R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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Type 'license()' or 'licence()' for distribution details.
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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(279055
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+ ,dim=c(7
+ ,164)
+ ,dimnames=list(c('Time'
+ ,'Logins'
+ ,'CompendiumViews'
+ ,'BloggedComputations'
+ ,'ReviewedCompendiums'
+ ,'LongFeedbackmessages'
+ ,'WritingTime')
+ ,1:164))
> y <- array(NA,dim=c(7,164),dimnames=list(c('Time','Logins','CompendiumViews','BloggedComputations','ReviewedCompendiums','LongFeedbackmessages','WritingTime'),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 CompendiumViews BloggedComputations ReviewedCompendiums
1 279055 73 504 96 42
2 209884 73 502 75 38
3 233939 83 710 70 46
4 222117 106 1154 134 42
5 179751 54 402 72 30
6 70849 28 179 8 35
7 568125 131 2452 169 40
8 33186 19 111 1 18
9 227332 62 763 88 38
10 258874 48 650 98 37
11 351915 118 933 106 46
12 260484 129 728 122 60
13 204003 83 764 57 37
14 368577 85 1186 139 55
15 269455 88 724 87 44
16 395936 187 1758 176 63
17 335567 76 845 114 40
18 423110 171 1382 121 43
19 182016 58 514 103 32
20 267365 88 692 135 52
21 279428 73 847 123 49
22 508849 111 1397 99 41
23 206722 47 533 74 25
24 200004 58 636 103 57
25 257139 132 1370 158 45
26 270815 137 1090 116 42
27 296850 133 1149 102 45
28 307100 90 715 132 43
29 184160 58 639 62 36
30 393860 79 1213 150 45
31 327660 89 1111 143 50
32 252512 82 728 50 50
33 373013 102 885 141 51
34 115602 46 410 48 42
35 430118 103 1293 141 44
36 273950 56 1186 83 42
37 428077 128 1348 112 44
38 251349 91 689 79 40
39 115658 34 284 33 17
40 388812 208 1304 149 43
41 343783 85 1556 126 41
42 207021 76 770 85 41
43 214344 81 676 84 40
44 182398 66 487 68 49
45 157164 84 1051 50 52
46 459455 157 2089 101 42
47 78800 42 330 20 26
48 217932 84 694 101 59
49 368086 122 1410 150 50
50 215843 67 1090 118 50
51 244765 80 690 99 47
52 24188 24 218 8 4
53 399093 333 862 88 51
54 65029 17 255 21 18
55 101097 64 454 30 14
56 300488 64 1208 97 41
57 369627 90 785 163 61
58 367127 204 1208 132 40
59 374193 152 1096 161 44
60 270099 88 887 89 40
61 391871 151 1335 160 51
62 315924 121 1190 139 29
63 291391 124 1257 104 43
64 295075 93 1030 103 42
65 276201 78 658 66 41
66 267432 71 542 163 30
67 215924 140 651 93 39
68 256641 157 888 85 51
69 260919 87 913 150 40
70 182961 73 637 143 29
71 256967 74 900 107 47
72 73566 32 385 22 23
73 272362 93 784 85 48
74 220707 61 891 91 38
75 228835 68 779 131 42
76 371391 91 1001 140 46
77 398210 104 1265 156 40
78 220401 110 586 81 45
79 229333 70 765 137 42
80 217623 71 737 102 41
81 200046 53 766 72 37
82 483074 131 1272 161 47
83 145943 71 653 30 26
84 295224 108 703 120 48
85 80953 25 437 49 8
86 180759 61 936 71 27
87 179344 61 459 76 38
88 415550 221 1586 85 41
89 369093 128 1053 146 61
90 180679 106 1051 165 45
91 299505 104 846 89 41
92 292260 84 732 168 42
93 199481 67 632 48 35
94 282361 78 1128 149 36
95 329281 89 971 75 40
96 234577 48 711 107 40
97 297995 67 738 116 38
98 305984 88 820 165 43
99 416463 163 1369 155 65
100 414359 118 1501 165 33
101 297080 142 893 121 51
102 318283 70 902 156 45
103 222281 197 782 86 36
104 43287 14 214 13 19
105 223456 86 795 113 25
106 258249 158 874 112 44
107 299566 60 1275 133 45
108 321797 95 1079 169 44
109 174736 89 443 30 35
110 169579 102 977 121 46
111 354041 77 677 82 44
112 303273 90 696 148 45
113 23668 13 156 12 1
114 196743 79 785 146 40
115 61857 25 192 23 11
116 207339 53 606 84 51
117 431443 123 1234 163 38
118 21054 16 146 4 0
119 252805 52 866 81 30
120 31961 22 200 18 8
121 360401 124 1350 118 43
122 251240 76 735 76 48
123 187003 96 522 55 49
124 180842 58 724 62 32
125 38214 34 276 16 8
126 278173 55 859 98 43
127 358276 84 1031 137 52
128 211775 66 511 50 53
129 445926 89 1708 152 49
130 348017 99 884 163 48
131 441946 133 1201 142 56
132 210700 42 559 77 45
133 126320 46 478 59 40
134 316128 361 1005 94 48
135 466139 198 1574 128 50
136 162279 62 575 63 43
137 412099 139 1812 127 46
138 173802 83 755 59 40
139 292443 54 668 118 45
140 283913 100 905 110 46
141 243609 124 682 45 37
142 387072 125 1613 96 45
143 246963 92 811 128 39
144 173260 63 716 41 21
145 346748 108 1034 146 50
146 176654 58 732 147 55
147 264767 92 1060 121 40
148 314070 112 852 185 48
149 1 0 0 0 0
150 14688 10 85 4 0
151 98 1 0 0 0
152 455 2 0 0 0
153 0 0 0 0 0
154 0 0 0 0 0
155 284420 92 809 85 46
156 410509 164 1134 157 52
157 0 0 0 0 0
158 203 4 0 0 0
159 7199 5 74 7 0
160 46660 20 259 12 5
161 17547 5 69 0 1
162 121550 46 309 37 48
163 969 2 0 0 0
164 242258 74 690 62 34
LongFeedbackmessages WritingTime
1 130 186099
2 143 113854
3 118 99776
4 146 106194
5 73 100792
6 89 47552
7 146 250931
8 22 6853
9 132 115466
10 92 110896
11 147 169351
12 203 94853
13 113 72591
14 171 101345
15 87 113713
16 208 165354
17 153 164263
18 97 135213
19 95 111669
20 197 134163
21 160 140303
22 148 150773
23 84 111848
24 227 102509
25 154 96785
26 151 116136
27 142 158376
28 148 153990
29 110 64057
30 149 230054
31 179 184531
32 149 114198
33 187 198299
34 153 33750
35 163 189723
36 127 100826
37 151 188355
38 100 104470
39 46 58391
40 156 164808
41 128 134097
42 111 80238
43 119 133252
44 148 54518
45 65 121850
46 134 79367
47 66 56968
48 201 106314
49 177 191889
50 156 104864
51 158 160792
52 7 15049
53 175 191179
54 61 25109
55 41 45824
56 133 129711
57 228 210012
58 140 194679
59 155 197680
60 141 81180
61 181 197765
62 75 214738
63 97 96252
64 142 124527
65 136 153242
66 87 145707
67 140 113963
68 169 134904
69 129 114268
70 92 94333
71 160 102204
72 67 23824
73 179 111563
74 90 91313
75 144 89770
76 144 100125
77 144 165278
78 134 181712
79 146 80906
80 121 75881
81 112 83963
82 145 175721
83 99 68580
84 96 136323
85 27 55792
86 77 25157
87 137 100922
88 151 118845
89 126 170492
90 159 81716
91 101 115750
92 144 105590
93 102 92795
94 135 82390
95 147 135599
96 155 127667
97 138 163073
98 113 211381
99 248 189944
100 116 226168
101 176 117495
102 140 195894
103 59 80684
104 64 19630
105 40 88634
106 98 139292
107 139 128602
108 135 135848
109 97 178377
110 142 106330
111 155 178303
112 115 116938
113 0 5841
114 103 106020
115 30 24610
116 130 74151
117 102 232241
118 0 6622
119 77 127097
120 9 13155
121 150 160501
122 163 91502
123 148 24469
124 94 88229
125 21 13983
126 151 80716
127 187 157384
128 171 122975
129 170 191469
130 145 231257
131 198 258287
132 152 122531
133 112 61394
134 173 86480
135 177 195791
136 153 18284
137 161 147581
138 115 72558
139 147 147341
140 124 114651
141 57 100187
142 144 130332
143 126 134218
144 78 10901
145 153 145758
146 196 75767
147 130 134969
148 159 169216
149 0 0
150 0 7953
151 0 0
152 0 0
153 0 0
154 0 0
155 94 105406
156 129 174586
157 0 0
158 0 0
159 0 4245
160 13 21509
161 4 7670
162 89 15673
163 0 0
164 71 75882
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Logins CompendiumViews
-5401.8951 224.1105 127.9143
BloggedComputations ReviewedCompendiums LongFeedbackmessages
123.3972 544.5622 102.5921
WritingTime
0.7589
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-124331 -18242 95 19117 146522
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -5.402e+03 7.653e+03 -0.706 0.48132
Logins 2.241e+02 7.598e+01 2.950 0.00367 **
CompendiumViews 1.279e+02 1.138e+01 11.241 < 2e-16 ***
BloggedComputations 1.234e+02 1.124e+02 1.098 0.27390
ReviewedCompendiums 5.446e+02 4.930e+02 1.105 0.27105
LongFeedbackmessages 1.026e+02 1.344e+02 0.763 0.44639
WritingTime 7.590e-01 8.078e-02 9.395 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 36490 on 157 degrees of freedom
Multiple R-squared: 0.9172, Adjusted R-squared: 0.9141
F-statistic: 289.9 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,] 0.4727614 9.455227e-01 5.272386e-01
[2,] 0.4471902 8.943804e-01 5.528098e-01
[3,] 0.4075930 8.151861e-01 5.924070e-01
[4,] 0.3091146 6.182292e-01 6.908854e-01
[5,] 0.4500365 9.000729e-01 5.499635e-01
[6,] 0.3547238 7.094476e-01 6.452762e-01
[7,] 0.3999249 7.998498e-01 6.000751e-01
[8,] 0.3782580 7.565160e-01 6.217420e-01
[9,] 0.6967317 6.065366e-01 3.032683e-01
[10,] 0.6677016 6.645968e-01 3.322984e-01
[11,] 0.5896472 8.207056e-01 4.103528e-01
[12,] 0.5269684 9.460632e-01 4.730316e-01
[13,] 0.9916967 1.660651e-02 8.303256e-03
[14,] 0.9875076 2.498475e-02 1.249238e-02
[15,] 0.9838874 3.222525e-02 1.611262e-02
[16,] 0.9867885 2.642307e-02 1.321154e-02
[17,] 0.9826330 3.473404e-02 1.736702e-02
[18,] 0.9900421 1.991575e-02 9.957877e-03
[19,] 0.9883266 2.334683e-02 1.167342e-02
[20,] 0.9829997 3.400053e-02 1.700026e-02
[21,] 0.9807342 3.853157e-02 1.926579e-02
[22,] 0.9788898 4.222039e-02 2.111020e-02
[23,] 0.9722166 5.556687e-02 2.778344e-02
[24,] 0.9663837 6.723257e-02 3.361629e-02
[25,] 0.9545254 9.094928e-02 4.547464e-02
[26,] 0.9578396 8.432080e-02 4.216040e-02
[27,] 0.9452799 1.094403e-01 5.472014e-02
[28,] 0.9365516 1.268967e-01 6.344837e-02
[29,] 0.9224366 1.551268e-01 7.756340e-02
[30,] 0.9023784 1.952432e-01 9.762158e-02
[31,] 0.8772818 2.454363e-01 1.227182e-01
[32,] 0.8546788 2.906424e-01 1.453212e-01
[33,] 0.8231460 3.537080e-01 1.768540e-01
[34,] 0.8355551 3.288898e-01 1.644449e-01
[35,] 0.8138037 3.723925e-01 1.861963e-01
[36,] 0.9869469 2.610621e-02 1.305311e-02
[37,] 0.9910973 1.780541e-02 8.902707e-03
[38,] 0.9920028 1.599443e-02 7.997216e-03
[39,] 0.9903043 1.939135e-02 9.695676e-03
[40,] 0.9913170 1.736593e-02 8.682965e-03
[41,] 0.9951507 9.698532e-03 4.849266e-03
[42,] 0.9947639 1.047216e-02 5.236080e-03
[43,] 0.9946503 1.069938e-02 5.349688e-03
[44,] 0.9936336 1.273280e-02 6.366399e-03
[45,] 0.9913175 1.736506e-02 8.682529e-03
[46,] 0.9894449 2.111028e-02 1.055514e-02
[47,] 0.9859466 2.810679e-02 1.405339e-02
[48,] 0.9826494 3.470125e-02 1.735062e-02
[49,] 0.9814374 3.712525e-02 1.856262e-02
[50,] 0.9753970 4.920598e-02 2.460299e-02
[51,] 0.9741024 5.179525e-02 2.589762e-02
[52,] 0.9689985 6.200306e-02 3.100153e-02
[53,] 0.9794988 4.100237e-02 2.050119e-02
[54,] 0.9746695 5.066102e-02 2.533051e-02
[55,] 0.9668909 6.621829e-02 3.310914e-02
[56,] 0.9592851 8.142977e-02 4.071488e-02
[57,] 0.9622461 7.550777e-02 3.775388e-02
[58,] 0.9571415 8.571695e-02 4.285847e-02
[59,] 0.9613832 7.723365e-02 3.861682e-02
[60,] 0.9511550 9.769000e-02 4.884500e-02
[61,] 0.9421577 1.156847e-01 5.784234e-02
[62,] 0.9277034 1.445932e-01 7.229658e-02
[63,] 0.9158725 1.682550e-01 8.412751e-02
[64,] 0.9002421 1.995159e-01 9.975794e-02
[65,] 0.8833401 2.333198e-01 1.166599e-01
[66,] 0.8595792 2.808415e-01 1.404208e-01
[67,] 0.9620324 7.593523e-02 3.796761e-02
[68,] 0.9623327 7.533465e-02 3.766732e-02
[69,] 0.9752874 4.942526e-02 2.471263e-02
[70,] 0.9680717 6.385667e-02 3.192833e-02
[71,] 0.9593902 8.121954e-02 4.060977e-02
[72,] 0.9494006 1.011989e-01 5.059943e-02
[73,] 0.9935811 1.283780e-02 6.418901e-03
[74,] 0.9929981 1.400373e-02 7.001865e-03
[75,] 0.9924523 1.509531e-02 7.547653e-03
[76,] 0.9916779 1.664429e-02 8.322146e-03
[77,] 0.9886328 2.273430e-02 1.136715e-02
[78,] 0.9848698 3.026039e-02 1.513020e-02
[79,] 0.9835135 3.297297e-02 1.648648e-02
[80,] 0.9790652 4.186962e-02 2.093481e-02
[81,] 0.9968347 6.330616e-03 3.165308e-03
[82,] 0.9971347 5.730514e-03 2.865257e-03
[83,] 0.9979631 4.073832e-03 2.036916e-03
[84,] 0.9970624 5.875174e-03 2.937587e-03
[85,] 0.9960440 7.911914e-03 3.955957e-03
[86,] 0.9964878 7.024349e-03 3.512175e-03
[87,] 0.9950708 9.858484e-03 4.929242e-03
[88,] 0.9941082 1.178352e-02 5.891758e-03
[89,] 0.9931745 1.365097e-02 6.825483e-03
[90,] 0.9907678 1.846436e-02 9.232178e-03
[91,] 0.9881047 2.379057e-02 1.189529e-02
[92,] 0.9839738 3.205246e-02 1.602623e-02
[93,] 0.9791288 4.174231e-02 2.087115e-02
[94,] 0.9739894 5.202130e-02 2.601065e-02
[95,] 0.9676905 6.461893e-02 3.230946e-02
[96,] 0.9580979 8.380424e-02 4.190212e-02
[97,] 0.9627700 7.446000e-02 3.723000e-02
[98,] 0.9580996 8.380086e-02 4.190043e-02
[99,] 0.9458615 1.082770e-01 5.413848e-02
[100,] 0.9844981 3.100372e-02 1.550186e-02
[101,] 0.9997099 5.801985e-04 2.900993e-04
[102,] 0.9999477 1.045761e-04 5.228804e-05
[103,] 0.9999832 3.368075e-05 1.684037e-05
[104,] 0.9999693 6.131464e-05 3.065732e-05
[105,] 0.9999901 1.973501e-05 9.867503e-06
[106,] 0.9999817 3.661343e-05 1.830672e-05
[107,] 0.9999676 6.473546e-05 3.236773e-05
[108,] 0.9999550 9.004272e-05 4.502136e-05
[109,] 0.9999186 1.628428e-04 8.142142e-05
[110,] 0.9998564 2.871683e-04 1.435841e-04
[111,] 0.9997936 4.128607e-04 2.064304e-04
[112,] 0.9996666 6.668687e-04 3.334344e-04
[113,] 0.9995599 8.801181e-04 4.400591e-04
[114,] 0.9995485 9.029315e-04 4.514658e-04
[115,] 0.9995206 9.588004e-04 4.794002e-04
[116,] 0.9994251 1.149888e-03 5.749442e-04
[117,] 0.9998310 3.380554e-04 1.690277e-04
[118,] 0.9999134 1.732021e-04 8.660104e-05
[119,] 0.9998353 3.294524e-04 1.647262e-04
[120,] 0.9996975 6.049542e-04 3.024771e-04
[121,] 0.9996011 7.978184e-04 3.989092e-04
[122,] 0.9992747 1.450617e-03 7.253084e-04
[123,] 0.9986930 2.613981e-03 1.306991e-03
[124,] 0.9989541 2.091778e-03 1.045889e-03
[125,] 0.9985046 2.990782e-03 1.495391e-03
[126,] 0.9974386 5.122712e-03 2.561356e-03
[127,] 0.9984143 3.171300e-03 1.585650e-03
[128,] 0.9975567 4.886502e-03 2.443251e-03
[129,] 0.9982292 3.541664e-03 1.770832e-03
[130,] 0.9999957 8.592944e-06 4.296472e-06
[131,] 0.9999877 2.454474e-05 1.227237e-05
[132,] 0.9999774 4.527886e-05 2.263943e-05
[133,] 0.9999368 1.264646e-04 6.323231e-05
[134,] 0.9998606 2.787802e-04 1.393901e-04
[135,] 0.9999009 1.982420e-04 9.912098e-05
[136,] 0.9999907 1.868046e-05 9.340228e-06
[137,] 0.9999956 8.798686e-06 4.399343e-06
[138,] 0.9999911 1.781359e-05 8.906796e-06
[139,] 0.9999619 7.616714e-05 3.808357e-05
[140,] 0.9998423 3.153416e-04 1.576708e-04
[141,] 0.9996451 7.098159e-04 3.549080e-04
[142,] 0.9985265 2.946982e-03 1.473491e-03
[143,] 0.9942217 1.155664e-02 5.778318e-03
[144,] 0.9805907 3.881863e-02 1.940931e-02
[145,] 0.9410019 1.179962e-01 5.899811e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1lhbb1324632680.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/2zjme1324632680.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/34kkj1324632680.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4a6mg1324632680.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/595ns1324632680.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
14333.5276 3684.5602 8402.0583 -78831.1351 12422.6315 -18187.9904
7 8 9 10 11 12
-17536.5604 2747.6792 -11486.9413 44529.6007 29787.9079 3310.9696
13 14 15 16 17 18
-791.0872 61660.9746 32600.9539 -68303.9988 39635.1880 62492.8743
19 20 21 22 23 24
-15961.7744 -2481.0050 -4632.6571 146522.1963 17162.1842 -33783.5636
25 26 27 28 29 30
-75540.5029 -34731.3311 -46387.6616 29114.3179 7670.1948 -6503.4099
31 32 33 34 35 36
-32284.3867 11060.4783 27496.0929 -11855.8878 44970.8341 -7569.3208
37 38 39 40 41 42
36139.6508 27146.3234 14747.7403 -2089.0663 -21678.9475 -8203.6729
43 44 45 46 47 48
-30365.0088 19079.7156 -124330.9379 53140.8837 -34055.9572 -30164.2049
49 50 51 52 53 54
-43743.3647 -70576.9703 -32076.1572 -18979.0843 17923.4772 -3705.1843
55 56 57 58 59 60
-16227.4524 -9359.1297 18334.6372 -27895.5182 -4422.6249 33477.3032
61 62 63 64 65 66
-23512.4844 -61623.7656 -11036.4548 3223.5370 19227.8992 31632.0929
67 68 69 70 71 72
-26890.7384 -44715.2177 -10212.6049 -23949.1688 -2118.5278 -17645.2156
73 74 75 76 77 78
16974.3512 -11991.2775 -2588.6988 95268.0321 37249.3892 -59965.1213
79 80 81 82 83 84
5033.6425 7923.1222 -8659.7414 102709.7816 -28160.9253 32240.4099
85 86 87 88 89 90
-30662.6921 2305.4718 -8358.9061 30046.7603 17559.2362 -95309.0886
91 92 93 94 95 96
41864.2597 46690.2289 3151.7678 11624.6961 41501.1196 -9506.0833
97 98 99 100 101 102
21051.3781 -29022.7229 -13903.7119 -20565.4384 6497.9775 -14173.3949
103 104 105 106 107 108
-14000.2999 -15237.2417 8962.1402 -37106.5443 -24349.3732 6122.2521
109 110 111 112 113 114
-64566.1669 -108098.7906 70284.3097 56160.3513 -256.5298 -46801.8861
115 116 117 118 119 120
6512.7482 15595.0688 23902.3080 -1324.7178 5087.4911 -10635.3599
121 122 123 124 125 126
-9849.1832 23907.3682 36894.2386 -21046.1292 -18405.8965 49110.5203
127 128 129 130 131 132
29119.0378 -8885.3584 4708.4825 -18485.3026 -441.8498 -7410.5963
133 134 135 136 137 138
-26878.4310 -9048.6163 16052.6047 19471.8739 -14676.4078 -31901.4782
139 140 141 142 143 144
34324.5530 12782.0704 26397.3118 8094.1535 -23815.8630 40185.6855
145 146 147 148 149 150
24118.8736 -50277.5049 -38523.6530 -8317.5178 5402.8951 446.5574
151 152 153 154 155 156
5275.7846 5408.6741 5401.8951 5401.8951 40540.9128 40674.9729
157 158 159 160 161 162
5401.8951 4708.4531 -2070.8391 -7411.6480 6226.1798 25386.8840
163 164
5922.6741 51774.4355
> postscript(file="/var/wessaorg/rcomp/tmp/61wnw1324632680.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 14333.5276 NA
1 3684.5602 14333.5276
2 8402.0583 3684.5602
3 -78831.1351 8402.0583
4 12422.6315 -78831.1351
5 -18187.9904 12422.6315
6 -17536.5604 -18187.9904
7 2747.6792 -17536.5604
8 -11486.9413 2747.6792
9 44529.6007 -11486.9413
10 29787.9079 44529.6007
11 3310.9696 29787.9079
12 -791.0872 3310.9696
13 61660.9746 -791.0872
14 32600.9539 61660.9746
15 -68303.9988 32600.9539
16 39635.1880 -68303.9988
17 62492.8743 39635.1880
18 -15961.7744 62492.8743
19 -2481.0050 -15961.7744
20 -4632.6571 -2481.0050
21 146522.1963 -4632.6571
22 17162.1842 146522.1963
23 -33783.5636 17162.1842
24 -75540.5029 -33783.5636
25 -34731.3311 -75540.5029
26 -46387.6616 -34731.3311
27 29114.3179 -46387.6616
28 7670.1948 29114.3179
29 -6503.4099 7670.1948
30 -32284.3867 -6503.4099
31 11060.4783 -32284.3867
32 27496.0929 11060.4783
33 -11855.8878 27496.0929
34 44970.8341 -11855.8878
35 -7569.3208 44970.8341
36 36139.6508 -7569.3208
37 27146.3234 36139.6508
38 14747.7403 27146.3234
39 -2089.0663 14747.7403
40 -21678.9475 -2089.0663
41 -8203.6729 -21678.9475
42 -30365.0088 -8203.6729
43 19079.7156 -30365.0088
44 -124330.9379 19079.7156
45 53140.8837 -124330.9379
46 -34055.9572 53140.8837
47 -30164.2049 -34055.9572
48 -43743.3647 -30164.2049
49 -70576.9703 -43743.3647
50 -32076.1572 -70576.9703
51 -18979.0843 -32076.1572
52 17923.4772 -18979.0843
53 -3705.1843 17923.4772
54 -16227.4524 -3705.1843
55 -9359.1297 -16227.4524
56 18334.6372 -9359.1297
57 -27895.5182 18334.6372
58 -4422.6249 -27895.5182
59 33477.3032 -4422.6249
60 -23512.4844 33477.3032
61 -61623.7656 -23512.4844
62 -11036.4548 -61623.7656
63 3223.5370 -11036.4548
64 19227.8992 3223.5370
65 31632.0929 19227.8992
66 -26890.7384 31632.0929
67 -44715.2177 -26890.7384
68 -10212.6049 -44715.2177
69 -23949.1688 -10212.6049
70 -2118.5278 -23949.1688
71 -17645.2156 -2118.5278
72 16974.3512 -17645.2156
73 -11991.2775 16974.3512
74 -2588.6988 -11991.2775
75 95268.0321 -2588.6988
76 37249.3892 95268.0321
77 -59965.1213 37249.3892
78 5033.6425 -59965.1213
79 7923.1222 5033.6425
80 -8659.7414 7923.1222
81 102709.7816 -8659.7414
82 -28160.9253 102709.7816
83 32240.4099 -28160.9253
84 -30662.6921 32240.4099
85 2305.4718 -30662.6921
86 -8358.9061 2305.4718
87 30046.7603 -8358.9061
88 17559.2362 30046.7603
89 -95309.0886 17559.2362
90 41864.2597 -95309.0886
91 46690.2289 41864.2597
92 3151.7678 46690.2289
93 11624.6961 3151.7678
94 41501.1196 11624.6961
95 -9506.0833 41501.1196
96 21051.3781 -9506.0833
97 -29022.7229 21051.3781
98 -13903.7119 -29022.7229
99 -20565.4384 -13903.7119
100 6497.9775 -20565.4384
101 -14173.3949 6497.9775
102 -14000.2999 -14173.3949
103 -15237.2417 -14000.2999
104 8962.1402 -15237.2417
105 -37106.5443 8962.1402
106 -24349.3732 -37106.5443
107 6122.2521 -24349.3732
108 -64566.1669 6122.2521
109 -108098.7906 -64566.1669
110 70284.3097 -108098.7906
111 56160.3513 70284.3097
112 -256.5298 56160.3513
113 -46801.8861 -256.5298
114 6512.7482 -46801.8861
115 15595.0688 6512.7482
116 23902.3080 15595.0688
117 -1324.7178 23902.3080
118 5087.4911 -1324.7178
119 -10635.3599 5087.4911
120 -9849.1832 -10635.3599
121 23907.3682 -9849.1832
122 36894.2386 23907.3682
123 -21046.1292 36894.2386
124 -18405.8965 -21046.1292
125 49110.5203 -18405.8965
126 29119.0378 49110.5203
127 -8885.3584 29119.0378
128 4708.4825 -8885.3584
129 -18485.3026 4708.4825
130 -441.8498 -18485.3026
131 -7410.5963 -441.8498
132 -26878.4310 -7410.5963
133 -9048.6163 -26878.4310
134 16052.6047 -9048.6163
135 19471.8739 16052.6047
136 -14676.4078 19471.8739
137 -31901.4782 -14676.4078
138 34324.5530 -31901.4782
139 12782.0704 34324.5530
140 26397.3118 12782.0704
141 8094.1535 26397.3118
142 -23815.8630 8094.1535
143 40185.6855 -23815.8630
144 24118.8736 40185.6855
145 -50277.5049 24118.8736
146 -38523.6530 -50277.5049
147 -8317.5178 -38523.6530
148 5402.8951 -8317.5178
149 446.5574 5402.8951
150 5275.7846 446.5574
151 5408.6741 5275.7846
152 5401.8951 5408.6741
153 5401.8951 5401.8951
154 40540.9128 5401.8951
155 40674.9729 40540.9128
156 5401.8951 40674.9729
157 4708.4531 5401.8951
158 -2070.8391 4708.4531
159 -7411.6480 -2070.8391
160 6226.1798 -7411.6480
161 25386.8840 6226.1798
162 5922.6741 25386.8840
163 51774.4355 5922.6741
164 NA 51774.4355
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 3684.5602 14333.5276
[2,] 8402.0583 3684.5602
[3,] -78831.1351 8402.0583
[4,] 12422.6315 -78831.1351
[5,] -18187.9904 12422.6315
[6,] -17536.5604 -18187.9904
[7,] 2747.6792 -17536.5604
[8,] -11486.9413 2747.6792
[9,] 44529.6007 -11486.9413
[10,] 29787.9079 44529.6007
[11,] 3310.9696 29787.9079
[12,] -791.0872 3310.9696
[13,] 61660.9746 -791.0872
[14,] 32600.9539 61660.9746
[15,] -68303.9988 32600.9539
[16,] 39635.1880 -68303.9988
[17,] 62492.8743 39635.1880
[18,] -15961.7744 62492.8743
[19,] -2481.0050 -15961.7744
[20,] -4632.6571 -2481.0050
[21,] 146522.1963 -4632.6571
[22,] 17162.1842 146522.1963
[23,] -33783.5636 17162.1842
[24,] -75540.5029 -33783.5636
[25,] -34731.3311 -75540.5029
[26,] -46387.6616 -34731.3311
[27,] 29114.3179 -46387.6616
[28,] 7670.1948 29114.3179
[29,] -6503.4099 7670.1948
[30,] -32284.3867 -6503.4099
[31,] 11060.4783 -32284.3867
[32,] 27496.0929 11060.4783
[33,] -11855.8878 27496.0929
[34,] 44970.8341 -11855.8878
[35,] -7569.3208 44970.8341
[36,] 36139.6508 -7569.3208
[37,] 27146.3234 36139.6508
[38,] 14747.7403 27146.3234
[39,] -2089.0663 14747.7403
[40,] -21678.9475 -2089.0663
[41,] -8203.6729 -21678.9475
[42,] -30365.0088 -8203.6729
[43,] 19079.7156 -30365.0088
[44,] -124330.9379 19079.7156
[45,] 53140.8837 -124330.9379
[46,] -34055.9572 53140.8837
[47,] -30164.2049 -34055.9572
[48,] -43743.3647 -30164.2049
[49,] -70576.9703 -43743.3647
[50,] -32076.1572 -70576.9703
[51,] -18979.0843 -32076.1572
[52,] 17923.4772 -18979.0843
[53,] -3705.1843 17923.4772
[54,] -16227.4524 -3705.1843
[55,] -9359.1297 -16227.4524
[56,] 18334.6372 -9359.1297
[57,] -27895.5182 18334.6372
[58,] -4422.6249 -27895.5182
[59,] 33477.3032 -4422.6249
[60,] -23512.4844 33477.3032
[61,] -61623.7656 -23512.4844
[62,] -11036.4548 -61623.7656
[63,] 3223.5370 -11036.4548
[64,] 19227.8992 3223.5370
[65,] 31632.0929 19227.8992
[66,] -26890.7384 31632.0929
[67,] -44715.2177 -26890.7384
[68,] -10212.6049 -44715.2177
[69,] -23949.1688 -10212.6049
[70,] -2118.5278 -23949.1688
[71,] -17645.2156 -2118.5278
[72,] 16974.3512 -17645.2156
[73,] -11991.2775 16974.3512
[74,] -2588.6988 -11991.2775
[75,] 95268.0321 -2588.6988
[76,] 37249.3892 95268.0321
[77,] -59965.1213 37249.3892
[78,] 5033.6425 -59965.1213
[79,] 7923.1222 5033.6425
[80,] -8659.7414 7923.1222
[81,] 102709.7816 -8659.7414
[82,] -28160.9253 102709.7816
[83,] 32240.4099 -28160.9253
[84,] -30662.6921 32240.4099
[85,] 2305.4718 -30662.6921
[86,] -8358.9061 2305.4718
[87,] 30046.7603 -8358.9061
[88,] 17559.2362 30046.7603
[89,] -95309.0886 17559.2362
[90,] 41864.2597 -95309.0886
[91,] 46690.2289 41864.2597
[92,] 3151.7678 46690.2289
[93,] 11624.6961 3151.7678
[94,] 41501.1196 11624.6961
[95,] -9506.0833 41501.1196
[96,] 21051.3781 -9506.0833
[97,] -29022.7229 21051.3781
[98,] -13903.7119 -29022.7229
[99,] -20565.4384 -13903.7119
[100,] 6497.9775 -20565.4384
[101,] -14173.3949 6497.9775
[102,] -14000.2999 -14173.3949
[103,] -15237.2417 -14000.2999
[104,] 8962.1402 -15237.2417
[105,] -37106.5443 8962.1402
[106,] -24349.3732 -37106.5443
[107,] 6122.2521 -24349.3732
[108,] -64566.1669 6122.2521
[109,] -108098.7906 -64566.1669
[110,] 70284.3097 -108098.7906
[111,] 56160.3513 70284.3097
[112,] -256.5298 56160.3513
[113,] -46801.8861 -256.5298
[114,] 6512.7482 -46801.8861
[115,] 15595.0688 6512.7482
[116,] 23902.3080 15595.0688
[117,] -1324.7178 23902.3080
[118,] 5087.4911 -1324.7178
[119,] -10635.3599 5087.4911
[120,] -9849.1832 -10635.3599
[121,] 23907.3682 -9849.1832
[122,] 36894.2386 23907.3682
[123,] -21046.1292 36894.2386
[124,] -18405.8965 -21046.1292
[125,] 49110.5203 -18405.8965
[126,] 29119.0378 49110.5203
[127,] -8885.3584 29119.0378
[128,] 4708.4825 -8885.3584
[129,] -18485.3026 4708.4825
[130,] -441.8498 -18485.3026
[131,] -7410.5963 -441.8498
[132,] -26878.4310 -7410.5963
[133,] -9048.6163 -26878.4310
[134,] 16052.6047 -9048.6163
[135,] 19471.8739 16052.6047
[136,] -14676.4078 19471.8739
[137,] -31901.4782 -14676.4078
[138,] 34324.5530 -31901.4782
[139,] 12782.0704 34324.5530
[140,] 26397.3118 12782.0704
[141,] 8094.1535 26397.3118
[142,] -23815.8630 8094.1535
[143,] 40185.6855 -23815.8630
[144,] 24118.8736 40185.6855
[145,] -50277.5049 24118.8736
[146,] -38523.6530 -50277.5049
[147,] -8317.5178 -38523.6530
[148,] 5402.8951 -8317.5178
[149,] 446.5574 5402.8951
[150,] 5275.7846 446.5574
[151,] 5408.6741 5275.7846
[152,] 5401.8951 5408.6741
[153,] 5401.8951 5401.8951
[154,] 40540.9128 5401.8951
[155,] 40674.9729 40540.9128
[156,] 5401.8951 40674.9729
[157,] 4708.4531 5401.8951
[158,] -2070.8391 4708.4531
[159,] -7411.6480 -2070.8391
[160,] 6226.1798 -7411.6480
[161,] 25386.8840 6226.1798
[162,] 5922.6741 25386.8840
[163,] 51774.4355 5922.6741
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 3684.5602 14333.5276
2 8402.0583 3684.5602
3 -78831.1351 8402.0583
4 12422.6315 -78831.1351
5 -18187.9904 12422.6315
6 -17536.5604 -18187.9904
7 2747.6792 -17536.5604
8 -11486.9413 2747.6792
9 44529.6007 -11486.9413
10 29787.9079 44529.6007
11 3310.9696 29787.9079
12 -791.0872 3310.9696
13 61660.9746 -791.0872
14 32600.9539 61660.9746
15 -68303.9988 32600.9539
16 39635.1880 -68303.9988
17 62492.8743 39635.1880
18 -15961.7744 62492.8743
19 -2481.0050 -15961.7744
20 -4632.6571 -2481.0050
21 146522.1963 -4632.6571
22 17162.1842 146522.1963
23 -33783.5636 17162.1842
24 -75540.5029 -33783.5636
25 -34731.3311 -75540.5029
26 -46387.6616 -34731.3311
27 29114.3179 -46387.6616
28 7670.1948 29114.3179
29 -6503.4099 7670.1948
30 -32284.3867 -6503.4099
31 11060.4783 -32284.3867
32 27496.0929 11060.4783
33 -11855.8878 27496.0929
34 44970.8341 -11855.8878
35 -7569.3208 44970.8341
36 36139.6508 -7569.3208
37 27146.3234 36139.6508
38 14747.7403 27146.3234
39 -2089.0663 14747.7403
40 -21678.9475 -2089.0663
41 -8203.6729 -21678.9475
42 -30365.0088 -8203.6729
43 19079.7156 -30365.0088
44 -124330.9379 19079.7156
45 53140.8837 -124330.9379
46 -34055.9572 53140.8837
47 -30164.2049 -34055.9572
48 -43743.3647 -30164.2049
49 -70576.9703 -43743.3647
50 -32076.1572 -70576.9703
51 -18979.0843 -32076.1572
52 17923.4772 -18979.0843
53 -3705.1843 17923.4772
54 -16227.4524 -3705.1843
55 -9359.1297 -16227.4524
56 18334.6372 -9359.1297
57 -27895.5182 18334.6372
58 -4422.6249 -27895.5182
59 33477.3032 -4422.6249
60 -23512.4844 33477.3032
61 -61623.7656 -23512.4844
62 -11036.4548 -61623.7656
63 3223.5370 -11036.4548
64 19227.8992 3223.5370
65 31632.0929 19227.8992
66 -26890.7384 31632.0929
67 -44715.2177 -26890.7384
68 -10212.6049 -44715.2177
69 -23949.1688 -10212.6049
70 -2118.5278 -23949.1688
71 -17645.2156 -2118.5278
72 16974.3512 -17645.2156
73 -11991.2775 16974.3512
74 -2588.6988 -11991.2775
75 95268.0321 -2588.6988
76 37249.3892 95268.0321
77 -59965.1213 37249.3892
78 5033.6425 -59965.1213
79 7923.1222 5033.6425
80 -8659.7414 7923.1222
81 102709.7816 -8659.7414
82 -28160.9253 102709.7816
83 32240.4099 -28160.9253
84 -30662.6921 32240.4099
85 2305.4718 -30662.6921
86 -8358.9061 2305.4718
87 30046.7603 -8358.9061
88 17559.2362 30046.7603
89 -95309.0886 17559.2362
90 41864.2597 -95309.0886
91 46690.2289 41864.2597
92 3151.7678 46690.2289
93 11624.6961 3151.7678
94 41501.1196 11624.6961
95 -9506.0833 41501.1196
96 21051.3781 -9506.0833
97 -29022.7229 21051.3781
98 -13903.7119 -29022.7229
99 -20565.4384 -13903.7119
100 6497.9775 -20565.4384
101 -14173.3949 6497.9775
102 -14000.2999 -14173.3949
103 -15237.2417 -14000.2999
104 8962.1402 -15237.2417
105 -37106.5443 8962.1402
106 -24349.3732 -37106.5443
107 6122.2521 -24349.3732
108 -64566.1669 6122.2521
109 -108098.7906 -64566.1669
110 70284.3097 -108098.7906
111 56160.3513 70284.3097
112 -256.5298 56160.3513
113 -46801.8861 -256.5298
114 6512.7482 -46801.8861
115 15595.0688 6512.7482
116 23902.3080 15595.0688
117 -1324.7178 23902.3080
118 5087.4911 -1324.7178
119 -10635.3599 5087.4911
120 -9849.1832 -10635.3599
121 23907.3682 -9849.1832
122 36894.2386 23907.3682
123 -21046.1292 36894.2386
124 -18405.8965 -21046.1292
125 49110.5203 -18405.8965
126 29119.0378 49110.5203
127 -8885.3584 29119.0378
128 4708.4825 -8885.3584
129 -18485.3026 4708.4825
130 -441.8498 -18485.3026
131 -7410.5963 -441.8498
132 -26878.4310 -7410.5963
133 -9048.6163 -26878.4310
134 16052.6047 -9048.6163
135 19471.8739 16052.6047
136 -14676.4078 19471.8739
137 -31901.4782 -14676.4078
138 34324.5530 -31901.4782
139 12782.0704 34324.5530
140 26397.3118 12782.0704
141 8094.1535 26397.3118
142 -23815.8630 8094.1535
143 40185.6855 -23815.8630
144 24118.8736 40185.6855
145 -50277.5049 24118.8736
146 -38523.6530 -50277.5049
147 -8317.5178 -38523.6530
148 5402.8951 -8317.5178
149 446.5574 5402.8951
150 5275.7846 446.5574
151 5408.6741 5275.7846
152 5401.8951 5408.6741
153 5401.8951 5401.8951
154 40540.9128 5401.8951
155 40674.9729 40540.9128
156 5401.8951 40674.9729
157 4708.4531 5401.8951
158 -2070.8391 4708.4531
159 -7411.6480 -2070.8391
160 6226.1798 -7411.6480
161 25386.8840 6226.1798
162 5922.6741 25386.8840
163 51774.4355 5922.6741
> 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/718tn1324632680.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/8ui6g1324632680.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/9zhsy1324632680.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/101ed61324632680.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11yxp91324632680.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/124bpe1324632680.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13hd6j1324632680.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/149ufa1324632680.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/1529yx1324632680.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/16r4dq1324632680.tab")
+ }
>
> try(system("convert tmp/1lhbb1324632680.ps tmp/1lhbb1324632680.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zjme1324632680.ps tmp/2zjme1324632680.png",intern=TRUE))
character(0)
> try(system("convert tmp/34kkj1324632680.ps tmp/34kkj1324632680.png",intern=TRUE))
character(0)
> try(system("convert tmp/4a6mg1324632680.ps tmp/4a6mg1324632680.png",intern=TRUE))
character(0)
> try(system("convert tmp/595ns1324632680.ps tmp/595ns1324632680.png",intern=TRUE))
character(0)
> try(system("convert tmp/61wnw1324632680.ps tmp/61wnw1324632680.png",intern=TRUE))
character(0)
> try(system("convert tmp/718tn1324632680.ps tmp/718tn1324632680.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ui6g1324632680.ps tmp/8ui6g1324632680.png",intern=TRUE))
character(0)
> try(system("convert tmp/9zhsy1324632680.ps tmp/9zhsy1324632680.png",intern=TRUE))
character(0)
> try(system("convert tmp/101ed61324632680.ps tmp/101ed61324632680.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.936 0.628 5.807