R version 2.12.0 (2010-10-15)
Copyright (C) 2010 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(252101
+ ,62
+ ,438
+ ,92
+ ,34
+ ,104
+ ,165119
+ ,134577
+ ,59
+ ,330
+ ,58
+ ,30
+ ,111
+ ,107269
+ ,198520
+ ,62
+ ,609
+ ,62
+ ,38
+ ,93
+ ,93497
+ ,189326
+ ,94
+ ,1015
+ ,108
+ ,34
+ ,119
+ ,100269
+ ,137449
+ ,43
+ ,294
+ ,55
+ ,25
+ ,57
+ ,91627
+ ,65295
+ ,27
+ ,164
+ ,8
+ ,31
+ ,80
+ ,47552
+ ,439387
+ ,103
+ ,1912
+ ,134
+ ,29
+ ,107
+ ,233933
+ ,33186
+ ,19
+ ,111
+ ,1
+ ,18
+ ,22
+ ,6853
+ ,178368
+ ,51
+ ,698
+ ,64
+ ,30
+ ,103
+ ,104380
+ ,186657
+ ,38
+ ,556
+ ,77
+ ,29
+ ,72
+ ,98431
+ ,261949
+ ,96
+ ,711
+ ,86
+ ,38
+ ,123
+ ,156949
+ ,191051
+ ,95
+ ,495
+ ,93
+ ,49
+ ,164
+ ,81817
+ ,138866
+ ,57
+ ,544
+ ,44
+ ,33
+ ,100
+ ,59238
+ ,296878
+ ,66
+ ,959
+ ,106
+ ,46
+ ,143
+ ,101138
+ ,192648
+ ,72
+ ,540
+ ,63
+ ,38
+ ,79
+ ,107158
+ ,333462
+ ,162
+ ,1486
+ ,160
+ ,52
+ ,183
+ ,155499
+ ,243571
+ ,58
+ ,635
+ ,104
+ ,32
+ ,123
+ ,156274
+ ,263451
+ ,130
+ ,940
+ ,86
+ ,35
+ ,81
+ ,121777
+ ,155679
+ ,48
+ ,452
+ ,93
+ ,25
+ ,74
+ ,105037
+ ,227053
+ ,70
+ ,617
+ ,119
+ ,42
+ ,158
+ ,118661
+ ,240028
+ ,63
+ ,695
+ ,107
+ ,40
+ ,133
+ ,131187
+ ,388549
+ ,90
+ ,1046
+ ,86
+ ,35
+ ,128
+ ,145026
+ ,156540
+ ,34
+ ,405
+ ,50
+ ,25
+ ,84
+ ,107016
+ ,148421
+ ,43
+ ,477
+ ,92
+ ,46
+ ,184
+ ,87242
+ ,177732
+ ,97
+ ,1012
+ ,123
+ ,36
+ ,127
+ ,91699
+ ,191441
+ ,105
+ ,842
+ ,81
+ ,35
+ ,128
+ ,110087
+ ,249893
+ ,122
+ ,994
+ ,93
+ ,38
+ ,118
+ ,145447
+ ,236812
+ ,76
+ ,530
+ ,113
+ ,35
+ ,125
+ ,143307
+ ,142329
+ ,45
+ ,515
+ ,52
+ ,28
+ ,89
+ ,61678
+ ,259667
+ ,53
+ ,766
+ ,113
+ ,37
+ ,122
+ ,210080
+ ,231625
+ ,65
+ ,734
+ ,112
+ ,40
+ ,151
+ ,165005
+ ,176062
+ ,67
+ ,551
+ ,44
+ ,42
+ ,122
+ ,97806
+ ,286683
+ ,79
+ ,718
+ ,123
+ ,44
+ ,162
+ ,184471
+ ,87485
+ ,33
+ ,280
+ ,38
+ ,33
+ ,121
+ ,27786
+ ,322865
+ ,83
+ ,1055
+ ,111
+ ,35
+ ,132
+ ,184458
+ ,247082
+ ,51
+ ,950
+ ,77
+ ,37
+ ,110
+ ,98765
+ ,344092
+ ,104
+ ,1035
+ ,92
+ ,39
+ ,135
+ ,178441
+ ,191653
+ ,74
+ ,552
+ ,74
+ ,32
+ ,80
+ ,100619
+ ,114673
+ ,31
+ ,275
+ ,33
+ ,17
+ ,46
+ ,58391
+ ,284224
+ ,161
+ ,986
+ ,105
+ ,34
+ ,127
+ ,151672
+ ,284195
+ ,72
+ ,1336
+ ,108
+ ,33
+ ,103
+ ,124437
+ ,155363
+ ,59
+ ,565
+ ,66
+ ,35
+ ,95
+ ,79929
+ ,177306
+ ,67
+ ,571
+ ,69
+ ,32
+ ,100
+ ,123064
+ ,144571
+ ,49
+ ,404
+ ,62
+ ,35
+ ,102
+ ,50466
+ ,140319
+ ,73
+ ,985
+ ,50
+ ,45
+ ,45
+ ,100991
+ ,405267
+ ,135
+ ,1851
+ ,91
+ ,38
+ ,122
+ ,79367
+ ,78800
+ ,42
+ ,330
+ ,20
+ ,26
+ ,66
+ ,56968
+ ,201970
+ ,69
+ ,611
+ ,101
+ ,45
+ ,159
+ ,106257
+ ,302674
+ ,99
+ ,1249
+ ,129
+ ,44
+ ,153
+ ,178412
+ ,164733
+ ,50
+ ,812
+ ,93
+ ,40
+ ,131
+ ,98520
+ ,194221
+ ,68
+ ,501
+ ,89
+ ,33
+ ,113
+ ,153670
+ ,24188
+ ,24
+ ,218
+ ,8
+ ,4
+ ,7
+ ,15049
+ ,342263
+ ,279
+ ,785
+ ,79
+ ,41
+ ,147
+ ,174478
+ ,65029
+ ,17
+ ,255
+ ,21
+ ,18
+ ,61
+ ,25109
+ ,101097
+ ,64
+ ,454
+ ,30
+ ,14
+ ,41
+ ,45824
+ ,246088
+ ,46
+ ,944
+ ,86
+ ,33
+ ,108
+ ,116772
+ ,273108
+ ,75
+ ,600
+ ,116
+ ,49
+ ,184
+ ,189150
+ ,282220
+ ,160
+ ,977
+ ,106
+ ,32
+ ,115
+ ,194404
+ ,273495
+ ,119
+ ,863
+ ,127
+ ,37
+ ,132
+ ,185881
+ ,214872
+ ,74
+ ,690
+ ,75
+ ,32
+ ,113
+ ,67508
+ ,335121
+ ,123
+ ,1176
+ ,138
+ ,41
+ ,141
+ ,188597
+ ,267171
+ ,106
+ ,1013
+ ,114
+ ,25
+ ,65
+ ,203618
+ ,187938
+ ,88
+ ,890
+ ,55
+ ,40
+ ,87
+ ,87232
+ ,229512
+ ,78
+ ,777
+ ,67
+ ,35
+ ,121
+ ,110875
+ ,209798
+ ,61
+ ,521
+ ,45
+ ,33
+ ,112
+ ,144756
+ ,201345
+ ,60
+ ,409
+ ,88
+ ,28
+ ,81
+ ,129825
+ ,163833
+ ,113
+ ,493
+ ,67
+ ,31
+ ,116
+ ,92189
+ ,204250
+ ,129
+ ,757
+ ,75
+ ,40
+ ,132
+ ,121158
+ ,197813
+ ,67
+ ,736
+ ,114
+ ,32
+ ,104
+ ,96219
+ ,132955
+ ,60
+ ,511
+ ,123
+ ,25
+ ,80
+ ,84128
+ ,216092
+ ,59
+ ,789
+ ,86
+ ,42
+ ,145
+ ,97960
+ ,73566
+ ,32
+ ,385
+ ,22
+ ,23
+ ,67
+ ,23824
+ ,213198
+ ,67
+ ,644
+ ,67
+ ,42
+ ,159
+ ,103515
+ ,181713
+ ,49
+ ,664
+ ,77
+ ,38
+ ,90
+ ,91313
+ ,148698
+ ,49
+ ,505
+ ,105
+ ,34
+ ,120
+ ,85407
+ ,300103
+ ,70
+ ,878
+ ,119
+ ,38
+ ,126
+ ,95871
+ ,251437
+ ,78
+ ,769
+ ,88
+ ,32
+ ,118
+ ,143846
+ ,197295
+ ,101
+ ,499
+ ,78
+ ,37
+ ,112
+ ,155387
+ ,158163
+ ,55
+ ,546
+ ,112
+ ,34
+ ,123
+ ,74429
+ ,155529
+ ,57
+ ,551
+ ,66
+ ,33
+ ,98
+ ,74004
+ ,132672
+ ,41
+ ,565
+ ,58
+ ,25
+ ,78
+ ,71987
+ ,377205
+ ,100
+ ,1086
+ ,132
+ ,40
+ ,119
+ ,150629
+ ,145905
+ ,66
+ ,649
+ ,30
+ ,26
+ ,99
+ ,68580
+ ,223701
+ ,86
+ ,540
+ ,100
+ ,40
+ ,81
+ ,119855
+ ,80953
+ ,25
+ ,437
+ ,49
+ ,8
+ ,27
+ ,55792
+ ,130805
+ ,47
+ ,732
+ ,26
+ ,27
+ ,77
+ ,25157
+ ,135082
+ ,48
+ ,308
+ ,67
+ ,32
+ ,118
+ ,90895
+ ,300170
+ ,154
+ ,1236
+ ,57
+ ,33
+ ,122
+ ,117510
+ ,271806
+ ,95
+ ,783
+ ,95
+ ,50
+ ,103
+ ,144774
+ ,150949
+ ,96
+ ,933
+ ,139
+ ,37
+ ,129
+ ,77529
+ ,225805
+ ,79
+ ,710
+ ,73
+ ,33
+ ,69
+ ,103123
+ ,197389
+ ,67
+ ,563
+ ,134
+ ,34
+ ,121
+ ,104669
+ ,156583
+ ,56
+ ,508
+ ,37
+ ,28
+ ,81
+ ,82414
+ ,222599
+ ,66
+ ,936
+ ,98
+ ,32
+ ,119
+ ,82390
+ ,261601
+ ,70
+ ,838
+ ,58
+ ,32
+ ,116
+ ,128446
+ ,178489
+ ,35
+ ,523
+ ,78
+ ,32
+ ,123
+ ,111542
+ ,200657
+ ,43
+ ,500
+ ,88
+ ,31
+ ,111
+ ,136048
+ ,259084
+ ,67
+ ,691
+ ,142
+ ,35
+ ,100
+ ,197257
+ ,313075
+ ,130
+ ,1060
+ ,127
+ ,58
+ ,221
+ ,162079
+ ,346933
+ ,100
+ ,1232
+ ,139
+ ,27
+ ,95
+ ,206286
+ ,246440
+ ,104
+ ,735
+ ,108
+ ,45
+ ,153
+ ,109858
+ ,252444
+ ,58
+ ,757
+ ,128
+ ,37
+ ,118
+ ,182125
+ ,159965
+ ,159
+ ,574
+ ,62
+ ,32
+ ,50
+ ,74168
+ ,43287
+ ,14
+ ,214
+ ,13
+ ,19
+ ,64
+ ,19630
+ ,172239
+ ,68
+ ,661
+ ,89
+ ,22
+ ,34
+ ,88634
+ ,181897
+ ,119
+ ,630
+ ,83
+ ,35
+ ,76
+ ,128321
+ ,227681
+ ,43
+ ,1015
+ ,116
+ ,36
+ ,112
+ ,118936
+ ,260464
+ ,81
+ ,893
+ ,157
+ ,36
+ ,115
+ ,127044
+ ,106288
+ ,54
+ ,293
+ ,28
+ ,23
+ ,69
+ ,178377
+ ,109632
+ ,76
+ ,446
+ ,83
+ ,36
+ ,108
+ ,69581
+ ,268905
+ ,58
+ ,538
+ ,72
+ ,36
+ ,130
+ ,168019
+ ,266805
+ ,78
+ ,627
+ ,134
+ ,42
+ ,110
+ ,113598
+ ,23623
+ ,11
+ ,156
+ ,12
+ ,1
+ ,0
+ ,5841
+ ,152474
+ ,65
+ ,577
+ ,106
+ ,32
+ ,83
+ ,93116
+ ,61857
+ ,25
+ ,192
+ ,23
+ ,11
+ ,30
+ ,24610
+ ,144889
+ ,43
+ ,437
+ ,83
+ ,40
+ ,106
+ ,60611
+ ,346600
+ ,99
+ ,1054
+ ,126
+ ,34
+ ,91
+ ,226620
+ ,21054
+ ,16
+ ,146
+ ,4
+ ,0
+ ,0
+ ,6622
+ ,224051
+ ,45
+ ,751
+ ,71
+ ,27
+ ,69
+ ,121996
+ ,31414
+ ,19
+ ,200
+ ,18
+ ,8
+ ,9
+ ,13155
+ ,261043
+ ,105
+ ,1050
+ ,98
+ ,35
+ ,123
+ ,154158
+ ,197819
+ ,57
+ ,590
+ ,66
+ ,41
+ ,143
+ ,78489
+ ,154984
+ ,73
+ ,430
+ ,44
+ ,40
+ ,125
+ ,22007
+ ,112933
+ ,45
+ ,467
+ ,29
+ ,28
+ ,81
+ ,72530
+ ,38214
+ ,34
+ ,276
+ ,16
+ ,8
+ ,21
+ ,13983
+ ,158671
+ ,33
+ ,528
+ ,56
+ ,35
+ ,124
+ ,73397
+ ,302148
+ ,70
+ ,898
+ ,112
+ ,47
+ ,168
+ ,143878
+ ,177918
+ ,55
+ ,411
+ ,46
+ ,46
+ ,149
+ ,119956
+ ,350552
+ ,70
+ ,1362
+ ,129
+ ,42
+ ,147
+ ,181558
+ ,275578
+ ,91
+ ,743
+ ,139
+ ,48
+ ,145
+ ,208236
+ ,366217
+ ,105
+ ,1068
+ ,136
+ ,49
+ ,172
+ ,237085
+ ,172464
+ ,31
+ ,431
+ ,66
+ ,35
+ ,126
+ ,110297
+ ,94381
+ ,35
+ ,380
+ ,42
+ ,32
+ ,89
+ ,61394
+ ,243875
+ ,278
+ ,788
+ ,70
+ ,36
+ ,137
+ ,81420
+ ,382487
+ ,153
+ ,1367
+ ,97
+ ,42
+ ,149
+ ,191154
+ ,114525
+ ,40
+ ,449
+ ,49
+ ,35
+ ,121
+ ,11798
+ ,335681
+ ,119
+ ,1461
+ ,113
+ ,37
+ ,133
+ ,135724
+ ,147989
+ ,72
+ ,651
+ ,55
+ ,34
+ ,93
+ ,68614
+ ,216638
+ ,44
+ ,494
+ ,100
+ ,36
+ ,119
+ ,139926
+ ,192862
+ ,72
+ ,667
+ ,80
+ ,36
+ ,102
+ ,105203
+ ,184818
+ ,107
+ ,510
+ ,29
+ ,32
+ ,45
+ ,80338
+ ,336707
+ ,105
+ ,1472
+ ,95
+ ,33
+ ,104
+ ,121376
+ ,215836
+ ,76
+ ,675
+ ,114
+ ,35
+ ,111
+ ,124922
+ ,173260
+ ,63
+ ,716
+ ,41
+ ,21
+ ,78
+ ,10901
+ ,271773
+ ,89
+ ,814
+ ,128
+ ,40
+ ,120
+ ,135471
+ ,130908
+ ,52
+ ,556
+ ,142
+ ,49
+ ,176
+ ,66395
+ ,204009
+ ,75
+ ,887
+ ,88
+ ,33
+ ,109
+ ,134041
+ ,245514
+ ,92
+ ,663
+ ,147
+ ,39
+ ,132
+ ,153554
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,14688
+ ,10
+ ,85
+ ,4
+ ,0
+ ,0
+ ,7953
+ ,98
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,455
+ ,2
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,195765
+ ,75
+ ,607
+ ,56
+ ,33
+ ,78
+ ,98922
+ ,326038
+ ,121
+ ,934
+ ,121
+ ,42
+ ,104
+ ,165395
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,203
+ ,4
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,7199
+ ,5
+ ,74
+ ,7
+ ,0
+ ,0
+ ,4245
+ ,46660
+ ,20
+ ,259
+ ,12
+ ,5
+ ,13
+ ,21509
+ ,17547
+ ,5
+ ,69
+ ,0
+ ,1
+ ,4
+ ,7670
+ ,107465
+ ,38
+ ,267
+ ,37
+ ,38
+ ,65
+ ,15167
+ ,969
+ ,2
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,173102
+ ,58
+ ,517
+ ,47
+ ,28
+ ,55
+ ,63891)
+ ,dim=c(7
+ ,164)
+ ,dimnames=list(c('Time'
+ ,'Logins'
+ ,'Views'
+ ,'Blogs'
+ ,'Reviews'
+ ,'LFM'
+ ,'Compendia_time
')
+ ,1:164))
> y <- array(NA,dim=c(7,164),dimnames=list(c('Time','Logins','Views','Blogs','Reviews','LFM','Compendia_time
'),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 Logins Views Blogs Reviews LFM Compendia_time\r
1 252101 62 438 92 34 104 165119
2 134577 59 330 58 30 111 107269
3 198520 62 609 62 38 93 93497
4 189326 94 1015 108 34 119 100269
5 137449 43 294 55 25 57 91627
6 65295 27 164 8 31 80 47552
7 439387 103 1912 134 29 107 233933
8 33186 19 111 1 18 22 6853
9 178368 51 698 64 30 103 104380
10 186657 38 556 77 29 72 98431
11 261949 96 711 86 38 123 156949
12 191051 95 495 93 49 164 81817
13 138866 57 544 44 33 100 59238
14 296878 66 959 106 46 143 101138
15 192648 72 540 63 38 79 107158
16 333462 162 1486 160 52 183 155499
17 243571 58 635 104 32 123 156274
18 263451 130 940 86 35 81 121777
19 155679 48 452 93 25 74 105037
20 227053 70 617 119 42 158 118661
21 240028 63 695 107 40 133 131187
22 388549 90 1046 86 35 128 145026
23 156540 34 405 50 25 84 107016
24 148421 43 477 92 46 184 87242
25 177732 97 1012 123 36 127 91699
26 191441 105 842 81 35 128 110087
27 249893 122 994 93 38 118 145447
28 236812 76 530 113 35 125 143307
29 142329 45 515 52 28 89 61678
30 259667 53 766 113 37 122 210080
31 231625 65 734 112 40 151 165005
32 176062 67 551 44 42 122 97806
33 286683 79 718 123 44 162 184471
34 87485 33 280 38 33 121 27786
35 322865 83 1055 111 35 132 184458
36 247082 51 950 77 37 110 98765
37 344092 104 1035 92 39 135 178441
38 191653 74 552 74 32 80 100619
39 114673 31 275 33 17 46 58391
40 284224 161 986 105 34 127 151672
41 284195 72 1336 108 33 103 124437
42 155363 59 565 66 35 95 79929
43 177306 67 571 69 32 100 123064
44 144571 49 404 62 35 102 50466
45 140319 73 985 50 45 45 100991
46 405267 135 1851 91 38 122 79367
47 78800 42 330 20 26 66 56968
48 201970 69 611 101 45 159 106257
49 302674 99 1249 129 44 153 178412
50 164733 50 812 93 40 131 98520
51 194221 68 501 89 33 113 153670
52 24188 24 218 8 4 7 15049
53 342263 279 785 79 41 147 174478
54 65029 17 255 21 18 61 25109
55 101097 64 454 30 14 41 45824
56 246088 46 944 86 33 108 116772
57 273108 75 600 116 49 184 189150
58 282220 160 977 106 32 115 194404
59 273495 119 863 127 37 132 185881
60 214872 74 690 75 32 113 67508
61 335121 123 1176 138 41 141 188597
62 267171 106 1013 114 25 65 203618
63 187938 88 890 55 40 87 87232
64 229512 78 777 67 35 121 110875
65 209798 61 521 45 33 112 144756
66 201345 60 409 88 28 81 129825
67 163833 113 493 67 31 116 92189
68 204250 129 757 75 40 132 121158
69 197813 67 736 114 32 104 96219
70 132955 60 511 123 25 80 84128
71 216092 59 789 86 42 145 97960
72 73566 32 385 22 23 67 23824
73 213198 67 644 67 42 159 103515
74 181713 49 664 77 38 90 91313
75 148698 49 505 105 34 120 85407
76 300103 70 878 119 38 126 95871
77 251437 78 769 88 32 118 143846
78 197295 101 499 78 37 112 155387
79 158163 55 546 112 34 123 74429
80 155529 57 551 66 33 98 74004
81 132672 41 565 58 25 78 71987
82 377205 100 1086 132 40 119 150629
83 145905 66 649 30 26 99 68580
84 223701 86 540 100 40 81 119855
85 80953 25 437 49 8 27 55792
86 130805 47 732 26 27 77 25157
87 135082 48 308 67 32 118 90895
88 300170 154 1236 57 33 122 117510
89 271806 95 783 95 50 103 144774
90 150949 96 933 139 37 129 77529
91 225805 79 710 73 33 69 103123
92 197389 67 563 134 34 121 104669
93 156583 56 508 37 28 81 82414
94 222599 66 936 98 32 119 82390
95 261601 70 838 58 32 116 128446
96 178489 35 523 78 32 123 111542
97 200657 43 500 88 31 111 136048
98 259084 67 691 142 35 100 197257
99 313075 130 1060 127 58 221 162079
100 346933 100 1232 139 27 95 206286
101 246440 104 735 108 45 153 109858
102 252444 58 757 128 37 118 182125
103 159965 159 574 62 32 50 74168
104 43287 14 214 13 19 64 19630
105 172239 68 661 89 22 34 88634
106 181897 119 630 83 35 76 128321
107 227681 43 1015 116 36 112 118936
108 260464 81 893 157 36 115 127044
109 106288 54 293 28 23 69 178377
110 109632 76 446 83 36 108 69581
111 268905 58 538 72 36 130 168019
112 266805 78 627 134 42 110 113598
113 23623 11 156 12 1 0 5841
114 152474 65 577 106 32 83 93116
115 61857 25 192 23 11 30 24610
116 144889 43 437 83 40 106 60611
117 346600 99 1054 126 34 91 226620
118 21054 16 146 4 0 0 6622
119 224051 45 751 71 27 69 121996
120 31414 19 200 18 8 9 13155
121 261043 105 1050 98 35 123 154158
122 197819 57 590 66 41 143 78489
123 154984 73 430 44 40 125 22007
124 112933 45 467 29 28 81 72530
125 38214 34 276 16 8 21 13983
126 158671 33 528 56 35 124 73397
127 302148 70 898 112 47 168 143878
128 177918 55 411 46 46 149 119956
129 350552 70 1362 129 42 147 181558
130 275578 91 743 139 48 145 208236
131 366217 105 1068 136 49 172 237085
132 172464 31 431 66 35 126 110297
133 94381 35 380 42 32 89 61394
134 243875 278 788 70 36 137 81420
135 382487 153 1367 97 42 149 191154
136 114525 40 449 49 35 121 11798
137 335681 119 1461 113 37 133 135724
138 147989 72 651 55 34 93 68614
139 216638 44 494 100 36 119 139926
140 192862 72 667 80 36 102 105203
141 184818 107 510 29 32 45 80338
142 336707 105 1472 95 33 104 121376
143 215836 76 675 114 35 111 124922
144 173260 63 716 41 21 78 10901
145 271773 89 814 128 40 120 135471
146 130908 52 556 142 49 176 66395
147 204009 75 887 88 33 109 134041
148 245514 92 663 147 39 132 153554
149 1 0 0 0 0 0 0
150 14688 10 85 4 0 0 7953
151 98 1 0 0 0 0 0
152 455 2 0 0 0 0 0
153 0 0 0 0 0 0 0
154 0 0 0 0 0 0 0
155 195765 75 607 56 33 78 98922
156 326038 121 934 121 42 104 165395
157 0 0 0 0 0 0 0
158 203 4 0 0 0 0 0
159 7199 5 74 7 0 0 4245
160 46660 20 259 12 5 13 21509
161 17547 5 69 0 1 4 7670
162 107465 38 267 37 38 65 15167
163 969 2 0 0 0 0 0
164 173102 58 517 47 28 55 63891
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Logins Views Blogs
-6086.5340 181.8718 128.2631 34.3390
Reviews LFM `Compendia_time\r`
609.8220 138.5176 0.6512
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-94368 -15493 2728 13380 107635
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -6.087e+03 5.975e+03 -1.019 0.3100
Logins 1.819e+02 7.307e+01 2.489 0.0138 *
Views 1.283e+02 1.026e+01 12.502 <2e-16 ***
Blogs 3.434e+01 1.056e+02 0.325 0.7454
Reviews 6.098e+02 4.299e+02 1.418 0.1580
LFM 1.385e+02 1.177e+02 1.177 0.2409
`Compendia_time\r` 6.512e-01 6.611e-02 9.850 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 27980 on 157 degrees of freedom
Multiple R-squared: 0.92, Adjusted R-squared: 0.9169
F-statistic: 300.8 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,] 0.08509053 1.701811e-01 9.149095e-01
[2,] 0.03839485 7.678969e-02 9.616052e-01
[3,] 0.11046219 2.209244e-01 8.895378e-01
[4,] 0.07701002 1.540200e-01 9.229900e-01
[5,] 0.13014508 2.602902e-01 8.698549e-01
[6,] 0.13236958 2.647392e-01 8.676304e-01
[7,] 0.08855954 1.771191e-01 9.114405e-01
[8,] 0.05357967 1.071593e-01 9.464203e-01
[9,] 0.10759405 2.151881e-01 8.924060e-01
[10,] 0.07494466 1.498893e-01 9.250553e-01
[11,] 0.04910402 9.820804e-02 9.508960e-01
[12,] 0.03260260 6.520520e-02 9.673974e-01
[13,] 0.92445429 1.510914e-01 7.554571e-02
[14,] 0.89700401 2.059920e-01 1.029960e-01
[15,] 0.90320014 1.935997e-01 9.679986e-02
[16,] 0.91960760 1.607848e-01 8.039240e-02
[17,] 0.91350200 1.729960e-01 8.649800e-02
[18,] 0.91387118 1.722576e-01 8.612882e-02
[19,] 0.90356670 1.928666e-01 9.643330e-02
[20,] 0.88612256 2.277549e-01 1.138774e-01
[21,] 0.96435668 7.128664e-02 3.564332e-02
[22,] 0.96556343 6.887315e-02 3.443657e-02
[23,] 0.95922187 8.155627e-02 4.077813e-02
[24,] 0.94553805 1.089239e-01 5.446195e-02
[25,] 0.92962546 1.407491e-01 7.037454e-02
[26,] 0.91284380 1.743124e-01 8.715620e-02
[27,] 0.89272352 2.145530e-01 1.072765e-01
[28,] 0.89835778 2.032844e-01 1.016422e-01
[29,] 0.87686132 2.462774e-01 1.231387e-01
[30,] 0.87333252 2.533350e-01 1.266675e-01
[31,] 0.85017790 2.996442e-01 1.498221e-01
[32,] 0.82049151 3.590170e-01 1.795085e-01
[33,] 0.79034742 4.193052e-01 2.096526e-01
[34,] 0.77898917 4.420217e-01 2.210108e-01
[35,] 0.76489804 4.702039e-01 2.351020e-01
[36,] 0.97503386 4.993229e-02 2.496614e-02
[37,] 0.99327890 1.344219e-02 6.721097e-03
[38,] 0.99367570 1.264860e-02 6.324299e-03
[39,] 0.99107964 1.784072e-02 8.920361e-03
[40,] 0.99278326 1.443348e-02 7.216741e-03
[41,] 0.99639536 7.209285e-03 3.604643e-03
[42,] 0.99544232 9.115364e-03 4.557682e-03
[43,] 0.99477484 1.045032e-02 5.225158e-03
[44,] 0.99536940 9.261209e-03 4.630604e-03
[45,] 0.99348687 1.302627e-02 6.513133e-03
[46,] 0.99128114 1.743771e-02 8.718856e-03
[47,] 0.98837590 2.324820e-02 1.162410e-02
[48,] 0.98468785 3.062430e-02 1.531215e-02
[49,] 0.98663446 2.673108e-02 1.336554e-02
[50,] 0.98347540 3.304920e-02 1.652460e-02
[51,] 0.98692507 2.614987e-02 1.307493e-02
[52,] 0.98241622 3.516756e-02 1.758378e-02
[53,] 0.98437629 3.124742e-02 1.562371e-02
[54,] 0.98642143 2.715714e-02 1.357857e-02
[55,] 0.98201422 3.597156e-02 1.798578e-02
[56,] 0.97683923 4.632154e-02 2.316077e-02
[57,] 0.97922928 4.154144e-02 2.077072e-02
[58,] 0.97405123 5.189753e-02 2.594877e-02
[59,] 0.97702947 4.594105e-02 2.297053e-02
[60,] 0.97036723 5.926555e-02 2.963277e-02
[61,] 0.96542886 6.914228e-02 3.457114e-02
[62,] 0.95569576 8.860847e-02 4.430424e-02
[63,] 0.94881633 1.023673e-01 5.118367e-02
[64,] 0.93667707 1.266459e-01 6.332293e-02
[65,] 0.92507861 1.498428e-01 7.492139e-02
[66,] 0.91091764 1.781647e-01 8.908236e-02
[67,] 0.98120183 3.759635e-02 1.879817e-02
[68,] 0.97663185 4.673629e-02 2.336815e-02
[69,] 0.97266043 5.467914e-02 2.733957e-02
[70,] 0.96459364 7.081273e-02 3.540636e-02
[71,] 0.95495127 9.009747e-02 4.504873e-02
[72,] 0.94799708 1.040058e-01 5.200292e-02
[73,] 0.99456130 1.087740e-02 5.438702e-03
[74,] 0.99359710 1.280580e-02 6.402901e-03
[75,] 0.99357501 1.284999e-02 6.424995e-03
[76,] 0.99245706 1.508588e-02 7.542939e-03
[77,] 0.99082326 1.835347e-02 9.176735e-03
[78,] 0.98754514 2.490972e-02 1.245486e-02
[79,] 0.98330894 3.338211e-02 1.669106e-02
[80,] 0.97946232 4.107536e-02 2.053768e-02
[81,] 0.99805262 3.894758e-03 1.947379e-03
[82,] 0.99789503 4.209940e-03 2.104970e-03
[83,] 0.99710399 5.792017e-03 2.896008e-03
[84,] 0.99587055 8.258903e-03 4.129452e-03
[85,] 0.99425655 1.148690e-02 5.743450e-03
[86,] 0.99414079 1.171841e-02 5.859207e-03
[87,] 0.99183209 1.633581e-02 8.167907e-03
[88,] 0.98955088 2.089823e-02 1.044912e-02
[89,] 0.98572744 2.854513e-02 1.427256e-02
[90,] 0.98247722 3.504557e-02 1.752278e-02
[91,] 0.97711355 4.577291e-02 2.288645e-02
[92,] 0.97214075 5.571851e-02 2.785925e-02
[93,] 0.96434280 7.131440e-02 3.565720e-02
[94,] 0.96007880 7.984241e-02 3.992120e-02
[95,] 0.95193347 9.613307e-02 4.806653e-02
[96,] 0.93989361 1.202128e-01 6.010639e-02
[97,] 0.95354517 9.290966e-02 4.645483e-02
[98,] 0.95658216 8.683568e-02 4.341784e-02
[99,] 0.94510564 1.097887e-01 5.489436e-02
[100,] 0.99250767 1.498466e-02 7.492332e-03
[101,] 0.99636076 7.278482e-03 3.639241e-03
[102,] 0.99870606 2.587887e-03 1.293944e-03
[103,] 0.99976274 4.745130e-04 2.372565e-04
[104,] 0.99961394 7.721184e-04 3.860592e-04
[105,] 0.99966507 6.698607e-04 3.349303e-04
[106,] 0.99948385 1.032302e-03 5.161512e-04
[107,] 0.99916996 1.660086e-03 8.300429e-04
[108,] 0.99877049 2.459011e-03 1.229505e-03
[109,] 0.99807029 3.859411e-03 1.929705e-03
[110,] 0.99729384 5.412320e-03 2.706160e-03
[111,] 0.99642813 7.143749e-03 3.571874e-03
[112,] 0.99718910 5.621796e-03 2.810898e-03
[113,] 0.99678801 6.423985e-03 3.211993e-03
[114,] 0.99788243 4.235148e-03 2.117574e-03
[115,] 0.99838823 3.223542e-03 1.611771e-03
[116,] 0.99829102 3.417963e-03 1.708981e-03
[117,] 0.99731315 5.373695e-03 2.686847e-03
[118,] 0.99893711 2.125773e-03 1.062887e-03
[119,] 0.99826964 3.460725e-03 1.730363e-03
[120,] 0.99710097 5.798062e-03 2.899031e-03
[121,] 0.99670601 6.587971e-03 3.293985e-03
[122,] 0.99507535 9.849298e-03 4.924649e-03
[123,] 0.99574779 8.504426e-03 4.252213e-03
[124,] 0.99600133 7.997330e-03 3.998665e-03
[125,] 0.99446195 1.107610e-02 5.538052e-03
[126,] 0.99213174 1.573653e-02 7.868263e-03
[127,] 0.99389040 1.221920e-02 6.109602e-03
[128,] 0.98981127 2.037746e-02 1.018873e-02
[129,] 0.99102237 1.795526e-02 8.977631e-03
[130,] 0.99990354 1.929182e-04 9.645910e-05
[131,] 0.99979429 4.114203e-04 2.057102e-04
[132,] 0.99999929 1.410922e-06 7.054609e-07
[133,] 0.99999759 4.824276e-06 2.412138e-06
[134,] 0.99999308 1.384642e-05 6.923211e-06
[135,] 0.99999844 3.128020e-06 1.564010e-06
[136,] 0.99999987 2.565418e-07 1.282709e-07
[137,] 0.99999990 1.956043e-07 9.780217e-08
[138,] 0.99999991 1.799219e-07 8.996093e-08
[139,] 0.99999994 1.157562e-07 5.787811e-08
[140,] 0.99999949 1.019756e-06 5.098780e-07
[141,] 0.99999783 4.339039e-06 2.169519e-06
[142,] 0.99998090 3.820233e-05 1.910117e-05
[143,] 0.99984313 3.137329e-04 1.568665e-04
[144,] 0.99882328 2.353440e-03 1.176720e-03
[145,] 0.99203065 1.593869e-02 7.969345e-03
> postscript(file="/var/www/rcomp/tmp/1fzxm1324646303.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/www/rcomp/tmp/2vqgi1324646303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3tc6a1324646303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4ki7h1324646303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/57zcq1324646303.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
44907.3456 -17909.3591 16148.3606 -58092.0724 13308.2494 -15790.7432
7 8 9 10 11 12
-7943.7840 3058.5501 -17080.7837 20117.3781 14011.1081 7298.3369
13 14 15 16 17 18
-9252.0377 50595.5714 10316.6259 -44328.7558 15772.6269 10508.5131
19 20 21 22 23 24
-2028.9904 12413.1671 13594.4325 107635.3590 6209.2521 -28004.9129
25 26 27 28 29 30
-67108.9609 -43110.9770 -31129.6760 25236.1552 2822.2116 -22282.7353
31 32 33 34 35 36
-24861.9547 -8423.9651 12685.0296 -4627.8586 14979.3268 17282.6281
37 38 39 40 41 42
36668.1673 14819.6243 23952.8076 -6138.7463 -13306.5179 -10568.8542
43 44 45 46 47 48
-17906.1719 19462.3434 -94368.1201 54504.5694 -27860.9353 -4990.7468
49 50 51 52 53 54
-38082.8655 -52312.4023 -15222.6625 -15535.3221 35222.6481 -1181.9161
55 56 57 58 59 60
-7775.3278 8648.6324 6069.4651 -31786.1816 -19007.2674 37294.8647
61 62 63 64 65 66
-4087.4540 -36711.8367 -31272.6262 9144.8862 6516.4303 28200.4573
67 68 69 70 71 72
-11172.6517 -34371.1456 -3180.3769 -22748.2553 -2194.0404 -15124.9585
73 74 75 76 77 78
7150.9022 -4026.0829 -15478.9735 73699.2492 12149.0894 -20935.0629
79 80 81 82 83 84
-5871.0155 -3580.9599 -16086.5801 82311.3830 -18513.0304 27787.8795
85 86 87 88 89 90
-20191.3043 -9951.2129 -4417.5060 4211.6398 17886.8640 -75786.0415
91 92 93 94 95 96
27114.2901 8821.2596 4093.3507 3612.0110 26253.6331 -738.4416
97 98 99 100 101 102
8894.9070 -4170.6348 -16330.0925 8080.7160 15454.8638 -11017.3710
103 104 105 106 107 108
-13356.7138 -14302.2361 2275.7811 -32749.1932 -23142.3418 11274.2288
109 110 111 112 113 114
-75732.3206 -40384.0311 43589.7115 58858.3587 2874.3322 -22557.5339
115 116 117 118 119 120
11090.7567 5708.1420 14250.5929 1054.5488 17722.6063 -6917.5616
121 122 123 124 125 126
-28778.0331 19674.2683 35091.2419 -25586.0725 -14726.3651 2793.5848
127 128 129 130 131 132
30850.9393 -7100.7440 577.7499 -19918.7538 3455.2008 4742.0496
133 134 135 136 137 138
-27902.5048 1974.6814 11348.9446 8276.6255 -518.0180 -22704.8731
139 140 141 142 143 144
18368.9321 -7035.7125 26970.3146 18061.1472 -460.7307 43934.9224
145 146 147 148 149 150
23637.3111 -46150.1989 -42846.4660 2719.9011 6087.5340 2737.0797
151 152 153 154 155 156
6002.6622 6177.7904 6086.5340 6086.5340 13085.6860 38441.2601
157 158 159 160 161 162
6086.5340 5562.0467 -120.0244 -3379.6752 7715.4028 29069.9417
163 164
6691.7904 34414.5323
> postscript(file="/var/www/rcomp/tmp/6vrso1324646303.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 44907.3456 NA
1 -17909.3591 44907.3456
2 16148.3606 -17909.3591
3 -58092.0724 16148.3606
4 13308.2494 -58092.0724
5 -15790.7432 13308.2494
6 -7943.7840 -15790.7432
7 3058.5501 -7943.7840
8 -17080.7837 3058.5501
9 20117.3781 -17080.7837
10 14011.1081 20117.3781
11 7298.3369 14011.1081
12 -9252.0377 7298.3369
13 50595.5714 -9252.0377
14 10316.6259 50595.5714
15 -44328.7558 10316.6259
16 15772.6269 -44328.7558
17 10508.5131 15772.6269
18 -2028.9904 10508.5131
19 12413.1671 -2028.9904
20 13594.4325 12413.1671
21 107635.3590 13594.4325
22 6209.2521 107635.3590
23 -28004.9129 6209.2521
24 -67108.9609 -28004.9129
25 -43110.9770 -67108.9609
26 -31129.6760 -43110.9770
27 25236.1552 -31129.6760
28 2822.2116 25236.1552
29 -22282.7353 2822.2116
30 -24861.9547 -22282.7353
31 -8423.9651 -24861.9547
32 12685.0296 -8423.9651
33 -4627.8586 12685.0296
34 14979.3268 -4627.8586
35 17282.6281 14979.3268
36 36668.1673 17282.6281
37 14819.6243 36668.1673
38 23952.8076 14819.6243
39 -6138.7463 23952.8076
40 -13306.5179 -6138.7463
41 -10568.8542 -13306.5179
42 -17906.1719 -10568.8542
43 19462.3434 -17906.1719
44 -94368.1201 19462.3434
45 54504.5694 -94368.1201
46 -27860.9353 54504.5694
47 -4990.7468 -27860.9353
48 -38082.8655 -4990.7468
49 -52312.4023 -38082.8655
50 -15222.6625 -52312.4023
51 -15535.3221 -15222.6625
52 35222.6481 -15535.3221
53 -1181.9161 35222.6481
54 -7775.3278 -1181.9161
55 8648.6324 -7775.3278
56 6069.4651 8648.6324
57 -31786.1816 6069.4651
58 -19007.2674 -31786.1816
59 37294.8647 -19007.2674
60 -4087.4540 37294.8647
61 -36711.8367 -4087.4540
62 -31272.6262 -36711.8367
63 9144.8862 -31272.6262
64 6516.4303 9144.8862
65 28200.4573 6516.4303
66 -11172.6517 28200.4573
67 -34371.1456 -11172.6517
68 -3180.3769 -34371.1456
69 -22748.2553 -3180.3769
70 -2194.0404 -22748.2553
71 -15124.9585 -2194.0404
72 7150.9022 -15124.9585
73 -4026.0829 7150.9022
74 -15478.9735 -4026.0829
75 73699.2492 -15478.9735
76 12149.0894 73699.2492
77 -20935.0629 12149.0894
78 -5871.0155 -20935.0629
79 -3580.9599 -5871.0155
80 -16086.5801 -3580.9599
81 82311.3830 -16086.5801
82 -18513.0304 82311.3830
83 27787.8795 -18513.0304
84 -20191.3043 27787.8795
85 -9951.2129 -20191.3043
86 -4417.5060 -9951.2129
87 4211.6398 -4417.5060
88 17886.8640 4211.6398
89 -75786.0415 17886.8640
90 27114.2901 -75786.0415
91 8821.2596 27114.2901
92 4093.3507 8821.2596
93 3612.0110 4093.3507
94 26253.6331 3612.0110
95 -738.4416 26253.6331
96 8894.9070 -738.4416
97 -4170.6348 8894.9070
98 -16330.0925 -4170.6348
99 8080.7160 -16330.0925
100 15454.8638 8080.7160
101 -11017.3710 15454.8638
102 -13356.7138 -11017.3710
103 -14302.2361 -13356.7138
104 2275.7811 -14302.2361
105 -32749.1932 2275.7811
106 -23142.3418 -32749.1932
107 11274.2288 -23142.3418
108 -75732.3206 11274.2288
109 -40384.0311 -75732.3206
110 43589.7115 -40384.0311
111 58858.3587 43589.7115
112 2874.3322 58858.3587
113 -22557.5339 2874.3322
114 11090.7567 -22557.5339
115 5708.1420 11090.7567
116 14250.5929 5708.1420
117 1054.5488 14250.5929
118 17722.6063 1054.5488
119 -6917.5616 17722.6063
120 -28778.0331 -6917.5616
121 19674.2683 -28778.0331
122 35091.2419 19674.2683
123 -25586.0725 35091.2419
124 -14726.3651 -25586.0725
125 2793.5848 -14726.3651
126 30850.9393 2793.5848
127 -7100.7440 30850.9393
128 577.7499 -7100.7440
129 -19918.7538 577.7499
130 3455.2008 -19918.7538
131 4742.0496 3455.2008
132 -27902.5048 4742.0496
133 1974.6814 -27902.5048
134 11348.9446 1974.6814
135 8276.6255 11348.9446
136 -518.0180 8276.6255
137 -22704.8731 -518.0180
138 18368.9321 -22704.8731
139 -7035.7125 18368.9321
140 26970.3146 -7035.7125
141 18061.1472 26970.3146
142 -460.7307 18061.1472
143 43934.9224 -460.7307
144 23637.3111 43934.9224
145 -46150.1989 23637.3111
146 -42846.4660 -46150.1989
147 2719.9011 -42846.4660
148 6087.5340 2719.9011
149 2737.0797 6087.5340
150 6002.6622 2737.0797
151 6177.7904 6002.6622
152 6086.5340 6177.7904
153 6086.5340 6086.5340
154 13085.6860 6086.5340
155 38441.2601 13085.6860
156 6086.5340 38441.2601
157 5562.0467 6086.5340
158 -120.0244 5562.0467
159 -3379.6752 -120.0244
160 7715.4028 -3379.6752
161 29069.9417 7715.4028
162 6691.7904 29069.9417
163 34414.5323 6691.7904
164 NA 34414.5323
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -17909.3591 44907.3456
[2,] 16148.3606 -17909.3591
[3,] -58092.0724 16148.3606
[4,] 13308.2494 -58092.0724
[5,] -15790.7432 13308.2494
[6,] -7943.7840 -15790.7432
[7,] 3058.5501 -7943.7840
[8,] -17080.7837 3058.5501
[9,] 20117.3781 -17080.7837
[10,] 14011.1081 20117.3781
[11,] 7298.3369 14011.1081
[12,] -9252.0377 7298.3369
[13,] 50595.5714 -9252.0377
[14,] 10316.6259 50595.5714
[15,] -44328.7558 10316.6259
[16,] 15772.6269 -44328.7558
[17,] 10508.5131 15772.6269
[18,] -2028.9904 10508.5131
[19,] 12413.1671 -2028.9904
[20,] 13594.4325 12413.1671
[21,] 107635.3590 13594.4325
[22,] 6209.2521 107635.3590
[23,] -28004.9129 6209.2521
[24,] -67108.9609 -28004.9129
[25,] -43110.9770 -67108.9609
[26,] -31129.6760 -43110.9770
[27,] 25236.1552 -31129.6760
[28,] 2822.2116 25236.1552
[29,] -22282.7353 2822.2116
[30,] -24861.9547 -22282.7353
[31,] -8423.9651 -24861.9547
[32,] 12685.0296 -8423.9651
[33,] -4627.8586 12685.0296
[34,] 14979.3268 -4627.8586
[35,] 17282.6281 14979.3268
[36,] 36668.1673 17282.6281
[37,] 14819.6243 36668.1673
[38,] 23952.8076 14819.6243
[39,] -6138.7463 23952.8076
[40,] -13306.5179 -6138.7463
[41,] -10568.8542 -13306.5179
[42,] -17906.1719 -10568.8542
[43,] 19462.3434 -17906.1719
[44,] -94368.1201 19462.3434
[45,] 54504.5694 -94368.1201
[46,] -27860.9353 54504.5694
[47,] -4990.7468 -27860.9353
[48,] -38082.8655 -4990.7468
[49,] -52312.4023 -38082.8655
[50,] -15222.6625 -52312.4023
[51,] -15535.3221 -15222.6625
[52,] 35222.6481 -15535.3221
[53,] -1181.9161 35222.6481
[54,] -7775.3278 -1181.9161
[55,] 8648.6324 -7775.3278
[56,] 6069.4651 8648.6324
[57,] -31786.1816 6069.4651
[58,] -19007.2674 -31786.1816
[59,] 37294.8647 -19007.2674
[60,] -4087.4540 37294.8647
[61,] -36711.8367 -4087.4540
[62,] -31272.6262 -36711.8367
[63,] 9144.8862 -31272.6262
[64,] 6516.4303 9144.8862
[65,] 28200.4573 6516.4303
[66,] -11172.6517 28200.4573
[67,] -34371.1456 -11172.6517
[68,] -3180.3769 -34371.1456
[69,] -22748.2553 -3180.3769
[70,] -2194.0404 -22748.2553
[71,] -15124.9585 -2194.0404
[72,] 7150.9022 -15124.9585
[73,] -4026.0829 7150.9022
[74,] -15478.9735 -4026.0829
[75,] 73699.2492 -15478.9735
[76,] 12149.0894 73699.2492
[77,] -20935.0629 12149.0894
[78,] -5871.0155 -20935.0629
[79,] -3580.9599 -5871.0155
[80,] -16086.5801 -3580.9599
[81,] 82311.3830 -16086.5801
[82,] -18513.0304 82311.3830
[83,] 27787.8795 -18513.0304
[84,] -20191.3043 27787.8795
[85,] -9951.2129 -20191.3043
[86,] -4417.5060 -9951.2129
[87,] 4211.6398 -4417.5060
[88,] 17886.8640 4211.6398
[89,] -75786.0415 17886.8640
[90,] 27114.2901 -75786.0415
[91,] 8821.2596 27114.2901
[92,] 4093.3507 8821.2596
[93,] 3612.0110 4093.3507
[94,] 26253.6331 3612.0110
[95,] -738.4416 26253.6331
[96,] 8894.9070 -738.4416
[97,] -4170.6348 8894.9070
[98,] -16330.0925 -4170.6348
[99,] 8080.7160 -16330.0925
[100,] 15454.8638 8080.7160
[101,] -11017.3710 15454.8638
[102,] -13356.7138 -11017.3710
[103,] -14302.2361 -13356.7138
[104,] 2275.7811 -14302.2361
[105,] -32749.1932 2275.7811
[106,] -23142.3418 -32749.1932
[107,] 11274.2288 -23142.3418
[108,] -75732.3206 11274.2288
[109,] -40384.0311 -75732.3206
[110,] 43589.7115 -40384.0311
[111,] 58858.3587 43589.7115
[112,] 2874.3322 58858.3587
[113,] -22557.5339 2874.3322
[114,] 11090.7567 -22557.5339
[115,] 5708.1420 11090.7567
[116,] 14250.5929 5708.1420
[117,] 1054.5488 14250.5929
[118,] 17722.6063 1054.5488
[119,] -6917.5616 17722.6063
[120,] -28778.0331 -6917.5616
[121,] 19674.2683 -28778.0331
[122,] 35091.2419 19674.2683
[123,] -25586.0725 35091.2419
[124,] -14726.3651 -25586.0725
[125,] 2793.5848 -14726.3651
[126,] 30850.9393 2793.5848
[127,] -7100.7440 30850.9393
[128,] 577.7499 -7100.7440
[129,] -19918.7538 577.7499
[130,] 3455.2008 -19918.7538
[131,] 4742.0496 3455.2008
[132,] -27902.5048 4742.0496
[133,] 1974.6814 -27902.5048
[134,] 11348.9446 1974.6814
[135,] 8276.6255 11348.9446
[136,] -518.0180 8276.6255
[137,] -22704.8731 -518.0180
[138,] 18368.9321 -22704.8731
[139,] -7035.7125 18368.9321
[140,] 26970.3146 -7035.7125
[141,] 18061.1472 26970.3146
[142,] -460.7307 18061.1472
[143,] 43934.9224 -460.7307
[144,] 23637.3111 43934.9224
[145,] -46150.1989 23637.3111
[146,] -42846.4660 -46150.1989
[147,] 2719.9011 -42846.4660
[148,] 6087.5340 2719.9011
[149,] 2737.0797 6087.5340
[150,] 6002.6622 2737.0797
[151,] 6177.7904 6002.6622
[152,] 6086.5340 6177.7904
[153,] 6086.5340 6086.5340
[154,] 13085.6860 6086.5340
[155,] 38441.2601 13085.6860
[156,] 6086.5340 38441.2601
[157,] 5562.0467 6086.5340
[158,] -120.0244 5562.0467
[159,] -3379.6752 -120.0244
[160,] 7715.4028 -3379.6752
[161,] 29069.9417 7715.4028
[162,] 6691.7904 29069.9417
[163,] 34414.5323 6691.7904
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -17909.3591 44907.3456
2 16148.3606 -17909.3591
3 -58092.0724 16148.3606
4 13308.2494 -58092.0724
5 -15790.7432 13308.2494
6 -7943.7840 -15790.7432
7 3058.5501 -7943.7840
8 -17080.7837 3058.5501
9 20117.3781 -17080.7837
10 14011.1081 20117.3781
11 7298.3369 14011.1081
12 -9252.0377 7298.3369
13 50595.5714 -9252.0377
14 10316.6259 50595.5714
15 -44328.7558 10316.6259
16 15772.6269 -44328.7558
17 10508.5131 15772.6269
18 -2028.9904 10508.5131
19 12413.1671 -2028.9904
20 13594.4325 12413.1671
21 107635.3590 13594.4325
22 6209.2521 107635.3590
23 -28004.9129 6209.2521
24 -67108.9609 -28004.9129
25 -43110.9770 -67108.9609
26 -31129.6760 -43110.9770
27 25236.1552 -31129.6760
28 2822.2116 25236.1552
29 -22282.7353 2822.2116
30 -24861.9547 -22282.7353
31 -8423.9651 -24861.9547
32 12685.0296 -8423.9651
33 -4627.8586 12685.0296
34 14979.3268 -4627.8586
35 17282.6281 14979.3268
36 36668.1673 17282.6281
37 14819.6243 36668.1673
38 23952.8076 14819.6243
39 -6138.7463 23952.8076
40 -13306.5179 -6138.7463
41 -10568.8542 -13306.5179
42 -17906.1719 -10568.8542
43 19462.3434 -17906.1719
44 -94368.1201 19462.3434
45 54504.5694 -94368.1201
46 -27860.9353 54504.5694
47 -4990.7468 -27860.9353
48 -38082.8655 -4990.7468
49 -52312.4023 -38082.8655
50 -15222.6625 -52312.4023
51 -15535.3221 -15222.6625
52 35222.6481 -15535.3221
53 -1181.9161 35222.6481
54 -7775.3278 -1181.9161
55 8648.6324 -7775.3278
56 6069.4651 8648.6324
57 -31786.1816 6069.4651
58 -19007.2674 -31786.1816
59 37294.8647 -19007.2674
60 -4087.4540 37294.8647
61 -36711.8367 -4087.4540
62 -31272.6262 -36711.8367
63 9144.8862 -31272.6262
64 6516.4303 9144.8862
65 28200.4573 6516.4303
66 -11172.6517 28200.4573
67 -34371.1456 -11172.6517
68 -3180.3769 -34371.1456
69 -22748.2553 -3180.3769
70 -2194.0404 -22748.2553
71 -15124.9585 -2194.0404
72 7150.9022 -15124.9585
73 -4026.0829 7150.9022
74 -15478.9735 -4026.0829
75 73699.2492 -15478.9735
76 12149.0894 73699.2492
77 -20935.0629 12149.0894
78 -5871.0155 -20935.0629
79 -3580.9599 -5871.0155
80 -16086.5801 -3580.9599
81 82311.3830 -16086.5801
82 -18513.0304 82311.3830
83 27787.8795 -18513.0304
84 -20191.3043 27787.8795
85 -9951.2129 -20191.3043
86 -4417.5060 -9951.2129
87 4211.6398 -4417.5060
88 17886.8640 4211.6398
89 -75786.0415 17886.8640
90 27114.2901 -75786.0415
91 8821.2596 27114.2901
92 4093.3507 8821.2596
93 3612.0110 4093.3507
94 26253.6331 3612.0110
95 -738.4416 26253.6331
96 8894.9070 -738.4416
97 -4170.6348 8894.9070
98 -16330.0925 -4170.6348
99 8080.7160 -16330.0925
100 15454.8638 8080.7160
101 -11017.3710 15454.8638
102 -13356.7138 -11017.3710
103 -14302.2361 -13356.7138
104 2275.7811 -14302.2361
105 -32749.1932 2275.7811
106 -23142.3418 -32749.1932
107 11274.2288 -23142.3418
108 -75732.3206 11274.2288
109 -40384.0311 -75732.3206
110 43589.7115 -40384.0311
111 58858.3587 43589.7115
112 2874.3322 58858.3587
113 -22557.5339 2874.3322
114 11090.7567 -22557.5339
115 5708.1420 11090.7567
116 14250.5929 5708.1420
117 1054.5488 14250.5929
118 17722.6063 1054.5488
119 -6917.5616 17722.6063
120 -28778.0331 -6917.5616
121 19674.2683 -28778.0331
122 35091.2419 19674.2683
123 -25586.0725 35091.2419
124 -14726.3651 -25586.0725
125 2793.5848 -14726.3651
126 30850.9393 2793.5848
127 -7100.7440 30850.9393
128 577.7499 -7100.7440
129 -19918.7538 577.7499
130 3455.2008 -19918.7538
131 4742.0496 3455.2008
132 -27902.5048 4742.0496
133 1974.6814 -27902.5048
134 11348.9446 1974.6814
135 8276.6255 11348.9446
136 -518.0180 8276.6255
137 -22704.8731 -518.0180
138 18368.9321 -22704.8731
139 -7035.7125 18368.9321
140 26970.3146 -7035.7125
141 18061.1472 26970.3146
142 -460.7307 18061.1472
143 43934.9224 -460.7307
144 23637.3111 43934.9224
145 -46150.1989 23637.3111
146 -42846.4660 -46150.1989
147 2719.9011 -42846.4660
148 6087.5340 2719.9011
149 2737.0797 6087.5340
150 6002.6622 2737.0797
151 6177.7904 6002.6622
152 6086.5340 6177.7904
153 6086.5340 6086.5340
154 13085.6860 6086.5340
155 38441.2601 13085.6860
156 6086.5340 38441.2601
157 5562.0467 6086.5340
158 -120.0244 5562.0467
159 -3379.6752 -120.0244
160 7715.4028 -3379.6752
161 29069.9417 7715.4028
162 6691.7904 29069.9417
163 34414.5323 6691.7904
> 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/www/rcomp/tmp/7dlmp1324646303.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/www/rcomp/tmp/89r4p1324646303.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/www/rcomp/tmp/9q1cm1324646303.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/www/rcomp/tmp/10rs5l1324646303.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/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/114bvo1324646303.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/12t3611324646303.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/133isy1324646303.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/149kmn1324646303.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/www/rcomp/tmp/1569dg1324646303.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/www/rcomp/tmp/160h6r1324646303.tab")
+ }
>
> try(system("convert tmp/1fzxm1324646303.ps tmp/1fzxm1324646303.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vqgi1324646303.ps tmp/2vqgi1324646303.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tc6a1324646303.ps tmp/3tc6a1324646303.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ki7h1324646303.ps tmp/4ki7h1324646303.png",intern=TRUE))
character(0)
> try(system("convert tmp/57zcq1324646303.ps tmp/57zcq1324646303.png",intern=TRUE))
character(0)
> try(system("convert tmp/6vrso1324646303.ps tmp/6vrso1324646303.png",intern=TRUE))
character(0)
> try(system("convert tmp/7dlmp1324646303.ps tmp/7dlmp1324646303.png",intern=TRUE))
character(0)
> try(system("convert tmp/89r4p1324646303.ps tmp/89r4p1324646303.png",intern=TRUE))
character(0)
> try(system("convert tmp/9q1cm1324646303.ps tmp/9q1cm1324646303.png",intern=TRUE))
character(0)
> try(system("convert tmp/10rs5l1324646303.ps tmp/10rs5l1324646303.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.280 0.260 6.541