.766837e-01
[22,] 0.6777414 6.445173e-01 3.222586e-01
[23,] 0.6280937 7.438126e-01 3.719063e-01
[24,] 0.5741975 8.516050e-01 4.258025e-01
[25,] 0.5324119 9.351761e-01 4.675881e-01
[26,] 0.5924982 8.150036e-01 4.075018e-01
[27,] 0.6755999 6.488002e-01 3.244001e-01
[28,] 0.6997458 6.005084e-01 3.002542e-01
[29,] 0.6889211 6.221578e-01 3.110789e-01
[30,] 0.7521616 4.956768e-01 2.478384e-01
[31,] 0.7259032 5.481935e-01 2.740968e-01
[32,] 0.6910693 6.178614e-01 3.089307e-01
[33,] 0.8685869 2.628262e-01 1.314131e-01
[34,] 0.8414037 3.171926e-01 1.585963e-01
[35,] 0.8437257 3.125486e-01 1.562743e-01
[36,] 0.8371118 3.257764e-01 1.628882e-01
[37,] 0.8117434 3.765132e-01 1.882566e-01
[38,] 0.7849379 4.301242e-01 2.150621e-01
[39,] 0.8111451 3.777099e-01 1.888549e-01
[40,] 0.8102247 3.795506e-01 1.897753e-01
[41,] 0.7778406 4.443187e-01 2.221594e-01
[42,] 0.7630562 4.738875e-01 2.369438e-01
[43,] 0.8552509 2.894982e-01 1.447491e-01
[44,] 0.8394535 3.210930e-01 1.605465e-01
[45,] 0.8394384 3.211233e-01 1.605616e-01
[46,] 0.8457382 3.085237e-01 1.542618e-01
[47,] 0.8258147 3.483706e-01 1.741853e-01
[48,] 0.8074870 3.850260e-01 1.925130e-01
[49,] 0.7788770 4.422460e-01 2.211230e-01
[50,] 0.8364259 3.271482e-01 1.635741e-01
[51,] 0.8092624 3.814752e-01 1.907376e-01
[52,] 0.7809946 4.380107e-01 2.190054e-01
[53,] 0.7792591 4.414819e-01 2.207409e-01
[54,] 0.7559518 4.880964e-01 2.440482e-01
[55,] 0.7382567 5.234866e-01 2.617433e-01
[56,] 0.9273882 1.452236e-01 7.261181e-02
[57,] 0.9152641 1.694718e-01 8.473592e-02
[58,] 0.9443783 1.112434e-01 5.562170e-02
[59,] 0.9332436 1.335128e-01 6.675641e-02
[60,] 0.9197998 1.604003e-01 8.020017e-02
[61,] 0.9066652 1.866696e-01 9.333482e-02
[62,] 0.9704955 5.900897e-02 2.950449e-02
[63,] 0.9803220 3.935600e-02 1.967800e-02
[64,] 0.9753324 4.933527e-02 2.466763e-02
[65,] 0.9706362 5.872769e-02 2.936384e-02
[66,] 0.9642204 7.155930e-02 3.577965e-02
[67,] 0.9584478 8.310448e-02 4.155224e-02
[68,] 0.9604690 7.906196e-02 3.953098e-02
[69,] 0.9539850 9.202990e-02 4.601495e-02
[70,] 0.9469202 1.061596e-01 5.307979e-02
[71,] 0.9672010 6.559810e-02 3.279905e-02
[72,] 0.9646588 7.068245e-02 3.534123e-02
[73,] 0.9764086 4.718279e-02 2.359139e-02
[74,] 0.9711175 5.776508e-02 2.888254e-02
[75,] 0.9726078 5.478450e-02 2.739225e-02
[76,] 0.9666671 6.666571e-02 3.333285e-02
[77,] 0.9651999 6.960026e-02 3.480013e-02
[78,] 0.9630398 7.392045e-02 3.696022e-02
[79,] 0.9592161 8.156782e-02 4.078391e-02
[80,] 0.9612229 7.755430e-02 3.877715e-02
[81,] 0.9537232 9.255357e-02 4.627678e-02
[82,] 0.9449740 1.100520e-01 5.502598e-02
[83,] 0.9372651 1.254699e-01 6.273494e-02
[84,] 0.9306185 1.387629e-01 6.938146e-02
[85,] 0.9663690 6.726196e-02 3.363098e-02
[86,] 0.9626473 7.470536e-02 3.735268e-02
[87,] 0.9555750 8.885001e-02 4.442501e-02
[88,] 0.9481436 1.037128e-01 5.185640e-02
[89,] 0.9443007 1.113986e-01 5.569929e-02
[90,] 0.9778058 4.438847e-02 2.219423e-02
[91,] 0.9759030 4.819407e-02 2.409704e-02
[92,] 0.9763289 4.734215e-02 2.367107e-02
[93,] 0.9711855 5.762899e-02 2.881449e-02
[94,] 0.9655346 6.893080e-02 3.446540e-02
[95,] 0.9602169 7.956621e-02 3.978311e-02
[96,] 0.9582411 8.351784e-02 4.175892e-02
[97,] 0.9516485 9.670298e-02 4.835149e-02
[98,] 0.9512111 9.757778e-02 4.878889e-02
[99,] 0.9562455 8.750891e-02 4.375446e-02
[100,] 0.9847490 3.050196e-02 1.525098e-02
[101,] 0.9823015 3.539706e-02 1.769853e-02
[102,] 0.9985538 2.892399e-03 1.446199e-03
[103,] 0.9988271 2.345713e-03 1.172857e-03
[104,] 0.9986696 2.660865e-03 1.330433e-03
[105,] 0.9991353 1.729480e-03 8.647398e-04
[106,] 0.9988897 2.220580e-03 1.110290e-03
[107,] 0.9987347 2.530618e-03 1.265309e-03
[108,] 0.9983525 3.295060e-03 1.647530e-03
[109,] 0.9978519 4.296299e-03 2.148149e-03
[110,] 0.9972017 5.596589e-03 2.798295e-03
[111,] 0.9979558 4.088415e-03 2.044207e-03
[112,] 0.9988926 2.214887e-03 1.107444e-03
[113,] 0.9986769 2.646210e-03 1.323105e-03
[114,] 0.9983910 3.217999e-03 1.609000e-03
[115,] 0.9982527 3.494637e-03 1.747319e-03
[116,] 0.9980518 3.896307e-03 1.948154e-03
[117,] 0.9975393 4.921414e-03 2.460707e-03
[118,] 0.9970727 5.854651e-03 2.927326e-03
[119,] 0.9975155 4.968973e-03 2.484486e-03
[120,] 0.9977938 4.412473e-03 2.206236e-03
[121,] 0.9971579 5.684132e-03 2.842066e-03
[122,] 0.9975372 4.925561e-03 2.462780e-03
[123,] 0.9987360 2.527954e-03 1.263977e-03
[124,] 0.9986286 2.742749e-03 1.371374e-03
[125,] 0.9985937 2.812607e-03 1.406303e-03
[126,] 0.9985280 2.943906e-03 1.471953e-03
[127,] 0.9986037 2.792647e-03 1.396324e-03
[128,] 0.9994939 1.012159e-03 5.060797e-04
[129,] 0.9995486 9.028319e-04 4.514160e-04
[130,] 0.9997952 4.095833e-04 2.047916e-04
[131,] 0.9998282 3.436709e-04 1.718355e-04
[132,] 0.9997817 4.365530e-04 2.182765e-04
[133,] 0.9997780 4.440233e-04 2.220116e-04
[134,] 0.9997076 5.848626e-04 2.924313e-04
[135,] 0.9996816 6.368316e-04 3.184158e-04
[136,] 0.9996001 7.998287e-04 3.999144e-04
[137,] 0.9994795 1.040960e-03 5.204801e-04
[138,] 0.9995983 8.033656e-04 4.016828e-04
[139,] 0.9995944 8.111380e-04 4.055690e-04
[140,] 0.9998427 3.146191e-04 1.573095e-04
[141,] 0.9997888 4.223936e-04 2.111968e-04
[142,] 0.9997659 4.682876e-04 2.341438e-04
[143,] 0.9998387 3.226708e-04 1.613354e-04
[144,] 0.9998783 2.433438e-04 1.216719e-04
[145,] 0.9999648 7.040389e-05 3.520195e-05
[146,] 0.9999604 7.915576e-05 3.957788e-05
[147,] 0.9999479 1.042333e-04 5.211664e-05
[148,] 0.9999348 1.304096e-04 6.520478e-05
[149,] 0.9999522 9.560270e-05 4.780135e-05
[150,] 0.9999482 1.035683e-04 5.178414e-05
[151,] 0.9999406 1.187572e-04 5.937862e-05
[152,] 0.9999553 8.943611e-05 4.471806e-05
[153,] 0.9999364 1.272969e-04 6.364843e-05
[154,] 0.9999105 1.790790e-04 8.953952e-05
[155,] 0.9999048 1.904889e-04 9.524444e-05
[156,] 0.9999015 1.969966e-04 9.849830e-05
[157,] 0.9998828 2.344238e-04 1.172119e-04
[158,] 0.9999081 1.838459e-04 9.192294e-05
[159,] 0.9999105 1.790295e-04 8.951476e-05
[160,] 0.9999237 1.526438e-04 7.632189e-05
[161,] 0.9998968 2.064796e-04 1.032398e-04
[162,] 0.9998608 2.783179e-04 1.391590e-04
[163,] 0.9999571 8.577974e-05 4.288987e-05
[164,] 0.9999558 8.845011e-05 4.422506e-05
[165,] 0.9999395 1.209265e-04 6.046327e-05
[166,] 0.9999150 1.699154e-04 8.495772e-05
[167,] 0.9998930 2.140819e-04 1.070410e-04
[168,] 0.9999705 5.891274e-05 2.945637e-05
[169,] 0.9999742 5.168557e-05 2.584278e-05
[170,] 0.9999653 6.933489e-05 3.466744e-05
[171,] 0.9999527 9.455456e-05 4.727728e-05
[172,] 0.9999386 1.228016e-04 6.140078e-05
[173,] 0.9999347 1.306352e-04 6.531758e-05
[174,] 0.9999699 6.028206e-05 3.014103e-05
[175,] 0.9999572 8.558336e-05 4.279168e-05
[176,] 0.9999801 3.980803e-05 1.990401e-05
[177,] 0.9999768 4.648793e-05 2.324396e-05
[178,] 0.9999859 2.820023e-05 1.410012e-05
[179,] 0.9999939 1.217200e-05 6.085999e-06
[180,] 0.9999955 9.089317e-06 4.544658e-06
[181,] 0.9999982 3.564659e-06 1.782330e-06
[182,] 0.9999976 4.860927e-06 2.430463e-06
[183,] 0.9999999 2.322191e-07 1.161096e-07
[184,] 0.9999998 3.460133e-07 1.730066e-07
[185,] 0.9999997 5.634948e-07 2.817474e-07
[186,] 0.9999997 5.848257e-07 2.924128e-07
[187,] 0.9999998 4.223117e-07 2.111558e-07
[188,] 0.9999997 6.459178e-07 3.229589e-07
[189,] 0.9999997 5.667389e-07 2.833695e-07
[190,] 0.9999996 7.343469e-07 3.671735e-07
[191,] 0.9999996 7.572415e-07 3.786208e-07
[192,] 0.9999994 1.113996e-06 5.569979e-07
[193,] 0.9999992 1.603102e-06 8.015512e-07
[194,] 0.9999987 2.592162e-06 1.296081e-06
[195,] 0.9999998 4.616424e-07 2.308212e-07
[196,] 0.9999997 6.118440e-07 3.059220e-07
[197,] 0.9999995 9.769950e-07 4.884975e-07
[198,] 0.9999992 1.592409e-06 7.962044e-07
[199,] 0.9999994 1.102138e-06 5.510691e-07
[200,] 0.9999991 1.810347e-06 9.051735e-07
[201,] 0.9999991 1.811902e-06 9.059508e-07
[202,] 0.9999985 2.970341e-06 1.485171e-06
[203,] 0.9999984 3.237980e-06 1.618990e-06
[204,] 0.9999991 1.856643e-06 9.283214e-07
[205,] 0.9999985 3.036307e-06 1.518154e-06
[206,] 0.9999982 3.632456e-06 1.816228e-06
[207,] 0.9999970 5.903882e-06 2.951941e-06
[208,] 0.9999979 4.206915e-06 2.103457e-06
[209,] 0.9999993 1.325530e-06 6.627649e-07
[210,] 0.9999989 2.188001e-06 1.094000e-06
[211,] 0.9999983 3.395952e-06 1.697976e-06
[212,] 0.9999974 5.189170e-06 2.594585e-06
[213,] 0.9999962 7.659492e-06 3.829746e-06
[214,] 0.9999955 9.011747e-06 4.505873e-06
[215,] 0.9999928 1.442199e-05 7.210993e-06
[216,] 0.9999886 2.271251e-05 1.135626e-05
[217,] 0.9999845 3.109588e-05 1.554794e-05
[218,] 0.9999908 1.833799e-05 9.168996e-06
[219,] 0.9999963 7.379638e-06 3.689819e-06
[220,] 0.9999985 3.087102e-06 1.543551e-06
[221,] 0.9999973 5.416370e-06 2.708185e-06
[222,] 0.9999955 9.016864e-06 4.508432e-06
[223,] 0.9999947 1.067899e-05 5.339497e-06
[224,] 0.9999974 5.221655e-06 2.610828e-06
[225,] 0.9999958 8.326447e-06 4.163223e-06
[226,] 0.9999952 9.654820e-06 4.827410e-06
[227,] 0.9999948 1.049222e-05 5.246109e-06
[228,] 0.9999941 1.178005e-05 5.890026e-06
[229,] 0.9999939 1.222700e-05 6.113501e-06
[230,] 0.9999903 1.938193e-05 9.690964e-06
[231,] 0.9999905 1.893848e-05 9.469241e-06
[232,] 0.9999851 2.972449e-05 1.486225e-05
[233,] 0.9999849 3.020581e-05 1.510290e-05
[234,] 0.9999755 4.893443e-05 2.446721e-05
[235,] 0.9999685 6.301048e-05 3.150524e-05
[236,] 0.9999609 7.815231e-05 3.907615e-05
[237,] 0.9999373 1.254717e-04 6.273586e-05
[238,] 0.9998917 2.165074e-04 1.082537e-04
[239,] 0.9998148 3.703471e-04 1.851735e-04
[240,] 0.9998703 2.593035e-04 1.296518e-04
[241,] 0.9997843 4.313097e-04 2.156548e-04
[242,] 0.9998605 2.789397e-04 1.394698e-04
[243,] 0.9999001 1.998980e-04 9.994901e-05
[244,] 0.9998466 3.067579e-04 1.533790e-04
[245,] 0.9997383 5.233631e-04 2.616815e-04
[246,] 0.9997640 4.719429e-04 2.359715e-04
[247,] 0.9995817 8.366357e-04 4.183178e-04
[248,] 0.9992908 1.418396e-03 7.091979e-04
[249,] 0.9991415 1.717081e-03 8.585403e-04
[250,] 0.9985980 2.803940e-03 1.401970e-03
[251,] 0.9976885 4.622998e-03 2.311499e-03
[252,] 0.9977268 4.546493e-03 2.273247e-03
[253,] 0.9962216 7.556834e-03 3.778417e-03
[254,] 0.9984982 3.003536e-03 1.501768e-03
[255,] 0.9975488 4.902402e-03 2.451201e-03
[256,] 0.9957858 8.428494e-03 4.214247e-03
[257,] 0.9934214 1.315725e-02 6.578624e-03
[258,] 0.9890765 2.184702e-02 1.092351e-02
[259,] 0.9828072 3.438551e-02 1.719276e-02
[260,] 0.9775080 4.498395e-02 2.249197e-02
[261,] 0.9661972 6.760568e-02 3.380284e-02
[262,] 0.9474008 1.051984e-01 5.259918e-02
[263,] 0.9279021 1.441958e-01 7.209790e-02
[264,] 0.8929863 2.140274e-01 1.070137e-01
[265,] 0.8650609 2.698782e-01 1.349391e-01
[266,] 0.9235225 1.529550e-01 7.647752e-02
[267,] 0.8884874 2.230252e-01 1.115126e-01
[268,] 0.8393985 3.212029e-01 1.606015e-01
[269,] 0.7951195 4.097611e-01 2.048805e-01
[270,] 0.7089693 5.820614e-01 2.910307e-01
[271,] 0.7029503 5.940993e-01 2.970497e-01
[272,] 0.5964337 8.071325e-01 4.035663e-01
[273,] 0.4930347 9.860695e-01 5.069653e-01
[274,] 0.4473136 8.946272e-01 5.526864e-01
> postscript(file="/var/wessaorg/rcomp/tmp/19qxr1324134631.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2woyx1324134631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3mazk1324134631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4xjxf1324134631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5heqv1324134631.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
-3.833858278 2.387644989 9.709801410 -0.864359820 1.336942461
6 7 8 9 10
7.045081081 -18.873918636 4.901504000 -5.809779340 -3.315420791
11 12 13 14 15
-0.043672036 7.115869049 17.265673361 7.183646973 6.722883345
16 17 18 19 20
8.396484884 8.612126116 -6.933931240 -1.915330845 -5.537418732
21 22 23 24 25
2.277776904 3.628549053 -6.495938002 0.046264856 11.504168195
26 27 28 29 30
6.496419648 3.113179281 -0.505957332 2.701610181 5.065179171
31 32 33 34 35
2.321230541 1.368277051 14.074663354 8.842282960 10.238934254
36 37 38 39 40
-5.094047327 -4.888122197 4.838467417 0.152716783 -9.729687611
41 42 43 44 45
2.937810233 -4.630282561 -0.454786261 -1.726302864 -2.266595416
46 47 48 49 50
10.575477900 -3.706994217 1.876650000 7.094867766 16.461643125
51 52 53 54 55
-4.873601049 9.197950053 9.680523965 -0.850446700 6.683348638
56 57 58 59 60
0.960776058 -7.187850881 -1.569449286 1.969300514 -4.218852331
61 62 63 64 65
-1.645587046 5.902138036 -19.795212775 -1.450116330 -9.790216143
66 67 68 69 70
-1.552140492 -0.336882817 -2.907314366 -16.421021698 11.675466302
71 72 73 74 75
1.577821407 -1.681289255 -0.656618910 -1.978069204 7.817040813
76 77 78 79 80
-2.833530449 -1.391225232 12.797585795 7.258065459 11.867930681
81 82 83 84 85
-0.238593211 8.145751492 -1.791853556 -5.843668659 -5.932803656
86 87 88 89 90
5.785096946 8.392914640 1.320575641 -1.928137450 4.693254581
91 92 93 94 95
4.510955159 -11.910330292 6.214352878 2.265457823 1.246174752
96 97 98 99 100
-4.933938457 15.622699331 5.249742954 7.449585430 0.648655611
101 102 103 104 105
2.204785043 3.805962945 -5.912931400 -2.806629268 -6.784352352
106 107 108 109 110
-9.331210311 15.191543377 4.155587725 -22.227451469 8.079638639
111 112 113 114 115
-4.311924118 10.525269407 2.469195924 -2.843244963 1.015694438
116 117 118 119 120
1.238840039 -0.504819147 -8.483115072 -9.623675563 -1.125436786
121 122 123 124 125
-1.491184425 -2.266291997 -3.280123970 1.778017941 -3.160846759
126 127 128 129 130
-6.077062808 -6.145599953 0.182910449 7.745648320 -9.814842565
131 132 133 134 135
-3.634526188 6.467308020 -4.486767739 6.844929569 13.211197206
136 137 138 139 140
-7.966494311 -10.512452308 -7.051448555 -1.841684259 -5.085204312
141 142 143 144 145
0.071776478 -4.833545929 2.085954888 1.487096035 9.266281898
146 147 148 149 150
5.470894672 12.967007109 -0.554230062 -4.408990068 9.113793184
151 152 153 154 155
7.799828317 13.437696262 -4.941441818 1.310972323 2.855046849
156 157 158 159 160
-6.960341717 5.164080224 -4.770049390 8.324234269 -0.756269353
161 162 163 164 165
-2.119718092 6.363557680 -5.610748963 -4.607108515 7.637367727
166 167 168 169 170
5.450859223 6.529887700 1.812632648 0.107234062 -13.187955604
171 172 173 174 175
-5.292078286 -2.450010410 -1.055043269 3.727275365 13.285657859
176 177 178 179 180
-6.803881321 -2.671490487 1.467997836 2.369283762 -5.423708704
181 182 183 184 185
-10.065138487 -0.755543518 -10.657551533 3.110017573 4.753281225
186 187 188 189 190
-9.902203412 -7.576634392 -9.587528024 -4.558670393 14.102251216
191 192 193 194 195
-1.239485649 -0.328013731 -5.283090620 7.924569616 -2.399283547
196 197 198 199 200
-8.367752711 3.193727592 -7.194376116 -3.777779151 -4.164211693
201 202 203 204 205
-0.800299755 10.593810681 -5.393430683 -2.652803665 0.958494396
206 207 208 209 210
6.493482602 0.094445504 -7.665439841 -2.034109238 3.161119053
211 212 213 214 215
-8.513263707 -2.387341010 3.230091277 -0.593398626 6.622263345
216 217 218 219 220
8.417522559 -1.999526380 -3.328962052 0.871115519 0.609648222
221 222 223 224 225
3.171968462 0.750661540 -1.257397393 1.428735873 5.605168949
226 227 228 229 230
-7.777506062 -10.005806919 -1.042655131 -0.735184487 3.388358424
231 232 233 234 235
5.743862435 -2.907348126 -4.473401400 2.791807742 3.754646129
236 237 238 239 240
2.612604909 -3.299559251 3.485834403 1.366833496 2.480581794
241 242 243 244 245
-3.226017401 -1.876252000 1.764329705 -1.159787133 -1.660063926
246 247 248 249 250
-1.335970607 -4.870887427 -1.864045250 -7.822998509 -9.023570844
251 252 253 254 255
-0.211528863 1.212160156 -9.947377734 0.414083343 0.966077140
256 257 258 259 260
-7.264686116 -3.726327327 -0.938925105 1.929756904 -3.852363814
261 262 263 264 265
4.742052946 0.593175850 -4.664662181 0.341806970 -1.820136404
266 267 268 269 270
-2.868382780 2.336842893 -3.832904954 -2.604550726 2.160978014
271 272 273 274 275
0.860635306 -0.009591897 -10.779101335 -2.432974522 -4.880913329
276 277 278 279 280
3.614701697 -2.987923755 -9.025616567 -2.813364501 0.695237318
281 282 283 284 285
2.641419810 -7.605719185 -6.677256565 -7.986628263 1.302867403
286 287 288 289
4.301885077 -1.316706915 -2.027915765 0.556082962
> postscript(file="/var/wessaorg/rcomp/tmp/6xlnm1324134631.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 -3.833858278 NA
1 2.387644989 -3.833858278
2 9.709801410 2.387644989
3 -0.864359820 9.709801410
4 1.336942461 -0.864359820
5 7.045081081 1.336942461
6 -18.873918636 7.045081081
7 4.901504000 -18.873918636
8 -5.809779340 4.901504000
9 -3.315420791 -5.809779340
10 -0.043672036 -3.315420791
11 7.115869049 -0.043672036
12 17.265673361 7.115869049
13 7.183646973 17.265673361
14 6.722883345 7.183646973
15 8.396484884 6.722883345
16 8.612126116 8.396484884
17 -6.933931240 8.612126116
18 -1.915330845 -6.933931240
19 -5.537418732 -1.915330845
20 2.277776904 -5.537418732
21 3.628549053 2.277776904
22 -6.495938002 3.628549053
23 0.046264856 -6.495938002
24 11.504168195 0.046264856
25 6.496419648 11.504168195
26 3.113179281 6.496419648
27 -0.505957332 3.113179281
28 2.701610181 -0.505957332
29 5.065179171 2.701610181
30 2.321230541 5.065179171
31 1.368277051 2.321230541
32 14.074663354 1.368277051
33 8.842282960 14.074663354
34 10.238934254 8.842282960
35 -5.094047327 10.238934254
36 -4.888122197 -5.094047327
37 4.838467417 -4.888122197
38 0.152716783 4.838467417
39 -9.729687611 0.152716783
40 2.937810233 -9.729687611
41 -4.630282561 2.937810233
42 -0.454786261 -4.630282561
43 -1.726302864 -0.454786261
44 -2.266595416 -1.726302864
45 10.575477900 -2.266595416
46 -3.706994217 10.575477900
47 1.876650000 -3.706994217
48 7.094867766 1.876650000
49 16.461643125 7.094867766
50 -4.873601049 16.461643125
51 9.197950053 -4.873601049
52 9.680523965 9.197950053
53 -0.850446700 9.680523965
54 6.683348638 -0.850446700
55 0.960776058 6.683348638
56 -7.187850881 0.960776058
57 -1.569449286 -7.187850881
58 1.969300514 -1.569449286
59 -4.218852331 1.969300514
60 -1.645587046 -4.218852331
61 5.902138036 -1.645587046
62 -19.795212775 5.902138036
63 -1.450116330 -19.795212775
64 -9.790216143 -1.450116330
65 -1.552140492 -9.790216143
66 -0.336882817 -1.552140492
67 -2.907314366 -0.336882817
68 -16.421021698 -2.907314366
69 11.675466302 -16.421021698
70 1.577821407 11.675466302
71 -1.681289255 1.577821407
72 -0.656618910 -1.681289255
73 -1.978069204 -0.656618910
74 7.817040813 -1.978069204
75 -2.833530449 7.817040813
76 -1.391225232 -2.833530449
77 12.797585795 -1.391225232
78 7.258065459 12.797585795
79 11.867930681 7.258065459
80 -0.238593211 11.867930681
81 8.145751492 -0.238593211
82 -1.791853556 8.145751492
83 -5.843668659 -1.791853556
84 -5.932803656 -5.843668659
85 5.785096946 -5.932803656
86 8.392914640 5.785096946
87 1.320575641 8.392914640
88 -1.928137450 1.320575641
89 4.693254581 -1.928137450
90 4.510955159 4.693254581
91 -11.910330292 4.510955159
92 6.214352878 -11.910330292
93 2.265457823 6.214352878
94 1.246174752 2.265457823
95 -4.933938457 1.246174752
96 15.622699331 -4.933938457
97 5.249742954 15.622699331
98 7.449585430 5.249742954
99 0.648655611 7.449585430
100 2.204785043 0.648655611
101 3.805962945 2.204785043
102 -5.912931400 3.805962945
103 -2.806629268 -5.912931400
104 -6.784352352 -2.806629268
105 -9.331210311 -6.784352352
106 15.191543377 -9.331210311
107 4.155587725 15.191543377
108 -22.227451469 4.155587725
109 8.079638639 -22.227451469
110 -4.311924118 8.079638639
111 10.525269407 -4.311924118
112 2.469195924 10.525269407
113 -2.843244963 2.469195924
114 1.015694438 -2.843244963
115 1.238840039 1.015694438
116 -0.504819147 1.238840039
117 -8.483115072 -0.504819147
118 -9.623675563 -8.483115072
119 -1.125436786 -9.623675563
120 -1.491184425 -1.125436786
121 -2.266291997 -1.491184425
122 -3.280123970 -2.266291997
123 1.778017941 -3.280123970
124 -3.160846759 1.778017941
125 -6.077062808 -3.160846759
126 -6.145599953 -6.077062808
127 0.182910449 -6.145599953
128 7.745648320 0.182910449
129 -9.814842565 7.745648320
130 -3.634526188 -9.814842565
131 6.467308020 -3.634526188
132 -4.486767739 6.467308020
133 6.844929569 -4.486767739
134 13.211197206 6.844929569
135 -7.966494311 13.211197206
136 -10.512452308 -7.966494311
137 -7.051448555 -10.512452308
138 -1.841684259 -7.051448555
139 -5.085204312 -1.841684259
140 0.071776478 -5.085204312
141 -4.833545929 0.071776478
142 2.085954888 -4.833545929
143 1.487096035 2.085954888
144 9.266281898 1.487096035
145 5.470894672 9.266281898
146 12.967007109 5.470894672
147 -0.554230062 12.967007109
148 -4.408990068 -0.554230062
149 9.113793184 -4.408990068
150 7.799828317 9.113793184
151 13.437696262 7.799828317
152 -4.941441818 13.437696262
153 1.310972323 -4.941441818
154 2.855046849 1.310972323
155 -6.960341717 2.855046849
156 5.164080224 -6.960341717
157 -4.770049390 5.164080224
158 8.324234269 -4.770049390
159 -0.756269353 8.324234269
160 -2.119718092 -0.756269353
161 6.363557680 -2.119718092
162 -5.610748963 6.363557680
163 -4.607108515 -5.610748963
164 7.637367727 -4.607108515
165 5.450859223 7.637367727
166 6.529887700 5.450859223
167 1.812632648 6.529887700
168 0.107234062 1.812632648
169 -13.187955604 0.107234062
170 -5.292078286 -13.187955604
171 -2.450010410 -5.292078286
172 -1.055043269 -2.450010410
173 3.727275365 -1.055043269
174 13.285657859 3.727275365
175 -6.803881321 13.285657859
176 -2.671490487 -6.803881321
177 1.467997836 -2.671490487
178 2.369283762 1.467997836
179 -5.423708704 2.369283762
180 -10.065138487 -5.423708704
181 -0.755543518 -10.065138487
182 -10.657551533 -0.755543518
183 3.110017573 -10.657551533
184 4.753281225 3.110017573
185 -9.902203412 4.753281225
186 -7.576634392 -9.902203412
187 -9.587528024 -7.576634392
188 -4.558670393 -9.587528024
189 14.102251216 -4.558670393
190 -1.239485649 14.102251216
191 -0.328013731 -1.239485649
192 -5.283090620 -0.328013731
193 7.924569616 -5.283090620
194 -2.399283547 7.924569616
195 -8.367752711 -2.399283547
196 3.193727592 -8.367752711
197 -7.194376116 3.193727592
198 -3.777779151 -7.194376116
199 -4.164211693 -3.777779151
200 -0.800299755 -4.164211693
201 10.593810681 -0.800299755
202 -5.393430683 10.593810681
203 -2.652803665 -5.393430683
204 0.958494396 -2.652803665
205 6.493482602 0.958494396
206 0.094445504 6.493482602
207 -7.665439841 0.094445504
208 -2.034109238 -7.665439841
209 3.161119053 -2.034109238
210 -8.513263707 3.161119053
211 -2.387341010 -8.513263707
212 3.230091277 -2.387341010
213 -0.593398626 3.230091277
214 6.622263345 -0.593398626
215 8.417522559 6.622263345
216 -1.999526380 8.417522559
217 -3.328962052 -1.999526380
218 0.871115519 -3.328962052
219 0.609648222 0.871115519
220 3.171968462 0.609648222
221 0.750661540 3.171968462
222 -1.257397393 0.750661540
223 1.428735873 -1.257397393
224 5.605168949 1.428735873
225 -7.777506062 5.605168949
226 -10.005806919 -7.777506062
227 -1.042655131 -10.005806919
228 -0.735184487 -1.042655131
229 3.388358424 -0.735184487
230 5.743862435 3.388358424
231 -2.907348126 5.743862435
232 -4.473401400 -2.907348126
233 2.791807742 -4.473401400
234 3.754646129 2.791807742
235 2.612604909 3.754646129
236 -3.299559251 2.612604909
237 3.485834403 -3.299559251
238 1.366833496 3.485834403
239 2.480581794 1.366833496
240 -3.226017401 2.480581794
241 -1.876252000 -3.226017401
242 1.764329705 -1.876252000
243 -1.159787133 1.764329705
244 -1.660063926 -1.159787133
245 -1.335970607 -1.660063926
246 -4.870887427 -1.335970607
247 -1.864045250 -4.870887427
248 -7.822998509 -1.864045250
249 -9.023570844 -7.822998509
250 -0.211528863 -9.023570844
251 1.212160156 -0.211528863
252 -9.947377734 1.212160156
253 0.414083343 -9.947377734
254 0.966077140 0.414083343
255 -7.264686116 0.966077140
256 -3.726327327 -7.264686116
257 -0.938925105 -3.726327327
258 1.929756904 -0.938925105
259 -3.852363814 1.929756904
260 4.742052946 -3.852363814
261 0.593175850 4.742052946
262 -4.664662181 0.593175850
263 0.341806970 -4.664662181
264 -1.820136404 0.341806970
265 -2.868382780 -1.820136404
266 2.336842893 -2.868382780
267 -3.832904954 2.336842893
268 -2.604550726 -3.832904954
269 2.160978014 -2.604550726
270 0.860635306 2.160978014
271 -0.009591897 0.860635306
272 -10.779101335 -0.009591897
273 -2.432974522 -10.779101335
274 -4.880913329 -2.432974522
275 3.614701697 -4.880913329
276 -2.987923755 3.614701697
277 -9.025616567 -2.987923755
278 -2.813364501 -9.025616567
279 0.695237318 -2.813364501
280 2.641419810 0.695237318
281 -7.605719185 2.641419810
282 -6.677256565 -7.605719185
283 -7.986628263 -6.677256565
284 1.302867403 -7.986628263
285 4.301885077 1.302867403
286 -1.316706915 4.301885077
287 -2.027915765 -1.316706915
288 0.556082962 -2.027915765
289 NA 0.556082962
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.387644989 -3.833858278
[2,] 9.709801410 2.387644989
[3,] -0.864359820 9.709801410
[4,] 1.336942461 -0.864359820
[5,] 7.045081081 1.336942461
[6,] -18.873918636 7.045081081
[7,] 4.901504000 -18.873918636
[8,] -5.809779340 4.901504000
[9,] -3.315420791 -5.809779340
[10,] -0.043672036 -3.315420791
[11,] 7.115869049 -0.043672036
[12,] 17.265673361 7.115869049
[13,] 7.183646973 17.265673361
[14,] 6.722883345 7.183646973
[15,] 8.396484884 6.722883345
[16,] 8.612126116 8.396484884
[17,] -6.933931240 8.612126116
[18,] -1.915330845 -6.933931240
[19,] -5.537418732 -1.915330845
[20,] 2.277776904 -5.537418732
[21,] 3.628549053 2.277776904
[22,] -6.495938002 3.628549053
[23,] 0.046264856 -6.495938002
[24,] 11.504168195 0.046264856
[25,] 6.496419648 11.504168195
[26,] 3.113179281 6.496419648
[27,] -0.505957332 3.113179281
[28,] 2.701610181 -0.505957332
[29,] 5.065179171 2.701610181
[30,] 2.321230541 5.065179171
[31,] 1.368277051 2.321230541
[32,] 14.074663354 1.368277051
[33,] 8.842282960 14.074663354
[34,] 10.238934254 8.842282960
[35,] -5.094047327 10.238934254
[36,] -4.888122197 -5.094047327
[37,] 4.838467417 -4.888122197
[38,] 0.152716783 4.838467417
[39,] -9.729687611 0.152716783
[40,] 2.937810233 -9.729687611
[41,] -4.630282561 2.937810233
[42,] -0.454786261 -4.630282561
[43,] -1.726302864 -0.454786261
[44,] -2.266595416 -1.726302864
[45,] 10.575477900 -2.266595416
[46,] -3.706994217 10.575477900
[47,] 1.876650000 -3.706994217
[48,] 7.094867766 1.876650000
[49,] 16.461643125 7.094867766
[50,] -4.873601049 16.461643125
[51,] 9.197950053 -4.873601049
[52,] 9.680523965 9.197950053
[53,] -0.850446700 9.680523965
[54,] 6.683348638 -0.850446700
[55,] 0.960776058 6.683348638
[56,] -7.187850881 0.960776058
[57,] -1.569449286 -7.187850881
[58,] 1.969300514 -1.569449286
[59,] -4.218852331 1.969300514
[60,] -1.645587046 -4.218852331
[61,] 5.902138036 -1.645587046
[62,] -19.795212775 5.902138036
[63,] -1.450116330 -19.795212775
[64,] -9.790216143 -1.450116330
[65,] -1.552140492 -9.790216143
[66,] -0.336882817 -1.552140492
[67,] -2.907314366 -0.336882817
[68,] -16.421021698 -2.907314366
[69,] 11.675466302 -16.421021698
[70,] 1.577821407 11.675466302
[71,] -1.681289255 1.577821407
[72,] -0.656618910 -1.681289255
[73,] -1.978069204 -0.656618910
[74,] 7.817040813 -1.978069204
[75,] -2.833530449 7.817040813
[76,] -1.391225232 -2.833530449
[77,] 12.797585795 -1.391225232
[78,] 7.258065459 12.797585795
[79,] 11.867930681 7.258065459
[80,] -0.238593211 11.867930681
[81,] 8.145751492 -0.238593211
[82,] -1.791853556 8.145751492
[83,] -5.843668659 -1.791853556
[84,] -5.932803656 -5.843668659
[85,] 5.785096946 -5.932803656
[86,] 8.392914640 5.785096946
[87,] 1.320575641 8.392914640
[88,] -1.928137450 1.320575641
[89,] 4.693254581 -1.928137450
[90,] 4.510955159 4.693254581
[91,] -11.910330292 4.510955159
[92,] 6.214352878 -11.910330292
[93,] 2.265457823 6.214352878
[94,] 1.246174752 2.265457823
[95,] -4.933938457 1.246174752
[96,] 15.622699331 -4.933938457
[97,] 5.249742954 15.622699331
[98,] 7.449585430 5.249742954
[99,] 0.648655611 7.449585430
[100,] 2.204785043 0.648655611
[101,] 3.805962945 2.204785043
[102,] -5.912931400 3.805962945
[103,] -2.806629268 -5.912931400
[104,] -6.784352352 -2.806629268
[105,] -9.331210311 -6.784352352
[106,] 15.191543377 -9.331210311
[107,] 4.155587725 15.191543377
[108,] -22.227451469 4.155587725
[109,] 8.079638639 -22.227451469
[110,] -4.311924118 8.079638639
[111,] 10.525269407 -4.311924118
[112,] 2.469195924 10.525269407
[113,] -2.843244963 2.469195924
[114,] 1.015694438 -2.843244963
[115,] 1.238840039 1.015694438
[116,] -0.504819147 1.238840039
[117,] -8.483115072 -0.504819147
[118,] -9.623675563 -8.483115072
[119,] -1.125436786 -9.623675563
[120,] -1.491184425 -1.125436786
[121,] -2.266291997 -1.491184425
[122,] -3.280123970 -2.266291997
[123,] 1.778017941 -3.280123970
[124,] -3.160846759 1.778017941
[125,] -6.077062808 -3.160846759
[126,] -6.145599953 -6.077062808
[127,] 0.182910449 -6.145599953
[128,] 7.745648320 0.182910449
[129,] -9.814842565 7.745648320
[130,] -3.634526188 -9.814842565
[131,] 6.467308020 -3.634526188
[132,] -4.486767739 6.467308020
[133,] 6.844929569 -4.486767739
[134,] 13.211197206 6.844929569
[135,] -7.966494311 13.211197206
[136,] -10.512452308 -7.966494311
[137,] -7.051448555 -10.512452308
[138,] -1.841684259 -7.051448555
[139,] -5.085204312 -1.841684259
[140,] 0.071776478 -5.085204312
[141,] -4.833545929 0.071776478
[142,] 2.085954888 -4.833545929
[143,] 1.487096035 2.085954888
[144,] 9.266281898 1.487096035
[145,] 5.470894672 9.266281898
[146,] 12.967007109 5.470894672
[147,] -0.554230062 12.967007109
[148,] -4.408990068 -0.554230062
[149,] 9.113793184 -4.408990068
[150,] 7.799828317 9.113793184
[151,] 13.437696262 7.799828317
[152,] -4.941441818 13.437696262
[153,] 1.310972323 -4.941441818
[154,] 2.855046849 1.310972323
[155,] -6.960341717 2.855046849
[156,] 5.164080224 -6.960341717
[157,] -4.770049390 5.164080224
[158,] 8.324234269 -4.770049390
[159,] -0.756269353 8.324234269
[160,] -2.119718092 -0.756269353
[161,] 6.363557680 -2.119718092
[162,] -5.610748963 6.363557680
[163,] -4.607108515 -5.610748963
[164,] 7.637367727 -4.607108515
[165,] 5.450859223 7.637367727
[166,] 6.529887700 5.450859223
[167,] 1.812632648 6.529887700
[168,] 0.107234062 1.812632648
[169,] -13.187955604 0.107234062
[170,] -5.292078286 -13.187955604
[171,] -2.450010410 -5.292078286
[172,] -1.055043269 -2.450010410
[173,] 3.727275365 -1.055043269
[174,] 13.285657859 3.727275365
[175,] -6.803881321 13.285657859
[176,] -2.671490487 -6.803881321
[177,] 1.467997836 -2.671490487
[178,] 2.369283762 1.467997836
[179,] -5.423708704 2.369283762
[180,] -10.065138487 -5.423708704
[181,] -0.755543518 -10.065138487
[182,] -10.657551533 -0.755543518
[183,] 3.110017573 -10.657551533
[184,] 4.753281225 3.110017573
[185,] -9.902203412 4.753281225
[186,] -7.576634392 -9.902203412
[187,] -9.587528024 -7.576634392
[188,] -4.558670393 -9.587528024
[189,] 14.102251216 -4.558670393
[190,] -1.239485649 14.102251216
[191,] -0.328013731 -1.239485649
[192,] -5.283090620 -0.328013731
[193,] 7.924569616 -5.283090620
[194,] -2.399283547 7.924569616
[195,] -8.367752711 -2.399283547
[196,] 3.193727592 -8.367752711
[197,] -7.194376116 3.193727592
[198,] -3.777779151 -7.194376116
[199,] -4.164211693 -3.777779151
[200,] -0.800299755 -4.164211693
[201,] 10.593810681 -0.800299755
[202,] -5.393430683 10.593810681
[203,] -2.652803665 -5.393430683
[204,] 0.958494396 -2.652803665
[205,] 6.493482602 0.958494396
[206,] 0.094445504 6.493482602
[207,] -7.665439841 0.094445504
[208,] -2.034109238 -7.665439841
[209,] 3.161119053 -2.034109238
[210,] -8.513263707 3.161119053
[211,] -2.387341010 -8.513263707
[212,] 3.230091277 -2.387341010
[213,] -0.593398626 3.230091277
[214,] 6.622263345 -0.593398626
[215,] 8.417522559 6.622263345
[216,] -1.999526380 8.417522559
[217,] -3.328962052 -1.999526380
[218,] 0.871115519 -3.328962052
[219,] 0.609648222 0.871115519
[220,] 3.171968462 0.609648222
[221,] 0.750661540 3.171968462
[222,] -1.257397393 0.750661540
[223,] 1.428735873 -1.257397393
[224,] 5.605168949 1.428735873
[225,] -7.777506062 5.605168949
[226,] -10.005806919 -7.777506062
[227,] -1.042655131 -10.005806919
[228,] -0.735184487 -1.042655131
[229,] 3.388358424 -0.735184487
[230,] 5.743862435 3.388358424
[231,] -2.907348126 5.743862435
[232,] -4.473401400 -2.907348126
[233,] 2.791807742 -4.473401400
[234,] 3.754646129 2.791807742
[235,] 2.612604909 3.754646129
[236,] -3.299559251 2.612604909
[237,] 3.485834403 -3.299559251
[238,] 1.366833496 3.485834403
[239,] 2.480581794 1.366833496
[240,] -3.226017401 2.480581794
[241,] -1.876252000 -3.226017401
[242,] 1.764329705 -1.876252000
[243,] -1.159787133 1.764329705
[244,] -1.660063926 -1.159787133
[245,] -1.335970607 -1.660063926
[246,] -4.870887427 -1.335970607
[247,] -1.864045250 -4.870887427
[248,] -7.822998509 -1.864045250
[249,] -9.023570844 -7.822998509
[250,] -0.211528863 -9.023570844
[251,] 1.212160156 -0.211528863
[252,] -9.947377734 1.212160156
[253,] 0.414083343 -9.947377734
[254,] 0.966077140 0.414083343
[255,] -7.264686116 0.966077140
[256,] -3.726327327 -7.264686116
[257,] -0.938925105 -3.726327327
[258,] 1.929756904 -0.938925105
[259,] -3.852363814 1.929756904
[260,] 4.742052946 -3.852363814
[261,] 0.593175850 4.742052946
[262,] -4.664662181 0.593175850
[263,] 0.341806970 -4.664662181
[264,] -1.820136404 0.341806970
[265,] -2.868382780 -1.820136404
[266,] 2.336842893 -2.868382780
[267,] -3.832904954 2.336842893
[268,] -2.604550726 -3.832904954
[269,] 2.160978014 -2.604550726
[270,] 0.860635306 2.160978014
[271,] -0.009591897 0.860635306
[272,] -10.779101335 -0.009591897
[273,] -2.432974522 -10.779101335
[274,] -4.880913329 -2.432974522
[275,] 3.614701697 -4.880913329
[276,] -2.987923755 3.614701697
[277,] -9.025616567 -2.987923755
[278,] -2.813364501 -9.025616567
[279,] 0.695237318 -2.813364501
[280,] 2.641419810 0.695237318
[281,] -7.605719185 2.641419810
[282,] -6.677256565 -7.605719185
[283,] -7.986628263 -6.677256565
[284,] 1.302867403 -7.986628263
[285,] 4.301885077 1.302867403
[286,] -1.316706915 4.301885077
[287,] -2.027915765 -1.316706915
[288,] 0.556082962 -2.027915765
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.387644989 -3.833858278
2 9.709801410 2.387644989
3 -0.864359820 9.709801410
4 1.336942461 -0.864359820
5 7.045081081 1.336942461
6 -18.873918636 7.045081081
7 4.901504000 -18.873918636
8 -5.809779340 4.901504000
9 -3.315420791 -5.809779340
10 -0.043672036 -3.315420791
11 7.115869049 -0.043672036
12 17.265673361 7.115869049
13 7.183646973 17.265673361
14 6.722883345 7.183646973
15 8.396484884 6.722883345
16 8.612126116 8.396484884
17 -6.933931240 8.612126116
18 -1.915330845 -6.933931240
19 -5.537418732 -1.915330845
20 2.277776904 -5.537418732
21 3.628549053 2.277776904
22 -6.495938002 3.628549053
23 0.046264856 -6.495938002
24 11.504168195 0.046264856
25 6.496419648 11.504168195
26 3.113179281 6.496419648
27 -0.505957332 3.113179281
28 2.701610181 -0.505957332
29 5.065179171 2.701610181
30 2.321230541 5.065179171
31 1.368277051 2.321230541
32 14.074663354 1.368277051
33 8.842282960 14.074663354
34 10.238934254 8.842282960
35 -5.094047327 10.238934254
36 -4.888122197 -5.094047327
37 4.838467417 -4.888122197
38 0.152716783 4.838467417
39 -9.729687611 0.152716783
40 2.937810233 -9.729687611
41 -4.630282561 2.937810233
42 -0.454786261 -4.630282561
43 -1.726302864 -0.454786261
44 -2.266595416 -1.726302864
45 10.575477900 -2.266595416
46 -3.706994217 10.575477900
47 1.876650000 -3.706994217
48 7.094867766 1.876650000
49 16.461643125 7.094867766
50 -4.873601049 16.461643125
51 9.197950053 -4.873601049
52 9.680523965 9.197950053
53 -0.850446700 9.680523965
54 6.683348638 -0.850446700
55 0.960776058 6.683348638
56 -7.187850881 0.960776058
57 -1.569449286 -7.187850881
58 1.969300514 -1.569449286
59 -4.218852331 1.969300514
60 -1.645587046 -4.218852331
61 5.902138036 -1.645587046
62 -19.795212775 5.902138036
63 -1.450116330 -19.795212775
64 -9.790216143 -1.450116330
65 -1.552140492 -9.790216143
66 -0.336882817 -1.552140492
67 -2.907314366 -0.336882817
68 -16.421021698 -2.907314366
69 11.675466302 -16.421021698
70 1.577821407 11.675466302
71 -1.681289255 1.577821407
72 -0.656618910 -1.681289255
73 -1.978069204 -0.656618910
74 7.817040813 -1.978069204
75 -2.833530449 7.817040813
76 -1.391225232 -2.833530449
77 12.797585795 -1.391225232
78 7.258065459 12.797585795
79 11.867930681 7.258065459
80 -0.238593211 11.867930681
81 8.145751492 -0.238593211
82 -1.791853556 8.145751492
83 -5.843668659 -1.791853556
84 -5.932803656 -5.843668659
85 5.785096946 -5.932803656
86 8.392914640 5.785096946
87 1.320575641 8.392914640
88 -1.928137450 1.320575641
89 4.693254581 -1.928137450
90 4.510955159 4.693254581
91 -11.910330292 4.510955159
92 6.214352878 -11.910330292
93 2.265457823 6.214352878
94 1.246174752 2.265457823
95 -4.933938457 1.246174752
96 15.622699331 -4.933938457
97 5.249742954 15.622699331
98 7.449585430 5.249742954
99 0.648655611 7.449585430
100 2.204785043 0.648655611
101 3.805962945 2.204785043
102 -5.912931400 3.805962945
103 -2.806629268 -5.912931400
104 -6.784352352 -2.806629268
105 -9.331210311 -6.784352352
106 15.191543377 -9.331210311
107 4.155587725 15.191543377
108 -22.227451469 4.155587725
109 8.079638639 -22.227451469
110 -4.311924118 8.079638639
111 10.525269407 -4.311924118
112 2.469195924 10.525269407
113 -2.843244963 2.469195924
114 1.015694438 -2.843244963
115 1.238840039 1.015694438
116 -0.504819147 1.238840039
117 -8.483115072 -0.504819147
118 -9.623675563 -8.483115072
119 -1.125436786 -9.623675563
120 -1.491184425 -1.125436786
121 -2.266291997 -1.491184425
122 -3.280123970 -2.266291997
123 1.778017941 -3.280123970
124 -3.160846759 1.778017941
125 -6.077062808 -3.160846759
126 -6.145599953 -6.077062808
127 0.182910449 -6.145599953
128 7.745648320 0.182910449
129 -9.814842565 7.745648320
130 -3.634526188 -9.814842565
131 6.467308020 -3.634526188
132 -4.486767739 6.467308020
133 6.844929569 -4.486767739
134 13.211197206 6.844929569
135 -7.966494311 13.211197206
136 -10.512452308 -7.966494311
137 -7.051448555 -10.512452308
138 -1.841684259 -7.051448555
139 -5.085204312 -1.841684259
140 0.071776478 -5.085204312
141 -4.833545929 0.071776478
142 2.085954888 -4.833545929
143 1.487096035 2.085954888
144 9.266281898 1.487096035
145 5.470894672 9.266281898
146 12.967007109 5.470894672
147 -0.554230062 12.967007109
148 -4.408990068 -0.554230062
149 9.113793184 -4.408990068
150 7.799828317 9.113793184
151 13.437696262 7.799828317
152 -4.941441818 13.437696262
153 1.310972323 -4.941441818
154 2.855046849 1.310972323
155 -6.960341717 2.855046849
156 5.164080224 -6.960341717
157 -4.770049390 5.164080224
158 8.324234269 -4.770049390
159 -0.756269353 8.324234269
160 -2.119718092 -0.756269353
161 6.363557680 -2.119718092
162 -5.610748963 6.363557680
163 -4.607108515 -5.610748963
164 7.637367727 -4.607108515
165 5.450859223 7.637367727
166 6.529887700 5.450859223
167 1.812632648 6.529887700
168 0.107234062 1.812632648
169 -13.187955604 0.107234062
170 -5.292078286 -13.187955604
171 -2.450010410 -5.292078286
172 -1.055043269 -2.450010410
173 3.727275365 -1.055043269
174 13.285657859 3.727275365
175 -6.803881321 13.285657859
176 -2.671490487 -6.803881321
177 1.467997836 -2.671490487
178 2.369283762 1.467997836
179 -5.423708704 2.369283762
180 -10.065138487 -5.423708704
181 -0.755543518 -10.065138487
182 -10.657551533 -0.755543518
183 3.110017573 -10.657551533
184 4.753281225 3.110017573
185 -9.902203412 4.753281225
186 -7.576634392 -9.902203412
187 -9.587528024 -7.576634392
188 -4.558670393 -9.587528024
189 14.102251216 -4.558670393
190 -1.239485649 14.102251216
191 -0.328013731 -1.239485649
192 -5.283090620 -0.328013731
193 7.924569616 -5.283090620
194 -2.399283547 7.924569616
195 -8.367752711 -2.399283547
196 3.193727592 -8.367752711
197 -7.194376116 3.193727592
198 -3.777779151 -7.194376116
199 -4.164211693 -3.777779151
200 -0.800299755 -4.164211693
201 10.593810681 -0.800299755
202 -5.393430683 10.593810681
203 -2.652803665 -5.393430683
204 0.958494396 -2.652803665
205 6.493482602 0.958494396
206 0.094445504 6.493482602
207 -7.665439841 0.094445504
208 -2.034109238 -7.665439841
209 3.161119053 -2.034109238
210 -8.513263707 3.161119053
211 -2.387341010 -8.513263707
212 3.230091277 -2.387341010
213 -0.593398626 3.230091277
214 6.622263345 -0.593398626
215 8.417522559 6.622263345
216 -1.999526380 8.417522559
217 -3.328962052 -1.999526380
218 0.871115519 -3.328962052
219 0.609648222 0.871115519
220 3.171968462 0.609648222
221 0.750661540 3.171968462
222 -1.257397393 0.750661540
223 1.428735873 -1.257397393
224 5.605168949 1.428735873
225 -7.777506062 5.605168949
226 -10.005806919 -7.777506062
227 -1.042655131 -10.005806919
228 -0.735184487 -1.042655131
229 3.388358424 -0.735184487
230 5.743862435 3.388358424
231 -2.907348126 5.743862435
232 -4.473401400 -2.907348126
233 2.791807742 -4.473401400
234 3.754646129 2.791807742
235 2.612604909 3.754646129
236 -3.299559251 2.612604909
237 3.485834403 -3.299559251
238 1.366833496 3.485834403
239 2.480581794 1.366833496
240 -3.226017401 2.480581794
241 -1.876252000 -3.226017401
242 1.764329705 -1.876252000
243 -1.159787133 1.764329705
244 -1.660063926 -1.159787133
245 -1.335970607 -1.660063926
246 -4.870887427 -1.335970607
247 -1.864045250 -4.870887427
248 -7.822998509 -1.864045250
249 -9.023570844 -7.822998509
250 -0.211528863 -9.023570844
251 1.212160156 -0.211528863
252 -9.947377734 1.212160156
253 0.414083343 -9.947377734
254 0.966077140 0.414083343
255 -7.264686116 0.966077140
256 -3.726327327 -7.264686116
257 -0.938925105 -3.726327327
258 1.929756904 -0.938925105
259 -3.852363814 1.929756904
260 4.742052946 -3.852363814
261 0.593175850 4.742052946
262 -4.664662181 0.593175850
263 0.341806970 -4.664662181
264 -1.820136404 0.341806970
265 -2.868382780 -1.820136404
266 2.336842893 -2.868382780
267 -3.832904954 2.336842893
268 -2.604550726 -3.832904954
269 2.160978014 -2.604550726
270 0.860635306 2.160978014
271 -0.009591897 0.860635306
272 -10.779101335 -0.009591897
273 -2.432974522 -10.779101335
274 -4.880913329 -2.432974522
275 3.614701697 -4.880913329
276 -2.987923755 3.614701697
277 -9.025616567 -2.987923755
278 -2.813364501 -9.025616567
279 0.695237318 -2.813364501
280 2.641419810 0.695237318
281 -7.605719185 2.641419810
282 -6.677256565 -7.605719185
283 -7.986628263 -6.677256565
284 1.302867403 -7.986628263
285 4.301885077 1.302867403
286 -1.316706915 4.301885077
287 -2.027915765 -1.316706915
288 0.556082962 -2.027915765
> 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/71uwg1324134631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/83zdd1324134631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9pa5m1324134631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10z4kl1324134631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ej6c1324134631.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/1233rl1324134631.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/13higf1324134631.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/1433251324134631.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/15yzl21324134631.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/16yyfo1324134631.tab")
+ }
>
> try(system("convert tmp/19qxr1324134631.ps tmp/19qxr1324134631.png",intern=TRUE))
character(0)
> try(system("convert tmp/2woyx1324134631.ps tmp/2woyx1324134631.png",intern=TRUE))
character(0)
> try(system("convert tmp/3mazk1324134631.ps tmp/3mazk1324134631.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xjxf1324134631.ps tmp/4xjxf1324134631.png",intern=TRUE))
character(0)
> try(system("convert tmp/5heqv1324134631.ps tmp/5heqv1324134631.png",intern=TRUE))
character(0)
> try(system("convert tmp/6xlnm1324134631.ps tmp/6xlnm1324134631.png",intern=TRUE))
character(0)
> try(system("convert tmp/71uwg1324134631.ps tmp/71uwg1324134631.png",intern=TRUE))
character(0)
> try(system("convert tmp/83zdd1324134631.ps tmp/83zdd1324134631.png",intern=TRUE))
character(0)
> try(system("convert tmp/9pa5m1324134631.ps tmp/9pa5m1324134631.png",intern=TRUE))
character(0)
> try(system("convert tmp/10z4kl1324134631.ps tmp/10z4kl1324134631.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
7.648 0.658 10.176