R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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> x <- array(list(56
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+ ,dim=c(4
+ ,289)
+ ,dimnames=list(c('X_1'
+ ,'X_2'
+ ,'X_3'
+ ,'Y_1')
+ ,1:289))
> y <- array(NA,dim=c(4,289),dimnames=list(c('X_1','X_2','X_3','Y_1'),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 = '4'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '4'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> 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
Y_1 X_1 X_2 X_3
1 58.585278 56 30 112285
2 33.606111 56 28 84786
3 49.030000 54 38 83123
4 49.811389 89 30 101193
5 34.218056 40 22 38361
6 14.651667 25 26 68504
7 107.092778 92 25 119182
8 9.213889 18 18 22807
9 28.234722 63 11 17140
10 41.405833 44 26 116174
11 45.957222 33 25 57635
12 65.892500 84 38 66198
13 48.146111 88 44 71701
14 36.980833 55 30 57793
15 71.909167 60 40 80444
16 50.023056 66 34 53855
17 90.221944 154 47 97668
18 64.156667 53 30 133824
19 65.773611 119 31 101481
20 37.631389 41 23 99645
21 56.368056 61 36 114789
22 59.763056 58 36 99052
23 95.638056 75 30 67654
24 42.759722 33 25 65553
25 36.928611 40 39 97500
26 48.534444 92 34 69112
27 48.448611 100 31 82753
28 62.652222 112 31 85323
29 62.120000 73 33 72654
30 34.671389 40 25 30727
31 61.582778 45 33 77873
32 58.546389 60 35 117478
33 47.296111 62 42 74007
34 72.378056 75 43 90183
35 23.570278 31 30 61542
36 81.784444 77 33 101494
37 28.058611 34 13 27570
38 59.900278 46 32 55813
39 90.307500 99 36 79215
40 1.993333 17 0 1423
41 46.539444 66 28 55461
42 29.557778 30 14 31081
43 26.822222 76 17 22996
44 73.824722 146 32 83122
45 74.903056 67 30 70106
46 41.420000 56 35 60578
47 48.840000 107 20 39992
48 42.464167 58 28 79892
49 31.018056 34 28 49810
50 32.335556 61 39 71570
51 100.639167 119 34 100708
52 21.888889 42 26 33032
53 50.879722 66 39 82875
54 77.212500 89 39 139077
55 41.841389 44 33 71595
56 46.891389 66 28 72260
57 6.718889 24 4 5950
58 91.463056 259 39 115762
59 18.063611 17 18 32551
60 28.082500 64 14 31701
61 60.818333 41 29 80670
62 67.792222 68 44 143558
63 94.880556 168 21 117105
64 28.776944 43 16 23789
65 64.813333 132 28 120733
66 71.239444 105 35 105195
67 57.266944 71 28 73107
68 86.520278 112 38 132068
69 65.500000 94 23 149193
70 49.427500 82 36 46821
71 57.548889 70 32 87011
72 54.598056 57 29 95260
73 48.384444 53 25 55183
74 39.790556 103 27 106671
75 52.099722 121 36 73511
76 52.133611 62 28 92945
77 33.060000 52 23 78664
78 50.608889 52 40 70054
79 20.435000 32 23 22618
80 54.160833 62 40 74011
81 46.524444 45 28 83737
82 39.932222 46 34 69094
83 76.539167 63 33 93133
84 67.555278 75 28 95536
85 50.833056 88 34 225920
86 37.680278 46 30 62133
87 42.305278 53 33 61370
88 33.394722 37 22 43836
89 96.245833 90 38 106117
90 40.497222 63 26 38692
91 53.705278 78 35 84651
92 22.486944 25 8 56622
93 34.103889 45 24 15986
94 36.273611 46 29 95364
95 31.280833 41 20 26706
96 79.574444 144 29 89691
97 66.962778 82 45 67267
98 41.235000 91 37 126846
99 56.864722 71 33 41140
100 50.577500 63 33 102860
101 38.984444 53 25 51715
102 61.254444 62 32 55801
103 67.516667 63 29 111813
104 45.212500 32 28 120293
105 50.725833 39 28 138599
106 64.482778 62 31 161647
107 73.699444 117 52 115929
108 23.770556 34 21 24266
109 86.344167 92 24 162901
110 62.516667 93 41 109825
111 64.532500 54 33 129838
112 40.268333 144 32 37510
113 12.024167 14 19 43750
114 43.265000 61 20 40652
115 45.752500 109 31 87771
116 56.094444 38 31 85872
117 65.403889 73 32 89275
118 61.333611 75 18 44418
119 27.629444 50 23 192565
120 25.739167 61 17 35232
121 37.035556 55 20 40909
122 17.044722 77 12 13294
123 34.980556 75 17 32387
124 27.986111 72 30 140867
125 62.374722 50 31 120662
126 22.865556 32 10 21233
127 28.336111 53 13 44332
128 28.200833 42 22 61056
129 67.641944 71 42 101338
130 6.371667 10 1 1168
131 11.546111 35 9 13497
132 42.353889 65 32 65567
133 17.182500 25 11 25162
134 27.756389 66 25 32334
135 36.801944 41 36 40735
136 88.165000 86 31 91413
137 5.848333 16 0 855
138 58.233611 42 24 97068
139 6.291111 19 13 44339
140 8.726111 19 8 14116
141 12.971667 45 13 10288
142 36.582778 65 19 65622
143 25.481944 35 18 16563
144 67.985833 95 33 76643
145 51.252778 49 40 110681
146 22.184167 37 22 29011
147 35.673056 64 38 92696
148 27.177500 38 24 94785
149 10.615000 34 8 8773
150 41.972500 32 35 83209
151 75.682778 65 43 93815
152 47.915000 52 43 86687
153 30.011944 62 14 34553
154 91.140833 65 41 105547
155 69.605278 83 38 103487
156 97.518611 95 45 213688
157 43.893056 29 31 71220
158 27.462778 18 13 23517
159 23.733056 33 28 56926
160 63.678333 247 31 91721
161 97.671944 139 40 115168
162 23.390833 29 30 111194
163 33.456944 118 16 51009
164 90.166111 110 37 135777
165 36.408056 67 30 51513
166 56.741944 42 35 74163
167 45.984167 65 32 51633
168 39.367222 94 27 75345
169 32.235556 64 20 33416
170 69.457500 81 18 83305
171 83.270833 95 31 98952
172 54.399444 67 31 102372
173 48.127778 63 21 37238
174 70.691111 83 39 103772
175 28.996944 45 41 123969
176 37.801111 30 13 27142
177 55.410000 70 32 135400
178 25.694167 32 18 21399
179 62.313889 83 39 130115
180 37.716944 31 14 24874
181 20.668889 67 7 34988
182 22.566667 66 17 45549
183 4.080000 10 0 6023
184 50.453611 70 30 64466
185 75.515556 103 37 54990
186 1.999722 5 0 1644
187 12.961111 20 5 6179
188 4.874167 5 1 3926
189 37.046667 36 16 32755
190 26.451944 34 32 34777
191 42.389167 48 24 73224
192 27.262778 40 17 27114
193 22.116389 43 11 20760
194 16.442778 31 24 37636
195 38.872778 42 22 65461
196 32.947778 46 12 30080
197 20.244444 33 19 24094
198 18.187500 18 13 69008
199 27.678611 55 17 54968
200 19.990278 35 15 46090
201 21.464444 59 16 27507
202 13.691389 19 24 10672
203 37.536389 66 15 34029
204 30.123889 60 17 46300
205 24.929444 36 18 24760
206 12.304444 25 20 18779
207 21.568889 47 16 21280
208 50.424444 54 16 40662
209 37.227500 53 18 28987
210 34.462222 40 22 22827
211 25.730556 40 8 18513
212 33.846667 39 17 30594
213 14.698611 14 18 24006
214 22.742222 45 16 27913
215 16.383611 36 23 42744
216 14.865278 28 22 12934
217 16.892222 44 13 22574
218 15.659722 30 13 41385
219 18.191667 22 16 18653
220 22.485833 17 16 18472
221 21.195000 31 20 30976
222 28.891944 55 22 63339
223 27.251111 54 17 25568
224 18.885833 21 18 33747
225 8.608056 14 17 4154
226 37.627222 81 12 19474
227 20.417778 35 7 35130
228 17.534167 43 17 39067
229 17.015000 46 14 13310
230 20.809444 30 23 65892
231 8.826111 23 17 4143
232 22.621389 38 14 28579
233 24.218333 54 15 51776
234 13.913889 20 17 21152
235 18.262500 53 21 38084
236 15.736944 45 18 27717
237 43.999722 39 18 32928
238 12.904167 20 17 11342
239 20.451111 24 17 19499
240 10.665278 31 16 16380
241 25.527500 35 15 36874
242 38.757222 151 21 48259
243 14.490000 52 16 16734
244 14.324167 30 14 28207
245 19.597500 31 15 30143
246 23.571111 29 17 41369
247 28.482778 57 15 45833
248 24.077222 40 15 29156
249 23.808056 44 10 35944
250 9.628333 25 6 36278
251 41.827778 77 22 45588
252 27.669722 35 21 45097
253 5.374722 11 1 3895
254 27.603611 63 18 28394
255 23.952778 44 17 18632
256 8.565833 19 4 2325
257 8.807222 13 10 25139
258 24.946111 42 16 27975
259 17.246667 38 16 14483
260 11.153056 29 9 13127
261 7.676111 20 16 5839
262 21.386111 27 17 24069
263 10.405556 20 7 3738
264 15.043611 19 15 18625
265 13.850556 37 14 36341
266 23.426944 26 14 24548
267 17.826389 42 18 21792
268 16.495000 49 12 26263
269 33.141111 30 16 23686
270 21.306111 49 21 49303
271 28.729167 67 19 25659
272 19.540000 28 16 28904
273 12.058333 19 1 2781
274 29.121667 49 16 29236
275 17.281944 27 10 19546
276 19.251111 30 19 22818
277 14.754722 22 12 32689
278 5.490000 12 2 5752
279 24.077778 31 14 22197
280 23.362500 20 17 20055
281 21.651389 20 19 25272
282 24.753611 39 14 82206
283 25.279167 29 11 32073
284 11.180000 16 4 5444
285 17.829722 27 16 20154
286 14.126944 21 20 36944
287 15.725833 19 12 8019
288 17.442222 35 15 30884
289 20.148611 14 16 19540
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X_1 X_2 X_3
-1.9670479 0.2507386 0.7145840 0.0001719
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-34.209 -6.217 -0.464 5.172 47.636
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.967e+00 1.714e+00 -1.147 0.252
X_1 2.507e-01 2.493e-02 10.057 < 2e-16 ***
X_2 7.146e-01 9.912e-02 7.209 5.07e-12 ***
X_3 1.719e-04 2.573e-05 6.681 1.24e-10 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.64 on 285 degrees of freedom
Multiple R-squared: 0.7435, Adjusted R-squared: 0.7408
F-statistic: 275.4 on 3 and 285 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,] 0.9899473 2.010541e-02 1.005271e-02
[2,] 0.9771043 4.579146e-02 2.289573e-02
[3,] 0.9625446 7.491085e-02 3.745542e-02
[4,] 0.9543930 9.121410e-02 4.560705e-02
[5,] 0.9766615 4.667697e-02 2.333848e-02
[6,] 0.9650538 6.989240e-02 3.494620e-02
[7,] 0.9618477 7.630465e-02 3.815233e-02
[8,] 0.9406172 1.187655e-01 5.938275e-02
[9,] 0.9777685 4.446303e-02 2.223152e-02
[10,] 0.9665556 6.688880e-02 3.344440e-02
[11,] 0.9627130 7.457401e-02 3.728700e-02
[12,] 0.9458973 1.082054e-01 5.410272e-02
[13,] 0.9500246 9.995089e-02 4.997544e-02
[14,] 0.9379059 1.241882e-01 6.209412e-02
[15,] 0.9159830 1.680340e-01 8.401702e-02
[16,] 0.8928338 2.143323e-01 1.071662e-01
[17,] 0.9974658 5.068380e-03 2.534190e-03
[18,] 0.9965850 6.830040e-03 3.415020e-03
[19,] 0.9960781 7.843895e-03 3.921948e-03
[20,] 0.9959267 8.146653e-03 4.073326e-03
[21,] 0.9970174 5.965252e-03 2.982626e-03
[22,] 0.9960208 7.958466e-03 3.979233e-03
[23,] 0.9951397 9.720681e-03 4.860341e-03
[24,] 0.9932687 1.346265e-02 6.731325e-03
[25,] 0.9946708 1.065849e-02 5.329247e-03
[26,] 0.9923256 1.534877e-02 7.674384e-03
[27,] 0.9898099 2.038022e-02 1.019011e-02
[28,] 0.9888123 2.237533e-02 1.118767e-02
[29,] 0.9884455 2.310893e-02 1.155446e-02
[30,] 0.9929096 1.418070e-02 7.090351e-03
[31,] 0.9905751 1.884978e-02 9.424889e-03
[32,] 0.9938627 1.227462e-02 6.137311e-03
[33,] 0.9975376 4.924799e-03 2.462400e-03
[34,] 0.9966470 6.705988e-03 3.352994e-03
[35,] 0.9952784 9.443182e-03 4.721591e-03
[36,] 0.9940030 1.199392e-02 5.996960e-03
[37,] 0.9937039 1.259227e-02 6.296133e-03
[38,] 0.9924886 1.502287e-02 7.511436e-03
[39,] 0.9969278 6.144397e-03 3.072198e-03
[40,] 0.9960183 7.963353e-03 3.981677e-03
[41,] 0.9947450 1.051005e-02 5.255023e-03
[42,] 0.9934379 1.312410e-02 6.562050e-03
[43,] 0.9913225 1.735499e-02 8.677493e-03
[44,] 0.9947698 1.046036e-02 5.230180e-03
[45,] 0.9980410 3.918024e-03 1.959012e-03
[46,] 0.9977233 4.553403e-03 2.276701e-03
[47,] 0.9970425 5.914905e-03 2.957452e-03
[48,] 0.9961285 7.742964e-03 3.871482e-03
[49,] 0.9947849 1.043015e-02 5.215074e-03
[50,] 0.9931360 1.372803e-02 6.864015e-03
[51,] 0.9910236 1.795286e-02 8.976430e-03
[52,] 0.9980432 3.913685e-03 1.956843e-03
[53,] 0.9973722 5.255693e-03 2.627846e-03
[54,] 0.9965040 6.991963e-03 3.495982e-03
[55,] 0.9971655 5.669057e-03 2.834529e-03
[56,] 0.9965727 6.854615e-03 3.427307e-03
[57,] 0.9969368 6.126396e-03 3.063198e-03
[58,] 0.9959886 8.022814e-03 4.011407e-03
[59,] 0.9962249 7.550182e-03 3.775091e-03
[60,] 0.9950706 9.858712e-03 4.929356e-03
[61,] 0.9941459 1.170816e-02 5.854080e-03
[62,] 0.9932679 1.346420e-02 6.732099e-03
[63,] 0.9923583 1.528341e-02 7.641703e-03
[64,] 0.9901275 1.974503e-02 9.872517e-03
[65,] 0.9875362 2.492761e-02 1.246381e-02
[66,] 0.9844941 3.101189e-02 1.550595e-02
[67,] 0.9826734 3.465318e-02 1.732659e-02
[68,] 0.9922413 1.551740e-02 7.758698e-03
[69,] 0.9930349 1.393014e-02 6.965071e-03
[70,] 0.9910947 1.781057e-02 8.905284e-03
[71,] 0.9904429 1.911416e-02 9.557078e-03
[72,] 0.9877795 2.444100e-02 1.222050e-02
[73,] 0.9853073 2.938550e-02 1.469275e-02
[74,] 0.9814844 3.703128e-02 1.851564e-02
[75,] 0.9770347 4.593063e-02 2.296531e-02
[76,] 0.9729376 5.412489e-02 2.706245e-02
[77,] 0.9841463 3.170744e-02 1.585372e-02
[78,] 0.9847185 3.056307e-02 1.528154e-02
[79,] 0.9979143 4.171362e-03 2.085681e-03
[80,] 0.9973460 5.308079e-03 2.654040e-03
[81,] 0.9965884 6.823117e-03 3.411558e-03
[82,] 0.9955804 8.839131e-03 4.419565e-03
[83,] 0.9990235 1.953090e-03 9.765451e-04
[84,] 0.9986937 2.612584e-03 1.306292e-03
[85,] 0.9983089 3.382295e-03 1.691148e-03
[86,] 0.9977744 4.451290e-03 2.225645e-03
[87,] 0.9971698 5.660473e-03 2.830236e-03
[88,] 0.9970240 5.951935e-03 2.975968e-03
[89,] 0.9961983 7.603388e-03 3.801694e-03
[90,] 0.9958217 8.356553e-03 4.178276e-03
[91,] 0.9948702 1.025964e-02 5.129820e-03
[92,] 0.9984037 3.192647e-03 1.596324e-03
[93,] 0.9982853 3.429341e-03 1.714671e-03
[94,] 0.9978197 4.360689e-03 2.180344e-03
[95,] 0.9971562 5.687528e-03 2.843764e-03
[96,] 0.9976051 4.789766e-03 2.394883e-03
[97,] 0.9978416 4.316843e-03 2.158421e-03
[98,] 0.9971836 5.632833e-03 2.816416e-03
[99,] 0.9963406 7.318888e-03 3.659444e-03
[100,] 0.9952969 9.406212e-03 4.703106e-03
[101,] 0.9948346 1.033070e-02 5.165352e-03
[102,] 0.9935388 1.292241e-02 6.461204e-03
[103,] 0.9961022 7.795607e-03 3.897804e-03
[104,] 0.9953195 9.361093e-03 4.680546e-03
[105,] 0.9946465 1.070691e-02 5.353457e-03
[106,] 0.9974889 5.022293e-03 2.511147e-03
[107,] 0.9974743 5.051460e-03 2.525730e-03
[108,] 0.9971062 5.787608e-03 2.893804e-03
[109,] 0.9977776 4.444883e-03 2.222441e-03
[110,] 0.9977935 4.413011e-03 2.206505e-03
[111,] 0.9977662 4.467638e-03 2.233819e-03
[112,] 0.9990445 1.910985e-03 9.554926e-04
[113,] 0.9998743 2.513539e-04 1.256770e-04
[114,] 0.9998446 3.107481e-04 1.553740e-04
[115,] 0.9997933 4.134807e-04 2.067403e-04
[116,] 0.9998002 3.995061e-04 1.997531e-04
[117,] 0.9997288 5.424875e-04 2.712438e-04
[118,] 0.9999805 3.909969e-05 1.954985e-05
[119,] 0.9999767 4.651626e-05 2.325813e-05
[120,] 0.9999691 6.188377e-05 3.094189e-05
[121,] 0.9999561 8.776045e-05 4.388023e-05
[122,] 0.9999455 1.089579e-04 5.447893e-05
[123,] 0.9999288 1.424983e-04 7.124916e-05
[124,] 0.9999032 1.935745e-04 9.678725e-05
[125,] 0.9998736 2.528111e-04 1.264056e-04
[126,] 0.9998380 3.239008e-04 1.619504e-04
[127,] 0.9997772 4.455915e-04 2.227957e-04
[128,] 0.9997580 4.839560e-04 2.419780e-04
[129,] 0.9996793 6.413243e-04 3.206621e-04
[130,] 0.9999636 7.276842e-05 3.638421e-05
[131,] 0.9999492 1.016633e-04 5.083164e-05
[132,] 0.9999627 7.457777e-05 3.728889e-05
[133,] 0.9999696 6.076172e-05 3.038086e-05
[134,] 0.9999577 8.453410e-05 4.226705e-05
[135,] 0.9999486 1.028924e-04 5.144622e-05
[136,] 0.9999286 1.428075e-04 7.140375e-05
[137,] 0.9999029 1.942417e-04 9.712083e-05
[138,] 0.9999018 1.964063e-04 9.820314e-05
[139,] 0.9998743 2.513122e-04 1.256561e-04
[140,] 0.9998384 3.231039e-04 1.615520e-04
[141,] 0.9999257 1.486974e-04 7.434868e-05
[142,] 0.9999411 1.177356e-04 5.886780e-05
[143,] 0.9999195 1.609710e-04 8.048552e-05
[144,] 0.9998904 2.191939e-04 1.095969e-04
[145,] 0.9999215 1.569318e-04 7.846590e-05
[146,] 0.9999052 1.895684e-04 9.478418e-05
[147,] 0.9998681 2.637973e-04 1.318986e-04
[148,] 0.9999881 2.382869e-05 1.191434e-05
[149,] 0.9999860 2.806634e-05 1.403317e-05
[150,] 0.9999837 3.257177e-05 1.628589e-05
[151,] 0.9999788 4.240861e-05 2.120430e-05
[152,] 0.9999793 4.148120e-05 2.074060e-05
[153,] 0.9999792 4.162796e-05 2.081398e-05
[154,] 0.9999994 1.246772e-06 6.233862e-07
[155,] 0.9999997 5.788306e-07 2.894153e-07
[156,] 0.9999999 1.829092e-07 9.145459e-08
[157,] 1.0000000 9.415688e-08 4.707844e-08
[158,] 1.0000000 4.527018e-08 2.263509e-08
[159,] 1.0000000 6.095488e-08 3.047744e-08
[160,] 1.0000000 3.423980e-08 1.711990e-08
[161,] 1.0000000 5.261332e-08 2.630666e-08
[162,] 1.0000000 3.651903e-08 1.825951e-08
[163,] 1.0000000 5.974187e-08 2.987093e-08
[164,] 1.0000000 6.463137e-09 3.231569e-09
[165,] 1.0000000 2.610830e-10 1.305415e-10
[166,] 1.0000000 3.685311e-10 1.842656e-10
[167,] 1.0000000 1.882911e-10 9.414554e-11
[168,] 1.0000000 8.111219e-11 4.055609e-11
[169,] 1.0000000 6.488127e-12 3.244064e-12
[170,] 1.0000000 1.029214e-12 5.146069e-13
[171,] 1.0000000 1.906864e-12 9.534320e-13
[172,] 1.0000000 3.234438e-12 1.617219e-12
[173,] 1.0000000 5.625792e-12 2.812896e-12
[174,] 1.0000000 8.920633e-13 4.460317e-13
[175,] 1.0000000 1.347269e-12 6.736344e-13
[176,] 1.0000000 1.114220e-12 5.571098e-13
[177,] 1.0000000 2.219317e-12 1.109659e-12
[178,] 1.0000000 2.716543e-12 1.358272e-12
[179,] 1.0000000 2.974646e-14 1.487323e-14
[180,] 1.0000000 5.563017e-14 2.781509e-14
[181,] 1.0000000 1.139977e-13 5.699884e-14
[182,] 1.0000000 2.313338e-13 1.156669e-13
[183,] 1.0000000 6.649080e-14 3.324540e-14
[184,] 1.0000000 1.254419e-13 6.272097e-14
[185,] 1.0000000 1.110835e-13 5.554177e-14
[186,] 1.0000000 1.897118e-13 9.485588e-14
[187,] 1.0000000 3.939298e-13 1.969649e-13
[188,] 1.0000000 4.566605e-13 2.283302e-13
[189,] 1.0000000 3.928280e-13 1.964140e-13
[190,] 1.0000000 3.064611e-13 1.532306e-13
[191,] 1.0000000 6.326824e-13 3.163412e-13
[192,] 1.0000000 1.212269e-12 6.061347e-13
[193,] 1.0000000 2.403311e-12 1.201655e-12
[194,] 1.0000000 4.496488e-12 2.248244e-12
[195,] 1.0000000 7.078172e-12 3.539086e-12
[196,] 1.0000000 1.211886e-11 6.059431e-12
[197,] 1.0000000 1.212581e-11 6.062903e-12
[198,] 1.0000000 2.430032e-11 1.215016e-11
[199,] 1.0000000 4.443165e-11 2.221582e-11
[200,] 1.0000000 5.813169e-11 2.906584e-11
[201,] 1.0000000 1.145212e-10 5.726059e-11
[202,] 1.0000000 8.054944e-13 4.027472e-13
[203,] 1.0000000 3.524510e-13 1.762255e-13
[204,] 1.0000000 1.611436e-13 8.057179e-14
[205,] 1.0000000 1.737372e-13 8.686859e-14
[206,] 1.0000000 6.078063e-14 3.039031e-14
[207,] 1.0000000 1.368012e-13 6.840060e-14
[208,] 1.0000000 3.133732e-13 1.566866e-13
[209,] 1.0000000 2.841564e-13 1.420782e-13
[210,] 1.0000000 4.869957e-13 2.434978e-13
[211,] 1.0000000 9.466356e-13 4.733178e-13
[212,] 1.0000000 1.700602e-12 8.503012e-13
[213,] 1.0000000 3.832986e-12 1.916493e-12
[214,] 1.0000000 5.037279e-12 2.518640e-12
[215,] 1.0000000 1.129853e-11 5.649267e-12
[216,] 1.0000000 2.319850e-11 1.159925e-11
[217,] 1.0000000 4.592853e-11 2.296427e-11
[218,] 1.0000000 1.014001e-10 5.070006e-11
[219,] 1.0000000 1.615051e-10 8.075257e-11
[220,] 1.0000000 6.922730e-11 3.461365e-11
[221,] 1.0000000 1.410358e-10 7.051790e-11
[222,] 1.0000000 1.960134e-10 9.800669e-11
[223,] 1.0000000 4.031483e-10 2.015742e-10
[224,] 1.0000000 4.385276e-10 2.192638e-10
[225,] 1.0000000 5.149181e-10 2.574591e-10
[226,] 1.0000000 1.081216e-09 5.406081e-10
[227,] 1.0000000 2.220270e-09 1.110135e-09
[228,] 1.0000000 3.896877e-09 1.948438e-09
[229,] 1.0000000 2.801935e-09 1.400967e-09
[230,] 1.0000000 2.733969e-09 1.366985e-09
[231,] 1.0000000 1.132560e-11 5.662802e-12
[232,] 1.0000000 2.161369e-11 1.080684e-11
[233,] 1.0000000 5.343023e-11 2.671512e-11
[234,] 1.0000000 3.912031e-11 1.956015e-11
[235,] 1.0000000 7.548995e-11 3.774498e-11
[236,] 1.0000000 6.686227e-11 3.343114e-11
[237,] 1.0000000 2.848078e-11 1.424039e-11
[238,] 1.0000000 4.865984e-11 2.432992e-11
[239,] 1.0000000 1.329536e-10 6.647682e-11
[240,] 1.0000000 3.282544e-10 1.641272e-10
[241,] 1.0000000 8.544767e-10 4.272384e-10
[242,] 1.0000000 2.097188e-09 1.048594e-09
[243,] 1.0000000 4.553665e-09 2.276833e-09
[244,] 1.0000000 8.095559e-09 4.047779e-09
[245,] 1.0000000 7.232135e-09 3.616067e-09
[246,] 1.0000000 1.588716e-08 7.943579e-09
[247,] 1.0000000 3.832605e-08 1.916303e-08
[248,] 1.0000000 9.700223e-08 4.850112e-08
[249,] 0.9999999 2.312373e-07 1.156186e-07
[250,] 0.9999997 5.399013e-07 2.699507e-07
[251,] 0.9999996 8.323345e-07 4.161673e-07
[252,] 0.9999991 1.720237e-06 8.601183e-07
[253,] 0.9999981 3.717006e-06 1.858503e-06
[254,] 0.9999968 6.464127e-06 3.232064e-06
[255,] 0.9999984 3.262161e-06 1.631081e-06
[256,] 0.9999960 8.047740e-06 4.023870e-06
[257,] 0.9999918 1.641586e-05 8.207929e-06
[258,] 0.9999829 3.417352e-05 1.708676e-05
[259,] 0.9999816 3.680206e-05 1.840103e-05
[260,] 0.9999669 6.620903e-05 3.310452e-05
[261,] 0.9999521 9.580653e-05 4.790326e-05
[262,] 0.9999390 1.220725e-04 6.103624e-05
[263,] 0.9999945 1.102734e-05 5.513671e-06
[264,] 0.9999946 1.080066e-05 5.400329e-06
[265,] 0.9999890 2.207966e-05 1.103983e-05
[266,] 0.9999658 6.842003e-05 3.421002e-05
[267,] 0.9998975 2.049568e-04 1.024784e-04
[268,] 0.9997178 5.643016e-04 2.821508e-04
[269,] 0.9991801 1.639790e-03 8.198948e-04
[270,] 0.9982126 3.574724e-03 1.787362e-03
[271,] 0.9956564 8.687176e-03 4.343588e-03
[272,] 0.9931286 1.374279e-02 6.871393e-03
[273,] 0.9867322 2.653555e-02 1.326777e-02
[274,] 0.9780793 4.384149e-02 2.192075e-02
[275,] 0.9534419 9.311620e-02 4.655810e-02
[276,] 0.8804682 2.390637e-01 1.195318e-01
> postscript(file="/var/wessaorg/rcomp/tmp/174fa1355345007.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/22jd21355345007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3v5g51355345007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4dtki1355345007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5a9pv1355345007.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
5.767726359 -13.054232280 -3.988778382 -9.373432563 3.839114779
6 7 8 9 10
-20.007167670 47.635722273 -10.116190644 3.597850540 -6.213174377
11 12 13 14 15
11.875824618 8.261564039 -15.721441336 -6.216898560 16.417402675
16 17 18 19 20
1.885943341 3.197258679 8.388023416 -1.697468743 -4.249737810
21 22 23 24 25
-2.421217910 4.431738591 45.730101410 7.316943442 -15.766320496
26 27 28 29 30
-8.745082618 -11.038437582 -0.285562222 9.710096087 3.461247748
31 32 33 34 35
15.296225187 0.260104829 -9.019552559 9.306986225 -14.254312653
36 37 38 39 40
23.412981405 7.470708135 17.870456287 28.106575837 -0.546837994
41 42 43 44 45
2.413708647 8.654581371 -6.368606131 2.025671262 26.579425404
46 47 48 49 50
-6.080229385 2.810317023 -3.856204066 -4.112441392 -21.166611988
51 52 53 54 55
31.157240585 -10.933623524 -5.819863137 5.082837738 -3.115017325
56 57 58 59 60
-0.122682641 -1.213138093 -19.283499669 -2.691064303 -1.452407505
61 62 63 64 65
17.912168882 -3.415290706 19.582813608 4.438728487 -7.083688187
66 67 68 69 70
3.781802058 8.853551126 10.543304669 1.810694632 -2.941206700
71 72 73 74 75
4.137314175 5.171542613 9.709859994 -21.702713706 -14.636733372
76 77 78 79 80
2.566018789 -7.971883152 -1.090562091 -5.945843817 -0.726350077
81 82 83 84 85
2.802585124 -5.810235751 23.115591999 14.282600504 -32.404297643
86 87 88 89 90
-4.007004789 -3.149740396 2.826653133 30.246993456 1.436047829
91 92 93 94 95
-3.450190950 2.733553551 4.889132443 -10.412658796 4.084224178
96 97 98 99 100
9.291181739 4.647432462 -27.864034655 10.374654425 -4.518486227
101 102 103 104 105
0.906130506 15.214869034 13.739682565 -1.535013044 -0.924291463
106 107 108 109 110
0.959156425 -10.760538884 -1.965946245 20.084869729 -7.015675826
111 112 113 114 115
7.054699006 -23.186942154 -10.618376878 8.655814193 -16.853965561
116 117 118 119 120
11.616921934 10.850837666 23.995746176 -32.484527789 -5.794379541
121 122 123 124 125
3.886613888 -11.155811517 0.425824378 -33.757503057 8.906718892
126 127 128 129 130
6.012433700 0.102201146 -6.581648976 4.370478681 4.915924755
131 132 133 134 135
-4.014553452 -6.117019249 0.694431597 -10.249254607 -4.240084565
136 137 138 139 140
30.699334368 3.656559646 15.830238284 -13.418890991 -2.214580071
141 142 143 144 145
-7.402980251 -2.607994774 2.962871221 9.373832222 -6.679659943
146 147 148 149 150
-5.834966331 -21.499042099 -13.830390983 -3.168121143 -3.401064230
151 152 153 154 155
14.494626304 -8.787997514 0.488155512 29.364708664 5.813796901
156 157 158 159 160
6.768772586 4.191371526 11.583544414 -12.370192143 -34.209198177
161 162 163 164 165
16.401563086 -22.469195615 -14.366734494 14.767492298 -8.718787502
166 167 168 169 170
10.416318335 -0.090999450 -14.483364708 -1.881724440 23.929168053
171 172 173 174 175
22.252302743 -0.186423798 12.889516854 6.136044761 -30.931795022
176 177 178 179 180
18.289750590 -6.321336488 3.095831598 -6.770460652 17.630209884
181 182 183 184 185
-5.181296604 -11.994425589 2.504097759 2.347478532 15.762218016
186 187 188 189 190
2.430416114 5.278081300 4.197920933 12.922051677 -8.952189953
191 192 193 194 195
2.580980095 2.390509728 1.871883996 -12.984031004 3.332921885
196 197 198 199 200
9.634039155 -3.782577976 -5.513227566 -5.743812452 -5.461767607
201 202 203 204 205
-7.524842904 -8.090502229 6.385155608 -3.061895114 0.750281615
206 207 208 209 210
-9.517418989 -3.340896480 20.427045281 8.059012309 6.754119427
211 212 213 214 215
8.768356282 8.626803457 -3.834664182 -2.806530734 -14.460550408
216 217 218 219 220
-8.133009401 -5.344079301 -6.300508228 0.002018764 5.580998509
221 222 223 224 225
-4.228385811 -9.542666847 -0.865685453 -3.077430603 -5.797382501
226 227 228 229 230
7.361176020 2.566811785 -10.145455916 -4.844557003 -12.510236583
231 232 233 234 235
-7.834082799 0.142465236 -6.975367202 -4.918531391 -14.613832211
236 237 238 239 240
-11.207277260 17.663978762 -4.241571452 0.899945068 -9.390209053
241 242 243 244 245
1.660007394 -20.440928358 -10.891861803 -6.084888605 -2.109743969
246 247 248 249 250
-0.993965810 -2.441328875 0.283030939 1.416735352 -5.198044311
251 252 253 254 255
0.928935775 -1.899095735 3.199375048 -3.970304846 -0.464092050
256 257 258 259 260
2.510763510 -3.953444826 0.138913899 -4.237829500 -2.839561635
261 262 263 264 265
-7.808884813 0.296986495 1.713051036 -1.674422903 -9.712188843
266 267 268 269 270
4.649953542 -7.346902338 -6.914678517 12.080205880 -12.496205365
271 272 273 274 275
-4.092045398 -1.916584816 8.068613158 2.342489453 1.972569746
276 277 278 279 280
-3.804306558 -2.989869070 2.030046995 4.451313167 4.718692392
281 282 283 284 285
0.681428487 -7.196408317 6.599901333 5.340880685 -1.871692946
286 287 288 289
-9.815163627 2.975093722 -5.395379853 3.812365443
> postscript(file="/var/wessaorg/rcomp/tmp/66en31355345007.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 5.767726359 NA
1 -13.054232280 5.767726359
2 -3.988778382 -13.054232280
3 -9.373432563 -3.988778382
4 3.839114779 -9.373432563
5 -20.007167670 3.839114779
6 47.635722273 -20.007167670
7 -10.116190644 47.635722273
8 3.597850540 -10.116190644
9 -6.213174377 3.597850540
10 11.875824618 -6.213174377
11 8.261564039 11.875824618
12 -15.721441336 8.261564039
13 -6.216898560 -15.721441336
14 16.417402675 -6.216898560
15 1.885943341 16.417402675
16 3.197258679 1.885943341
17 8.388023416 3.197258679
18 -1.697468743 8.388023416
19 -4.249737810 -1.697468743
20 -2.421217910 -4.249737810
21 4.431738591 -2.421217910
22 45.730101410 4.431738591
23 7.316943442 45.730101410
24 -15.766320496 7.316943442
25 -8.745082618 -15.766320496
26 -11.038437582 -8.745082618
27 -0.285562222 -11.038437582
28 9.710096087 -0.285562222
29 3.461247748 9.710096087
30 15.296225187 3.461247748
31 0.260104829 15.296225187
32 -9.019552559 0.260104829
33 9.306986225 -9.019552559
34 -14.254312653 9.306986225
35 23.412981405 -14.254312653
36 7.470708135 23.412981405
37 17.870456287 7.470708135
38 28.106575837 17.870456287
39 -0.546837994 28.106575837
40 2.413708647 -0.546837994
41 8.654581371 2.413708647
42 -6.368606131 8.654581371
43 2.025671262 -6.368606131
44 26.579425404 2.025671262
45 -6.080229385 26.579425404
46 2.810317023 -6.080229385
47 -3.856204066 2.810317023
48 -4.112441392 -3.856204066
49 -21.166611988 -4.112441392
50 31.157240585 -21.166611988
51 -10.933623524 31.157240585
52 -5.819863137 -10.933623524
53 5.082837738 -5.819863137
54 -3.115017325 5.082837738
55 -0.122682641 -3.115017325
56 -1.213138093 -0.122682641
57 -19.283499669 -1.213138093
58 -2.691064303 -19.283499669
59 -1.452407505 -2.691064303
60 17.912168882 -1.452407505
61 -3.415290706 17.912168882
62 19.582813608 -3.415290706
63 4.438728487 19.582813608
64 -7.083688187 4.438728487
65 3.781802058 -7.083688187
66 8.853551126 3.781802058
67 10.543304669 8.853551126
68 1.810694632 10.543304669
69 -2.941206700 1.810694632
70 4.137314175 -2.941206700
71 5.171542613 4.137314175
72 9.709859994 5.171542613
73 -21.702713706 9.709859994
74 -14.636733372 -21.702713706
75 2.566018789 -14.636733372
76 -7.971883152 2.566018789
77 -1.090562091 -7.971883152
78 -5.945843817 -1.090562091
79 -0.726350077 -5.945843817
80 2.802585124 -0.726350077
81 -5.810235751 2.802585124
82 23.115591999 -5.810235751
83 14.282600504 23.115591999
84 -32.404297643 14.282600504
85 -4.007004789 -32.404297643
86 -3.149740396 -4.007004789
87 2.826653133 -3.149740396
88 30.246993456 2.826653133
89 1.436047829 30.246993456
90 -3.450190950 1.436047829
91 2.733553551 -3.450190950
92 4.889132443 2.733553551
93 -10.412658796 4.889132443
94 4.084224178 -10.412658796
95 9.291181739 4.084224178
96 4.647432462 9.291181739
97 -27.864034655 4.647432462
98 10.374654425 -27.864034655
99 -4.518486227 10.374654425
100 0.906130506 -4.518486227
101 15.214869034 0.906130506
102 13.739682565 15.214869034
103 -1.535013044 13.739682565
104 -0.924291463 -1.535013044
105 0.959156425 -0.924291463
106 -10.760538884 0.959156425
107 -1.965946245 -10.760538884
108 20.084869729 -1.965946245
109 -7.015675826 20.084869729
110 7.054699006 -7.015675826
111 -23.186942154 7.054699006
112 -10.618376878 -23.186942154
113 8.655814193 -10.618376878
114 -16.853965561 8.655814193
115 11.616921934 -16.853965561
116 10.850837666 11.616921934
117 23.995746176 10.850837666
118 -32.484527789 23.995746176
119 -5.794379541 -32.484527789
120 3.886613888 -5.794379541
121 -11.155811517 3.886613888
122 0.425824378 -11.155811517
123 -33.757503057 0.425824378
124 8.906718892 -33.757503057
125 6.012433700 8.906718892
126 0.102201146 6.012433700
127 -6.581648976 0.102201146
128 4.370478681 -6.581648976
129 4.915924755 4.370478681
130 -4.014553452 4.915924755
131 -6.117019249 -4.014553452
132 0.694431597 -6.117019249
133 -10.249254607 0.694431597
134 -4.240084565 -10.249254607
135 30.699334368 -4.240084565
136 3.656559646 30.699334368
137 15.830238284 3.656559646
138 -13.418890991 15.830238284
139 -2.214580071 -13.418890991
140 -7.402980251 -2.214580071
141 -2.607994774 -7.402980251
142 2.962871221 -2.607994774
143 9.373832222 2.962871221
144 -6.679659943 9.373832222
145 -5.834966331 -6.679659943
146 -21.499042099 -5.834966331
147 -13.830390983 -21.499042099
148 -3.168121143 -13.830390983
149 -3.401064230 -3.168121143
150 14.494626304 -3.401064230
151 -8.787997514 14.494626304
152 0.488155512 -8.787997514
153 29.364708664 0.488155512
154 5.813796901 29.364708664
155 6.768772586 5.813796901
156 4.191371526 6.768772586
157 11.583544414 4.191371526
158 -12.370192143 11.583544414
159 -34.209198177 -12.370192143
160 16.401563086 -34.209198177
161 -22.469195615 16.401563086
162 -14.366734494 -22.469195615
163 14.767492298 -14.366734494
164 -8.718787502 14.767492298
165 10.416318335 -8.718787502
166 -0.090999450 10.416318335
167 -14.483364708 -0.090999450
168 -1.881724440 -14.483364708
169 23.929168053 -1.881724440
170 22.252302743 23.929168053
171 -0.186423798 22.252302743
172 12.889516854 -0.186423798
173 6.136044761 12.889516854
174 -30.931795022 6.136044761
175 18.289750590 -30.931795022
176 -6.321336488 18.289750590
177 3.095831598 -6.321336488
178 -6.770460652 3.095831598
179 17.630209884 -6.770460652
180 -5.181296604 17.630209884
181 -11.994425589 -5.181296604
182 2.504097759 -11.994425589
183 2.347478532 2.504097759
184 15.762218016 2.347478532
185 2.430416114 15.762218016
186 5.278081300 2.430416114
187 4.197920933 5.278081300
188 12.922051677 4.197920933
189 -8.952189953 12.922051677
190 2.580980095 -8.952189953
191 2.390509728 2.580980095
192 1.871883996 2.390509728
193 -12.984031004 1.871883996
194 3.332921885 -12.984031004
195 9.634039155 3.332921885
196 -3.782577976 9.634039155
197 -5.513227566 -3.782577976
198 -5.743812452 -5.513227566
199 -5.461767607 -5.743812452
200 -7.524842904 -5.461767607
201 -8.090502229 -7.524842904
202 6.385155608 -8.090502229
203 -3.061895114 6.385155608
204 0.750281615 -3.061895114
205 -9.517418989 0.750281615
206 -3.340896480 -9.517418989
207 20.427045281 -3.340896480
208 8.059012309 20.427045281
209 6.754119427 8.059012309
210 8.768356282 6.754119427
211 8.626803457 8.768356282
212 -3.834664182 8.626803457
213 -2.806530734 -3.834664182
214 -14.460550408 -2.806530734
215 -8.133009401 -14.460550408
216 -5.344079301 -8.133009401
217 -6.300508228 -5.344079301
218 0.002018764 -6.300508228
219 5.580998509 0.002018764
220 -4.228385811 5.580998509
221 -9.542666847 -4.228385811
222 -0.865685453 -9.542666847
223 -3.077430603 -0.865685453
224 -5.797382501 -3.077430603
225 7.361176020 -5.797382501
226 2.566811785 7.361176020
227 -10.145455916 2.566811785
228 -4.844557003 -10.145455916
229 -12.510236583 -4.844557003
230 -7.834082799 -12.510236583
231 0.142465236 -7.834082799
232 -6.975367202 0.142465236
233 -4.918531391 -6.975367202
234 -14.613832211 -4.918531391
235 -11.207277260 -14.613832211
236 17.663978762 -11.207277260
237 -4.241571452 17.663978762
238 0.899945068 -4.241571452
239 -9.390209053 0.899945068
240 1.660007394 -9.390209053
241 -20.440928358 1.660007394
242 -10.891861803 -20.440928358
243 -6.084888605 -10.891861803
244 -2.109743969 -6.084888605
245 -0.993965810 -2.109743969
246 -2.441328875 -0.993965810
247 0.283030939 -2.441328875
248 1.416735352 0.283030939
249 -5.198044311 1.416735352
250 0.928935775 -5.198044311
251 -1.899095735 0.928935775
252 3.199375048 -1.899095735
253 -3.970304846 3.199375048
254 -0.464092050 -3.970304846
255 2.510763510 -0.464092050
256 -3.953444826 2.510763510
257 0.138913899 -3.953444826
258 -4.237829500 0.138913899
259 -2.839561635 -4.237829500
260 -7.808884813 -2.839561635
261 0.296986495 -7.808884813
262 1.713051036 0.296986495
263 -1.674422903 1.713051036
264 -9.712188843 -1.674422903
265 4.649953542 -9.712188843
266 -7.346902338 4.649953542
267 -6.914678517 -7.346902338
268 12.080205880 -6.914678517
269 -12.496205365 12.080205880
270 -4.092045398 -12.496205365
271 -1.916584816 -4.092045398
272 8.068613158 -1.916584816
273 2.342489453 8.068613158
274 1.972569746 2.342489453
275 -3.804306558 1.972569746
276 -2.989869070 -3.804306558
277 2.030046995 -2.989869070
278 4.451313167 2.030046995
279 4.718692392 4.451313167
280 0.681428487 4.718692392
281 -7.196408317 0.681428487
282 6.599901333 -7.196408317
283 5.340880685 6.599901333
284 -1.871692946 5.340880685
285 -9.815163627 -1.871692946
286 2.975093722 -9.815163627
287 -5.395379853 2.975093722
288 3.812365443 -5.395379853
289 NA 3.812365443
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -13.054232280 5.767726359
[2,] -3.988778382 -13.054232280
[3,] -9.373432563 -3.988778382
[4,] 3.839114779 -9.373432563
[5,] -20.007167670 3.839114779
[6,] 47.635722273 -20.007167670
[7,] -10.116190644 47.635722273
[8,] 3.597850540 -10.116190644
[9,] -6.213174377 3.597850540
[10,] 11.875824618 -6.213174377
[11,] 8.261564039 11.875824618
[12,] -15.721441336 8.261564039
[13,] -6.216898560 -15.721441336
[14,] 16.417402675 -6.216898560
[15,] 1.885943341 16.417402675
[16,] 3.197258679 1.885943341
[17,] 8.388023416 3.197258679
[18,] -1.697468743 8.388023416
[19,] -4.249737810 -1.697468743
[20,] -2.421217910 -4.249737810
[21,] 4.431738591 -2.421217910
[22,] 45.730101410 4.431738591
[23,] 7.316943442 45.730101410
[24,] -15.766320496 7.316943442
[25,] -8.745082618 -15.766320496
[26,] -11.038437582 -8.745082618
[27,] -0.285562222 -11.038437582
[28,] 9.710096087 -0.285562222
[29,] 3.461247748 9.710096087
[30,] 15.296225187 3.461247748
[31,] 0.260104829 15.296225187
[32,] -9.019552559 0.260104829
[33,] 9.306986225 -9.019552559
[34,] -14.254312653 9.306986225
[35,] 23.412981405 -14.254312653
[36,] 7.470708135 23.412981405
[37,] 17.870456287 7.470708135
[38,] 28.106575837 17.870456287
[39,] -0.546837994 28.106575837
[40,] 2.413708647 -0.546837994
[41,] 8.654581371 2.413708647
[42,] -6.368606131 8.654581371
[43,] 2.025671262 -6.368606131
[44,] 26.579425404 2.025671262
[45,] -6.080229385 26.579425404
[46,] 2.810317023 -6.080229385
[47,] -3.856204066 2.810317023
[48,] -4.112441392 -3.856204066
[49,] -21.166611988 -4.112441392
[50,] 31.157240585 -21.166611988
[51,] -10.933623524 31.157240585
[52,] -5.819863137 -10.933623524
[53,] 5.082837738 -5.819863137
[54,] -3.115017325 5.082837738
[55,] -0.122682641 -3.115017325
[56,] -1.213138093 -0.122682641
[57,] -19.283499669 -1.213138093
[58,] -2.691064303 -19.283499669
[59,] -1.452407505 -2.691064303
[60,] 17.912168882 -1.452407505
[61,] -3.415290706 17.912168882
[62,] 19.582813608 -3.415290706
[63,] 4.438728487 19.582813608
[64,] -7.083688187 4.438728487
[65,] 3.781802058 -7.083688187
[66,] 8.853551126 3.781802058
[67,] 10.543304669 8.853551126
[68,] 1.810694632 10.543304669
[69,] -2.941206700 1.810694632
[70,] 4.137314175 -2.941206700
[71,] 5.171542613 4.137314175
[72,] 9.709859994 5.171542613
[73,] -21.702713706 9.709859994
[74,] -14.636733372 -21.702713706
[75,] 2.566018789 -14.636733372
[76,] -7.971883152 2.566018789
[77,] -1.090562091 -7.971883152
[78,] -5.945843817 -1.090562091
[79,] -0.726350077 -5.945843817
[80,] 2.802585124 -0.726350077
[81,] -5.810235751 2.802585124
[82,] 23.115591999 -5.810235751
[83,] 14.282600504 23.115591999
[84,] -32.404297643 14.282600504
[85,] -4.007004789 -32.404297643
[86,] -3.149740396 -4.007004789
[87,] 2.826653133 -3.149740396
[88,] 30.246993456 2.826653133
[89,] 1.436047829 30.246993456
[90,] -3.450190950 1.436047829
[91,] 2.733553551 -3.450190950
[92,] 4.889132443 2.733553551
[93,] -10.412658796 4.889132443
[94,] 4.084224178 -10.412658796
[95,] 9.291181739 4.084224178
[96,] 4.647432462 9.291181739
[97,] -27.864034655 4.647432462
[98,] 10.374654425 -27.864034655
[99,] -4.518486227 10.374654425
[100,] 0.906130506 -4.518486227
[101,] 15.214869034 0.906130506
[102,] 13.739682565 15.214869034
[103,] -1.535013044 13.739682565
[104,] -0.924291463 -1.535013044
[105,] 0.959156425 -0.924291463
[106,] -10.760538884 0.959156425
[107,] -1.965946245 -10.760538884
[108,] 20.084869729 -1.965946245
[109,] -7.015675826 20.084869729
[110,] 7.054699006 -7.015675826
[111,] -23.186942154 7.054699006
[112,] -10.618376878 -23.186942154
[113,] 8.655814193 -10.618376878
[114,] -16.853965561 8.655814193
[115,] 11.616921934 -16.853965561
[116,] 10.850837666 11.616921934
[117,] 23.995746176 10.850837666
[118,] -32.484527789 23.995746176
[119,] -5.794379541 -32.484527789
[120,] 3.886613888 -5.794379541
[121,] -11.155811517 3.886613888
[122,] 0.425824378 -11.155811517
[123,] -33.757503057 0.425824378
[124,] 8.906718892 -33.757503057
[125,] 6.012433700 8.906718892
[126,] 0.102201146 6.012433700
[127,] -6.581648976 0.102201146
[128,] 4.370478681 -6.581648976
[129,] 4.915924755 4.370478681
[130,] -4.014553452 4.915924755
[131,] -6.117019249 -4.014553452
[132,] 0.694431597 -6.117019249
[133,] -10.249254607 0.694431597
[134,] -4.240084565 -10.249254607
[135,] 30.699334368 -4.240084565
[136,] 3.656559646 30.699334368
[137,] 15.830238284 3.656559646
[138,] -13.418890991 15.830238284
[139,] -2.214580071 -13.418890991
[140,] -7.402980251 -2.214580071
[141,] -2.607994774 -7.402980251
[142,] 2.962871221 -2.607994774
[143,] 9.373832222 2.962871221
[144,] -6.679659943 9.373832222
[145,] -5.834966331 -6.679659943
[146,] -21.499042099 -5.834966331
[147,] -13.830390983 -21.499042099
[148,] -3.168121143 -13.830390983
[149,] -3.401064230 -3.168121143
[150,] 14.494626304 -3.401064230
[151,] -8.787997514 14.494626304
[152,] 0.488155512 -8.787997514
[153,] 29.364708664 0.488155512
[154,] 5.813796901 29.364708664
[155,] 6.768772586 5.813796901
[156,] 4.191371526 6.768772586
[157,] 11.583544414 4.191371526
[158,] -12.370192143 11.583544414
[159,] -34.209198177 -12.370192143
[160,] 16.401563086 -34.209198177
[161,] -22.469195615 16.401563086
[162,] -14.366734494 -22.469195615
[163,] 14.767492298 -14.366734494
[164,] -8.718787502 14.767492298
[165,] 10.416318335 -8.718787502
[166,] -0.090999450 10.416318335
[167,] -14.483364708 -0.090999450
[168,] -1.881724440 -14.483364708
[169,] 23.929168053 -1.881724440
[170,] 22.252302743 23.929168053
[171,] -0.186423798 22.252302743
[172,] 12.889516854 -0.186423798
[173,] 6.136044761 12.889516854
[174,] -30.931795022 6.136044761
[175,] 18.289750590 -30.931795022
[176,] -6.321336488 18.289750590
[177,] 3.095831598 -6.321336488
[178,] -6.770460652 3.095831598
[179,] 17.630209884 -6.770460652
[180,] -5.181296604 17.630209884
[181,] -11.994425589 -5.181296604
[182,] 2.504097759 -11.994425589
[183,] 2.347478532 2.504097759
[184,] 15.762218016 2.347478532
[185,] 2.430416114 15.762218016
[186,] 5.278081300 2.430416114
[187,] 4.197920933 5.278081300
[188,] 12.922051677 4.197920933
[189,] -8.952189953 12.922051677
[190,] 2.580980095 -8.952189953
[191,] 2.390509728 2.580980095
[192,] 1.871883996 2.390509728
[193,] -12.984031004 1.871883996
[194,] 3.332921885 -12.984031004
[195,] 9.634039155 3.332921885
[196,] -3.782577976 9.634039155
[197,] -5.513227566 -3.782577976
[198,] -5.743812452 -5.513227566
[199,] -5.461767607 -5.743812452
[200,] -7.524842904 -5.461767607
[201,] -8.090502229 -7.524842904
[202,] 6.385155608 -8.090502229
[203,] -3.061895114 6.385155608
[204,] 0.750281615 -3.061895114
[205,] -9.517418989 0.750281615
[206,] -3.340896480 -9.517418989
[207,] 20.427045281 -3.340896480
[208,] 8.059012309 20.427045281
[209,] 6.754119427 8.059012309
[210,] 8.768356282 6.754119427
[211,] 8.626803457 8.768356282
[212,] -3.834664182 8.626803457
[213,] -2.806530734 -3.834664182
[214,] -14.460550408 -2.806530734
[215,] -8.133009401 -14.460550408
[216,] -5.344079301 -8.133009401
[217,] -6.300508228 -5.344079301
[218,] 0.002018764 -6.300508228
[219,] 5.580998509 0.002018764
[220,] -4.228385811 5.580998509
[221,] -9.542666847 -4.228385811
[222,] -0.865685453 -9.542666847
[223,] -3.077430603 -0.865685453
[224,] -5.797382501 -3.077430603
[225,] 7.361176020 -5.797382501
[226,] 2.566811785 7.361176020
[227,] -10.145455916 2.566811785
[228,] -4.844557003 -10.145455916
[229,] -12.510236583 -4.844557003
[230,] -7.834082799 -12.510236583
[231,] 0.142465236 -7.834082799
[232,] -6.975367202 0.142465236
[233,] -4.918531391 -6.975367202
[234,] -14.613832211 -4.918531391
[235,] -11.207277260 -14.613832211
[236,] 17.663978762 -11.207277260
[237,] -4.241571452 17.663978762
[238,] 0.899945068 -4.241571452
[239,] -9.390209053 0.899945068
[240,] 1.660007394 -9.390209053
[241,] -20.440928358 1.660007394
[242,] -10.891861803 -20.440928358
[243,] -6.084888605 -10.891861803
[244,] -2.109743969 -6.084888605
[245,] -0.993965810 -2.109743969
[246,] -2.441328875 -0.993965810
[247,] 0.283030939 -2.441328875
[248,] 1.416735352 0.283030939
[249,] -5.198044311 1.416735352
[250,] 0.928935775 -5.198044311
[251,] -1.899095735 0.928935775
[252,] 3.199375048 -1.899095735
[253,] -3.970304846 3.199375048
[254,] -0.464092050 -3.970304846
[255,] 2.510763510 -0.464092050
[256,] -3.953444826 2.510763510
[257,] 0.138913899 -3.953444826
[258,] -4.237829500 0.138913899
[259,] -2.839561635 -4.237829500
[260,] -7.808884813 -2.839561635
[261,] 0.296986495 -7.808884813
[262,] 1.713051036 0.296986495
[263,] -1.674422903 1.713051036
[264,] -9.712188843 -1.674422903
[265,] 4.649953542 -9.712188843
[266,] -7.346902338 4.649953542
[267,] -6.914678517 -7.346902338
[268,] 12.080205880 -6.914678517
[269,] -12.496205365 12.080205880
[270,] -4.092045398 -12.496205365
[271,] -1.916584816 -4.092045398
[272,] 8.068613158 -1.916584816
[273,] 2.342489453 8.068613158
[274,] 1.972569746 2.342489453
[275,] -3.804306558 1.972569746
[276,] -2.989869070 -3.804306558
[277,] 2.030046995 -2.989869070
[278,] 4.451313167 2.030046995
[279,] 4.718692392 4.451313167
[280,] 0.681428487 4.718692392
[281,] -7.196408317 0.681428487
[282,] 6.599901333 -7.196408317
[283,] 5.340880685 6.599901333
[284,] -1.871692946 5.340880685
[285,] -9.815163627 -1.871692946
[286,] 2.975093722 -9.815163627
[287,] -5.395379853 2.975093722
[288,] 3.812365443 -5.395379853
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -13.054232280 5.767726359
2 -3.988778382 -13.054232280
3 -9.373432563 -3.988778382
4 3.839114779 -9.373432563
5 -20.007167670 3.839114779
6 47.635722273 -20.007167670
7 -10.116190644 47.635722273
8 3.597850540 -10.116190644
9 -6.213174377 3.597850540
10 11.875824618 -6.213174377
11 8.261564039 11.875824618
12 -15.721441336 8.261564039
13 -6.216898560 -15.721441336
14 16.417402675 -6.216898560
15 1.885943341 16.417402675
16 3.197258679 1.885943341
17 8.388023416 3.197258679
18 -1.697468743 8.388023416
19 -4.249737810 -1.697468743
20 -2.421217910 -4.249737810
21 4.431738591 -2.421217910
22 45.730101410 4.431738591
23 7.316943442 45.730101410
24 -15.766320496 7.316943442
25 -8.745082618 -15.766320496
26 -11.038437582 -8.745082618
27 -0.285562222 -11.038437582
28 9.710096087 -0.285562222
29 3.461247748 9.710096087
30 15.296225187 3.461247748
31 0.260104829 15.296225187
32 -9.019552559 0.260104829
33 9.306986225 -9.019552559
34 -14.254312653 9.306986225
35 23.412981405 -14.254312653
36 7.470708135 23.412981405
37 17.870456287 7.470708135
38 28.106575837 17.870456287
39 -0.546837994 28.106575837
40 2.413708647 -0.546837994
41 8.654581371 2.413708647
42 -6.368606131 8.654581371
43 2.025671262 -6.368606131
44 26.579425404 2.025671262
45 -6.080229385 26.579425404
46 2.810317023 -6.080229385
47 -3.856204066 2.810317023
48 -4.112441392 -3.856204066
49 -21.166611988 -4.112441392
50 31.157240585 -21.166611988
51 -10.933623524 31.157240585
52 -5.819863137 -10.933623524
53 5.082837738 -5.819863137
54 -3.115017325 5.082837738
55 -0.122682641 -3.115017325
56 -1.213138093 -0.122682641
57 -19.283499669 -1.213138093
58 -2.691064303 -19.283499669
59 -1.452407505 -2.691064303
60 17.912168882 -1.452407505
61 -3.415290706 17.912168882
62 19.582813608 -3.415290706
63 4.438728487 19.582813608
64 -7.083688187 4.438728487
65 3.781802058 -7.083688187
66 8.853551126 3.781802058
67 10.543304669 8.853551126
68 1.810694632 10.543304669
69 -2.941206700 1.810694632
70 4.137314175 -2.941206700
71 5.171542613 4.137314175
72 9.709859994 5.171542613
73 -21.702713706 9.709859994
74 -14.636733372 -21.702713706
75 2.566018789 -14.636733372
76 -7.971883152 2.566018789
77 -1.090562091 -7.971883152
78 -5.945843817 -1.090562091
79 -0.726350077 -5.945843817
80 2.802585124 -0.726350077
81 -5.810235751 2.802585124
82 23.115591999 -5.810235751
83 14.282600504 23.115591999
84 -32.404297643 14.282600504
85 -4.007004789 -32.404297643
86 -3.149740396 -4.007004789
87 2.826653133 -3.149740396
88 30.246993456 2.826653133
89 1.436047829 30.246993456
90 -3.450190950 1.436047829
91 2.733553551 -3.450190950
92 4.889132443 2.733553551
93 -10.412658796 4.889132443
94 4.084224178 -10.412658796
95 9.291181739 4.084224178
96 4.647432462 9.291181739
97 -27.864034655 4.647432462
98 10.374654425 -27.864034655
99 -4.518486227 10.374654425
100 0.906130506 -4.518486227
101 15.214869034 0.906130506
102 13.739682565 15.214869034
103 -1.535013044 13.739682565
104 -0.924291463 -1.535013044
105 0.959156425 -0.924291463
106 -10.760538884 0.959156425
107 -1.965946245 -10.760538884
108 20.084869729 -1.965946245
109 -7.015675826 20.084869729
110 7.054699006 -7.015675826
111 -23.186942154 7.054699006
112 -10.618376878 -23.186942154
113 8.655814193 -10.618376878
114 -16.853965561 8.655814193
115 11.616921934 -16.853965561
116 10.850837666 11.616921934
117 23.995746176 10.850837666
118 -32.484527789 23.995746176
119 -5.794379541 -32.484527789
120 3.886613888 -5.794379541
121 -11.155811517 3.886613888
122 0.425824378 -11.155811517
123 -33.757503057 0.425824378
124 8.906718892 -33.757503057
125 6.012433700 8.906718892
126 0.102201146 6.012433700
127 -6.581648976 0.102201146
128 4.370478681 -6.581648976
129 4.915924755 4.370478681
130 -4.014553452 4.915924755
131 -6.117019249 -4.014553452
132 0.694431597 -6.117019249
133 -10.249254607 0.694431597
134 -4.240084565 -10.249254607
135 30.699334368 -4.240084565
136 3.656559646 30.699334368
137 15.830238284 3.656559646
138 -13.418890991 15.830238284
139 -2.214580071 -13.418890991
140 -7.402980251 -2.214580071
141 -2.607994774 -7.402980251
142 2.962871221 -2.607994774
143 9.373832222 2.962871221
144 -6.679659943 9.373832222
145 -5.834966331 -6.679659943
146 -21.499042099 -5.834966331
147 -13.830390983 -21.499042099
148 -3.168121143 -13.830390983
149 -3.401064230 -3.168121143
150 14.494626304 -3.401064230
151 -8.787997514 14.494626304
152 0.488155512 -8.787997514
153 29.364708664 0.488155512
154 5.813796901 29.364708664
155 6.768772586 5.813796901
156 4.191371526 6.768772586
157 11.583544414 4.191371526
158 -12.370192143 11.583544414
159 -34.209198177 -12.370192143
160 16.401563086 -34.209198177
161 -22.469195615 16.401563086
162 -14.366734494 -22.469195615
163 14.767492298 -14.366734494
164 -8.718787502 14.767492298
165 10.416318335 -8.718787502
166 -0.090999450 10.416318335
167 -14.483364708 -0.090999450
168 -1.881724440 -14.483364708
169 23.929168053 -1.881724440
170 22.252302743 23.929168053
171 -0.186423798 22.252302743
172 12.889516854 -0.186423798
173 6.136044761 12.889516854
174 -30.931795022 6.136044761
175 18.289750590 -30.931795022
176 -6.321336488 18.289750590
177 3.095831598 -6.321336488
178 -6.770460652 3.095831598
179 17.630209884 -6.770460652
180 -5.181296604 17.630209884
181 -11.994425589 -5.181296604
182 2.504097759 -11.994425589
183 2.347478532 2.504097759
184 15.762218016 2.347478532
185 2.430416114 15.762218016
186 5.278081300 2.430416114
187 4.197920933 5.278081300
188 12.922051677 4.197920933
189 -8.952189953 12.922051677
190 2.580980095 -8.952189953
191 2.390509728 2.580980095
192 1.871883996 2.390509728
193 -12.984031004 1.871883996
194 3.332921885 -12.984031004
195 9.634039155 3.332921885
196 -3.782577976 9.634039155
197 -5.513227566 -3.782577976
198 -5.743812452 -5.513227566
199 -5.461767607 -5.743812452
200 -7.524842904 -5.461767607
201 -8.090502229 -7.524842904
202 6.385155608 -8.090502229
203 -3.061895114 6.385155608
204 0.750281615 -3.061895114
205 -9.517418989 0.750281615
206 -3.340896480 -9.517418989
207 20.427045281 -3.340896480
208 8.059012309 20.427045281
209 6.754119427 8.059012309
210 8.768356282 6.754119427
211 8.626803457 8.768356282
212 -3.834664182 8.626803457
213 -2.806530734 -3.834664182
214 -14.460550408 -2.806530734
215 -8.133009401 -14.460550408
216 -5.344079301 -8.133009401
217 -6.300508228 -5.344079301
218 0.002018764 -6.300508228
219 5.580998509 0.002018764
220 -4.228385811 5.580998509
221 -9.542666847 -4.228385811
222 -0.865685453 -9.542666847
223 -3.077430603 -0.865685453
224 -5.797382501 -3.077430603
225 7.361176020 -5.797382501
226 2.566811785 7.361176020
227 -10.145455916 2.566811785
228 -4.844557003 -10.145455916
229 -12.510236583 -4.844557003
230 -7.834082799 -12.510236583
231 0.142465236 -7.834082799
232 -6.975367202 0.142465236
233 -4.918531391 -6.975367202
234 -14.613832211 -4.918531391
235 -11.207277260 -14.613832211
236 17.663978762 -11.207277260
237 -4.241571452 17.663978762
238 0.899945068 -4.241571452
239 -9.390209053 0.899945068
240 1.660007394 -9.390209053
241 -20.440928358 1.660007394
242 -10.891861803 -20.440928358
243 -6.084888605 -10.891861803
244 -2.109743969 -6.084888605
245 -0.993965810 -2.109743969
246 -2.441328875 -0.993965810
247 0.283030939 -2.441328875
248 1.416735352 0.283030939
249 -5.198044311 1.416735352
250 0.928935775 -5.198044311
251 -1.899095735 0.928935775
252 3.199375048 -1.899095735
253 -3.970304846 3.199375048
254 -0.464092050 -3.970304846
255 2.510763510 -0.464092050
256 -3.953444826 2.510763510
257 0.138913899 -3.953444826
258 -4.237829500 0.138913899
259 -2.839561635 -4.237829500
260 -7.808884813 -2.839561635
261 0.296986495 -7.808884813
262 1.713051036 0.296986495
263 -1.674422903 1.713051036
264 -9.712188843 -1.674422903
265 4.649953542 -9.712188843
266 -7.346902338 4.649953542
267 -6.914678517 -7.346902338
268 12.080205880 -6.914678517
269 -12.496205365 12.080205880
270 -4.092045398 -12.496205365
271 -1.916584816 -4.092045398
272 8.068613158 -1.916584816
273 2.342489453 8.068613158
274 1.972569746 2.342489453
275 -3.804306558 1.972569746
276 -2.989869070 -3.804306558
277 2.030046995 -2.989869070
278 4.451313167 2.030046995
279 4.718692392 4.451313167
280 0.681428487 4.718692392
281 -7.196408317 0.681428487
282 6.599901333 -7.196408317
283 5.340880685 6.599901333
284 -1.871692946 5.340880685
285 -9.815163627 -1.871692946
286 2.975093722 -9.815163627
287 -5.395379853 2.975093722
288 3.812365443 -5.395379853
> 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/7m7tr1355345007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/83kqs1355345007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9hoqi1355345007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/1029s01355345007.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11r5y81355345007.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/124sjp1355345007.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/135dv61355345007.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/14458c1355345007.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/1544kh1355345007.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/166atp1355345007.tab")
+ }
>
> try(system("convert tmp/174fa1355345007.ps tmp/174fa1355345007.png",intern=TRUE))
character(0)
> try(system("convert tmp/22jd21355345007.ps tmp/22jd21355345007.png",intern=TRUE))
character(0)
> try(system("convert tmp/3v5g51355345007.ps tmp/3v5g51355345007.png",intern=TRUE))
character(0)
> try(system("convert tmp/4dtki1355345007.ps tmp/4dtki1355345007.png",intern=TRUE))
character(0)
> try(system("convert tmp/5a9pv1355345007.ps tmp/5a9pv1355345007.png",intern=TRUE))
character(0)
> try(system("convert tmp/66en31355345007.ps tmp/66en31355345007.png",intern=TRUE))
character(0)
> try(system("convert tmp/7m7tr1355345007.ps tmp/7m7tr1355345007.png",intern=TRUE))
character(0)
> try(system("convert tmp/83kqs1355345007.ps tmp/83kqs1355345007.png",intern=TRUE))
character(0)
> try(system("convert tmp/9hoqi1355345007.ps tmp/9hoqi1355345007.png",intern=TRUE))
character(0)
> try(system("convert tmp/1029s01355345007.ps tmp/1029s01355345007.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
11.043 0.884 11.983