R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(10
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+ ,54
+ ,32
+ ,16
+ ,60
+ ,40662
+ ,12
+ ,236785
+ ,119
+ ,77
+ ,31
+ ,71
+ ,101481
+ ,12
+ ,224330
+ ,83
+ ,131
+ ,39
+ ,132
+ ,130115
+ ,12
+ ,202925
+ ,61
+ ,115
+ ,36
+ ,134
+ ,114789
+ ,12
+ ,30837
+ ,19
+ ,8
+ ,4
+ ,4
+ ,2325
+ ,12
+ ,329267
+ ,259
+ ,79
+ ,39
+ ,140
+ ,115762
+ ,12
+ ,125930
+ ,75
+ ,37
+ ,17
+ ,65
+ ,32387
+ ,12
+ ,204271
+ ,42
+ ,92
+ ,35
+ ,116
+ ,74163
+ ,12
+ ,51567
+ ,30
+ ,21
+ ,14
+ ,45
+ ,28207
+ ,12
+ ,325107
+ ,99
+ ,84
+ ,36
+ ,126
+ ,79215
+ ,12
+ ,119016
+ ,52
+ ,118
+ ,23
+ ,74
+ ,78664
+ ,12
+ ,265769
+ ,146
+ ,96
+ ,32
+ ,120
+ ,83122)
+ ,dim=c(7
+ ,289)
+ ,dimnames=list(c('Maand'
+ ,'Time_in_rfc'
+ ,'Logins'
+ ,'Blogged_computations'
+ ,'Compendiums_reviewed'
+ ,'Feedback_messages_p120'
+ ,'Total_number_of_characters')
+ ,1:289))
> y <- array(NA,dim=c(7,289),dimnames=list(c('Maand','Time_in_rfc','Logins','Blogged_computations','Compendiums_reviewed','Feedback_messages_p120','Total_number_of_characters'),1:289))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '2'
> 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_in_rfc Maand Logins Blogged_computations Compendiums_reviewed
1 14688 10 10 4 0
2 46660 10 20 12 5
3 7199 10 5 7 0
4 21054 10 16 4 0
5 80953 10 25 49 8
6 19349 10 11 13 1
7 173260 11 63 41 21
8 38214 11 34 16 8
9 17547 11 5 0 1
10 43287 11 14 13 19
11 78800 11 42 20 26
12 65029 11 17 21 18
13 31414 11 19 18 8
14 7176 11 17 0 0
15 24188 11 24 8 4
16 61857 11 25 23 11
17 22938 11 10 12 1
18 43410 11 19 7 1
19 19764 11 12 10 2
20 53117 11 22 3 12
21 33170 11 18 1 18
22 232138 11 62 131 31
23 111665 11 34 39 28
24 152871 11 58 59 28
25 100750 11 72 83 30
26 221698 11 45 105 33
27 209641 11 42 62 24
28 52746 11 25 0 26
29 215641 11 46 71 32
30 85439 11 33 32 28
31 145790 11 63 30 26
32 132943 11 40 83 39
33 132487 11 41 71 36
34 135473 11 41 82 23
35 84853 11 31 38 30
36 210767 11 60 94 35
37 97839 11 38 25 24
38 120221 11 37 53 22
39 224549 11 50 54 31
40 116408 11 61 34 39
41 158015 11 29 59 31
42 150629 12 44 85 33
43 123185 12 40 49 22
44 124817 12 40 47 25
45 104389 12 45 135 41
46 162765 12 32 68 28
47 149061 12 44 43 26
48 84207 12 29 14 30
49 201940 12 38 109 31
50 168809 12 66 76 28
51 176508 12 54 60 38
52 99466 12 50 28 23
53 106408 12 30 33 14
54 344297 12 75 80 30
55 218946 12 41 76 29
56 122774 12 45 24 24
57 153935 12 33 50 25
58 206161 12 71 75 28
59 183167 12 66 91 39
60 144966 12 144 39 32
61 34662 12 25 18 6
62 116048 12 64 50 20
63 77945 12 20 28 19
64 65490 12 22 27 16
65 81872 12 45 32 16
66 101011 12 34 30 13
67 71965 12 35 32 15
68 72880 12 33 14 19
69 62792 12 35 28 15
70 31774 12 23 0 17
71 182192 12 52 77 40
72 67989 12 21 23 18
73 52915 12 14 20 18
74 56375 12 30 10 13
75 30989 12 14 5 17
76 135131 12 66 38 15
77 76990 12 27 42 17
78 64175 12 42 37 18
79 59194 12 31 7 24
80 53515 12 28 5 22
81 89746 12 36 28 18
82 49862 12 37 17 14
83 85574 12 34 37 21
84 220801 12 75 51 18
85 49289 12 19 15 24
86 135781 12 31 45 14
87 82316 12 32 27 10
88 133368 12 36 37 16
89 92499 12 32 25 18
90 37460 12 20 5 7
91 91735 12 35 7 18
92 187681 12 62 114 28
93 79619 12 43 42 11
94 98104 12 54 55 17
95 80949 12 17 11 16
96 31706 12 13 26 10
97 70344 12 28 20 16
98 99923 12 66 44 25
99 91899 12 35 18 15
100 235454 12 73 151 32
101 46455 12 20 22 17
102 60812 12 44 26 13
103 77648 12 47 31 16
104 101523 12 42 59 22
105 254488 12 83 120 39
106 103597 12 43 27 16
107 136084 12 30 27 13
108 62088 12 38 13 16
109 86680 12 31 37 14
110 38395 12 31 16 16
111 179321 12 89 108 30
112 40248 12 16 8 4
113 70551 12 31 23 15
114 84105 12 20 17 17
115 112611 12 41 46 20
116 73624 12 24 30 17
117 89806 12 42 27 16
118 98866 12 18 25 13
119 61254 12 46 36 14
120 99643 12 55 33 17
121 310839 12 92 130 24
122 181633 12 70 47 30
123 50090 12 20 16 17
124 92661 12 61 40 17
125 46698 12 45 14 13
126 61361 12 77 27 12
127 84337 12 26 38 14
128 72535 12 14 17 16
129 84856 12 29 29 17
130 124064 12 40 43 22
131 54157 12 19 37 15
132 76302 12 31 29 20
133 59382 12 49 29 12
134 65745 12 53 26 21
135 74914 12 30 35 23
136 101645 12 63 20 11
137 73504 12 35 23 7
138 99373 12 63 12 18
139 135458 12 81 43 12
140 184510 12 49 64 40
141 385534 12 92 121 25
142 108043 12 62 45 14
143 328107 12 65 129 41
144 362301 12 119 76 34
145 130585 12 46 67 29
146 85709 12 44 21 10
147 174184 12 53 72 25
148 81437 12 38 37 14
149 120982 12 56 58 28
150 187559 12 121 75 36
151 235800 12 94 105 23
152 220516 12 62 98 32
153 210907 12 56 79 30
154 155754 12 61 74 20
155 152299 12 53 62 33
156 79863 12 37 29 22
157 346485 12 90 118 38
158 135649 12 46 99 30
159 134019 12 53 32 18
160 167488 12 45 69 28
161 108446 12 60 22 17
162 27634 12 20 2 16
163 232317 12 54 118 33
164 22648 12 19 12 13
165 119308 12 30 32 16
166 194979 12 62 66 40
167 81240 12 66 58 17
168 121848 12 39 37 17
169 86678 12 40 12 15
170 73566 12 32 22 23
171 102010 12 53 28 13
172 151101 12 32 48 35
173 207176 12 70 56 32
174 165543 12 65 70 32
175 182999 12 88 73 34
176 256462 12 105 123 35
177 244052 12 68 101 44
178 63123 12 43 34 17
179 87186 12 54 28 15
180 182079 12 63 124 33
181 95227 12 34 37 32
182 165446 12 33 69 25
183 229242 12 247 63 31
184 167542 12 66 59 28
185 225060 12 93 93 41
186 164709 12 109 81 31
187 131698 12 65 60 19
188 56613 12 19 15 12
189 250579 12 83 130 38
190 44296 12 25 10 20
191 152474 12 65 106 32
192 86230 12 44 21 17
193 258873 12 60 104 40
194 41566 12 35 0 9
195 250047 12 81 41 18
196 243511 12 71 133 42
197 62215 12 27 24 10
198 104838 12 49 46 16
199 77272 12 59 21 16
200 148446 12 91 135 37
201 69304 12 30 40 19
202 102538 12 57 50 15
203 101097 12 64 30 14
204 223632 12 73 105 33
205 141722 12 94 19 27
206 351067 12 95 136 45
207 311473 12 112 128 38
208 152601 12 48 46 24
209 215147 12 58 101 36
210 52164 12 52 32 16
211 91005 12 29 29 11
212 265318 12 117 110 52
213 299775 12 95 91 31
214 241066 12 82 75 45
215 118612 12 46 54 12
216 173326 12 88 86 44
217 225548 12 112 81 31
218 277965 12 89 115 39
219 317394 12 86 116 31
220 177939 12 82 55 36
221 92630 12 40 27 8
222 140344 12 53 33 25
223 230964 12 53 102 30
224 199476 12 70 87 32
225 174724 12 92 123 34
226 128423 12 64 32 38
227 341570 12 168 94 21
228 64187 12 27 10 16
229 150580 12 77 27 22
230 204713 12 71 68 33
231 244749 12 95 98 33
232 98146 12 40 15 17
233 351619 12 139 95 40
234 58981 12 36 0 23
235 233328 12 132 92 28
236 182613 12 39 81 28
237 89113 12 39 19 14
238 324799 12 154 158 47
239 143246 12 103 67 27
240 40151 12 29 16 9
241 158399 12 39 23 18
242 195838 12 67 111 31
243 286468 12 144 57 29
244 175824 12 107 57 20
245 143756 12 46 105 34
246 139942 12 42 54 22
247 104011 12 55 25 22
248 196553 12 57 41 29
249 180083 12 66 63 34
250 260561 12 75 114 43
251 294424 12 77 107 33
252 99611 12 35 41 21
253 131069 12 67 47 30
254 65475 12 18 16 13
255 237213 12 84 78 38
256 324598 12 110 113 37
257 170266 12 62 44 42
258 269651 12 67 106 30
259 243060 12 63 58 29
260 149112 12 56 56 35
261 174415 12 100 73 31
262 133131 12 55 44 30
263 133328 12 55 56 20
264 56653 12 45 38 18
265 50857 12 21 15 20
266 74408 12 67 29 7
267 193339 12 78 100 35
268 275541 12 63 116 33
269 96560 12 76 42 17
270 243199 12 75 88 28
271 76702 12 49 35 21
272 272458 12 65 100 43
273 103425 12 67 17 19
274 271856 12 103 109 37
275 139526 12 151 28 21
276 172494 12 52 46 43
277 120445 12 118 36 16
278 181528 12 54 32 16
279 236785 12 119 77 31
280 224330 12 83 131 39
281 202925 12 61 115 36
282 30837 12 19 8 4
283 329267 12 259 79 39
284 125930 12 75 37 17
285 204271 12 42 92 35
286 51567 12 30 21 14
287 325107 12 99 84 36
288 119016 12 52 118 23
289 265769 12 146 96 32
Feedback_messages_p120 Total_number_of_characters
1 0 6023
2 13 6179
3 0 1644
4 0 855
5 27 56622
6 0 3895
7 78 37238
8 21 8773
9 4 3926
10 64 43750
11 66 33032
12 61 32551
13 9 14116
14 0 1423
15 7 5950
16 30 25162
17 0 1168
18 3 2781
19 4 5752
20 32 32689
21 22 22807
22 90 161647
23 80 49810
24 90 79892
25 93 140867
26 110 77873
27 60 97068
28 70 68504
29 92 55813
30 78 56926
31 99 38692
32 156 97500
33 98 40735
34 66 99645
35 109 61542
36 133 117478
37 66 94785
38 69 43836
39 114 120662
40 31 71570
41 114 71220
42 113 71595
43 51 38361
44 81 30727
45 148 123969
46 107 120293
47 93 116174
48 101 111194
49 92 85872
50 100 72260
51 93 83123
52 69 192565
53 37 31081
54 108 67654
55 96 80670
56 69 15986
57 84 65553
58 99 73107
59 138 82875
60 50 37510
61 7 36278
62 50 33416
63 67 25272
64 40 18653
65 61 27913
66 39 27570
67 56 46090
68 67 24094
69 51 30884
70 47 4143
71 138 70054
72 57 33747
73 49 24006
74 40 41385
75 41 4154
76 60 34029
77 67 24069
78 59 21792
79 68 37636
80 81 12934
81 55 24760
82 54 36341
83 36 24266
84 63 44418
85 44 10672
86 44 24874
87 38 21233
88 57 32755
89 55 21399
90 14 3738
91 49 16563
92 91 92945
93 32 20760
94 47 25568
95 56 18472
96 25 25139
97 61 28904
98 80 32334
99 33 36874
100 106 89275
101 12 11342
102 43 22574
103 52 21280
104 87 61056
105 117 103772
106 49 23789
107 41 27142
108 38 14483
109 49 22197
110 43 16380
111 103 101193
112 7 5444
113 47 30143
114 63 20055
115 73 26706
116 40 19499
117 40 27975
118 39 23517
119 30 13310
120 46 54968
121 85 162901
122 73 64466
123 36 21152
124 41 35232
125 33 10288
126 25 13294
127 35 24548
128 39 19540
129 43 41369
130 86 22827
131 30 18625
132 68 30976
133 24 26263
134 42 38084
135 79 65892
136 38 17140
137 3 35130
138 62 28394
139 29 19474
140 140 110681
141 91 119182
142 38 34553
143 144 105547
144 110 100708
145 107 95364
146 35 35944
147 70 55183
148 40 28579
149 103 84786
150 116 73511
151 62 149193
152 119 55801
153 94 112285
154 31 40652
155 98 61370
156 49 29011
157 111 106117
158 108 62133
159 54 28987
160 72 83737
161 65 46300
162 17 5839
163 106 129838
164 28 44339
165 58 23686
166 151 74011
167 50 45549
168 52 30594
169 50 29156
170 67 22618
171 44 44332
172 124 83209
173 114 87011
174 90 51633
175 104 225920
176 124 105195
177 164 143558
178 60 39067
179 48 51776
180 118 102860
181 48 34777
182 60 57635
183 119 91721
184 70 55461
185 139 109825
186 63 87771
187 59 65622
188 35 8019
189 120 103487
190 38 18779
191 83 65567
192 54 18632
193 124 80444
194 27 13497
195 61 83305
196 110 101338
197 25 19546
198 52 29236
199 48 27507
200 129 126846
201 40 22818
202 45 45833
203 41 31701
204 120 72654
205 36 75345
206 160 213688
207 129 132068
208 46 73224
209 117 99052
210 43 16734
211 23 32073
212 197 115929
213 97 98952
214 93 67267
215 43 30080
216 148 71701
217 94 85323
218 133 139077
219 82 91413
220 73 46821
221 24 18513
222 73 51715
223 115 133824
224 105 135400
225 120 69112
226 120 92696
227 78 117105
228 54 20154
229 71 45588
230 69 41140
231 115 76643
232 48 27114
233 141 115168
234 61 42744
235 102 120733
236 99 138599
237 32 82206
238 168 97668
239 104 106671
240 19 13127
241 57 32928
242 98 102372
243 107 89691
244 77 39992
245 120 69094
246 87 65461
247 79 63339
248 99 95260
249 70 53855
250 158 90183
251 124 101494
252 67 45097
253 83 51513
254 46 69008
255 123 66198
256 133 135777
257 122 74007
258 93 70106
259 104 111813
260 95 60578
261 114 82753
262 90 57793
263 56 40909
264 49 27717
265 37 36944
266 21 34988
267 71 84651
268 115 93133
269 38 22996
270 105 95536
271 42 49303
272 152 93815
273 46 25659
274 86 54990
275 77 48259
276 139 86687
277 56 51009
278 60 40662
279 71 101481
280 132 130115
281 134 114789
282 4 2325
283 140 115762
284 65 32387
285 116 74163
286 45 28207
287 126 79215
288 74 78664
289 120 83122
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Maand
-35357.049 3296.670
Logins Blogged_computations
747.014 926.976
Compendiums_reviewed Feedback_messages_p120
512.733 260.244
Total_number_of_characters
0.248
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-148856 -18556 -1359 15388 149642
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.536e+04 6.294e+04 -0.562 0.57470
Maand 3.297e+03 5.427e+03 0.608 0.54401
Logins 7.470e+02 8.181e+01 9.131 < 2e-16 ***
Blogged_computations 9.270e+02 1.054e+02 8.795 < 2e-16 ***
Compendiums_reviewed 5.127e+02 5.331e+02 0.962 0.33700
Feedback_messages_p120 2.602e+02 1.496e+02 1.740 0.08296 .
Total_number_of_characters 2.480e-01 9.189e-02 2.699 0.00738 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 36760 on 282 degrees of freedom
Multiple R-squared: 0.8049, Adjusted R-squared: 0.8007
F-statistic: 193.9 on 6 and 282 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,] 4.956198e-02 9.912396e-02 0.9504380
[2,] 3.893820e-02 7.787640e-02 0.9610618
[3,] 1.295183e-02 2.590367e-02 0.9870482
[4,] 6.105382e-03 1.221076e-02 0.9938946
[5,] 2.165600e-03 4.331200e-03 0.9978344
[6,] 6.602801e-04 1.320560e-03 0.9993397
[7,] 2.125397e-04 4.250793e-04 0.9997875
[8,] 5.803258e-05 1.160652e-04 0.9999420
[9,] 4.170545e-05 8.341090e-05 0.9999583
[10,] 1.181112e-05 2.362224e-05 0.9999882
[11,] 2.322789e-05 4.645577e-05 0.9999768
[12,] 3.474006e-05 6.948012e-05 0.9999653
[13,] 1.154981e-05 2.309961e-05 0.9999885
[14,] 4.060192e-06 8.120384e-06 0.9999959
[15,] 2.002367e-06 4.004733e-06 0.9999980
[16,] 8.677559e-04 1.735512e-03 0.9991322
[17,] 6.175717e-04 1.235143e-03 0.9993824
[18,] 6.949220e-02 1.389844e-01 0.9305078
[19,] 5.162843e-02 1.032569e-01 0.9483716
[20,] 5.113938e-02 1.022788e-01 0.9488606
[21,] 4.226143e-02 8.452286e-02 0.9577386
[22,] 3.221429e-02 6.442859e-02 0.9677857
[23,] 5.153835e-02 1.030767e-01 0.9484617
[24,] 8.468821e-02 1.693764e-01 0.9153118
[25,] 6.648044e-02 1.329609e-01 0.9335196
[26,] 5.260663e-02 1.052133e-01 0.9473934
[27,] 4.359161e-02 8.718323e-02 0.9564084
[28,] 3.692600e-02 7.385200e-02 0.9630740
[29,] 2.673375e-02 5.346750e-02 0.9732663
[30,] 1.222281e-01 2.444562e-01 0.8777719
[31,] 9.869339e-02 1.973868e-01 0.9013066
[32,] 8.594527e-02 1.718905e-01 0.9140547
[33,] 7.689406e-02 1.537881e-01 0.9231059
[34,] 6.103889e-02 1.220778e-01 0.9389611
[35,] 4.661709e-02 9.323417e-02 0.9533829
[36,] 3.490404e-01 6.980809e-01 0.6509596
[37,] 3.559503e-01 7.119006e-01 0.6440497
[38,] 3.241190e-01 6.482380e-01 0.6758810
[39,] 2.874153e-01 5.748305e-01 0.7125847
[40,] 2.945718e-01 5.891436e-01 0.7054282
[41,] 2.587209e-01 5.174419e-01 0.7412791
[42,] 2.322834e-01 4.645668e-01 0.7677166
[43,] 2.201142e-01 4.402283e-01 0.7798858
[44,] 2.046041e-01 4.092082e-01 0.7953959
[45,] 7.172260e-01 5.655479e-01 0.2827740
[46,] 7.713982e-01 4.572036e-01 0.2286018
[47,] 7.422543e-01 5.154913e-01 0.2577457
[48,] 7.275760e-01 5.448479e-01 0.2724240
[49,] 6.960375e-01 6.079250e-01 0.3039625
[50,] 7.096229e-01 5.807542e-01 0.2903771
[51,] 8.508480e-01 2.983040e-01 0.1491520
[52,] 8.358809e-01 3.282381e-01 0.1641191
[53,] 8.185348e-01 3.629303e-01 0.1814652
[54,] 7.912967e-01 4.174065e-01 0.2087033
[55,] 7.618701e-01 4.762598e-01 0.2381299
[56,] 7.446175e-01 5.107650e-01 0.2553825
[57,] 7.164154e-01 5.671692e-01 0.2835846
[58,] 6.964938e-01 6.070124e-01 0.3035062
[59,] 6.622696e-01 6.754609e-01 0.3377304
[60,] 6.426055e-01 7.147889e-01 0.3573945
[61,] 6.123822e-01 7.752356e-01 0.3876178
[62,] 5.740780e-01 8.518440e-01 0.4259220
[63,] 5.350910e-01 9.298180e-01 0.4649090
[64,] 4.966759e-01 9.933519e-01 0.5033241
[65,] 4.579936e-01 9.159873e-01 0.5420064
[66,] 4.216042e-01 8.432083e-01 0.5783958
[67,] 3.858577e-01 7.717153e-01 0.6141423
[68,] 3.602778e-01 7.205555e-01 0.6397222
[69,] 3.640739e-01 7.281479e-01 0.6359261
[70,] 3.320898e-01 6.641797e-01 0.6679102
[71,] 3.026076e-01 6.052152e-01 0.6973924
[72,] 2.696366e-01 5.392732e-01 0.7303634
[73,] 2.562195e-01 5.124391e-01 0.7437805
[74,] 2.261481e-01 4.522961e-01 0.7738519
[75,] 3.167065e-01 6.334130e-01 0.6832935
[76,] 2.842992e-01 5.685984e-01 0.7157008
[77,] 2.937376e-01 5.874752e-01 0.7062624
[78,] 2.629751e-01 5.259503e-01 0.7370249
[79,] 2.607320e-01 5.214640e-01 0.7392680
[80,] 2.336271e-01 4.672542e-01 0.7663729
[81,] 2.061780e-01 4.123561e-01 0.7938220
[82,] 1.942009e-01 3.884018e-01 0.8057991
[83,] 1.837911e-01 3.675823e-01 0.8162089
[84,] 1.670067e-01 3.340134e-01 0.8329933
[85,] 1.589431e-01 3.178861e-01 0.8410569
[86,] 1.485460e-01 2.970921e-01 0.8514540
[87,] 1.347269e-01 2.694539e-01 0.8652731
[88,] 1.162202e-01 2.324405e-01 0.8837798
[89,] 1.225403e-01 2.450806e-01 0.8774597
[90,] 1.106135e-01 2.212271e-01 0.8893865
[91,] 1.010044e-01 2.020087e-01 0.8989956
[92,] 8.601208e-02 1.720242e-01 0.9139879
[93,] 7.986110e-02 1.597222e-01 0.9201389
[94,] 7.105218e-02 1.421044e-01 0.9289478
[95,] 7.070332e-02 1.414066e-01 0.9292967
[96,] 6.007411e-02 1.201482e-01 0.9399259
[97,] 5.149415e-02 1.029883e-01 0.9485059
[98,] 7.195617e-02 1.439123e-01 0.9280438
[99,] 6.077926e-02 1.215585e-01 0.9392207
[100,] 5.073342e-02 1.014668e-01 0.9492666
[101,] 4.719121e-02 9.438242e-02 0.9528088
[102,] 6.008671e-02 1.201734e-01 0.9399133
[103,] 5.110160e-02 1.022032e-01 0.9488984
[104,] 4.256447e-02 8.512894e-02 0.9574355
[105,] 3.698324e-02 7.396647e-02 0.9630168
[106,] 3.038916e-02 6.077832e-02 0.9696108
[107,] 2.477836e-02 4.955673e-02 0.9752216
[108,] 2.011800e-02 4.023600e-02 0.9798820
[109,] 2.033838e-02 4.067676e-02 0.9796616
[110,] 1.898740e-02 3.797480e-02 0.9810126
[111,] 1.546290e-02 3.092580e-02 0.9845371
[112,] 2.009993e-02 4.019985e-02 0.9799001
[113,] 1.939230e-02 3.878461e-02 0.9806077
[114,] 1.569178e-02 3.138356e-02 0.9843082
[115,] 1.383251e-02 2.766502e-02 0.9861675
[116,] 1.224781e-02 2.449561e-02 0.9877522
[117,] 1.378566e-02 2.757133e-02 0.9862143
[118,] 1.103810e-02 2.207619e-02 0.9889619
[119,] 9.418052e-03 1.883610e-02 0.9905819
[120,] 7.453259e-03 1.490652e-02 0.9925467
[121,] 5.976638e-03 1.195328e-02 0.9940234
[122,] 4.913194e-03 9.826387e-03 0.9950868
[123,] 3.936483e-03 7.872967e-03 0.9960635
[124,] 3.500984e-03 7.001967e-03 0.9964990
[125,] 3.297943e-03 6.595885e-03 0.9967021
[126,] 3.075757e-03 6.151515e-03 0.9969242
[127,] 2.418488e-03 4.836976e-03 0.9975815
[128,] 1.887752e-03 3.775503e-03 0.9981122
[129,] 1.433562e-03 2.867125e-03 0.9985664
[130,] 1.113783e-03 2.227566e-03 0.9988862
[131,] 8.507589e-04 1.701518e-03 0.9991492
[132,] 2.185800e-02 4.371599e-02 0.9781420
[133,] 1.815983e-02 3.631965e-02 0.9818402
[134,] 3.258687e-02 6.517373e-02 0.9674131
[135,] 1.572317e-01 3.144634e-01 0.8427683
[136,] 1.574445e-01 3.148890e-01 0.8425555
[137,] 1.381897e-01 2.763794e-01 0.8618103
[138,] 1.249617e-01 2.499233e-01 0.8750383
[139,] 1.093532e-01 2.187065e-01 0.8906468
[140,] 1.156564e-01 2.313127e-01 0.8843436
[141,] 1.339255e-01 2.678510e-01 0.8660745
[142,] 1.165034e-01 2.330067e-01 0.8834966
[143,] 1.041522e-01 2.083043e-01 0.8958478
[144,] 9.582231e-02 1.916446e-01 0.9041777
[145,] 8.309917e-02 1.661983e-01 0.9169008
[146,] 7.129768e-02 1.425954e-01 0.9287023
[147,] 6.115423e-02 1.223085e-01 0.9388458
[148,] 1.293195e-01 2.586390e-01 0.8706805
[149,] 1.497951e-01 2.995901e-01 0.8502049
[150,] 1.419303e-01 2.838606e-01 0.8580697
[151,] 1.259692e-01 2.519384e-01 0.8740308
[152,] 1.091743e-01 2.183486e-01 0.8908257
[153,] 9.484337e-02 1.896867e-01 0.9051566
[154,] 8.123026e-02 1.624605e-01 0.9187697
[155,] 7.763581e-02 1.552716e-01 0.9223642
[156,] 7.576211e-02 1.515242e-01 0.9242379
[157,] 6.429440e-02 1.285888e-01 0.9357056
[158,] 8.483481e-02 1.696696e-01 0.9151652
[159,] 7.743771e-02 1.548754e-01 0.9225623
[160,] 6.686775e-02 1.337355e-01 0.9331322
[161,] 5.729107e-02 1.145821e-01 0.9427089
[162,] 4.808374e-02 9.616748e-02 0.9519163
[163,] 4.073123e-02 8.146245e-02 0.9592688
[164,] 3.734273e-02 7.468547e-02 0.9626573
[165,] 3.097487e-02 6.194974e-02 0.9690251
[166,] 4.733086e-02 9.466171e-02 0.9526691
[167,] 4.190571e-02 8.381141e-02 0.9580943
[168,] 3.557336e-02 7.114673e-02 0.9644266
[169,] 3.627042e-02 7.254083e-02 0.9637296
[170,] 3.140194e-02 6.280389e-02 0.9685981
[171,] 4.057646e-02 8.115293e-02 0.9594235
[172,] 3.431783e-02 6.863565e-02 0.9656822
[173,] 3.229628e-02 6.459257e-02 0.9677037
[174,] 7.473045e-02 1.494609e-01 0.9252696
[175,] 6.437805e-02 1.287561e-01 0.9356219
[176,] 5.748782e-02 1.149756e-01 0.9425122
[177,] 6.827555e-02 1.365511e-01 0.9317244
[178,] 5.976346e-02 1.195269e-01 0.9402365
[179,] 5.054660e-02 1.010932e-01 0.9494534
[180,] 4.270257e-02 8.540515e-02 0.9572974
[181,] 3.634624e-02 7.269248e-02 0.9636538
[182,] 4.307458e-02 8.614916e-02 0.9569254
[183,] 3.557874e-02 7.115749e-02 0.9644213
[184,] 3.715908e-02 7.431815e-02 0.9628409
[185,] 3.046428e-02 6.092857e-02 0.9695357
[186,] 9.036276e-02 1.807255e-01 0.9096372
[187,] 7.855774e-02 1.571155e-01 0.9214423
[188,] 6.612436e-02 1.322487e-01 0.9338756
[189,] 5.542554e-02 1.108511e-01 0.9445745
[190,] 4.764364e-02 9.528727e-02 0.9523564
[191,] 2.849797e-01 5.699595e-01 0.7150203
[192,] 2.629126e-01 5.258252e-01 0.7370874
[193,] 2.423587e-01 4.847173e-01 0.7576413
[194,] 2.142415e-01 4.284830e-01 0.7857585
[195,] 1.882223e-01 3.764446e-01 0.8117777
[196,] 1.697063e-01 3.394126e-01 0.8302937
[197,] 1.566027e-01 3.132054e-01 0.8433973
[198,] 1.386485e-01 2.772971e-01 0.8613515
[199,] 1.243065e-01 2.486130e-01 0.8756935
[200,] 1.063016e-01 2.126032e-01 0.8936984
[201,] 1.102095e-01 2.204191e-01 0.8897905
[202,] 9.638323e-02 1.927665e-01 0.9036168
[203,] 9.494522e-02 1.898904e-01 0.9050548
[204,] 1.422608e-01 2.845217e-01 0.8577392
[205,] 1.391209e-01 2.782419e-01 0.8608791
[206,] 1.199287e-01 2.398574e-01 0.8800713
[207,] 1.508844e-01 3.017689e-01 0.8491156
[208,] 1.292744e-01 2.585488e-01 0.8707256
[209,] 1.105038e-01 2.210076e-01 0.8894962
[210,] 1.992302e-01 3.984603e-01 0.8007698
[211,] 1.741853e-01 3.483707e-01 0.8258147
[212,] 1.603380e-01 3.206761e-01 0.8396620
[213,] 1.419409e-01 2.838818e-01 0.8580591
[214,] 1.219966e-01 2.439932e-01 0.8780034
[215,] 1.085802e-01 2.171603e-01 0.8914198
[216,] 1.776849e-01 3.553698e-01 0.8223151
[217,] 1.893222e-01 3.786444e-01 0.8106778
[218,] 2.937566e-01 5.875132e-01 0.7062434
[219,] 2.587612e-01 5.175224e-01 0.7412388
[220,] 2.337844e-01 4.675688e-01 0.7662156
[221,] 2.368989e-01 4.737979e-01 0.7631011
[222,] 2.076662e-01 4.153324e-01 0.7923338
[223,] 1.869938e-01 3.739876e-01 0.8130062
[224,] 2.435000e-01 4.870000e-01 0.7565000
[225,] 2.223416e-01 4.446833e-01 0.7776584
[226,] 1.982638e-01 3.965275e-01 0.8017362
[227,] 1.699510e-01 3.399019e-01 0.8300490
[228,] 1.432648e-01 2.865295e-01 0.8567352
[229,] 1.386193e-01 2.772385e-01 0.8613807
[230,] 2.156320e-01 4.312640e-01 0.7843680
[231,] 1.841266e-01 3.682532e-01 0.8158734
[232,] 2.720260e-01 5.440521e-01 0.7279740
[233,] 2.572023e-01 5.144046e-01 0.7427977
[234,] 2.954288e-01 5.908575e-01 0.7045712
[235,] 2.574698e-01 5.149396e-01 0.7425302
[236,] 3.653801e-01 7.307602e-01 0.6346199
[237,] 3.204663e-01 6.409325e-01 0.6795337
[238,] 2.868279e-01 5.736558e-01 0.7131721
[239,] 2.839684e-01 5.679368e-01 0.7160316
[240,] 2.565472e-01 5.130944e-01 0.7434528
[241,] 2.325534e-01 4.651068e-01 0.7674466
[242,] 2.504799e-01 5.009598e-01 0.7495201
[243,] 2.131143e-01 4.262285e-01 0.7868857
[244,] 1.862622e-01 3.725244e-01 0.8137378
[245,] 1.520088e-01 3.040177e-01 0.8479912
[246,] 1.262346e-01 2.524692e-01 0.8737654
[247,] 1.332513e-01 2.665026e-01 0.8667487
[248,] 1.108417e-01 2.216834e-01 0.8891583
[249,] 1.554589e-01 3.109179e-01 0.8445411
[250,] 2.812212e-01 5.624424e-01 0.7187788
[251,] 2.487914e-01 4.975829e-01 0.7512086
[252,] 2.546303e-01 5.092606e-01 0.7453697
[253,] 2.192163e-01 4.384326e-01 0.7807837
[254,] 1.750338e-01 3.500675e-01 0.8249662
[255,] 2.001173e-01 4.002345e-01 0.7998827
[256,] 1.592189e-01 3.184377e-01 0.8407811
[257,] 1.247528e-01 2.495056e-01 0.8752472
[258,] 9.340118e-02 1.868024e-01 0.9065988
[259,] 1.073604e-01 2.147208e-01 0.8926396
[260,] 9.067974e-02 1.813595e-01 0.9093203
[261,] 1.378058e-01 2.756115e-01 0.8621942
[262,] 1.150767e-01 2.301534e-01 0.8849233
[263,] 8.496098e-02 1.699220e-01 0.9150390
[264,] 6.091601e-02 1.218320e-01 0.9390840
[265,] 4.263614e-02 8.527229e-02 0.9573639
[266,] 5.373861e-02 1.074772e-01 0.9462614
[267,] 1.685081e-01 3.370161e-01 0.8314919
[268,] 1.152771e-01 2.305543e-01 0.8847229
[269,] 3.775697e-01 7.551393e-01 0.6224303
[270,] 2.788053e-01 5.576106e-01 0.7211947
> postscript(file="/var/wessaorg/rcomp/tmp/1c7f51323953651.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/2gpfw1323953651.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3m5fn1323953651.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4tsh91323953651.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5pw9i1323953651.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 289
Frequency = 1
1 2 3 4 5
4.406508e+03 1.550703e+04 -1.042287e+03 7.572173e+03 -5.925438e+03
6 7 8 9 10
-7.242415e+00 4.698374e+04 -1.466524e+04 1.037819e+04 -1.737645e+04
11 12 13 14 15
-1.072005e+04 -1.220304e+03 -1.031620e+04 -6.782481e+03 -7.410794e+03
16 17 18 19 20
1.266923e+03 2.635418e+03 1.983839e+04 -2.869274e+03 1.040744e+04
21 22 23 24 25
-2.720610e+03 -1.592478e+04 1.678418e+03 -3.646697e+03 -1.054023e+05
26 27 28 29 30
2.498280e+04 6.789293e+04 -1.537391e+04 6.036432e+04 -1.855613e+04
31 32 33 34 35
2.132107e+04 -5.955911e+04 -1.892741e+04 -2.575545e+04 -3.344784e+04
36 37 38 39 40
-3.790442e+03 -7.618158e+03 2.436446e+03 6.074661e+04 -7.398009e+03
41 42 43 44 45
1.752744e+04 -2.932003e+04 9.612921e+03 5.646707e+03 -1.488558e+05
46 47 48 49 50
-4.140425e+02 5.782648e+03 -2.388161e+04 7.175297e+03 -1.344965e+04
51 52 53 54 55
1.204531e+04 -4.555195e+04 2.468851e+04 1.496423e+05 5.380513e+04
56 57 58 59 60
2.848075e+04 2.779473e+04 2.114443e+04 -3.115831e+04 -4.168178e+04
61 62 63 64 65
-1.879754e+04 -1.386724e+04 -5.997330e+02 -3.415376e+03 -1.661133e+04
66 67 68 69 70
1.994741e+04 -2.174243e+04 -2.106089e+03 -2.213497e+04 -1.158577e+04
71 72 73 74 75
-6.030375e+03 -5.654631e+03 -8.220728e+03 -6.847605e+03 -8.723787e+03
76 77 78 79 80
1.465463e+04 -1.843766e+04 -3.568904e+04 -1.399177e+04 -1.180699e+04
81 82 83 84 85
3.011692e+03 -2.798369e+04 -4.480102e+03 7.665525e+04 -9.415045e+03
86 87 88 89 90
4.190852e+04 8.897489e+03 3.681300e+04 1.236726e+04 5.522224e+03
91 92 93 94 95
2.880865e+04 -2.960269e+04 -1.475526e+04 -2.471062e+04 2.649129e+04
96 97 98 99 100
-2.417785e+04 -4.562169e+03 -3.602704e+04 1.944056e+04 -2.938932e+04
101 102 103 104 105
-7.734119e+03 -2.381571e+04 -1.741509e+04 -3.781038e+04 8.634837e+02
106 107 108 109 110
1.538832e+04 6.037506e+04 -4.237220e+03 -4.139597e+02 -2.725376e+04
111 112 113 114 115
-5.876424e+04 1.145414e+04 -5.528280e+03 1.911734e+04 -7.364413e+02
116 117 118 119 120
-2.788853e+02 3.648340e+03 3.539472e+04 -2.896943e+04 -1.055660e+04
121 122 123 124 125
4.257545e+04 3.120276e+04 -7.216163e+03 -2.231344e+04 -2.190345e+04
126 127 128 129 130
-4.134643e+04 3.111465e+03 1.891575e+04 1.940174e+03 1.079792e+04
131 132 133 134 135
-1.865497e+04 -1.357452e+04 -2.721927e+04 -3.329419e+04 -3.283798e+04
136 137 138 139 140
1.206029e+04 8.752411e+03 4.577931e+03 1.235719e+04 -1.729201e+01
141 142 143 144 145
1.343821e+05 -9.825999e+03 7.109367e+04 1.277162e+05 -3.645520e+04
146 147 148 149 150
6.020342e+03 1.892533e+04 -1.012670e+04 -4.100833e+04 -4.343447e+04
151 152 153 154 155
-8.850265e+02 1.793847e+04 2.394671e+04 8.982378e+03 -6.613084e+03
156 157 158 159 160
-1.008908e+04 9.097794e+04 -5.358557e+04 3.008943e+04 1.184583e+04
161 162 163 164 165
1.913236e+03 -7.439258e+03 1.684128e+03 -3.182111e+04 3.385897e+04
166 167 168 169 170
5.118646e+03 -5.905605e+04 2.437641e+04 1.353639e+04 -9.773740e+03
171 172 173 174 175
3.148631e+03 7.645628e+03 3.111598e+04 -4.739437e+03 -5.514057e+04
176 177 178 179 180
-1.650145e+04 -5.417480e+03 -3.873912e+04 -1.633506e+04 -5.727080e+04
181 182 183 184 185
-6.196991e+03 2.990284e+04 -8.748495e+04 1.301569e+04 -1.925839e+04
186 187 188 189 190
-5.006227e+04 -1.805108e+04 7.061932e+03 -1.251259e+04 -1.265352e+04
191 192 193 194 195
-5.281372e+04 2.301232e+03 4.071270e+04 -3.771135e+03 1.015648e+05
196 197 198 199 200
-1.231285e+04 -8.859377e+02 -7.596976e+03 -1.798892e+04 -1.328795e+05
201 202 203 204 205
-2.019936e+04 -2.136287e+04 -4.434780e+03 1.395693e+03 7.787812e+03
206 207 208 209 210
3.211886e+04 1.914121e+04 2.746290e+04 5.192054e+02 -4.409146e+04
211 212 213 214 215
1.867601e+04 -3.493542e+04 7.457080e+04 4.212570e+04 5.186062e+03
216 217 218 219 220
-5.519351e+04 1.075267e+03 1.157316e+04 8.151198e+04 1.242864e+04
221 222 223 224 225
1.857887e+04 2.131678e+04 1.411716e+04 -1.497933e+04 -7.802539e+04
226 227 228 229 230
-2.695535e+04 6.462259e+04 3.289453e+03 2.276458e+04 3.935726e+04
231 232 233 234 235
1.287910e+04 2.222493e+04 6.975112e+04 -1.038344e+04 -2.560775e+04
236 237 238 239 240
-3.040573e+02 2.269437e+03 -3.294900e+04 -6.737211e+04 -1.336195e+04
241 242 243 244 245
7.151224e+04 -2.809779e+04 5.689720e+04 -1.359210e+03 -5.794073e+04
246 247 248 249 250
4.150986e+03 -1.200065e+04 4.750477e+04 1.917070e+04 9.123802e+03
251 252 253 254 255
5.915192e+04 -8.132014e+03 -1.651009e+04 -2.757711e+03 3.004468e+04
256 257 258 259 260
4.621674e+04 7.321720e+03 6.016654e+04 6.836446e+04 -6.527575e+03
261 262 263 264 265
-3.824524e+04 -6.082242e+03 1.154182e+03 -4.524611e+04 -1.198432e+04
266 267 268 269 270
-2.445906e+04 -1.924645e+04 4.680019e+04 -2.765814e+04 3.601947e+04
271 272 273 274 275
-3.047441e+04 4.212927e+04 5.336494e+03 3.467970e+04 -4.620660e+04
276 277 278 279 280
7.084178e+03 -4.070521e+04 7.341983e+04 1.276924e+04 -4.992840e+04
281 282 283 284 285
-3.524868e+04 1.356397e+03 -2.678528e+04 -2.261959e+03 1.688406e+04
286 287 288 289
-2.039793e+04 9.818793e+04 -8.397572e+04 -4.740038e+03
> postscript(file="/var/wessaorg/rcomp/tmp/6aeg91323953651.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 289
Frequency = 1
lag(myerror, k = 1) myerror
0 4.406508e+03 NA
1 1.550703e+04 4.406508e+03
2 -1.042287e+03 1.550703e+04
3 7.572173e+03 -1.042287e+03
4 -5.925438e+03 7.572173e+03
5 -7.242415e+00 -5.925438e+03
6 4.698374e+04 -7.242415e+00
7 -1.466524e+04 4.698374e+04
8 1.037819e+04 -1.466524e+04
9 -1.737645e+04 1.037819e+04
10 -1.072005e+04 -1.737645e+04
11 -1.220304e+03 -1.072005e+04
12 -1.031620e+04 -1.220304e+03
13 -6.782481e+03 -1.031620e+04
14 -7.410794e+03 -6.782481e+03
15 1.266923e+03 -7.410794e+03
16 2.635418e+03 1.266923e+03
17 1.983839e+04 2.635418e+03
18 -2.869274e+03 1.983839e+04
19 1.040744e+04 -2.869274e+03
20 -2.720610e+03 1.040744e+04
21 -1.592478e+04 -2.720610e+03
22 1.678418e+03 -1.592478e+04
23 -3.646697e+03 1.678418e+03
24 -1.054023e+05 -3.646697e+03
25 2.498280e+04 -1.054023e+05
26 6.789293e+04 2.498280e+04
27 -1.537391e+04 6.789293e+04
28 6.036432e+04 -1.537391e+04
29 -1.855613e+04 6.036432e+04
30 2.132107e+04 -1.855613e+04
31 -5.955911e+04 2.132107e+04
32 -1.892741e+04 -5.955911e+04
33 -2.575545e+04 -1.892741e+04
34 -3.344784e+04 -2.575545e+04
35 -3.790442e+03 -3.344784e+04
36 -7.618158e+03 -3.790442e+03
37 2.436446e+03 -7.618158e+03
38 6.074661e+04 2.436446e+03
39 -7.398009e+03 6.074661e+04
40 1.752744e+04 -7.398009e+03
41 -2.932003e+04 1.752744e+04
42 9.612921e+03 -2.932003e+04
43 5.646707e+03 9.612921e+03
44 -1.488558e+05 5.646707e+03
45 -4.140425e+02 -1.488558e+05
46 5.782648e+03 -4.140425e+02
47 -2.388161e+04 5.782648e+03
48 7.175297e+03 -2.388161e+04
49 -1.344965e+04 7.175297e+03
50 1.204531e+04 -1.344965e+04
51 -4.555195e+04 1.204531e+04
52 2.468851e+04 -4.555195e+04
53 1.496423e+05 2.468851e+04
54 5.380513e+04 1.496423e+05
55 2.848075e+04 5.380513e+04
56 2.779473e+04 2.848075e+04
57 2.114443e+04 2.779473e+04
58 -3.115831e+04 2.114443e+04
59 -4.168178e+04 -3.115831e+04
60 -1.879754e+04 -4.168178e+04
61 -1.386724e+04 -1.879754e+04
62 -5.997330e+02 -1.386724e+04
63 -3.415376e+03 -5.997330e+02
64 -1.661133e+04 -3.415376e+03
65 1.994741e+04 -1.661133e+04
66 -2.174243e+04 1.994741e+04
67 -2.106089e+03 -2.174243e+04
68 -2.213497e+04 -2.106089e+03
69 -1.158577e+04 -2.213497e+04
70 -6.030375e+03 -1.158577e+04
71 -5.654631e+03 -6.030375e+03
72 -8.220728e+03 -5.654631e+03
73 -6.847605e+03 -8.220728e+03
74 -8.723787e+03 -6.847605e+03
75 1.465463e+04 -8.723787e+03
76 -1.843766e+04 1.465463e+04
77 -3.568904e+04 -1.843766e+04
78 -1.399177e+04 -3.568904e+04
79 -1.180699e+04 -1.399177e+04
80 3.011692e+03 -1.180699e+04
81 -2.798369e+04 3.011692e+03
82 -4.480102e+03 -2.798369e+04
83 7.665525e+04 -4.480102e+03
84 -9.415045e+03 7.665525e+04
85 4.190852e+04 -9.415045e+03
86 8.897489e+03 4.190852e+04
87 3.681300e+04 8.897489e+03
88 1.236726e+04 3.681300e+04
89 5.522224e+03 1.236726e+04
90 2.880865e+04 5.522224e+03
91 -2.960269e+04 2.880865e+04
92 -1.475526e+04 -2.960269e+04
93 -2.471062e+04 -1.475526e+04
94 2.649129e+04 -2.471062e+04
95 -2.417785e+04 2.649129e+04
96 -4.562169e+03 -2.417785e+04
97 -3.602704e+04 -4.562169e+03
98 1.944056e+04 -3.602704e+04
99 -2.938932e+04 1.944056e+04
100 -7.734119e+03 -2.938932e+04
101 -2.381571e+04 -7.734119e+03
102 -1.741509e+04 -2.381571e+04
103 -3.781038e+04 -1.741509e+04
104 8.634837e+02 -3.781038e+04
105 1.538832e+04 8.634837e+02
106 6.037506e+04 1.538832e+04
107 -4.237220e+03 6.037506e+04
108 -4.139597e+02 -4.237220e+03
109 -2.725376e+04 -4.139597e+02
110 -5.876424e+04 -2.725376e+04
111 1.145414e+04 -5.876424e+04
112 -5.528280e+03 1.145414e+04
113 1.911734e+04 -5.528280e+03
114 -7.364413e+02 1.911734e+04
115 -2.788853e+02 -7.364413e+02
116 3.648340e+03 -2.788853e+02
117 3.539472e+04 3.648340e+03
118 -2.896943e+04 3.539472e+04
119 -1.055660e+04 -2.896943e+04
120 4.257545e+04 -1.055660e+04
121 3.120276e+04 4.257545e+04
122 -7.216163e+03 3.120276e+04
123 -2.231344e+04 -7.216163e+03
124 -2.190345e+04 -2.231344e+04
125 -4.134643e+04 -2.190345e+04
126 3.111465e+03 -4.134643e+04
127 1.891575e+04 3.111465e+03
128 1.940174e+03 1.891575e+04
129 1.079792e+04 1.940174e+03
130 -1.865497e+04 1.079792e+04
131 -1.357452e+04 -1.865497e+04
132 -2.721927e+04 -1.357452e+04
133 -3.329419e+04 -2.721927e+04
134 -3.283798e+04 -3.329419e+04
135 1.206029e+04 -3.283798e+04
136 8.752411e+03 1.206029e+04
137 4.577931e+03 8.752411e+03
138 1.235719e+04 4.577931e+03
139 -1.729201e+01 1.235719e+04
140 1.343821e+05 -1.729201e+01
141 -9.825999e+03 1.343821e+05
142 7.109367e+04 -9.825999e+03
143 1.277162e+05 7.109367e+04
144 -3.645520e+04 1.277162e+05
145 6.020342e+03 -3.645520e+04
146 1.892533e+04 6.020342e+03
147 -1.012670e+04 1.892533e+04
148 -4.100833e+04 -1.012670e+04
149 -4.343447e+04 -4.100833e+04
150 -8.850265e+02 -4.343447e+04
151 1.793847e+04 -8.850265e+02
152 2.394671e+04 1.793847e+04
153 8.982378e+03 2.394671e+04
154 -6.613084e+03 8.982378e+03
155 -1.008908e+04 -6.613084e+03
156 9.097794e+04 -1.008908e+04
157 -5.358557e+04 9.097794e+04
158 3.008943e+04 -5.358557e+04
159 1.184583e+04 3.008943e+04
160 1.913236e+03 1.184583e+04
161 -7.439258e+03 1.913236e+03
162 1.684128e+03 -7.439258e+03
163 -3.182111e+04 1.684128e+03
164 3.385897e+04 -3.182111e+04
165 5.118646e+03 3.385897e+04
166 -5.905605e+04 5.118646e+03
167 2.437641e+04 -5.905605e+04
168 1.353639e+04 2.437641e+04
169 -9.773740e+03 1.353639e+04
170 3.148631e+03 -9.773740e+03
171 7.645628e+03 3.148631e+03
172 3.111598e+04 7.645628e+03
173 -4.739437e+03 3.111598e+04
174 -5.514057e+04 -4.739437e+03
175 -1.650145e+04 -5.514057e+04
176 -5.417480e+03 -1.650145e+04
177 -3.873912e+04 -5.417480e+03
178 -1.633506e+04 -3.873912e+04
179 -5.727080e+04 -1.633506e+04
180 -6.196991e+03 -5.727080e+04
181 2.990284e+04 -6.196991e+03
182 -8.748495e+04 2.990284e+04
183 1.301569e+04 -8.748495e+04
184 -1.925839e+04 1.301569e+04
185 -5.006227e+04 -1.925839e+04
186 -1.805108e+04 -5.006227e+04
187 7.061932e+03 -1.805108e+04
188 -1.251259e+04 7.061932e+03
189 -1.265352e+04 -1.251259e+04
190 -5.281372e+04 -1.265352e+04
191 2.301232e+03 -5.281372e+04
192 4.071270e+04 2.301232e+03
193 -3.771135e+03 4.071270e+04
194 1.015648e+05 -3.771135e+03
195 -1.231285e+04 1.015648e+05
196 -8.859377e+02 -1.231285e+04
197 -7.596976e+03 -8.859377e+02
198 -1.798892e+04 -7.596976e+03
199 -1.328795e+05 -1.798892e+04
200 -2.019936e+04 -1.328795e+05
201 -2.136287e+04 -2.019936e+04
202 -4.434780e+03 -2.136287e+04
203 1.395693e+03 -4.434780e+03
204 7.787812e+03 1.395693e+03
205 3.211886e+04 7.787812e+03
206 1.914121e+04 3.211886e+04
207 2.746290e+04 1.914121e+04
208 5.192054e+02 2.746290e+04
209 -4.409146e+04 5.192054e+02
210 1.867601e+04 -4.409146e+04
211 -3.493542e+04 1.867601e+04
212 7.457080e+04 -3.493542e+04
213 4.212570e+04 7.457080e+04
214 5.186062e+03 4.212570e+04
215 -5.519351e+04 5.186062e+03
216 1.075267e+03 -5.519351e+04
217 1.157316e+04 1.075267e+03
218 8.151198e+04 1.157316e+04
219 1.242864e+04 8.151198e+04
220 1.857887e+04 1.242864e+04
221 2.131678e+04 1.857887e+04
222 1.411716e+04 2.131678e+04
223 -1.497933e+04 1.411716e+04
224 -7.802539e+04 -1.497933e+04
225 -2.695535e+04 -7.802539e+04
226 6.462259e+04 -2.695535e+04
227 3.289453e+03 6.462259e+04
228 2.276458e+04 3.289453e+03
229 3.935726e+04 2.276458e+04
230 1.287910e+04 3.935726e+04
231 2.222493e+04 1.287910e+04
232 6.975112e+04 2.222493e+04
233 -1.038344e+04 6.975112e+04
234 -2.560775e+04 -1.038344e+04
235 -3.040573e+02 -2.560775e+04
236 2.269437e+03 -3.040573e+02
237 -3.294900e+04 2.269437e+03
238 -6.737211e+04 -3.294900e+04
239 -1.336195e+04 -6.737211e+04
240 7.151224e+04 -1.336195e+04
241 -2.809779e+04 7.151224e+04
242 5.689720e+04 -2.809779e+04
243 -1.359210e+03 5.689720e+04
244 -5.794073e+04 -1.359210e+03
245 4.150986e+03 -5.794073e+04
246 -1.200065e+04 4.150986e+03
247 4.750477e+04 -1.200065e+04
248 1.917070e+04 4.750477e+04
249 9.123802e+03 1.917070e+04
250 5.915192e+04 9.123802e+03
251 -8.132014e+03 5.915192e+04
252 -1.651009e+04 -8.132014e+03
253 -2.757711e+03 -1.651009e+04
254 3.004468e+04 -2.757711e+03
255 4.621674e+04 3.004468e+04
256 7.321720e+03 4.621674e+04
257 6.016654e+04 7.321720e+03
258 6.836446e+04 6.016654e+04
259 -6.527575e+03 6.836446e+04
260 -3.824524e+04 -6.527575e+03
261 -6.082242e+03 -3.824524e+04
262 1.154182e+03 -6.082242e+03
263 -4.524611e+04 1.154182e+03
264 -1.198432e+04 -4.524611e+04
265 -2.445906e+04 -1.198432e+04
266 -1.924645e+04 -2.445906e+04
267 4.680019e+04 -1.924645e+04
268 -2.765814e+04 4.680019e+04
269 3.601947e+04 -2.765814e+04
270 -3.047441e+04 3.601947e+04
271 4.212927e+04 -3.047441e+04
272 5.336494e+03 4.212927e+04
273 3.467970e+04 5.336494e+03
274 -4.620660e+04 3.467970e+04
275 7.084178e+03 -4.620660e+04
276 -4.070521e+04 7.084178e+03
277 7.341983e+04 -4.070521e+04
278 1.276924e+04 7.341983e+04
279 -4.992840e+04 1.276924e+04
280 -3.524868e+04 -4.992840e+04
281 1.356397e+03 -3.524868e+04
282 -2.678528e+04 1.356397e+03
283 -2.261959e+03 -2.678528e+04
284 1.688406e+04 -2.261959e+03
285 -2.039793e+04 1.688406e+04
286 9.818793e+04 -2.039793e+04
287 -8.397572e+04 9.818793e+04
288 -4.740038e+03 -8.397572e+04
289 NA -4.740038e+03
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.550703e+04 4.406508e+03
[2,] -1.042287e+03 1.550703e+04
[3,] 7.572173e+03 -1.042287e+03
[4,] -5.925438e+03 7.572173e+03
[5,] -7.242415e+00 -5.925438e+03
[6,] 4.698374e+04 -7.242415e+00
[7,] -1.466524e+04 4.698374e+04
[8,] 1.037819e+04 -1.466524e+04
[9,] -1.737645e+04 1.037819e+04
[10,] -1.072005e+04 -1.737645e+04
[11,] -1.220304e+03 -1.072005e+04
[12,] -1.031620e+04 -1.220304e+03
[13,] -6.782481e+03 -1.031620e+04
[14,] -7.410794e+03 -6.782481e+03
[15,] 1.266923e+03 -7.410794e+03
[16,] 2.635418e+03 1.266923e+03
[17,] 1.983839e+04 2.635418e+03
[18,] -2.869274e+03 1.983839e+04
[19,] 1.040744e+04 -2.869274e+03
[20,] -2.720610e+03 1.040744e+04
[21,] -1.592478e+04 -2.720610e+03
[22,] 1.678418e+03 -1.592478e+04
[23,] -3.646697e+03 1.678418e+03
[24,] -1.054023e+05 -3.646697e+03
[25,] 2.498280e+04 -1.054023e+05
[26,] 6.789293e+04 2.498280e+04
[27,] -1.537391e+04 6.789293e+04
[28,] 6.036432e+04 -1.537391e+04
[29,] -1.855613e+04 6.036432e+04
[30,] 2.132107e+04 -1.855613e+04
[31,] -5.955911e+04 2.132107e+04
[32,] -1.892741e+04 -5.955911e+04
[33,] -2.575545e+04 -1.892741e+04
[34,] -3.344784e+04 -2.575545e+04
[35,] -3.790442e+03 -3.344784e+04
[36,] -7.618158e+03 -3.790442e+03
[37,] 2.436446e+03 -7.618158e+03
[38,] 6.074661e+04 2.436446e+03
[39,] -7.398009e+03 6.074661e+04
[40,] 1.752744e+04 -7.398009e+03
[41,] -2.932003e+04 1.752744e+04
[42,] 9.612921e+03 -2.932003e+04
[43,] 5.646707e+03 9.612921e+03
[44,] -1.488558e+05 5.646707e+03
[45,] -4.140425e+02 -1.488558e+05
[46,] 5.782648e+03 -4.140425e+02
[47,] -2.388161e+04 5.782648e+03
[48,] 7.175297e+03 -2.388161e+04
[49,] -1.344965e+04 7.175297e+03
[50,] 1.204531e+04 -1.344965e+04
[51,] -4.555195e+04 1.204531e+04
[52,] 2.468851e+04 -4.555195e+04
[53,] 1.496423e+05 2.468851e+04
[54,] 5.380513e+04 1.496423e+05
[55,] 2.848075e+04 5.380513e+04
[56,] 2.779473e+04 2.848075e+04
[57,] 2.114443e+04 2.779473e+04
[58,] -3.115831e+04 2.114443e+04
[59,] -4.168178e+04 -3.115831e+04
[60,] -1.879754e+04 -4.168178e+04
[61,] -1.386724e+04 -1.879754e+04
[62,] -5.997330e+02 -1.386724e+04
[63,] -3.415376e+03 -5.997330e+02
[64,] -1.661133e+04 -3.415376e+03
[65,] 1.994741e+04 -1.661133e+04
[66,] -2.174243e+04 1.994741e+04
[67,] -2.106089e+03 -2.174243e+04
[68,] -2.213497e+04 -2.106089e+03
[69,] -1.158577e+04 -2.213497e+04
[70,] -6.030375e+03 -1.158577e+04
[71,] -5.654631e+03 -6.030375e+03
[72,] -8.220728e+03 -5.654631e+03
[73,] -6.847605e+03 -8.220728e+03
[74,] -8.723787e+03 -6.847605e+03
[75,] 1.465463e+04 -8.723787e+03
[76,] -1.843766e+04 1.465463e+04
[77,] -3.568904e+04 -1.843766e+04
[78,] -1.399177e+04 -3.568904e+04
[79,] -1.180699e+04 -1.399177e+04
[80,] 3.011692e+03 -1.180699e+04
[81,] -2.798369e+04 3.011692e+03
[82,] -4.480102e+03 -2.798369e+04
[83,] 7.665525e+04 -4.480102e+03
[84,] -9.415045e+03 7.665525e+04
[85,] 4.190852e+04 -9.415045e+03
[86,] 8.897489e+03 4.190852e+04
[87,] 3.681300e+04 8.897489e+03
[88,] 1.236726e+04 3.681300e+04
[89,] 5.522224e+03 1.236726e+04
[90,] 2.880865e+04 5.522224e+03
[91,] -2.960269e+04 2.880865e+04
[92,] -1.475526e+04 -2.960269e+04
[93,] -2.471062e+04 -1.475526e+04
[94,] 2.649129e+04 -2.471062e+04
[95,] -2.417785e+04 2.649129e+04
[96,] -4.562169e+03 -2.417785e+04
[97,] -3.602704e+04 -4.562169e+03
[98,] 1.944056e+04 -3.602704e+04
[99,] -2.938932e+04 1.944056e+04
[100,] -7.734119e+03 -2.938932e+04
[101,] -2.381571e+04 -7.734119e+03
[102,] -1.741509e+04 -2.381571e+04
[103,] -3.781038e+04 -1.741509e+04
[104,] 8.634837e+02 -3.781038e+04
[105,] 1.538832e+04 8.634837e+02
[106,] 6.037506e+04 1.538832e+04
[107,] -4.237220e+03 6.037506e+04
[108,] -4.139597e+02 -4.237220e+03
[109,] -2.725376e+04 -4.139597e+02
[110,] -5.876424e+04 -2.725376e+04
[111,] 1.145414e+04 -5.876424e+04
[112,] -5.528280e+03 1.145414e+04
[113,] 1.911734e+04 -5.528280e+03
[114,] -7.364413e+02 1.911734e+04
[115,] -2.788853e+02 -7.364413e+02
[116,] 3.648340e+03 -2.788853e+02
[117,] 3.539472e+04 3.648340e+03
[118,] -2.896943e+04 3.539472e+04
[119,] -1.055660e+04 -2.896943e+04
[120,] 4.257545e+04 -1.055660e+04
[121,] 3.120276e+04 4.257545e+04
[122,] -7.216163e+03 3.120276e+04
[123,] -2.231344e+04 -7.216163e+03
[124,] -2.190345e+04 -2.231344e+04
[125,] -4.134643e+04 -2.190345e+04
[126,] 3.111465e+03 -4.134643e+04
[127,] 1.891575e+04 3.111465e+03
[128,] 1.940174e+03 1.891575e+04
[129,] 1.079792e+04 1.940174e+03
[130,] -1.865497e+04 1.079792e+04
[131,] -1.357452e+04 -1.865497e+04
[132,] -2.721927e+04 -1.357452e+04
[133,] -3.329419e+04 -2.721927e+04
[134,] -3.283798e+04 -3.329419e+04
[135,] 1.206029e+04 -3.283798e+04
[136,] 8.752411e+03 1.206029e+04
[137,] 4.577931e+03 8.752411e+03
[138,] 1.235719e+04 4.577931e+03
[139,] -1.729201e+01 1.235719e+04
[140,] 1.343821e+05 -1.729201e+01
[141,] -9.825999e+03 1.343821e+05
[142,] 7.109367e+04 -9.825999e+03
[143,] 1.277162e+05 7.109367e+04
[144,] -3.645520e+04 1.277162e+05
[145,] 6.020342e+03 -3.645520e+04
[146,] 1.892533e+04 6.020342e+03
[147,] -1.012670e+04 1.892533e+04
[148,] -4.100833e+04 -1.012670e+04
[149,] -4.343447e+04 -4.100833e+04
[150,] -8.850265e+02 -4.343447e+04
[151,] 1.793847e+04 -8.850265e+02
[152,] 2.394671e+04 1.793847e+04
[153,] 8.982378e+03 2.394671e+04
[154,] -6.613084e+03 8.982378e+03
[155,] -1.008908e+04 -6.613084e+03
[156,] 9.097794e+04 -1.008908e+04
[157,] -5.358557e+04 9.097794e+04
[158,] 3.008943e+04 -5.358557e+04
[159,] 1.184583e+04 3.008943e+04
[160,] 1.913236e+03 1.184583e+04
[161,] -7.439258e+03 1.913236e+03
[162,] 1.684128e+03 -7.439258e+03
[163,] -3.182111e+04 1.684128e+03
[164,] 3.385897e+04 -3.182111e+04
[165,] 5.118646e+03 3.385897e+04
[166,] -5.905605e+04 5.118646e+03
[167,] 2.437641e+04 -5.905605e+04
[168,] 1.353639e+04 2.437641e+04
[169,] -9.773740e+03 1.353639e+04
[170,] 3.148631e+03 -9.773740e+03
[171,] 7.645628e+03 3.148631e+03
[172,] 3.111598e+04 7.645628e+03
[173,] -4.739437e+03 3.111598e+04
[174,] -5.514057e+04 -4.739437e+03
[175,] -1.650145e+04 -5.514057e+04
[176,] -5.417480e+03 -1.650145e+04
[177,] -3.873912e+04 -5.417480e+03
[178,] -1.633506e+04 -3.873912e+04
[179,] -5.727080e+04 -1.633506e+04
[180,] -6.196991e+03 -5.727080e+04
[181,] 2.990284e+04 -6.196991e+03
[182,] -8.748495e+04 2.990284e+04
[183,] 1.301569e+04 -8.748495e+04
[184,] -1.925839e+04 1.301569e+04
[185,] -5.006227e+04 -1.925839e+04
[186,] -1.805108e+04 -5.006227e+04
[187,] 7.061932e+03 -1.805108e+04
[188,] -1.251259e+04 7.061932e+03
[189,] -1.265352e+04 -1.251259e+04
[190,] -5.281372e+04 -1.265352e+04
[191,] 2.301232e+03 -5.281372e+04
[192,] 4.071270e+04 2.301232e+03
[193,] -3.771135e+03 4.071270e+04
[194,] 1.015648e+05 -3.771135e+03
[195,] -1.231285e+04 1.015648e+05
[196,] -8.859377e+02 -1.231285e+04
[197,] -7.596976e+03 -8.859377e+02
[198,] -1.798892e+04 -7.596976e+03
[199,] -1.328795e+05 -1.798892e+04
[200,] -2.019936e+04 -1.328795e+05
[201,] -2.136287e+04 -2.019936e+04
[202,] -4.434780e+03 -2.136287e+04
[203,] 1.395693e+03 -4.434780e+03
[204,] 7.787812e+03 1.395693e+03
[205,] 3.211886e+04 7.787812e+03
[206,] 1.914121e+04 3.211886e+04
[207,] 2.746290e+04 1.914121e+04
[208,] 5.192054e+02 2.746290e+04
[209,] -4.409146e+04 5.192054e+02
[210,] 1.867601e+04 -4.409146e+04
[211,] -3.493542e+04 1.867601e+04
[212,] 7.457080e+04 -3.493542e+04
[213,] 4.212570e+04 7.457080e+04
[214,] 5.186062e+03 4.212570e+04
[215,] -5.519351e+04 5.186062e+03
[216,] 1.075267e+03 -5.519351e+04
[217,] 1.157316e+04 1.075267e+03
[218,] 8.151198e+04 1.157316e+04
[219,] 1.242864e+04 8.151198e+04
[220,] 1.857887e+04 1.242864e+04
[221,] 2.131678e+04 1.857887e+04
[222,] 1.411716e+04 2.131678e+04
[223,] -1.497933e+04 1.411716e+04
[224,] -7.802539e+04 -1.497933e+04
[225,] -2.695535e+04 -7.802539e+04
[226,] 6.462259e+04 -2.695535e+04
[227,] 3.289453e+03 6.462259e+04
[228,] 2.276458e+04 3.289453e+03
[229,] 3.935726e+04 2.276458e+04
[230,] 1.287910e+04 3.935726e+04
[231,] 2.222493e+04 1.287910e+04
[232,] 6.975112e+04 2.222493e+04
[233,] -1.038344e+04 6.975112e+04
[234,] -2.560775e+04 -1.038344e+04
[235,] -3.040573e+02 -2.560775e+04
[236,] 2.269437e+03 -3.040573e+02
[237,] -3.294900e+04 2.269437e+03
[238,] -6.737211e+04 -3.294900e+04
[239,] -1.336195e+04 -6.737211e+04
[240,] 7.151224e+04 -1.336195e+04
[241,] -2.809779e+04 7.151224e+04
[242,] 5.689720e+04 -2.809779e+04
[243,] -1.359210e+03 5.689720e+04
[244,] -5.794073e+04 -1.359210e+03
[245,] 4.150986e+03 -5.794073e+04
[246,] -1.200065e+04 4.150986e+03
[247,] 4.750477e+04 -1.200065e+04
[248,] 1.917070e+04 4.750477e+04
[249,] 9.123802e+03 1.917070e+04
[250,] 5.915192e+04 9.123802e+03
[251,] -8.132014e+03 5.915192e+04
[252,] -1.651009e+04 -8.132014e+03
[253,] -2.757711e+03 -1.651009e+04
[254,] 3.004468e+04 -2.757711e+03
[255,] 4.621674e+04 3.004468e+04
[256,] 7.321720e+03 4.621674e+04
[257,] 6.016654e+04 7.321720e+03
[258,] 6.836446e+04 6.016654e+04
[259,] -6.527575e+03 6.836446e+04
[260,] -3.824524e+04 -6.527575e+03
[261,] -6.082242e+03 -3.824524e+04
[262,] 1.154182e+03 -6.082242e+03
[263,] -4.524611e+04 1.154182e+03
[264,] -1.198432e+04 -4.524611e+04
[265,] -2.445906e+04 -1.198432e+04
[266,] -1.924645e+04 -2.445906e+04
[267,] 4.680019e+04 -1.924645e+04
[268,] -2.765814e+04 4.680019e+04
[269,] 3.601947e+04 -2.765814e+04
[270,] -3.047441e+04 3.601947e+04
[271,] 4.212927e+04 -3.047441e+04
[272,] 5.336494e+03 4.212927e+04
[273,] 3.467970e+04 5.336494e+03
[274,] -4.620660e+04 3.467970e+04
[275,] 7.084178e+03 -4.620660e+04
[276,] -4.070521e+04 7.084178e+03
[277,] 7.341983e+04 -4.070521e+04
[278,] 1.276924e+04 7.341983e+04
[279,] -4.992840e+04 1.276924e+04
[280,] -3.524868e+04 -4.992840e+04
[281,] 1.356397e+03 -3.524868e+04
[282,] -2.678528e+04 1.356397e+03
[283,] -2.261959e+03 -2.678528e+04
[284,] 1.688406e+04 -2.261959e+03
[285,] -2.039793e+04 1.688406e+04
[286,] 9.818793e+04 -2.039793e+04
[287,] -8.397572e+04 9.818793e+04
[288,] -4.740038e+03 -8.397572e+04
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.550703e+04 4.406508e+03
2 -1.042287e+03 1.550703e+04
3 7.572173e+03 -1.042287e+03
4 -5.925438e+03 7.572173e+03
5 -7.242415e+00 -5.925438e+03
6 4.698374e+04 -7.242415e+00
7 -1.466524e+04 4.698374e+04
8 1.037819e+04 -1.466524e+04
9 -1.737645e+04 1.037819e+04
10 -1.072005e+04 -1.737645e+04
11 -1.220304e+03 -1.072005e+04
12 -1.031620e+04 -1.220304e+03
13 -6.782481e+03 -1.031620e+04
14 -7.410794e+03 -6.782481e+03
15 1.266923e+03 -7.410794e+03
16 2.635418e+03 1.266923e+03
17 1.983839e+04 2.635418e+03
18 -2.869274e+03 1.983839e+04
19 1.040744e+04 -2.869274e+03
20 -2.720610e+03 1.040744e+04
21 -1.592478e+04 -2.720610e+03
22 1.678418e+03 -1.592478e+04
23 -3.646697e+03 1.678418e+03
24 -1.054023e+05 -3.646697e+03
25 2.498280e+04 -1.054023e+05
26 6.789293e+04 2.498280e+04
27 -1.537391e+04 6.789293e+04
28 6.036432e+04 -1.537391e+04
29 -1.855613e+04 6.036432e+04
30 2.132107e+04 -1.855613e+04
31 -5.955911e+04 2.132107e+04
32 -1.892741e+04 -5.955911e+04
33 -2.575545e+04 -1.892741e+04
34 -3.344784e+04 -2.575545e+04
35 -3.790442e+03 -3.344784e+04
36 -7.618158e+03 -3.790442e+03
37 2.436446e+03 -7.618158e+03
38 6.074661e+04 2.436446e+03
39 -7.398009e+03 6.074661e+04
40 1.752744e+04 -7.398009e+03
41 -2.932003e+04 1.752744e+04
42 9.612921e+03 -2.932003e+04
43 5.646707e+03 9.612921e+03
44 -1.488558e+05 5.646707e+03
45 -4.140425e+02 -1.488558e+05
46 5.782648e+03 -4.140425e+02
47 -2.388161e+04 5.782648e+03
48 7.175297e+03 -2.388161e+04
49 -1.344965e+04 7.175297e+03
50 1.204531e+04 -1.344965e+04
51 -4.555195e+04 1.204531e+04
52 2.468851e+04 -4.555195e+04
53 1.496423e+05 2.468851e+04
54 5.380513e+04 1.496423e+05
55 2.848075e+04 5.380513e+04
56 2.779473e+04 2.848075e+04
57 2.114443e+04 2.779473e+04
58 -3.115831e+04 2.114443e+04
59 -4.168178e+04 -3.115831e+04
60 -1.879754e+04 -4.168178e+04
61 -1.386724e+04 -1.879754e+04
62 -5.997330e+02 -1.386724e+04
63 -3.415376e+03 -5.997330e+02
64 -1.661133e+04 -3.415376e+03
65 1.994741e+04 -1.661133e+04
66 -2.174243e+04 1.994741e+04
67 -2.106089e+03 -2.174243e+04
68 -2.213497e+04 -2.106089e+03
69 -1.158577e+04 -2.213497e+04
70 -6.030375e+03 -1.158577e+04
71 -5.654631e+03 -6.030375e+03
72 -8.220728e+03 -5.654631e+03
73 -6.847605e+03 -8.220728e+03
74 -8.723787e+03 -6.847605e+03
75 1.465463e+04 -8.723787e+03
76 -1.843766e+04 1.465463e+04
77 -3.568904e+04 -1.843766e+04
78 -1.399177e+04 -3.568904e+04
79 -1.180699e+04 -1.399177e+04
80 3.011692e+03 -1.180699e+04
81 -2.798369e+04 3.011692e+03
82 -4.480102e+03 -2.798369e+04
83 7.665525e+04 -4.480102e+03
84 -9.415045e+03 7.665525e+04
85 4.190852e+04 -9.415045e+03
86 8.897489e+03 4.190852e+04
87 3.681300e+04 8.897489e+03
88 1.236726e+04 3.681300e+04
89 5.522224e+03 1.236726e+04
90 2.880865e+04 5.522224e+03
91 -2.960269e+04 2.880865e+04
92 -1.475526e+04 -2.960269e+04
93 -2.471062e+04 -1.475526e+04
94 2.649129e+04 -2.471062e+04
95 -2.417785e+04 2.649129e+04
96 -4.562169e+03 -2.417785e+04
97 -3.602704e+04 -4.562169e+03
98 1.944056e+04 -3.602704e+04
99 -2.938932e+04 1.944056e+04
100 -7.734119e+03 -2.938932e+04
101 -2.381571e+04 -7.734119e+03
102 -1.741509e+04 -2.381571e+04
103 -3.781038e+04 -1.741509e+04
104 8.634837e+02 -3.781038e+04
105 1.538832e+04 8.634837e+02
106 6.037506e+04 1.538832e+04
107 -4.237220e+03 6.037506e+04
108 -4.139597e+02 -4.237220e+03
109 -2.725376e+04 -4.139597e+02
110 -5.876424e+04 -2.725376e+04
111 1.145414e+04 -5.876424e+04
112 -5.528280e+03 1.145414e+04
113 1.911734e+04 -5.528280e+03
114 -7.364413e+02 1.911734e+04
115 -2.788853e+02 -7.364413e+02
116 3.648340e+03 -2.788853e+02
117 3.539472e+04 3.648340e+03
118 -2.896943e+04 3.539472e+04
119 -1.055660e+04 -2.896943e+04
120 4.257545e+04 -1.055660e+04
121 3.120276e+04 4.257545e+04
122 -7.216163e+03 3.120276e+04
123 -2.231344e+04 -7.216163e+03
124 -2.190345e+04 -2.231344e+04
125 -4.134643e+04 -2.190345e+04
126 3.111465e+03 -4.134643e+04
127 1.891575e+04 3.111465e+03
128 1.940174e+03 1.891575e+04
129 1.079792e+04 1.940174e+03
130 -1.865497e+04 1.079792e+04
131 -1.357452e+04 -1.865497e+04
132 -2.721927e+04 -1.357452e+04
133 -3.329419e+04 -2.721927e+04
134 -3.283798e+04 -3.329419e+04
135 1.206029e+04 -3.283798e+04
136 8.752411e+03 1.206029e+04
137 4.577931e+03 8.752411e+03
138 1.235719e+04 4.577931e+03
139 -1.729201e+01 1.235719e+04
140 1.343821e+05 -1.729201e+01
141 -9.825999e+03 1.343821e+05
142 7.109367e+04 -9.825999e+03
143 1.277162e+05 7.109367e+04
144 -3.645520e+04 1.277162e+05
145 6.020342e+03 -3.645520e+04
146 1.892533e+04 6.020342e+03
147 -1.012670e+04 1.892533e+04
148 -4.100833e+04 -1.012670e+04
149 -4.343447e+04 -4.100833e+04
150 -8.850265e+02 -4.343447e+04
151 1.793847e+04 -8.850265e+02
152 2.394671e+04 1.793847e+04
153 8.982378e+03 2.394671e+04
154 -6.613084e+03 8.982378e+03
155 -1.008908e+04 -6.613084e+03
156 9.097794e+04 -1.008908e+04
157 -5.358557e+04 9.097794e+04
158 3.008943e+04 -5.358557e+04
159 1.184583e+04 3.008943e+04
160 1.913236e+03 1.184583e+04
161 -7.439258e+03 1.913236e+03
162 1.684128e+03 -7.439258e+03
163 -3.182111e+04 1.684128e+03
164 3.385897e+04 -3.182111e+04
165 5.118646e+03 3.385897e+04
166 -5.905605e+04 5.118646e+03
167 2.437641e+04 -5.905605e+04
168 1.353639e+04 2.437641e+04
169 -9.773740e+03 1.353639e+04
170 3.148631e+03 -9.773740e+03
171 7.645628e+03 3.148631e+03
172 3.111598e+04 7.645628e+03
173 -4.739437e+03 3.111598e+04
174 -5.514057e+04 -4.739437e+03
175 -1.650145e+04 -5.514057e+04
176 -5.417480e+03 -1.650145e+04
177 -3.873912e+04 -5.417480e+03
178 -1.633506e+04 -3.873912e+04
179 -5.727080e+04 -1.633506e+04
180 -6.196991e+03 -5.727080e+04
181 2.990284e+04 -6.196991e+03
182 -8.748495e+04 2.990284e+04
183 1.301569e+04 -8.748495e+04
184 -1.925839e+04 1.301569e+04
185 -5.006227e+04 -1.925839e+04
186 -1.805108e+04 -5.006227e+04
187 7.061932e+03 -1.805108e+04
188 -1.251259e+04 7.061932e+03
189 -1.265352e+04 -1.251259e+04
190 -5.281372e+04 -1.265352e+04
191 2.301232e+03 -5.281372e+04
192 4.071270e+04 2.301232e+03
193 -3.771135e+03 4.071270e+04
194 1.015648e+05 -3.771135e+03
195 -1.231285e+04 1.015648e+05
196 -8.859377e+02 -1.231285e+04
197 -7.596976e+03 -8.859377e+02
198 -1.798892e+04 -7.596976e+03
199 -1.328795e+05 -1.798892e+04
200 -2.019936e+04 -1.328795e+05
201 -2.136287e+04 -2.019936e+04
202 -4.434780e+03 -2.136287e+04
203 1.395693e+03 -4.434780e+03
204 7.787812e+03 1.395693e+03
205 3.211886e+04 7.787812e+03
206 1.914121e+04 3.211886e+04
207 2.746290e+04 1.914121e+04
208 5.192054e+02 2.746290e+04
209 -4.409146e+04 5.192054e+02
210 1.867601e+04 -4.409146e+04
211 -3.493542e+04 1.867601e+04
212 7.457080e+04 -3.493542e+04
213 4.212570e+04 7.457080e+04
214 5.186062e+03 4.212570e+04
215 -5.519351e+04 5.186062e+03
216 1.075267e+03 -5.519351e+04
217 1.157316e+04 1.075267e+03
218 8.151198e+04 1.157316e+04
219 1.242864e+04 8.151198e+04
220 1.857887e+04 1.242864e+04
221 2.131678e+04 1.857887e+04
222 1.411716e+04 2.131678e+04
223 -1.497933e+04 1.411716e+04
224 -7.802539e+04 -1.497933e+04
225 -2.695535e+04 -7.802539e+04
226 6.462259e+04 -2.695535e+04
227 3.289453e+03 6.462259e+04
228 2.276458e+04 3.289453e+03
229 3.935726e+04 2.276458e+04
230 1.287910e+04 3.935726e+04
231 2.222493e+04 1.287910e+04
232 6.975112e+04 2.222493e+04
233 -1.038344e+04 6.975112e+04
234 -2.560775e+04 -1.038344e+04
235 -3.040573e+02 -2.560775e+04
236 2.269437e+03 -3.040573e+02
237 -3.294900e+04 2.269437e+03
238 -6.737211e+04 -3.294900e+04
239 -1.336195e+04 -6.737211e+04
240 7.151224e+04 -1.336195e+04
241 -2.809779e+04 7.151224e+04
242 5.689720e+04 -2.809779e+04
243 -1.359210e+03 5.689720e+04
244 -5.794073e+04 -1.359210e+03
245 4.150986e+03 -5.794073e+04
246 -1.200065e+04 4.150986e+03
247 4.750477e+04 -1.200065e+04
248 1.917070e+04 4.750477e+04
249 9.123802e+03 1.917070e+04
250 5.915192e+04 9.123802e+03
251 -8.132014e+03 5.915192e+04
252 -1.651009e+04 -8.132014e+03
253 -2.757711e+03 -1.651009e+04
254 3.004468e+04 -2.757711e+03
255 4.621674e+04 3.004468e+04
256 7.321720e+03 4.621674e+04
257 6.016654e+04 7.321720e+03
258 6.836446e+04 6.016654e+04
259 -6.527575e+03 6.836446e+04
260 -3.824524e+04 -6.527575e+03
261 -6.082242e+03 -3.824524e+04
262 1.154182e+03 -6.082242e+03
263 -4.524611e+04 1.154182e+03
264 -1.198432e+04 -4.524611e+04
265 -2.445906e+04 -1.198432e+04
266 -1.924645e+04 -2.445906e+04
267 4.680019e+04 -1.924645e+04
268 -2.765814e+04 4.680019e+04
269 3.601947e+04 -2.765814e+04
270 -3.047441e+04 3.601947e+04
271 4.212927e+04 -3.047441e+04
272 5.336494e+03 4.212927e+04
273 3.467970e+04 5.336494e+03
274 -4.620660e+04 3.467970e+04
275 7.084178e+03 -4.620660e+04
276 -4.070521e+04 7.084178e+03
277 7.341983e+04 -4.070521e+04
278 1.276924e+04 7.341983e+04
279 -4.992840e+04 1.276924e+04
280 -3.524868e+04 -4.992840e+04
281 1.356397e+03 -3.524868e+04
282 -2.678528e+04 1.356397e+03
283 -2.261959e+03 -2.678528e+04
284 1.688406e+04 -2.261959e+03
285 -2.039793e+04 1.688406e+04
286 9.818793e+04 -2.039793e+04
287 -8.397572e+04 9.818793e+04
288 -4.740038e+03 -8.397572e+04
> 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/7w4os1323953652.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/8bcko1323953652.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/9k0t11323953652.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/10p8xb1323953652.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11edy71323953652.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/125ggv1323953652.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13cqen1323953652.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/145ux11323953652.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/15zlta1323953652.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/16yezj1323953652.tab")
+ }
>
> try(system("convert tmp/1c7f51323953651.ps tmp/1c7f51323953651.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gpfw1323953651.ps tmp/2gpfw1323953651.png",intern=TRUE))
character(0)
> try(system("convert tmp/3m5fn1323953651.ps tmp/3m5fn1323953651.png",intern=TRUE))
character(0)
> try(system("convert tmp/4tsh91323953651.ps tmp/4tsh91323953651.png",intern=TRUE))
character(0)
> try(system("convert tmp/5pw9i1323953651.ps tmp/5pw9i1323953651.png",intern=TRUE))
character(0)
> try(system("convert tmp/6aeg91323953651.ps tmp/6aeg91323953651.png",intern=TRUE))
character(0)
> try(system("convert tmp/7w4os1323953652.ps tmp/7w4os1323953652.png",intern=TRUE))
character(0)
> try(system("convert tmp/8bcko1323953652.ps tmp/8bcko1323953652.png",intern=TRUE))
character(0)
> try(system("convert tmp/9k0t11323953652.ps tmp/9k0t11323953652.png",intern=TRUE))
character(0)
> try(system("convert tmp/10p8xb1323953652.ps tmp/10p8xb1323953652.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
8.508 0.669 9.190