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(210907
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+ ,dimnames=list(c('time_in_rfc'
+ ,'logins'
+ ,'feedback_messages_p1'
+ ,'totsize'
+ ,'totblogs')
+ ,1:289))
> y <- array(NA,dim=c(5,289),dimnames=list(c('time_in_rfc','logins','feedback_messages_p1','totsize','totblogs'),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 = '5'
> 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
totblogs time_in_rfc logins feedback_messages_p1 totsize
1 145 210907 56 115 112285
2 101 120982 56 109 84786
3 98 176508 54 146 83123
4 132 179321 89 116 101193
5 60 123185 40 68 38361
6 38 52746 25 101 68504
7 144 385534 92 96 119182
8 5 33170 18 67 22807
9 28 101645 63 44 17140
10 84 149061 44 100 116174
11 79 165446 33 93 57635
12 127 237213 84 140 66198
13 78 173326 88 166 71701
14 60 133131 55 99 57793
15 131 258873 60 139 80444
16 84 180083 66 130 53855
17 133 324799 154 181 97668
18 150 230964 53 116 133824
19 91 236785 119 116 101481
20 132 135473 41 88 99645
21 136 202925 61 139 114789
22 124 215147 58 135 99052
23 118 344297 75 108 67654
24 70 153935 33 89 65553
25 107 132943 40 156 97500
26 119 174724 92 129 69112
27 89 174415 100 118 82753
28 112 225548 112 118 85323
29 108 223632 73 125 72654
30 52 124817 40 95 30727
31 112 221698 45 126 77873
32 116 210767 60 135 117478
33 123 170266 62 154 74007
34 125 260561 75 165 90183
35 27 84853 31 113 61542
36 162 294424 77 127 101494
37 32 101011 34 52 27570
38 64 215641 46 121 55813
39 92 325107 99 136 79215
40 0 7176 17 0 1423
41 83 167542 66 108 55461
42 41 106408 30 46 31081
43 47 96560 76 54 22996
44 120 265769 146 124 83122
45 105 269651 67 115 70106
46 79 149112 56 128 60578
47 65 175824 107 80 39992
48 70 152871 58 97 79892
49 55 111665 34 104 49810
50 39 116408 61 59 71570
51 67 362301 119 125 100708
52 21 78800 42 82 33032
53 127 183167 66 149 82875
54 152 277965 89 149 139077
55 113 150629 44 122 71595
56 99 168809 66 118 72260
57 7 24188 24 12 5950
58 141 329267 259 144 115762
59 21 65029 17 67 32551
60 35 101097 64 52 31701
61 109 218946 41 108 80670
62 133 244052 68 166 143558
63 123 341570 168 80 117105
64 26 103597 43 60 23789
65 230 233328 132 107 120733
66 166 256462 105 127 105195
67 68 206161 71 107 73107
68 147 311473 112 146 132068
69 179 235800 94 84 149193
70 61 177939 82 141 46821
71 101 207176 70 123 87011
72 108 196553 57 111 95260
73 90 174184 53 98 55183
74 114 143246 103 105 106671
75 103 187559 121 135 73511
76 142 187681 62 107 92945
77 79 119016 52 85 78664
78 88 182192 52 155 70054
79 25 73566 32 88 22618
80 83 194979 62 155 74011
81 113 167488 45 104 83737
82 118 143756 46 132 69094
83 110 275541 63 127 93133
84 129 243199 75 108 95536
85 51 182999 88 129 225920
86 93 135649 46 116 62133
87 76 152299 53 122 61370
88 49 120221 37 85 43836
89 118 346485 90 147 106117
90 38 145790 63 99 38692
91 141 193339 78 87 84651
92 58 80953 25 28 56622
93 27 122774 45 90 15986
94 91 130585 46 109 95364
95 48 112611 41 78 26706
96 63 286468 144 111 89691
97 56 241066 82 158 67267
98 144 148446 91 141 126846
99 73 204713 71 122 41140
100 168 182079 63 124 102860
101 64 140344 53 93 51715
102 97 220516 62 124 55801
103 117 243060 63 112 111813
104 100 162765 32 108 120293
105 149 182613 39 99 138599
106 187 232138 62 117 161647
107 127 265318 117 199 115929
108 37 85574 34 78 24266
109 245 310839 92 91 162901
110 87 225060 93 158 109825
111 177 232317 54 126 129838
112 49 144966 144 122 37510
113 49 43287 14 71 43750
114 73 155754 61 75 40652
115 177 164709 109 115 87771
116 94 201940 38 119 85872
117 117 235454 73 124 89275
118 60 220801 75 72 44418
119 55 99466 50 91 192565
120 39 92661 61 45 35232
121 64 133328 55 78 40909
122 26 61361 77 39 13294
123 64 125930 75 68 32387
124 58 100750 72 119 140867
125 95 224549 50 117 120662
126 25 82316 32 39 21233
127 26 102010 53 50 44332
128 76 101523 42 88 61056
129 129 243511 71 155 101338
130 11 22938 10 0 1168
131 2 41566 35 36 13497
132 101 152474 65 123 65567
133 28 61857 25 32 25162
134 36 99923 66 99 32334
135 89 132487 41 136 40735
136 193 317394 86 117 91413
137 4 21054 16 0 855
138 84 209641 42 88 97068
139 23 22648 19 39 44339
140 39 31414 19 25 14116
141 14 46698 45 52 10288
142 78 131698 65 75 65622
143 14 91735 35 71 16563
144 101 244749 95 124 76643
145 82 184510 49 151 110681
146 24 79863 37 71 29011
147 36 128423 64 145 92696
148 75 97839 38 87 94785
149 16 38214 34 27 8773
150 55 151101 32 131 83209
151 131 272458 65 162 93815
152 131 172494 52 165 86687
153 39 108043 62 54 34553
154 144 328107 65 159 105547
155 139 250579 83 147 103487
156 211 351067 95 170 213688
157 78 158015 29 119 71220
158 50 98866 18 49 23517
159 39 85439 33 104 56926
160 90 229242 247 120 91721
161 166 351619 139 150 115168
162 12 84207 29 112 111194
163 57 120445 118 59 51009
164 133 324598 110 136 135777
165 69 131069 67 107 51513
166 119 204271 42 130 74163
167 119 165543 65 115 51633
168 65 141722 94 107 75345
169 61 116048 64 75 33416
170 49 250047 81 71 83305
171 101 299775 95 120 98952
172 196 195838 67 116 102372
173 15 173260 63 79 37238
174 136 254488 83 150 103772
175 89 104389 45 156 123969
176 40 136084 30 51 27142
177 123 199476 70 118 135400
178 21 92499 32 71 21399
179 163 224330 83 144 130115
180 29 135781 31 47 24874
181 35 74408 67 28 34988
182 13 81240 66 68 45549
183 5 14688 10 0 6023
184 96 181633 70 110 64466
185 151 271856 103 147 54990
186 6 7199 5 0 1644
187 13 46660 20 15 6179
188 3 17547 5 4 3926
189 56 133368 36 64 32755
190 23 95227 34 111 34777
191 57 152601 48 85 73224
192 14 98146 40 68 27114
193 43 79619 43 40 20760
194 20 59194 31 80 37636
195 72 139942 42 88 65461
196 87 118612 46 48 30080
197 21 72880 33 76 24094
198 56 65475 18 51 69008
199 59 99643 55 67 54968
200 82 71965 35 59 46090
201 43 77272 59 61 27507
202 25 49289 19 76 10672
203 38 135131 66 60 34029
204 25 108446 60 68 46300
205 38 89746 36 71 24760
206 12 44296 25 76 18779
207 29 77648 47 62 21280
208 47 181528 54 61 40662
209 45 134019 53 67 28987
210 40 124064 40 88 22827
211 30 92630 40 30 18513
212 41 121848 39 64 30594
213 25 52915 14 68 24006
214 23 81872 45 64 27913
215 14 58981 36 91 42744
216 16 53515 28 88 12934
217 26 60812 44 52 22574
218 21 56375 30 49 41385
219 27 65490 22 62 18653
220 9 80949 17 61 18472
221 33 76302 31 76 30976
222 42 104011 55 88 63339
223 68 98104 54 66 25568
224 32 67989 21 71 33747
225 6 30989 14 68 4154
226 67 135458 81 48 19474
227 33 73504 35 25 35130
228 77 63123 43 68 39067
229 46 61254 46 41 13310
230 30 74914 30 90 65892
231 0 31774 23 66 4143
232 36 81437 38 54 28579
233 46 87186 54 59 51776
234 18 50090 20 60 21152
235 48 65745 53 77 38084
236 29 56653 45 68 27717
237 28 158399 39 72 32928
238 34 46455 20 67 11342
239 33 73624 24 64 19499
240 34 38395 31 63 16380
241 33 91899 35 59 36874
242 80 139526 151 84 48259
243 32 52164 52 64 16734
244 30 51567 30 56 28207
245 41 70551 31 54 30143
246 41 84856 29 67 41369
247 51 102538 57 58 45833
248 18 86678 40 59 29156
249 34 85709 44 40 35944
250 31 34662 25 22 36278
251 39 150580 77 83 45588
252 54 99611 35 81 45097
253 14 19349 11 2 3895
254 24 99373 63 72 28394
255 24 86230 44 61 18632
256 8 30837 19 15 2325
257 26 31706 13 32 25139
258 19 89806 42 62 27975
259 11 62088 38 58 14483
260 14 40151 29 36 13127
261 1 27634 20 59 5839
262 39 76990 27 68 24069
263 5 37460 20 21 3738
264 37 54157 19 55 18625
265 32 49862 37 54 36341
266 38 84337 26 55 24548
267 47 64175 42 72 21792
268 47 59382 49 41 26263
269 37 119308 30 61 23686
270 51 76702 49 67 49303
271 45 103425 67 76 25659
272 21 70344 28 64 28904
273 1 43410 19 3 2781
274 42 104838 49 63 29236
275 26 62215 27 40 19546
276 21 69304 30 69 22818
277 4 53117 22 48 32689
278 10 19764 12 8 5752
279 43 86680 31 52 22197
280 34 84105 20 66 20055
281 31 77945 20 76 25272
282 19 89113 39 43 82206
283 34 91005 29 39 32073
284 6 40248 16 14 5444
285 11 64187 27 61 20154
286 24 50857 21 71 36944
287 16 56613 19 44 8019
288 72 62792 35 60 30884
289 21 72535 14 64 19540
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time_in_rfc logins
-6.3606027 0.0002701 -0.0098632
feedback_messages_p1 totsize
0.1055117 0.0004805
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-113.36 -12.47 -0.17 10.10 105.34
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -6.361e+00 3.609e+00 -1.763 0.0790 .
time_in_rfc 2.701e-04 3.505e-05 7.706 2.18e-13 ***
logins -9.863e-03 6.150e-02 -0.160 0.8727
feedback_messages_p1 1.055e-01 6.066e-02 1.739 0.0831 .
totsize 4.805e-04 5.853e-05 8.209 7.90e-15 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 24.68 on 284 degrees of freedom
Multiple R-squared: 0.7478, Adjusted R-squared: 0.7443
F-statistic: 210.6 on 4 and 284 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.499663480 9.993270e-01 5.003365e-01
[2,] 0.338082781 6.761656e-01 6.619172e-01
[3,] 0.323884573 6.477691e-01 6.761154e-01
[4,] 0.261130763 5.222615e-01 7.388692e-01
[5,] 0.169470259 3.389405e-01 8.305297e-01
[6,] 0.333022206 6.660444e-01 6.669778e-01
[7,] 0.254747092 5.094942e-01 7.452529e-01
[8,] 0.204242132 4.084843e-01 7.957579e-01
[9,] 0.141915243 2.838305e-01 8.580848e-01
[10,] 0.144004772 2.880095e-01 8.559952e-01
[11,] 0.105967763 2.119355e-01 8.940322e-01
[12,] 0.108587441 2.171749e-01 8.914126e-01
[13,] 0.197117035 3.942341e-01 8.028830e-01
[14,] 0.150273045 3.005461e-01 8.497270e-01
[15,] 0.109607239 2.192145e-01 8.903928e-01
[16,] 0.081432411 1.628648e-01 9.185676e-01
[17,] 0.062506433 1.250129e-01 9.374936e-01
[18,] 0.043524906 8.704981e-02 9.564751e-01
[19,] 0.069526846 1.390537e-01 9.304732e-01
[20,] 0.049951513 9.990303e-02 9.500485e-01
[21,] 0.035833891 7.166778e-02 9.641661e-01
[22,] 0.024978207 4.995641e-02 9.750218e-01
[23,] 0.016742536 3.348507e-02 9.832575e-01
[24,] 0.011089280 2.217856e-02 9.889107e-01
[25,] 0.009493713 1.898743e-02 9.905063e-01
[26,] 0.010548853 2.109771e-02 9.894511e-01
[27,] 0.007279504 1.455901e-02 9.927205e-01
[28,] 0.018626170 3.725234e-02 9.813738e-01
[29,] 0.019501803 3.900361e-02 9.804982e-01
[30,] 0.013601873 2.720375e-02 9.863981e-01
[31,] 0.017107661 3.421532e-02 9.828923e-01
[32,] 0.031600926 6.320185e-02 9.683991e-01
[33,] 0.024888857 4.977771e-02 9.751111e-01
[34,] 0.018724479 3.744896e-02 9.812755e-01
[35,] 0.013378900 2.675780e-02 9.866211e-01
[36,] 0.011257274 2.251455e-02 9.887427e-01
[37,] 0.007954554 1.590911e-02 9.920454e-01
[38,] 0.005522037 1.104407e-02 9.944780e-01
[39,] 0.003765996 7.531992e-03 9.962340e-01
[40,] 0.002539144 5.078287e-03 9.974609e-01
[41,] 0.002293871 4.587742e-03 9.977061e-01
[42,] 0.001562572 3.125144e-03 9.984374e-01
[43,] 0.002280077 4.560154e-03 9.977199e-01
[44,] 0.063248871 1.264977e-01 9.367511e-01
[45,] 0.059149154 1.182983e-01 9.408508e-01
[46,] 0.059779618 1.195592e-01 9.402204e-01
[47,] 0.047353935 9.470787e-02 9.526461e-01
[48,] 0.051374180 1.027484e-01 9.486258e-01
[49,] 0.042538177 8.507635e-02 9.574618e-01
[50,] 0.034084658 6.816932e-02 9.659153e-01
[51,] 0.026949106 5.389821e-02 9.730509e-01
[52,] 0.023305142 4.661028e-02 9.766949e-01
[53,] 0.017832489 3.566498e-02 9.821675e-01
[54,] 0.013910415 2.782083e-02 9.860896e-01
[55,] 0.014257405 2.851481e-02 9.857426e-01
[56,] 0.012259058 2.451812e-02 9.877409e-01
[57,] 0.009665209 1.933042e-02 9.903348e-01
[58,] 0.339723122 6.794462e-01 6.602769e-01
[59,] 0.394563426 7.891269e-01 6.054366e-01
[60,] 0.400055451 8.001109e-01 5.999445e-01
[61,] 0.371161810 7.423236e-01 6.288382e-01
[62,] 0.390728989 7.814580e-01 6.092710e-01
[63,] 0.364107062 7.282141e-01 6.358929e-01
[64,] 0.328490020 6.569800e-01 6.715100e-01
[65,] 0.293529184 5.870584e-01 7.064708e-01
[66,] 0.275857519 5.517150e-01 7.241425e-01
[67,] 0.252210053 5.044201e-01 7.477899e-01
[68,] 0.224875179 4.497504e-01 7.751248e-01
[69,] 0.269273113 5.385462e-01 7.307269e-01
[70,] 0.240470677 4.809414e-01 7.595293e-01
[71,] 0.212259544 4.245191e-01 7.877405e-01
[72,] 0.186947546 3.738951e-01 8.130525e-01
[73,] 0.171209769 3.424195e-01 8.287902e-01
[74,] 0.162667929 3.253359e-01 8.373321e-01
[75,] 0.194213079 3.884262e-01 8.057869e-01
[76,] 0.176072118 3.521442e-01 8.239279e-01
[77,] 0.158374617 3.167492e-01 8.416254e-01
[78,] 0.940890598 1.182188e-01 5.910940e-02
[79,] 0.936190652 1.276187e-01 6.380935e-02
[80,] 0.924315426 1.513691e-01 7.568457e-02
[81,] 0.911985900 1.760282e-01 8.801410e-02
[82,] 0.921655674 1.566887e-01 7.834433e-02
[83,] 0.921428789 1.571424e-01 7.857121e-02
[84,] 0.947902565 1.041949e-01 5.209744e-02
[85,] 0.939762658 1.204747e-01 6.023734e-02
[86,] 0.934294119 1.314118e-01 6.570588e-02
[87,] 0.922484379 1.550312e-01 7.751562e-02
[88,] 0.908731798 1.825364e-01 9.126820e-02
[89,] 0.961329623 7.734075e-02 3.867038e-02
[90,] 0.979368023 4.126395e-02 2.063198e-02
[91,] 0.982564283 3.487143e-02 1.743572e-02
[92,] 0.978924308 4.215138e-02 2.107569e-02
[93,] 0.993502830 1.299434e-02 6.497170e-03
[94,] 0.991740858 1.651828e-02 8.259142e-03
[95,] 0.989682704 2.063459e-02 1.031730e-02
[96,] 0.987326575 2.534685e-02 1.267343e-02
[97,] 0.984683483 3.063303e-02 1.531652e-02
[98,] 0.985689996 2.862001e-02 1.431000e-02
[99,] 0.990259607 1.948079e-02 9.740393e-03
[100,] 0.988632932 2.273414e-02 1.136707e-02
[101,] 0.985792264 2.841547e-02 1.420774e-02
[102,] 0.998794719 2.410561e-03 1.205281e-03
[103,] 0.999131614 1.736772e-03 8.683861e-04
[104,] 0.999623064 7.538727e-04 3.769364e-04
[105,] 0.999571636 8.567277e-04 4.283639e-04
[106,] 0.999494837 1.010326e-03 5.051628e-04
[107,] 0.999348750 1.302499e-03 6.512495e-04
[108,] 0.999987049 2.590108e-05 1.295054e-05
[109,] 0.999981802 3.639622e-05 1.819811e-05
[110,] 0.999974205 5.159049e-05 2.579524e-05
[111,] 0.999973834 5.233187e-05 2.616594e-05
[112,] 0.999997552 4.895787e-06 2.447893e-06
[113,] 0.999996348 7.303308e-06 3.651654e-06
[114,] 0.999994695 1.061050e-05 5.305249e-06
[115,] 0.999992243 1.551444e-05 7.757221e-06
[116,] 0.999989720 2.055902e-05 1.027951e-05
[117,] 0.999994090 1.181961e-05 5.909806e-06
[118,] 0.999994491 1.101752e-05 5.508760e-06
[119,] 0.999992088 1.582312e-05 7.911559e-06
[120,] 0.999991388 1.722378e-05 8.611891e-06
[121,] 0.999989811 2.037707e-05 1.018853e-05
[122,] 0.999985520 2.895922e-05 1.447961e-05
[123,] 0.999980273 3.945304e-05 1.972652e-05
[124,] 0.999974762 5.047572e-05 2.523786e-05
[125,] 0.999973641 5.271710e-05 2.635855e-05
[126,] 0.999962476 7.504821e-05 3.752411e-05
[127,] 0.999950352 9.929501e-05 4.964750e-05
[128,] 0.999952254 9.549286e-05 4.774643e-05
[129,] 0.999992493 1.501488e-05 7.507439e-06
[130,] 0.999989076 2.184703e-05 1.092352e-05
[131,] 0.999987411 2.517797e-05 1.258899e-05
[132,] 0.999981889 3.622169e-05 1.811085e-05
[133,] 0.999983904 3.219174e-05 1.609587e-05
[134,] 0.999976886 4.622700e-05 2.311350e-05
[135,] 0.999969521 6.095873e-05 3.047936e-05
[136,] 0.999966594 6.681203e-05 3.340602e-05
[137,] 0.999953765 9.247013e-05 4.623507e-05
[138,] 0.999957861 8.427820e-05 4.213910e-05
[139,] 0.999945611 1.087786e-04 5.438930e-05
[140,] 0.999984418 3.116383e-05 1.558191e-05
[141,] 0.999977908 4.418391e-05 2.209196e-05
[142,] 0.999968690 6.261997e-05 3.130998e-05
[143,] 0.999976644 4.671141e-05 2.335571e-05
[144,] 0.999966408 6.718362e-05 3.359181e-05
[145,] 0.999975376 4.924895e-05 2.462448e-05
[146,] 0.999965192 6.961664e-05 3.480832e-05
[147,] 0.999950480 9.904040e-05 4.952020e-05
[148,] 0.999939219 1.215623e-04 6.078114e-05
[149,] 0.999927179 1.456425e-04 7.282123e-05
[150,] 0.999897860 2.042796e-04 1.021398e-04
[151,] 0.999873556 2.528871e-04 1.264436e-04
[152,] 0.999844136 3.117289e-04 1.558644e-04
[153,] 0.999878247 2.435065e-04 1.217533e-04
[154,] 0.999837264 3.254716e-04 1.627358e-04
[155,] 0.999986415 2.716994e-05 1.358497e-05
[156,] 0.999980636 3.872894e-05 1.936447e-05
[157,] 0.999980423 3.915393e-05 1.957697e-05
[158,] 0.999971573 5.685495e-05 2.842747e-05
[159,] 0.999974663 5.067318e-05 2.533659e-05
[160,] 0.999991750 1.650074e-05 8.250370e-06
[161,] 0.999990631 1.873775e-05 9.368876e-06
[162,] 0.999987300 2.539924e-05 1.269962e-05
[163,] 0.999998397 3.205860e-06 1.602930e-06
[164,] 0.999999068 1.864178e-06 9.320889e-07
[165,] 1.000000000 5.811120e-10 2.905560e-10
[166,] 1.000000000 3.053172e-11 1.526586e-11
[167,] 1.000000000 4.547154e-11 2.273577e-11
[168,] 1.000000000 8.212964e-11 4.106482e-11
[169,] 1.000000000 1.446209e-10 7.231043e-11
[170,] 1.000000000 2.522569e-10 1.261284e-10
[171,] 1.000000000 3.605425e-10 1.802713e-10
[172,] 1.000000000 3.862991e-11 1.931495e-11
[173,] 1.000000000 4.992729e-11 2.496365e-11
[174,] 1.000000000 8.989351e-11 4.494676e-11
[175,] 1.000000000 2.985608e-11 1.492804e-11
[176,] 1.000000000 5.661076e-11 2.830538e-11
[177,] 1.000000000 6.562373e-11 3.281186e-11
[178,] 1.000000000 8.363632e-13 4.181816e-13
[179,] 1.000000000 1.663369e-12 8.316844e-13
[180,] 1.000000000 3.229779e-12 1.614889e-12
[181,] 1.000000000 6.047795e-12 3.023897e-12
[182,] 1.000000000 8.276713e-12 4.138356e-12
[183,] 1.000000000 1.158609e-11 5.793043e-12
[184,] 1.000000000 2.040346e-11 1.020173e-11
[185,] 1.000000000 1.644637e-11 8.223186e-12
[186,] 1.000000000 2.669925e-11 1.334962e-11
[187,] 1.000000000 3.945186e-11 1.972593e-11
[188,] 1.000000000 4.614026e-11 2.307013e-11
[189,] 1.000000000 1.383028e-12 6.915141e-13
[190,] 1.000000000 2.412287e-12 1.206143e-12
[191,] 1.000000000 2.530671e-12 1.265336e-12
[192,] 1.000000000 4.087624e-12 2.043812e-12
[193,] 1.000000000 6.058753e-14 3.029376e-14
[194,] 1.000000000 1.295023e-13 6.475114e-14
[195,] 1.000000000 2.728100e-13 1.364050e-13
[196,] 1.000000000 4.551580e-13 2.275790e-13
[197,] 1.000000000 2.941809e-13 1.470905e-13
[198,] 1.000000000 6.075253e-13 3.037626e-13
[199,] 1.000000000 9.757309e-13 4.878655e-13
[200,] 1.000000000 1.985483e-12 9.927417e-13
[201,] 1.000000000 3.879233e-12 1.939616e-12
[202,] 1.000000000 8.302233e-12 4.151116e-12
[203,] 1.000000000 1.738752e-11 8.693761e-12
[204,] 1.000000000 3.675440e-11 1.837720e-11
[205,] 1.000000000 7.444805e-11 3.722403e-11
[206,] 1.000000000 1.492546e-10 7.462730e-11
[207,] 1.000000000 2.185929e-10 1.092965e-10
[208,] 1.000000000 1.611310e-10 8.056548e-11
[209,] 1.000000000 2.602978e-10 1.301489e-10
[210,] 1.000000000 4.937670e-10 2.468835e-10
[211,] 1.000000000 8.284713e-10 4.142356e-10
[212,] 0.999999999 1.675529e-09 8.377643e-10
[213,] 0.999999999 2.140732e-09 1.070366e-09
[214,] 0.999999998 4.339771e-09 2.169886e-09
[215,] 0.999999997 6.891332e-09 3.445666e-09
[216,] 0.999999999 2.770757e-09 1.385379e-09
[217,] 0.999999997 5.570713e-09 2.785357e-09
[218,] 0.999999996 8.671407e-09 4.335703e-09
[219,] 0.999999997 6.428509e-09 3.214255e-09
[220,] 0.999999994 1.256521e-08 6.282606e-09
[221,] 1.000000000 6.942271e-10 3.471135e-10
[222,] 1.000000000 6.141536e-10 3.070768e-10
[223,] 1.000000000 7.170653e-10 3.585327e-10
[224,] 1.000000000 4.235163e-10 2.117581e-10
[225,] 1.000000000 9.055707e-10 4.527853e-10
[226,] 0.999999999 1.986522e-09 9.932611e-10
[227,] 0.999999998 3.733558e-09 1.866779e-09
[228,] 0.999999996 7.714192e-09 3.857096e-09
[229,] 0.999999993 1.458846e-08 7.294231e-09
[230,] 0.999999988 2.371309e-08 1.185654e-08
[231,] 0.999999980 4.080695e-08 2.040347e-08
[232,] 0.999999959 8.121571e-08 4.060786e-08
[233,] 0.999999925 1.500914e-07 7.504571e-08
[234,] 0.999999844 3.122399e-07 1.561199e-07
[235,] 0.999999743 5.147654e-07 2.573827e-07
[236,] 0.999999476 1.047781e-06 5.238907e-07
[237,] 0.999998939 2.122034e-06 1.061017e-06
[238,] 0.999998371 3.258635e-06 1.629318e-06
[239,] 0.999996944 6.112970e-06 3.056485e-06
[240,] 0.999995268 9.463674e-06 4.731837e-06
[241,] 0.999993914 1.217234e-05 6.086168e-06
[242,] 0.999988282 2.343519e-05 1.171759e-05
[243,] 0.999982023 3.595486e-05 1.797743e-05
[244,] 0.999977654 4.469148e-05 2.234574e-05
[245,] 0.999968926 6.214722e-05 3.107361e-05
[246,] 0.999950956 9.808855e-05 4.904428e-05
[247,] 0.999959638 8.072376e-05 4.036188e-05
[248,] 0.999941338 1.173235e-04 5.866177e-05
[249,] 0.999886051 2.278973e-04 1.139487e-04
[250,] 0.999859944 2.801129e-04 1.400565e-04
[251,] 0.999878216 2.435688e-04 1.217844e-04
[252,] 0.999910688 1.786232e-04 8.931161e-05
[253,] 0.999833964 3.320725e-04 1.660362e-04
[254,] 0.999870362 2.592767e-04 1.296384e-04
[255,] 0.999755157 4.896860e-04 2.448430e-04
[256,] 0.999591956 8.160885e-04 4.080442e-04
[257,] 0.999472697 1.054606e-03 5.273029e-04
[258,] 0.998947337 2.105325e-03 1.052663e-03
[259,] 0.998325722 3.348557e-03 1.674278e-03
[260,] 0.996989055 6.021891e-03 3.010945e-03
[261,] 0.995534975 8.930049e-03 4.465025e-03
[262,] 0.991742294 1.651541e-02 8.257706e-03
[263,] 0.988025689 2.394862e-02 1.197431e-02
[264,] 0.985225055 2.954989e-02 1.477494e-02
[265,] 0.976852882 4.629424e-02 2.314712e-02
[266,] 0.963770683 7.245863e-02 3.622932e-02
[267,] 0.956792556 8.641489e-02 4.320744e-02
[268,] 0.925908512 1.481830e-01 7.409149e-02
[269,] 0.933460960 1.330781e-01 6.653904e-02
[270,] 0.915109210 1.697816e-01 8.489079e-02
[271,] 0.879963430 2.400731e-01 1.200366e-01
[272,] 0.792876698 4.142466e-01 2.071233e-01
[273,] 0.671630366 6.567393e-01 3.283696e-01
[274,] 0.504314998 9.913700e-01 4.956850e-01
> postscript(file="/var/wessaorg/rcomp/tmp/1eih91323805620.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/2x1381323805620.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3xoxm1323805620.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4yjx31323805620.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5rm0l1323805620.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
2.885916e+01 2.299548e+01 1.871819e+00 2.994060e+01 7.873934e+00
6 7 8 9 10
-1.321101e+01 -2.026606e+01 -1.544908e+01 -5.352573e+00 -1.583882e+01
11 12 13 14 15
3.490916e+00 2.353458e+01 -1.355571e+01 -7.271958e+00 1.470781e+01
16 17 18 19 20
2.774775e+00 -1.288032e+01 1.795751e+01 -2.642440e+01 4.500973e+01
21 22 23 24 25
1.832927e+01 1.098125e+01 -1.180353e+01 -5.781902e+00 1.453908e+01
26 27 28 29 30
3.225395e+01 -2.977006e+00 5.094219e+00 6.575487e+00 2.521071e-01
31 32 33 34 35
8.208709e+00 -4.668832e+00 3.217263e+01 9.772775e-01 -3.074594e+01
36 37 38 39 40
2.742469e+01 -7.322639e+00 -2.701876e+01 -4.089203e+01 3.906158e+00
41 42 43 44 45
6.712062e+00 -8.737871e-01 1.128055e+01 2.989254e+00 -6.635288e+00
46 47 48 49 50
3.023103e+00 -2.734165e+00 -1.298132e+01 -3.372604e+00 -2.609430e+01
51 52 53 54 55
-8.490773e+01 -1.803359e+01 2.899403e+01 1.610651e+00 3.183480e+01
56 57 58 59 60
1.324344e+01 2.938633e+00 -9.841124e+00 -1.274649e+01 -6.034756e+00
61 62 63 64 65
6.468005e+00 -1.238234e+01 -2.595454e+01 -1.295989e+01 1.053374e+02
66 67 68 69 70
4.017719e+01 -2.704331e+01 -8.529795e+00 4.204775e+01 -1.726934e+01
71 72 73 74 75
-2.695855e+00 4.348295e+00 1.297835e+01 2.035214e+01 1.032630e+01
76 77 78 79 80
4.232848e+01 6.960757e+00 -4.353773e+00 -8.347939e+00 -1.461042e+01
81 82 83 84 85
2.335607e+01 3.885762e+01 -1.559548e+01 1.310947e+01 -1.133608e+02
86 87 88 89 90
2.108020e+01 -6.148328e-01 -6.779221e+00 -3.484152e+01 -2.343530e+01
91 92 93 94 95
4.605309e+01 1.258073e+01 -1.653669e+01 5.220524e+00 3.284757e+00
96 97 98 99 100
-6.140630e+01 -5.093877e+01 3.533742e+01 -7.875966e+00 6.329413e+01
101 102 103 104 105
-1.686795e+00 4.511414e+00 -7.213844e+00 -6.482096e+00 2.937979e+01
106 107 108 109 110
4.125579e+01 -1.385079e+01 6.914329e-01 8.043331e+01 -3.595406e+01
111 112 113 114 115
4.546189e+01 -1.327267e+01 1.529428e+01 1.044401e+01 8.563919e+01
116 117 118 119 120
-7.627805e+00 4.501840e+00 -2.148166e+01 -6.713598e+01 -7.434870e-01
121 122 123 124 125
7.002664e+00 6.042673e+00 1.434792e+01 -4.238133e+01 -2.912091e+01
126 127 128 129 130
-4.876032e+00 -2.124755e+01 1.673085e+01 5.239054e+00 1.070191e+01
131 132 133 134 135
-1.280543e+01 2.233425e+01 2.432286e+00 -9.961082e+00 2.605568e+01
136 137 138 139 140
5.820730e+01 4.420388e+00 -2.177696e+01 -1.987894e+00 2.764230e+01
141 142 143 144 145
-2.239479e+00 9.984521e+00 -1.952338e+01 -7.722817e+00 -3.010713e+01
146 147 148 149 150
-1.227749e+01 -5.153448e+01 5.866066e-01 5.309464e+00 -3.294073e+01
151 152 153 154 155
2.236461e+00 3.221930e+01 -5.512074e+00 -5.116003e+00 1.325975e+01
156 157 158 159 160
2.859715e+00 -4.811587e+00 1.336281e+01 -1.571710e+01 -1.985711e+01
161 162 163 164 165
7.589766e+00 -6.934147e+01 1.256148e+00 -2.682184e+01 4.576597e+00
166 167 168 169 170
2.124707e+01 4.434280e+01 -1.348508e+01 1.267583e+01 -5.890074e+01
171 172 173 174 175
-3.288331e+01 8.869548e+01 -5.104684e+01 8.750358e+00 -8.415735e+00
176 177 178 179 180
-8.525070e+00 -1.337319e+00 -1.508285e+01 3.187312e+01 -1.792163e+01
181 182 183 184 185
2.157232e+00 -3.099274e+01 4.597812e+00 1.140760e+01 4.301042e+01
186 187 188 189 190
9.675405e+00 2.402350e+00 2.361685e+00 4.199296e+00 -2.444810e+01
191 192 193 194 195
-2.153717e+01 -2.595865e+01 1.408274e+01 -1.584701e+01 2.364525e-01
196 197 198 199 200
4.225732e+01 -1.159579e+01 6.314945e+00 5.507694e+00 4.089660e+01
201 202 203 204 205
9.417124e+00 5.087406e+00 -1.417110e+01 -2.676179e+01 1.085428e+00
206 207 208 209 210
-1.039977e+01 -1.916487e+00 -2.111490e+01 -5.315043e+00 -7.010270e+00
211 212 213 214 215
-3.267487e-01 -6.620989e+00 -1.503751e+00 -1.247514e+01 -2.535498e+01
216 217 218 219 220
-7.318319e+00 3.516526e-02 -1.262577e+01 3.832948e-01 -2.164942e+01
221 222 223 224 225
-3.846414e+00 -1.890989e+01 2.914460e+01 -3.503286e+00 -5.042872e+00
226 227 228 229 230
2.314775e+01 3.341141e-01 4.078862e+01 2.554711e+01 -2.473426e+01
231 232 233 234 235
-1.094984e+01 1.308451e+00 -1.759488e+00 -5.466139e+00 1.070167e+01
236 237 238 239 240
9.288227e-03 -3.145985e+01 1.549050e+01 3.588324e+00 1.577770e+01
241 242 243 244 245
-9.060172e+00 1.811083e+01 9.989868e+00 3.265916e+00 8.428560e+00
246 247 248 249 250
-2.220616e+00 2.084015e+00 -1.889234e+01 -3.847774e+00 8.492681e+00
251 252 253 254 255
-2.521619e+01 3.584535e+00 1.316001e+01 -1.710027e+01 -7.886527e+00
256 257 258 259 260
3.518384e+00 8.469546e+00 -1.846668e+01 -1.211436e+01 -3.046149e-01
261 262 263 264 265
-8.937391e+00 6.090919e+00 -2.572758e+00 1.416708e+01 2.098482e+00
266 267 268 269 270
4.237952e+00 1.837249e+01 2.085897e+01 -6.388083e+00 6.367282e+00
271 272 273 274 275
3.736641e+00 -1.200494e+01 -5.830860e+00 -1.695386e-01 2.209479e+00
276 277 278 279 280
-9.307759e+00 -2.454101e+01 7.532490e+00 1.010046e+01 1.239522e+00
281 282 283 284 285
-3.658180e+00 -4.236019e+01 -3.460935e+00 -2.446405e+00 -1.583107e+01
286 287 288 289
-8.411520e+00 -1.239962e+00 4.057483e+01 -8.235839e+00
> postscript(file="/var/wessaorg/rcomp/tmp/6bv7r1323805620.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 2.885916e+01 NA
1 2.299548e+01 2.885916e+01
2 1.871819e+00 2.299548e+01
3 2.994060e+01 1.871819e+00
4 7.873934e+00 2.994060e+01
5 -1.321101e+01 7.873934e+00
6 -2.026606e+01 -1.321101e+01
7 -1.544908e+01 -2.026606e+01
8 -5.352573e+00 -1.544908e+01
9 -1.583882e+01 -5.352573e+00
10 3.490916e+00 -1.583882e+01
11 2.353458e+01 3.490916e+00
12 -1.355571e+01 2.353458e+01
13 -7.271958e+00 -1.355571e+01
14 1.470781e+01 -7.271958e+00
15 2.774775e+00 1.470781e+01
16 -1.288032e+01 2.774775e+00
17 1.795751e+01 -1.288032e+01
18 -2.642440e+01 1.795751e+01
19 4.500973e+01 -2.642440e+01
20 1.832927e+01 4.500973e+01
21 1.098125e+01 1.832927e+01
22 -1.180353e+01 1.098125e+01
23 -5.781902e+00 -1.180353e+01
24 1.453908e+01 -5.781902e+00
25 3.225395e+01 1.453908e+01
26 -2.977006e+00 3.225395e+01
27 5.094219e+00 -2.977006e+00
28 6.575487e+00 5.094219e+00
29 2.521071e-01 6.575487e+00
30 8.208709e+00 2.521071e-01
31 -4.668832e+00 8.208709e+00
32 3.217263e+01 -4.668832e+00
33 9.772775e-01 3.217263e+01
34 -3.074594e+01 9.772775e-01
35 2.742469e+01 -3.074594e+01
36 -7.322639e+00 2.742469e+01
37 -2.701876e+01 -7.322639e+00
38 -4.089203e+01 -2.701876e+01
39 3.906158e+00 -4.089203e+01
40 6.712062e+00 3.906158e+00
41 -8.737871e-01 6.712062e+00
42 1.128055e+01 -8.737871e-01
43 2.989254e+00 1.128055e+01
44 -6.635288e+00 2.989254e+00
45 3.023103e+00 -6.635288e+00
46 -2.734165e+00 3.023103e+00
47 -1.298132e+01 -2.734165e+00
48 -3.372604e+00 -1.298132e+01
49 -2.609430e+01 -3.372604e+00
50 -8.490773e+01 -2.609430e+01
51 -1.803359e+01 -8.490773e+01
52 2.899403e+01 -1.803359e+01
53 1.610651e+00 2.899403e+01
54 3.183480e+01 1.610651e+00
55 1.324344e+01 3.183480e+01
56 2.938633e+00 1.324344e+01
57 -9.841124e+00 2.938633e+00
58 -1.274649e+01 -9.841124e+00
59 -6.034756e+00 -1.274649e+01
60 6.468005e+00 -6.034756e+00
61 -1.238234e+01 6.468005e+00
62 -2.595454e+01 -1.238234e+01
63 -1.295989e+01 -2.595454e+01
64 1.053374e+02 -1.295989e+01
65 4.017719e+01 1.053374e+02
66 -2.704331e+01 4.017719e+01
67 -8.529795e+00 -2.704331e+01
68 4.204775e+01 -8.529795e+00
69 -1.726934e+01 4.204775e+01
70 -2.695855e+00 -1.726934e+01
71 4.348295e+00 -2.695855e+00
72 1.297835e+01 4.348295e+00
73 2.035214e+01 1.297835e+01
74 1.032630e+01 2.035214e+01
75 4.232848e+01 1.032630e+01
76 6.960757e+00 4.232848e+01
77 -4.353773e+00 6.960757e+00
78 -8.347939e+00 -4.353773e+00
79 -1.461042e+01 -8.347939e+00
80 2.335607e+01 -1.461042e+01
81 3.885762e+01 2.335607e+01
82 -1.559548e+01 3.885762e+01
83 1.310947e+01 -1.559548e+01
84 -1.133608e+02 1.310947e+01
85 2.108020e+01 -1.133608e+02
86 -6.148328e-01 2.108020e+01
87 -6.779221e+00 -6.148328e-01
88 -3.484152e+01 -6.779221e+00
89 -2.343530e+01 -3.484152e+01
90 4.605309e+01 -2.343530e+01
91 1.258073e+01 4.605309e+01
92 -1.653669e+01 1.258073e+01
93 5.220524e+00 -1.653669e+01
94 3.284757e+00 5.220524e+00
95 -6.140630e+01 3.284757e+00
96 -5.093877e+01 -6.140630e+01
97 3.533742e+01 -5.093877e+01
98 -7.875966e+00 3.533742e+01
99 6.329413e+01 -7.875966e+00
100 -1.686795e+00 6.329413e+01
101 4.511414e+00 -1.686795e+00
102 -7.213844e+00 4.511414e+00
103 -6.482096e+00 -7.213844e+00
104 2.937979e+01 -6.482096e+00
105 4.125579e+01 2.937979e+01
106 -1.385079e+01 4.125579e+01
107 6.914329e-01 -1.385079e+01
108 8.043331e+01 6.914329e-01
109 -3.595406e+01 8.043331e+01
110 4.546189e+01 -3.595406e+01
111 -1.327267e+01 4.546189e+01
112 1.529428e+01 -1.327267e+01
113 1.044401e+01 1.529428e+01
114 8.563919e+01 1.044401e+01
115 -7.627805e+00 8.563919e+01
116 4.501840e+00 -7.627805e+00
117 -2.148166e+01 4.501840e+00
118 -6.713598e+01 -2.148166e+01
119 -7.434870e-01 -6.713598e+01
120 7.002664e+00 -7.434870e-01
121 6.042673e+00 7.002664e+00
122 1.434792e+01 6.042673e+00
123 -4.238133e+01 1.434792e+01
124 -2.912091e+01 -4.238133e+01
125 -4.876032e+00 -2.912091e+01
126 -2.124755e+01 -4.876032e+00
127 1.673085e+01 -2.124755e+01
128 5.239054e+00 1.673085e+01
129 1.070191e+01 5.239054e+00
130 -1.280543e+01 1.070191e+01
131 2.233425e+01 -1.280543e+01
132 2.432286e+00 2.233425e+01
133 -9.961082e+00 2.432286e+00
134 2.605568e+01 -9.961082e+00
135 5.820730e+01 2.605568e+01
136 4.420388e+00 5.820730e+01
137 -2.177696e+01 4.420388e+00
138 -1.987894e+00 -2.177696e+01
139 2.764230e+01 -1.987894e+00
140 -2.239479e+00 2.764230e+01
141 9.984521e+00 -2.239479e+00
142 -1.952338e+01 9.984521e+00
143 -7.722817e+00 -1.952338e+01
144 -3.010713e+01 -7.722817e+00
145 -1.227749e+01 -3.010713e+01
146 -5.153448e+01 -1.227749e+01
147 5.866066e-01 -5.153448e+01
148 5.309464e+00 5.866066e-01
149 -3.294073e+01 5.309464e+00
150 2.236461e+00 -3.294073e+01
151 3.221930e+01 2.236461e+00
152 -5.512074e+00 3.221930e+01
153 -5.116003e+00 -5.512074e+00
154 1.325975e+01 -5.116003e+00
155 2.859715e+00 1.325975e+01
156 -4.811587e+00 2.859715e+00
157 1.336281e+01 -4.811587e+00
158 -1.571710e+01 1.336281e+01
159 -1.985711e+01 -1.571710e+01
160 7.589766e+00 -1.985711e+01
161 -6.934147e+01 7.589766e+00
162 1.256148e+00 -6.934147e+01
163 -2.682184e+01 1.256148e+00
164 4.576597e+00 -2.682184e+01
165 2.124707e+01 4.576597e+00
166 4.434280e+01 2.124707e+01
167 -1.348508e+01 4.434280e+01
168 1.267583e+01 -1.348508e+01
169 -5.890074e+01 1.267583e+01
170 -3.288331e+01 -5.890074e+01
171 8.869548e+01 -3.288331e+01
172 -5.104684e+01 8.869548e+01
173 8.750358e+00 -5.104684e+01
174 -8.415735e+00 8.750358e+00
175 -8.525070e+00 -8.415735e+00
176 -1.337319e+00 -8.525070e+00
177 -1.508285e+01 -1.337319e+00
178 3.187312e+01 -1.508285e+01
179 -1.792163e+01 3.187312e+01
180 2.157232e+00 -1.792163e+01
181 -3.099274e+01 2.157232e+00
182 4.597812e+00 -3.099274e+01
183 1.140760e+01 4.597812e+00
184 4.301042e+01 1.140760e+01
185 9.675405e+00 4.301042e+01
186 2.402350e+00 9.675405e+00
187 2.361685e+00 2.402350e+00
188 4.199296e+00 2.361685e+00
189 -2.444810e+01 4.199296e+00
190 -2.153717e+01 -2.444810e+01
191 -2.595865e+01 -2.153717e+01
192 1.408274e+01 -2.595865e+01
193 -1.584701e+01 1.408274e+01
194 2.364525e-01 -1.584701e+01
195 4.225732e+01 2.364525e-01
196 -1.159579e+01 4.225732e+01
197 6.314945e+00 -1.159579e+01
198 5.507694e+00 6.314945e+00
199 4.089660e+01 5.507694e+00
200 9.417124e+00 4.089660e+01
201 5.087406e+00 9.417124e+00
202 -1.417110e+01 5.087406e+00
203 -2.676179e+01 -1.417110e+01
204 1.085428e+00 -2.676179e+01
205 -1.039977e+01 1.085428e+00
206 -1.916487e+00 -1.039977e+01
207 -2.111490e+01 -1.916487e+00
208 -5.315043e+00 -2.111490e+01
209 -7.010270e+00 -5.315043e+00
210 -3.267487e-01 -7.010270e+00
211 -6.620989e+00 -3.267487e-01
212 -1.503751e+00 -6.620989e+00
213 -1.247514e+01 -1.503751e+00
214 -2.535498e+01 -1.247514e+01
215 -7.318319e+00 -2.535498e+01
216 3.516526e-02 -7.318319e+00
217 -1.262577e+01 3.516526e-02
218 3.832948e-01 -1.262577e+01
219 -2.164942e+01 3.832948e-01
220 -3.846414e+00 -2.164942e+01
221 -1.890989e+01 -3.846414e+00
222 2.914460e+01 -1.890989e+01
223 -3.503286e+00 2.914460e+01
224 -5.042872e+00 -3.503286e+00
225 2.314775e+01 -5.042872e+00
226 3.341141e-01 2.314775e+01
227 4.078862e+01 3.341141e-01
228 2.554711e+01 4.078862e+01
229 -2.473426e+01 2.554711e+01
230 -1.094984e+01 -2.473426e+01
231 1.308451e+00 -1.094984e+01
232 -1.759488e+00 1.308451e+00
233 -5.466139e+00 -1.759488e+00
234 1.070167e+01 -5.466139e+00
235 9.288227e-03 1.070167e+01
236 -3.145985e+01 9.288227e-03
237 1.549050e+01 -3.145985e+01
238 3.588324e+00 1.549050e+01
239 1.577770e+01 3.588324e+00
240 -9.060172e+00 1.577770e+01
241 1.811083e+01 -9.060172e+00
242 9.989868e+00 1.811083e+01
243 3.265916e+00 9.989868e+00
244 8.428560e+00 3.265916e+00
245 -2.220616e+00 8.428560e+00
246 2.084015e+00 -2.220616e+00
247 -1.889234e+01 2.084015e+00
248 -3.847774e+00 -1.889234e+01
249 8.492681e+00 -3.847774e+00
250 -2.521619e+01 8.492681e+00
251 3.584535e+00 -2.521619e+01
252 1.316001e+01 3.584535e+00
253 -1.710027e+01 1.316001e+01
254 -7.886527e+00 -1.710027e+01
255 3.518384e+00 -7.886527e+00
256 8.469546e+00 3.518384e+00
257 -1.846668e+01 8.469546e+00
258 -1.211436e+01 -1.846668e+01
259 -3.046149e-01 -1.211436e+01
260 -8.937391e+00 -3.046149e-01
261 6.090919e+00 -8.937391e+00
262 -2.572758e+00 6.090919e+00
263 1.416708e+01 -2.572758e+00
264 2.098482e+00 1.416708e+01
265 4.237952e+00 2.098482e+00
266 1.837249e+01 4.237952e+00
267 2.085897e+01 1.837249e+01
268 -6.388083e+00 2.085897e+01
269 6.367282e+00 -6.388083e+00
270 3.736641e+00 6.367282e+00
271 -1.200494e+01 3.736641e+00
272 -5.830860e+00 -1.200494e+01
273 -1.695386e-01 -5.830860e+00
274 2.209479e+00 -1.695386e-01
275 -9.307759e+00 2.209479e+00
276 -2.454101e+01 -9.307759e+00
277 7.532490e+00 -2.454101e+01
278 1.010046e+01 7.532490e+00
279 1.239522e+00 1.010046e+01
280 -3.658180e+00 1.239522e+00
281 -4.236019e+01 -3.658180e+00
282 -3.460935e+00 -4.236019e+01
283 -2.446405e+00 -3.460935e+00
284 -1.583107e+01 -2.446405e+00
285 -8.411520e+00 -1.583107e+01
286 -1.239962e+00 -8.411520e+00
287 4.057483e+01 -1.239962e+00
288 -8.235839e+00 4.057483e+01
289 NA -8.235839e+00
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.299548e+01 2.885916e+01
[2,] 1.871819e+00 2.299548e+01
[3,] 2.994060e+01 1.871819e+00
[4,] 7.873934e+00 2.994060e+01
[5,] -1.321101e+01 7.873934e+00
[6,] -2.026606e+01 -1.321101e+01
[7,] -1.544908e+01 -2.026606e+01
[8,] -5.352573e+00 -1.544908e+01
[9,] -1.583882e+01 -5.352573e+00
[10,] 3.490916e+00 -1.583882e+01
[11,] 2.353458e+01 3.490916e+00
[12,] -1.355571e+01 2.353458e+01
[13,] -7.271958e+00 -1.355571e+01
[14,] 1.470781e+01 -7.271958e+00
[15,] 2.774775e+00 1.470781e+01
[16,] -1.288032e+01 2.774775e+00
[17,] 1.795751e+01 -1.288032e+01
[18,] -2.642440e+01 1.795751e+01
[19,] 4.500973e+01 -2.642440e+01
[20,] 1.832927e+01 4.500973e+01
[21,] 1.098125e+01 1.832927e+01
[22,] -1.180353e+01 1.098125e+01
[23,] -5.781902e+00 -1.180353e+01
[24,] 1.453908e+01 -5.781902e+00
[25,] 3.225395e+01 1.453908e+01
[26,] -2.977006e+00 3.225395e+01
[27,] 5.094219e+00 -2.977006e+00
[28,] 6.575487e+00 5.094219e+00
[29,] 2.521071e-01 6.575487e+00
[30,] 8.208709e+00 2.521071e-01
[31,] -4.668832e+00 8.208709e+00
[32,] 3.217263e+01 -4.668832e+00
[33,] 9.772775e-01 3.217263e+01
[34,] -3.074594e+01 9.772775e-01
[35,] 2.742469e+01 -3.074594e+01
[36,] -7.322639e+00 2.742469e+01
[37,] -2.701876e+01 -7.322639e+00
[38,] -4.089203e+01 -2.701876e+01
[39,] 3.906158e+00 -4.089203e+01
[40,] 6.712062e+00 3.906158e+00
[41,] -8.737871e-01 6.712062e+00
[42,] 1.128055e+01 -8.737871e-01
[43,] 2.989254e+00 1.128055e+01
[44,] -6.635288e+00 2.989254e+00
[45,] 3.023103e+00 -6.635288e+00
[46,] -2.734165e+00 3.023103e+00
[47,] -1.298132e+01 -2.734165e+00
[48,] -3.372604e+00 -1.298132e+01
[49,] -2.609430e+01 -3.372604e+00
[50,] -8.490773e+01 -2.609430e+01
[51,] -1.803359e+01 -8.490773e+01
[52,] 2.899403e+01 -1.803359e+01
[53,] 1.610651e+00 2.899403e+01
[54,] 3.183480e+01 1.610651e+00
[55,] 1.324344e+01 3.183480e+01
[56,] 2.938633e+00 1.324344e+01
[57,] -9.841124e+00 2.938633e+00
[58,] -1.274649e+01 -9.841124e+00
[59,] -6.034756e+00 -1.274649e+01
[60,] 6.468005e+00 -6.034756e+00
[61,] -1.238234e+01 6.468005e+00
[62,] -2.595454e+01 -1.238234e+01
[63,] -1.295989e+01 -2.595454e+01
[64,] 1.053374e+02 -1.295989e+01
[65,] 4.017719e+01 1.053374e+02
[66,] -2.704331e+01 4.017719e+01
[67,] -8.529795e+00 -2.704331e+01
[68,] 4.204775e+01 -8.529795e+00
[69,] -1.726934e+01 4.204775e+01
[70,] -2.695855e+00 -1.726934e+01
[71,] 4.348295e+00 -2.695855e+00
[72,] 1.297835e+01 4.348295e+00
[73,] 2.035214e+01 1.297835e+01
[74,] 1.032630e+01 2.035214e+01
[75,] 4.232848e+01 1.032630e+01
[76,] 6.960757e+00 4.232848e+01
[77,] -4.353773e+00 6.960757e+00
[78,] -8.347939e+00 -4.353773e+00
[79,] -1.461042e+01 -8.347939e+00
[80,] 2.335607e+01 -1.461042e+01
[81,] 3.885762e+01 2.335607e+01
[82,] -1.559548e+01 3.885762e+01
[83,] 1.310947e+01 -1.559548e+01
[84,] -1.133608e+02 1.310947e+01
[85,] 2.108020e+01 -1.133608e+02
[86,] -6.148328e-01 2.108020e+01
[87,] -6.779221e+00 -6.148328e-01
[88,] -3.484152e+01 -6.779221e+00
[89,] -2.343530e+01 -3.484152e+01
[90,] 4.605309e+01 -2.343530e+01
[91,] 1.258073e+01 4.605309e+01
[92,] -1.653669e+01 1.258073e+01
[93,] 5.220524e+00 -1.653669e+01
[94,] 3.284757e+00 5.220524e+00
[95,] -6.140630e+01 3.284757e+00
[96,] -5.093877e+01 -6.140630e+01
[97,] 3.533742e+01 -5.093877e+01
[98,] -7.875966e+00 3.533742e+01
[99,] 6.329413e+01 -7.875966e+00
[100,] -1.686795e+00 6.329413e+01
[101,] 4.511414e+00 -1.686795e+00
[102,] -7.213844e+00 4.511414e+00
[103,] -6.482096e+00 -7.213844e+00
[104,] 2.937979e+01 -6.482096e+00
[105,] 4.125579e+01 2.937979e+01
[106,] -1.385079e+01 4.125579e+01
[107,] 6.914329e-01 -1.385079e+01
[108,] 8.043331e+01 6.914329e-01
[109,] -3.595406e+01 8.043331e+01
[110,] 4.546189e+01 -3.595406e+01
[111,] -1.327267e+01 4.546189e+01
[112,] 1.529428e+01 -1.327267e+01
[113,] 1.044401e+01 1.529428e+01
[114,] 8.563919e+01 1.044401e+01
[115,] -7.627805e+00 8.563919e+01
[116,] 4.501840e+00 -7.627805e+00
[117,] -2.148166e+01 4.501840e+00
[118,] -6.713598e+01 -2.148166e+01
[119,] -7.434870e-01 -6.713598e+01
[120,] 7.002664e+00 -7.434870e-01
[121,] 6.042673e+00 7.002664e+00
[122,] 1.434792e+01 6.042673e+00
[123,] -4.238133e+01 1.434792e+01
[124,] -2.912091e+01 -4.238133e+01
[125,] -4.876032e+00 -2.912091e+01
[126,] -2.124755e+01 -4.876032e+00
[127,] 1.673085e+01 -2.124755e+01
[128,] 5.239054e+00 1.673085e+01
[129,] 1.070191e+01 5.239054e+00
[130,] -1.280543e+01 1.070191e+01
[131,] 2.233425e+01 -1.280543e+01
[132,] 2.432286e+00 2.233425e+01
[133,] -9.961082e+00 2.432286e+00
[134,] 2.605568e+01 -9.961082e+00
[135,] 5.820730e+01 2.605568e+01
[136,] 4.420388e+00 5.820730e+01
[137,] -2.177696e+01 4.420388e+00
[138,] -1.987894e+00 -2.177696e+01
[139,] 2.764230e+01 -1.987894e+00
[140,] -2.239479e+00 2.764230e+01
[141,] 9.984521e+00 -2.239479e+00
[142,] -1.952338e+01 9.984521e+00
[143,] -7.722817e+00 -1.952338e+01
[144,] -3.010713e+01 -7.722817e+00
[145,] -1.227749e+01 -3.010713e+01
[146,] -5.153448e+01 -1.227749e+01
[147,] 5.866066e-01 -5.153448e+01
[148,] 5.309464e+00 5.866066e-01
[149,] -3.294073e+01 5.309464e+00
[150,] 2.236461e+00 -3.294073e+01
[151,] 3.221930e+01 2.236461e+00
[152,] -5.512074e+00 3.221930e+01
[153,] -5.116003e+00 -5.512074e+00
[154,] 1.325975e+01 -5.116003e+00
[155,] 2.859715e+00 1.325975e+01
[156,] -4.811587e+00 2.859715e+00
[157,] 1.336281e+01 -4.811587e+00
[158,] -1.571710e+01 1.336281e+01
[159,] -1.985711e+01 -1.571710e+01
[160,] 7.589766e+00 -1.985711e+01
[161,] -6.934147e+01 7.589766e+00
[162,] 1.256148e+00 -6.934147e+01
[163,] -2.682184e+01 1.256148e+00
[164,] 4.576597e+00 -2.682184e+01
[165,] 2.124707e+01 4.576597e+00
[166,] 4.434280e+01 2.124707e+01
[167,] -1.348508e+01 4.434280e+01
[168,] 1.267583e+01 -1.348508e+01
[169,] -5.890074e+01 1.267583e+01
[170,] -3.288331e+01 -5.890074e+01
[171,] 8.869548e+01 -3.288331e+01
[172,] -5.104684e+01 8.869548e+01
[173,] 8.750358e+00 -5.104684e+01
[174,] -8.415735e+00 8.750358e+00
[175,] -8.525070e+00 -8.415735e+00
[176,] -1.337319e+00 -8.525070e+00
[177,] -1.508285e+01 -1.337319e+00
[178,] 3.187312e+01 -1.508285e+01
[179,] -1.792163e+01 3.187312e+01
[180,] 2.157232e+00 -1.792163e+01
[181,] -3.099274e+01 2.157232e+00
[182,] 4.597812e+00 -3.099274e+01
[183,] 1.140760e+01 4.597812e+00
[184,] 4.301042e+01 1.140760e+01
[185,] 9.675405e+00 4.301042e+01
[186,] 2.402350e+00 9.675405e+00
[187,] 2.361685e+00 2.402350e+00
[188,] 4.199296e+00 2.361685e+00
[189,] -2.444810e+01 4.199296e+00
[190,] -2.153717e+01 -2.444810e+01
[191,] -2.595865e+01 -2.153717e+01
[192,] 1.408274e+01 -2.595865e+01
[193,] -1.584701e+01 1.408274e+01
[194,] 2.364525e-01 -1.584701e+01
[195,] 4.225732e+01 2.364525e-01
[196,] -1.159579e+01 4.225732e+01
[197,] 6.314945e+00 -1.159579e+01
[198,] 5.507694e+00 6.314945e+00
[199,] 4.089660e+01 5.507694e+00
[200,] 9.417124e+00 4.089660e+01
[201,] 5.087406e+00 9.417124e+00
[202,] -1.417110e+01 5.087406e+00
[203,] -2.676179e+01 -1.417110e+01
[204,] 1.085428e+00 -2.676179e+01
[205,] -1.039977e+01 1.085428e+00
[206,] -1.916487e+00 -1.039977e+01
[207,] -2.111490e+01 -1.916487e+00
[208,] -5.315043e+00 -2.111490e+01
[209,] -7.010270e+00 -5.315043e+00
[210,] -3.267487e-01 -7.010270e+00
[211,] -6.620989e+00 -3.267487e-01
[212,] -1.503751e+00 -6.620989e+00
[213,] -1.247514e+01 -1.503751e+00
[214,] -2.535498e+01 -1.247514e+01
[215,] -7.318319e+00 -2.535498e+01
[216,] 3.516526e-02 -7.318319e+00
[217,] -1.262577e+01 3.516526e-02
[218,] 3.832948e-01 -1.262577e+01
[219,] -2.164942e+01 3.832948e-01
[220,] -3.846414e+00 -2.164942e+01
[221,] -1.890989e+01 -3.846414e+00
[222,] 2.914460e+01 -1.890989e+01
[223,] -3.503286e+00 2.914460e+01
[224,] -5.042872e+00 -3.503286e+00
[225,] 2.314775e+01 -5.042872e+00
[226,] 3.341141e-01 2.314775e+01
[227,] 4.078862e+01 3.341141e-01
[228,] 2.554711e+01 4.078862e+01
[229,] -2.473426e+01 2.554711e+01
[230,] -1.094984e+01 -2.473426e+01
[231,] 1.308451e+00 -1.094984e+01
[232,] -1.759488e+00 1.308451e+00
[233,] -5.466139e+00 -1.759488e+00
[234,] 1.070167e+01 -5.466139e+00
[235,] 9.288227e-03 1.070167e+01
[236,] -3.145985e+01 9.288227e-03
[237,] 1.549050e+01 -3.145985e+01
[238,] 3.588324e+00 1.549050e+01
[239,] 1.577770e+01 3.588324e+00
[240,] -9.060172e+00 1.577770e+01
[241,] 1.811083e+01 -9.060172e+00
[242,] 9.989868e+00 1.811083e+01
[243,] 3.265916e+00 9.989868e+00
[244,] 8.428560e+00 3.265916e+00
[245,] -2.220616e+00 8.428560e+00
[246,] 2.084015e+00 -2.220616e+00
[247,] -1.889234e+01 2.084015e+00
[248,] -3.847774e+00 -1.889234e+01
[249,] 8.492681e+00 -3.847774e+00
[250,] -2.521619e+01 8.492681e+00
[251,] 3.584535e+00 -2.521619e+01
[252,] 1.316001e+01 3.584535e+00
[253,] -1.710027e+01 1.316001e+01
[254,] -7.886527e+00 -1.710027e+01
[255,] 3.518384e+00 -7.886527e+00
[256,] 8.469546e+00 3.518384e+00
[257,] -1.846668e+01 8.469546e+00
[258,] -1.211436e+01 -1.846668e+01
[259,] -3.046149e-01 -1.211436e+01
[260,] -8.937391e+00 -3.046149e-01
[261,] 6.090919e+00 -8.937391e+00
[262,] -2.572758e+00 6.090919e+00
[263,] 1.416708e+01 -2.572758e+00
[264,] 2.098482e+00 1.416708e+01
[265,] 4.237952e+00 2.098482e+00
[266,] 1.837249e+01 4.237952e+00
[267,] 2.085897e+01 1.837249e+01
[268,] -6.388083e+00 2.085897e+01
[269,] 6.367282e+00 -6.388083e+00
[270,] 3.736641e+00 6.367282e+00
[271,] -1.200494e+01 3.736641e+00
[272,] -5.830860e+00 -1.200494e+01
[273,] -1.695386e-01 -5.830860e+00
[274,] 2.209479e+00 -1.695386e-01
[275,] -9.307759e+00 2.209479e+00
[276,] -2.454101e+01 -9.307759e+00
[277,] 7.532490e+00 -2.454101e+01
[278,] 1.010046e+01 7.532490e+00
[279,] 1.239522e+00 1.010046e+01
[280,] -3.658180e+00 1.239522e+00
[281,] -4.236019e+01 -3.658180e+00
[282,] -3.460935e+00 -4.236019e+01
[283,] -2.446405e+00 -3.460935e+00
[284,] -1.583107e+01 -2.446405e+00
[285,] -8.411520e+00 -1.583107e+01
[286,] -1.239962e+00 -8.411520e+00
[287,] 4.057483e+01 -1.239962e+00
[288,] -8.235839e+00 4.057483e+01
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.299548e+01 2.885916e+01
2 1.871819e+00 2.299548e+01
3 2.994060e+01 1.871819e+00
4 7.873934e+00 2.994060e+01
5 -1.321101e+01 7.873934e+00
6 -2.026606e+01 -1.321101e+01
7 -1.544908e+01 -2.026606e+01
8 -5.352573e+00 -1.544908e+01
9 -1.583882e+01 -5.352573e+00
10 3.490916e+00 -1.583882e+01
11 2.353458e+01 3.490916e+00
12 -1.355571e+01 2.353458e+01
13 -7.271958e+00 -1.355571e+01
14 1.470781e+01 -7.271958e+00
15 2.774775e+00 1.470781e+01
16 -1.288032e+01 2.774775e+00
17 1.795751e+01 -1.288032e+01
18 -2.642440e+01 1.795751e+01
19 4.500973e+01 -2.642440e+01
20 1.832927e+01 4.500973e+01
21 1.098125e+01 1.832927e+01
22 -1.180353e+01 1.098125e+01
23 -5.781902e+00 -1.180353e+01
24 1.453908e+01 -5.781902e+00
25 3.225395e+01 1.453908e+01
26 -2.977006e+00 3.225395e+01
27 5.094219e+00 -2.977006e+00
28 6.575487e+00 5.094219e+00
29 2.521071e-01 6.575487e+00
30 8.208709e+00 2.521071e-01
31 -4.668832e+00 8.208709e+00
32 3.217263e+01 -4.668832e+00
33 9.772775e-01 3.217263e+01
34 -3.074594e+01 9.772775e-01
35 2.742469e+01 -3.074594e+01
36 -7.322639e+00 2.742469e+01
37 -2.701876e+01 -7.322639e+00
38 -4.089203e+01 -2.701876e+01
39 3.906158e+00 -4.089203e+01
40 6.712062e+00 3.906158e+00
41 -8.737871e-01 6.712062e+00
42 1.128055e+01 -8.737871e-01
43 2.989254e+00 1.128055e+01
44 -6.635288e+00 2.989254e+00
45 3.023103e+00 -6.635288e+00
46 -2.734165e+00 3.023103e+00
47 -1.298132e+01 -2.734165e+00
48 -3.372604e+00 -1.298132e+01
49 -2.609430e+01 -3.372604e+00
50 -8.490773e+01 -2.609430e+01
51 -1.803359e+01 -8.490773e+01
52 2.899403e+01 -1.803359e+01
53 1.610651e+00 2.899403e+01
54 3.183480e+01 1.610651e+00
55 1.324344e+01 3.183480e+01
56 2.938633e+00 1.324344e+01
57 -9.841124e+00 2.938633e+00
58 -1.274649e+01 -9.841124e+00
59 -6.034756e+00 -1.274649e+01
60 6.468005e+00 -6.034756e+00
61 -1.238234e+01 6.468005e+00
62 -2.595454e+01 -1.238234e+01
63 -1.295989e+01 -2.595454e+01
64 1.053374e+02 -1.295989e+01
65 4.017719e+01 1.053374e+02
66 -2.704331e+01 4.017719e+01
67 -8.529795e+00 -2.704331e+01
68 4.204775e+01 -8.529795e+00
69 -1.726934e+01 4.204775e+01
70 -2.695855e+00 -1.726934e+01
71 4.348295e+00 -2.695855e+00
72 1.297835e+01 4.348295e+00
73 2.035214e+01 1.297835e+01
74 1.032630e+01 2.035214e+01
75 4.232848e+01 1.032630e+01
76 6.960757e+00 4.232848e+01
77 -4.353773e+00 6.960757e+00
78 -8.347939e+00 -4.353773e+00
79 -1.461042e+01 -8.347939e+00
80 2.335607e+01 -1.461042e+01
81 3.885762e+01 2.335607e+01
82 -1.559548e+01 3.885762e+01
83 1.310947e+01 -1.559548e+01
84 -1.133608e+02 1.310947e+01
85 2.108020e+01 -1.133608e+02
86 -6.148328e-01 2.108020e+01
87 -6.779221e+00 -6.148328e-01
88 -3.484152e+01 -6.779221e+00
89 -2.343530e+01 -3.484152e+01
90 4.605309e+01 -2.343530e+01
91 1.258073e+01 4.605309e+01
92 -1.653669e+01 1.258073e+01
93 5.220524e+00 -1.653669e+01
94 3.284757e+00 5.220524e+00
95 -6.140630e+01 3.284757e+00
96 -5.093877e+01 -6.140630e+01
97 3.533742e+01 -5.093877e+01
98 -7.875966e+00 3.533742e+01
99 6.329413e+01 -7.875966e+00
100 -1.686795e+00 6.329413e+01
101 4.511414e+00 -1.686795e+00
102 -7.213844e+00 4.511414e+00
103 -6.482096e+00 -7.213844e+00
104 2.937979e+01 -6.482096e+00
105 4.125579e+01 2.937979e+01
106 -1.385079e+01 4.125579e+01
107 6.914329e-01 -1.385079e+01
108 8.043331e+01 6.914329e-01
109 -3.595406e+01 8.043331e+01
110 4.546189e+01 -3.595406e+01
111 -1.327267e+01 4.546189e+01
112 1.529428e+01 -1.327267e+01
113 1.044401e+01 1.529428e+01
114 8.563919e+01 1.044401e+01
115 -7.627805e+00 8.563919e+01
116 4.501840e+00 -7.627805e+00
117 -2.148166e+01 4.501840e+00
118 -6.713598e+01 -2.148166e+01
119 -7.434870e-01 -6.713598e+01
120 7.002664e+00 -7.434870e-01
121 6.042673e+00 7.002664e+00
122 1.434792e+01 6.042673e+00
123 -4.238133e+01 1.434792e+01
124 -2.912091e+01 -4.238133e+01
125 -4.876032e+00 -2.912091e+01
126 -2.124755e+01 -4.876032e+00
127 1.673085e+01 -2.124755e+01
128 5.239054e+00 1.673085e+01
129 1.070191e+01 5.239054e+00
130 -1.280543e+01 1.070191e+01
131 2.233425e+01 -1.280543e+01
132 2.432286e+00 2.233425e+01
133 -9.961082e+00 2.432286e+00
134 2.605568e+01 -9.961082e+00
135 5.820730e+01 2.605568e+01
136 4.420388e+00 5.820730e+01
137 -2.177696e+01 4.420388e+00
138 -1.987894e+00 -2.177696e+01
139 2.764230e+01 -1.987894e+00
140 -2.239479e+00 2.764230e+01
141 9.984521e+00 -2.239479e+00
142 -1.952338e+01 9.984521e+00
143 -7.722817e+00 -1.952338e+01
144 -3.010713e+01 -7.722817e+00
145 -1.227749e+01 -3.010713e+01
146 -5.153448e+01 -1.227749e+01
147 5.866066e-01 -5.153448e+01
148 5.309464e+00 5.866066e-01
149 -3.294073e+01 5.309464e+00
150 2.236461e+00 -3.294073e+01
151 3.221930e+01 2.236461e+00
152 -5.512074e+00 3.221930e+01
153 -5.116003e+00 -5.512074e+00
154 1.325975e+01 -5.116003e+00
155 2.859715e+00 1.325975e+01
156 -4.811587e+00 2.859715e+00
157 1.336281e+01 -4.811587e+00
158 -1.571710e+01 1.336281e+01
159 -1.985711e+01 -1.571710e+01
160 7.589766e+00 -1.985711e+01
161 -6.934147e+01 7.589766e+00
162 1.256148e+00 -6.934147e+01
163 -2.682184e+01 1.256148e+00
164 4.576597e+00 -2.682184e+01
165 2.124707e+01 4.576597e+00
166 4.434280e+01 2.124707e+01
167 -1.348508e+01 4.434280e+01
168 1.267583e+01 -1.348508e+01
169 -5.890074e+01 1.267583e+01
170 -3.288331e+01 -5.890074e+01
171 8.869548e+01 -3.288331e+01
172 -5.104684e+01 8.869548e+01
173 8.750358e+00 -5.104684e+01
174 -8.415735e+00 8.750358e+00
175 -8.525070e+00 -8.415735e+00
176 -1.337319e+00 -8.525070e+00
177 -1.508285e+01 -1.337319e+00
178 3.187312e+01 -1.508285e+01
179 -1.792163e+01 3.187312e+01
180 2.157232e+00 -1.792163e+01
181 -3.099274e+01 2.157232e+00
182 4.597812e+00 -3.099274e+01
183 1.140760e+01 4.597812e+00
184 4.301042e+01 1.140760e+01
185 9.675405e+00 4.301042e+01
186 2.402350e+00 9.675405e+00
187 2.361685e+00 2.402350e+00
188 4.199296e+00 2.361685e+00
189 -2.444810e+01 4.199296e+00
190 -2.153717e+01 -2.444810e+01
191 -2.595865e+01 -2.153717e+01
192 1.408274e+01 -2.595865e+01
193 -1.584701e+01 1.408274e+01
194 2.364525e-01 -1.584701e+01
195 4.225732e+01 2.364525e-01
196 -1.159579e+01 4.225732e+01
197 6.314945e+00 -1.159579e+01
198 5.507694e+00 6.314945e+00
199 4.089660e+01 5.507694e+00
200 9.417124e+00 4.089660e+01
201 5.087406e+00 9.417124e+00
202 -1.417110e+01 5.087406e+00
203 -2.676179e+01 -1.417110e+01
204 1.085428e+00 -2.676179e+01
205 -1.039977e+01 1.085428e+00
206 -1.916487e+00 -1.039977e+01
207 -2.111490e+01 -1.916487e+00
208 -5.315043e+00 -2.111490e+01
209 -7.010270e+00 -5.315043e+00
210 -3.267487e-01 -7.010270e+00
211 -6.620989e+00 -3.267487e-01
212 -1.503751e+00 -6.620989e+00
213 -1.247514e+01 -1.503751e+00
214 -2.535498e+01 -1.247514e+01
215 -7.318319e+00 -2.535498e+01
216 3.516526e-02 -7.318319e+00
217 -1.262577e+01 3.516526e-02
218 3.832948e-01 -1.262577e+01
219 -2.164942e+01 3.832948e-01
220 -3.846414e+00 -2.164942e+01
221 -1.890989e+01 -3.846414e+00
222 2.914460e+01 -1.890989e+01
223 -3.503286e+00 2.914460e+01
224 -5.042872e+00 -3.503286e+00
225 2.314775e+01 -5.042872e+00
226 3.341141e-01 2.314775e+01
227 4.078862e+01 3.341141e-01
228 2.554711e+01 4.078862e+01
229 -2.473426e+01 2.554711e+01
230 -1.094984e+01 -2.473426e+01
231 1.308451e+00 -1.094984e+01
232 -1.759488e+00 1.308451e+00
233 -5.466139e+00 -1.759488e+00
234 1.070167e+01 -5.466139e+00
235 9.288227e-03 1.070167e+01
236 -3.145985e+01 9.288227e-03
237 1.549050e+01 -3.145985e+01
238 3.588324e+00 1.549050e+01
239 1.577770e+01 3.588324e+00
240 -9.060172e+00 1.577770e+01
241 1.811083e+01 -9.060172e+00
242 9.989868e+00 1.811083e+01
243 3.265916e+00 9.989868e+00
244 8.428560e+00 3.265916e+00
245 -2.220616e+00 8.428560e+00
246 2.084015e+00 -2.220616e+00
247 -1.889234e+01 2.084015e+00
248 -3.847774e+00 -1.889234e+01
249 8.492681e+00 -3.847774e+00
250 -2.521619e+01 8.492681e+00
251 3.584535e+00 -2.521619e+01
252 1.316001e+01 3.584535e+00
253 -1.710027e+01 1.316001e+01
254 -7.886527e+00 -1.710027e+01
255 3.518384e+00 -7.886527e+00
256 8.469546e+00 3.518384e+00
257 -1.846668e+01 8.469546e+00
258 -1.211436e+01 -1.846668e+01
259 -3.046149e-01 -1.211436e+01
260 -8.937391e+00 -3.046149e-01
261 6.090919e+00 -8.937391e+00
262 -2.572758e+00 6.090919e+00
263 1.416708e+01 -2.572758e+00
264 2.098482e+00 1.416708e+01
265 4.237952e+00 2.098482e+00
266 1.837249e+01 4.237952e+00
267 2.085897e+01 1.837249e+01
268 -6.388083e+00 2.085897e+01
269 6.367282e+00 -6.388083e+00
270 3.736641e+00 6.367282e+00
271 -1.200494e+01 3.736641e+00
272 -5.830860e+00 -1.200494e+01
273 -1.695386e-01 -5.830860e+00
274 2.209479e+00 -1.695386e-01
275 -9.307759e+00 2.209479e+00
276 -2.454101e+01 -9.307759e+00
277 7.532490e+00 -2.454101e+01
278 1.010046e+01 7.532490e+00
279 1.239522e+00 1.010046e+01
280 -3.658180e+00 1.239522e+00
281 -4.236019e+01 -3.658180e+00
282 -3.460935e+00 -4.236019e+01
283 -2.446405e+00 -3.460935e+00
284 -1.583107e+01 -2.446405e+00
285 -8.411520e+00 -1.583107e+01
286 -1.239962e+00 -8.411520e+00
287 4.057483e+01 -1.239962e+00
288 -8.235839e+00 4.057483e+01
> 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/7h0zm1323805620.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/826og1323805620.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/9o5pl1323805620.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/107tt51323805620.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11irrg1323805620.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12apk11323805620.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13blmn1323805620.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14htfy1323805620.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/15ufkw1323805620.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/16l8d91323805621.tab")
+ }
>
> try(system("convert tmp/1eih91323805620.ps tmp/1eih91323805620.png",intern=TRUE))
character(0)
> try(system("convert tmp/2x1381323805620.ps tmp/2x1381323805620.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xoxm1323805620.ps tmp/3xoxm1323805620.png",intern=TRUE))
character(0)
> try(system("convert tmp/4yjx31323805620.ps tmp/4yjx31323805620.png",intern=TRUE))
character(0)
> try(system("convert tmp/5rm0l1323805620.ps tmp/5rm0l1323805620.png",intern=TRUE))
character(0)
> try(system("convert tmp/6bv7r1323805620.ps tmp/6bv7r1323805620.png",intern=TRUE))
character(0)
> try(system("convert tmp/7h0zm1323805620.ps tmp/7h0zm1323805620.png",intern=TRUE))
character(0)
> try(system("convert tmp/826og1323805620.ps tmp/826og1323805620.png",intern=TRUE))
character(0)
> try(system("convert tmp/9o5pl1323805620.ps tmp/9o5pl1323805620.png",intern=TRUE))
character(0)
> try(system("convert tmp/107tt51323805620.ps tmp/107tt51323805620.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
8.107 0.630 10.040