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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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.
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+ ,'year')
+ ,1:287))
> y <- array(NA,dim=c(5,287),dimnames=list(c('TimeRfc','logins','bloggedcomp','totsize','year'),1:287))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '1'
> #'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
TimeRfc logins bloggedcomp totsize year
1 101645 63 20 17140 1
2 101011 34 30 27570 1
3 7176 17 0 1423 1
4 96560 76 42 22996 1
5 175824 107 57 39992 1
6 341570 168 94 117105 1
7 103597 43 27 23789 1
8 112611 41 46 26706 1
9 85574 34 37 24266 1
10 220801 75 51 44418 1
11 92661 61 40 35232 1
12 133328 55 56 40909 1
13 61361 77 27 13294 1
14 125930 75 37 32387 1
15 82316 32 27 21233 1
16 102010 53 28 44332 1
17 101523 42 59 61056 1
18 41566 35 0 13497 1
19 99923 66 44 32334 1
20 22648 19 12 44339 1
21 46698 45 14 10288 1
22 131698 65 60 65622 1
23 91735 35 7 16563 1
24 79863 37 29 29011 1
25 108043 62 45 34553 1
26 98866 18 25 23517 1
27 120445 118 36 51009 1
28 116048 64 50 33416 1
29 250047 81 41 83305 1
30 136084 30 27 27142 1
31 92499 32 25 21399 1
32 135781 31 45 24874 1
33 74408 67 29 34988 1
34 81240 66 58 45549 1
35 133368 36 37 32755 1
36 98146 40 15 27114 1
37 79619 43 42 20760 1
38 59194 31 7 37636 1
39 139942 42 54 65461 1
40 118612 46 54 30080 1
41 72880 33 14 24094 1
42 65475 18 16 69008 1
43 99643 55 33 54968 1
44 71965 35 32 46090 1
45 77272 59 21 27507 1
46 49289 19 15 10672 1
47 135131 66 38 34029 1
48 108446 60 22 46300 1
49 89746 36 28 24760 1
50 44296 25 10 18779 1
51 77648 47 31 21280 1
52 181528 54 32 40662 1
53 134019 53 32 28987 1
54 124064 40 43 22827 1
55 92630 40 27 18513 1
56 121848 39 37 30594 1
57 52915 14 20 24006 1
58 81872 45 32 27913 1
59 58981 36 0 42744 1
60 53515 28 5 12934 1
61 60812 44 26 22574 1
62 56375 30 10 41385 1
63 65490 22 27 18653 1
64 80949 17 11 18472 1
65 76302 31 29 30976 1
66 104011 55 25 63339 1
67 98104 54 55 25568 1
68 67989 21 23 33747 1
69 30989 14 5 4154 1
70 135458 81 43 19474 1
71 73504 35 23 35130 1
72 63123 43 34 39067 1
73 61254 46 36 13310 1
74 74914 30 35 65892 1
75 31774 23 0 4143 1
76 81437 38 37 28579 1
77 87186 54 28 51776 1
78 50090 20 16 21152 1
79 65745 53 26 38084 1
80 56653 45 38 27717 1
81 158399 39 23 32928 1
82 46455 20 22 11342 1
83 73624 24 30 19499 1
84 38395 31 16 16380 1
85 91899 35 18 36874 1
86 139526 151 28 48259 1
87 52164 52 32 16734 1
88 51567 30 21 28207 1
89 70551 31 23 30143 1
90 84856 29 29 41369 1
91 102538 57 50 45833 1
92 86678 40 12 29156 1
93 85709 44 21 35944 1
94 34662 25 18 36278 1
95 150580 77 27 45588 1
96 99611 35 41 45097 1
97 19349 11 13 3895 1
98 99373 63 12 28394 1
99 86230 44 21 18632 1
100 30837 19 8 2325 1
101 31706 13 26 25139 1
102 89806 42 27 27975 1
103 62088 38 13 14483 1
104 40151 29 16 13127 1
105 27634 20 2 5839 1
106 76990 27 42 24069 1
107 37460 20 5 3738 1
108 54157 19 37 18625 1
109 49862 37 17 36341 1
110 84337 26 38 24548 1
111 64175 42 37 21792 1
112 59382 49 29 26263 1
113 119308 30 32 23686 1
114 76702 49 35 49303 1
115 103425 67 17 25659 1
116 70344 28 20 28904 1
117 43410 19 7 2781 1
118 104838 49 46 29236 1
119 62215 27 24 19546 1
120 69304 30 40 22818 1
121 53117 22 3 32689 1
122 19764 12 10 5752 1
123 86680 31 37 22197 1
124 84105 20 17 20055 1
125 77945 20 28 25272 1
126 89113 39 19 82206 1
127 91005 29 29 32073 1
128 40248 16 8 5444 1
129 64187 27 10 20154 1
130 50857 21 15 36944 1
131 56613 19 15 8019 1
132 210907 56 79 112285 0
133 120982 56 58 84786 0
134 176508 54 60 83123 0
135 179321 89 108 101193 0
136 123185 40 49 38361 0
137 52746 25 0 68504 0
138 385534 92 121 119182 0
139 33170 18 1 22807 0
140 149061 44 43 116174 0
141 165446 33 69 57635 0
142 237213 84 78 66198 0
143 173326 88 86 71701 0
144 133131 55 44 57793 0
145 258873 60 104 80444 0
146 180083 66 63 53855 0
147 324799 154 158 97668 0
148 230964 53 102 133824 0
149 236785 119 77 101481 0
150 135473 41 82 99645 0
151 202925 61 115 114789 0
152 215147 58 101 99052 0
153 344297 75 80 67654 0
154 153935 33 50 65553 0
155 132943 40 83 97500 0
156 174724 92 123 69112 0
157 174415 100 73 82753 0
158 225548 112 81 85323 0
159 223632 73 105 72654 0
160 124817 40 47 30727 0
161 221698 45 105 77873 0
162 210767 60 94 117478 0
163 170266 62 44 74007 0
164 260561 75 114 90183 0
165 84853 31 38 61542 0
166 294424 77 107 101494 0
167 215641 46 71 55813 0
168 325107 99 84 79215 0
169 167542 66 59 55461 0
170 106408 30 33 31081 0
171 265769 146 96 83122 0
172 269651 67 106 70106 0
173 149112 56 56 60578 0
174 152871 58 59 79892 0
175 111665 34 39 49810 0
176 116408 61 34 71570 0
177 362301 119 76 100708 0
178 78800 42 20 33032 0
179 183167 66 91 82875 0
180 277965 89 115 139077 0
181 150629 44 85 71595 0
182 168809 66 76 72260 0
183 24188 24 8 5950 0
184 329267 259 79 115762 0
185 65029 17 21 32551 0
186 101097 64 30 31701 0
187 218946 41 76 80670 0
188 244052 68 101 143558 0
189 233328 132 92 120733 0
190 256462 105 123 105195 0
191 206161 71 75 73107 0
192 311473 112 128 132068 0
193 235800 94 105 149193 0
194 177939 82 55 46821 0
195 207176 70 56 87011 0
196 196553 57 41 95260 0
197 174184 53 72 55183 0
198 143246 103 67 106671 0
199 187559 121 75 73511 0
200 187681 62 114 92945 0
201 119016 52 118 78664 0
202 182192 52 77 70054 0
203 73566 32 22 22618 0
204 194979 62 66 74011 0
205 167488 45 69 83737 0
206 143756 46 105 69094 0
207 275541 63 116 93133 0
208 243199 75 88 95536 0
209 182999 88 73 225920 0
210 135649 46 99 62133 0
211 152299 53 62 61370 0
212 120221 37 53 43836 0
213 346485 90 118 106117 0
214 145790 63 30 38692 0
215 193339 78 100 84651 0
216 80953 25 49 56622 0
217 122774 45 24 15986 0
218 130585 46 67 95364 0
219 286468 144 57 89691 0
220 241066 82 75 67267 0
221 148446 91 135 126846 0
222 204713 71 68 41140 0
223 182079 63 124 102860 0
224 140344 53 33 51715 0
225 220516 62 98 55801 0
226 243060 63 58 111813 0
227 162765 32 68 120293 0
228 182613 39 81 138599 0
229 232138 62 131 161647 0
230 265318 117 110 115929 0
231 310839 92 130 162901 0
232 225060 93 93 109825 0
233 232317 54 118 129838 0
234 144966 144 39 37510 0
235 43287 14 13 43750 0
236 155754 61 74 40652 0
237 164709 109 81 87771 0
238 201940 38 109 85872 0
239 235454 73 151 89275 0
240 99466 50 28 192565 0
241 100750 72 83 140867 0
242 224549 50 54 120662 0
243 243511 71 133 101338 0
244 22938 10 12 1168 0
245 152474 65 106 65567 0
246 61857 25 23 25162 0
247 132487 41 71 40735 0
248 317394 86 116 91413 0
249 21054 16 4 855 0
250 209641 42 62 97068 0
251 31414 19 18 14116 0
252 244749 95 98 76643 0
253 184510 49 64 110681 0
254 128423 64 32 92696 0
255 97839 38 25 94785 0
256 38214 34 16 8773 0
257 151101 32 48 83209 0
258 272458 65 100 93815 0
259 172494 52 46 86687 0
260 328107 65 129 105547 0
261 250579 83 130 103487 0
262 351067 95 136 213688 0
263 158015 29 59 71220 0
264 85439 33 32 56926 0
265 229242 247 63 91721 0
266 351619 139 95 115168 0
267 84207 29 14 111194 0
268 324598 110 113 135777 0
269 131069 67 47 51513 0
270 204271 42 92 74163 0
271 165543 65 70 51633 0
272 141722 94 19 75345 0
273 299775 95 91 98952 0
274 195838 67 111 102372 0
275 173260 63 41 37238 0
276 254488 83 120 103772 0
277 104389 45 135 123969 0
278 199476 70 87 135400 0
279 224330 83 131 130115 0
280 14688 10 4 6023 0
281 181633 70 47 64466 0
282 271856 103 109 54990 0
283 7199 5 7 1644 0
284 46660 20 12 6179 0
285 17547 5 0 3926 0
286 95227 34 37 34777 0
287 152601 48 46 73224 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) logins bloggedcomp totsize year
2.435e+04 8.179e+02 1.061e+03 3.253e-01 -1.173e+04
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-140262 -20171 -1112 17374 151759
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.435e+04 7.225e+03 3.370 0.000857 ***
logins 8.179e+02 8.100e+01 10.097 < 2e-16 ***
bloggedcomp 1.061e+03 1.004e+02 10.562 < 2e-16 ***
totsize 3.253e-01 9.071e-02 3.586 0.000396 ***
year -1.173e+04 5.978e+03 -1.961 0.050828 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 37520 on 282 degrees of freedom
Multiple R-squared: 0.7956, Adjusted R-squared: 0.7927
F-statistic: 274.4 on 4 and 282 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 1.628577e-01 3.257154e-01 0.837142280
[2,] 7.759312e-02 1.551862e-01 0.922406883
[3,] 3.805884e-01 7.611769e-01 0.619411560
[4,] 4.007267e-01 8.014535e-01 0.599273273
[5,] 3.063666e-01 6.127331e-01 0.693633443
[6,] 2.633657e-01 5.267314e-01 0.736634294
[7,] 1.823263e-01 3.646526e-01 0.817673688
[8,] 1.210942e-01 2.421883e-01 0.878905838
[9,] 9.855076e-02 1.971015e-01 0.901449236
[10,] 2.122704e-01 4.245408e-01 0.787729585
[11,] 1.532930e-01 3.065860e-01 0.846707015
[12,] 1.285509e-01 2.571018e-01 0.871449105
[13,] 1.379292e-01 2.758584e-01 0.862070821
[14,] 1.005740e-01 2.011480e-01 0.899426018
[15,] 9.346352e-02 1.869270e-01 0.906536475
[16,] 1.248631e-01 2.497262e-01 0.875136891
[17,] 9.081083e-02 1.816217e-01 0.909189172
[18,] 6.825727e-02 1.365145e-01 0.931742728
[19,] 8.780046e-02 1.756009e-01 0.912199545
[20,] 1.142310e-01 2.284620e-01 0.885768999
[21,] 8.895678e-02 1.779136e-01 0.911043216
[22,] 2.240430e-01 4.480861e-01 0.775956951
[23,] 3.068158e-01 6.136317e-01 0.693184172
[24,] 2.703589e-01 5.407178e-01 0.729641102
[25,] 2.848556e-01 5.697112e-01 0.715144414
[26,] 2.875705e-01 5.751410e-01 0.712429497
[27,] 4.103631e-01 8.207261e-01 0.589636925
[28,] 4.038034e-01 8.076068e-01 0.596196622
[29,] 3.680168e-01 7.360336e-01 0.631983183
[30,] 3.238757e-01 6.477513e-01 0.676124331
[31,] 2.910147e-01 5.820294e-01 0.708985306
[32,] 2.543173e-01 5.086346e-01 0.745682712
[33,] 2.140108e-01 4.280216e-01 0.785989178
[34,] 1.784032e-01 3.568064e-01 0.821596804
[35,] 1.850108e-01 3.700216e-01 0.814989215
[36,] 1.665990e-01 3.331980e-01 0.833400983
[37,] 1.558616e-01 3.117232e-01 0.844138399
[38,] 1.309744e-01 2.619487e-01 0.869025638
[39,] 1.065049e-01 2.130099e-01 0.893495059
[40,] 9.046025e-02 1.809205e-01 0.909539751
[41,] 7.209714e-02 1.441943e-01 0.927902859
[42,] 5.768709e-02 1.153742e-01 0.942312911
[43,] 4.523013e-02 9.046026e-02 0.954769869
[44,] 3.563539e-02 7.127078e-02 0.964364609
[45,] 7.909615e-02 1.581923e-01 0.920903848
[46,] 7.789566e-02 1.557913e-01 0.922104340
[47,] 7.026421e-02 1.405284e-01 0.929735791
[48,] 5.787762e-02 1.157552e-01 0.942122381
[49,] 5.097096e-02 1.019419e-01 0.949029043
[50,] 4.051903e-02 8.103805e-02 0.959480974
[51,] 3.271306e-02 6.542613e-02 0.967286936
[52,] 2.564989e-02 5.129978e-02 0.974350112
[53,] 2.005411e-02 4.010822e-02 0.979945892
[54,] 1.718172e-02 3.436344e-02 0.982818282
[55,] 1.368364e-02 2.736728e-02 0.986316362
[56,] 1.026962e-02 2.053925e-02 0.989730377
[57,] 1.025666e-02 2.051331e-02 0.989743343
[58,] 7.792666e-03 1.558533e-02 0.992207334
[59,] 6.132798e-03 1.226560e-02 0.993867202
[60,] 5.321695e-03 1.064339e-02 0.994678305
[61,] 3.934160e-03 7.868321e-03 0.996065840
[62,] 2.851202e-03 5.702404e-03 0.997148798
[63,] 2.126704e-03 4.253407e-03 0.997873296
[64,] 1.559437e-03 3.118874e-03 0.998440563
[65,] 1.739712e-03 3.479424e-03 0.998260288
[66,] 1.536648e-03 3.073297e-03 0.998463352
[67,] 1.601729e-03 3.203458e-03 0.998398271
[68,] 1.139650e-03 2.279300e-03 0.998860350
[69,] 8.384372e-04 1.676874e-03 0.999161563
[70,] 6.918513e-04 1.383703e-03 0.999308149
[71,] 4.844263e-04 9.688526e-04 0.999515574
[72,] 4.704160e-04 9.408319e-04 0.999529584
[73,] 5.635149e-04 1.127030e-03 0.999436485
[74,] 2.156217e-03 4.312434e-03 0.997843783
[75,] 1.589422e-03 3.178844e-03 0.998410578
[76,] 1.151115e-03 2.302231e-03 0.998848885
[77,] 9.270412e-04 1.854082e-03 0.999072959
[78,] 7.107808e-04 1.421562e-03 0.999289219
[79,] 7.069466e-04 1.413893e-03 0.999293053
[80,] 7.473133e-04 1.494627e-03 0.999252687
[81,] 5.906495e-04 1.181299e-03 0.999409350
[82,] 4.200726e-04 8.401452e-04 0.999579927
[83,] 2.967377e-04 5.934754e-04 0.999703262
[84,] 2.614208e-04 5.228416e-04 0.999738579
[85,] 2.021492e-04 4.042983e-04 0.999797851
[86,] 1.399818e-04 2.799636e-04 0.999860018
[87,] 1.406532e-04 2.813065e-04 0.999859347
[88,] 1.326370e-04 2.652740e-04 0.999867363
[89,] 9.229160e-05 1.845832e-04 0.999907708
[90,] 6.692519e-05 1.338504e-04 0.999933075
[91,] 4.914983e-05 9.829966e-05 0.999950850
[92,] 3.499161e-05 6.998322e-05 0.999965008
[93,] 2.346662e-05 4.693325e-05 0.999976533
[94,] 2.094752e-05 4.189505e-05 0.999979052
[95,] 1.407214e-05 2.814429e-05 0.999985928
[96,] 9.310444e-06 1.862089e-05 0.999990690
[97,] 6.564831e-06 1.312966e-05 0.999993435
[98,] 4.275190e-06 8.550381e-06 0.999995725
[99,] 2.834958e-06 5.669915e-06 0.999997165
[100,] 1.848448e-06 3.696897e-06 0.999998152
[101,] 1.316921e-06 2.633843e-06 0.999998683
[102,] 1.101284e-06 2.202568e-06 0.999998899
[103,] 6.992646e-07 1.398529e-06 0.999999301
[104,] 5.784742e-07 1.156948e-06 0.999999422
[105,] 5.384926e-07 1.076985e-06 0.999999462
[106,] 6.816436e-07 1.363287e-06 0.999999318
[107,] 6.838205e-07 1.367641e-06 0.999999316
[108,] 4.571703e-07 9.143407e-07 0.999999543
[109,] 2.870050e-07 5.740101e-07 0.999999713
[110,] 1.880717e-07 3.761434e-07 0.999999812
[111,] 1.175713e-07 2.351425e-07 0.999999882
[112,] 7.274687e-08 1.454937e-07 0.999999927
[113,] 5.009196e-08 1.001839e-07 0.999999950
[114,] 3.046687e-08 6.093374e-08 0.999999970
[115,] 2.010914e-08 4.021829e-08 0.999999980
[116,] 1.225203e-08 2.450406e-08 0.999999988
[117,] 1.081613e-08 2.163226e-08 0.999999989
[118,] 6.706538e-09 1.341308e-08 0.999999993
[119,] 4.738628e-09 9.477255e-09 0.999999995
[120,] 2.949215e-09 5.898429e-09 0.999999997
[121,] 1.760692e-09 3.521385e-09 0.999999998
[122,] 1.087622e-09 2.175243e-09 0.999999999
[123,] 6.744623e-10 1.348925e-09 0.999999999
[124,] 4.135944e-10 8.271889e-10 1.000000000
[125,] 2.486873e-10 4.973745e-10 1.000000000
[126,] 2.787002e-10 5.574005e-10 1.000000000
[127,] 2.080762e-10 4.161523e-10 1.000000000
[128,] 5.094372e-10 1.018874e-09 0.999999999
[129,] 3.816065e-10 7.632131e-10 1.000000000
[130,] 2.312349e-10 4.624698e-10 1.000000000
[131,] 6.504572e-08 1.300914e-07 0.999999935
[132,] 4.144879e-08 8.289757e-08 0.999999959
[133,] 2.645878e-08 5.291756e-08 0.999999974
[134,] 1.960403e-08 3.920806e-08 0.999999980
[135,] 2.244106e-08 4.488212e-08 0.999999978
[136,] 2.543639e-08 5.087278e-08 0.999999975
[137,] 1.557227e-08 3.114454e-08 0.999999984
[138,] 1.930899e-08 3.861797e-08 0.999999981
[139,] 1.327189e-08 2.654378e-08 0.999999987
[140,] 1.161026e-08 2.322052e-08 0.999999988
[141,] 7.688278e-09 1.537656e-08 0.999999992
[142,] 4.641928e-09 9.283856e-09 0.999999995
[143,] 8.086124e-09 1.617225e-08 0.999999992
[144,] 8.869607e-09 1.773921e-08 0.999999991
[145,] 5.381913e-09 1.076383e-08 0.999999995
[146,] 8.495543e-06 1.699109e-05 0.999991504
[147,] 6.825159e-06 1.365032e-05 0.999993175
[148,] 9.738671e-06 1.947734e-05 0.999990261
[149,] 3.572992e-05 7.145984e-05 0.999964270
[150,] 3.573011e-05 7.146022e-05 0.999964270
[151,] 2.497559e-05 4.995118e-05 0.999975024
[152,] 1.741481e-05 3.482962e-05 0.999982585
[153,] 1.230640e-05 2.461279e-05 0.999987694
[154,] 9.683937e-06 1.936787e-05 0.999990316
[155,] 6.691209e-06 1.338242e-05 0.999993309
[156,] 5.235497e-06 1.047099e-05 0.999994765
[157,] 4.101381e-06 8.202763e-06 0.999995899
[158,] 3.409735e-06 6.819471e-06 0.999996590
[159,] 5.936868e-06 1.187374e-05 0.999994063
[160,] 1.065942e-05 2.131884e-05 0.999989341
[161,] 1.104843e-04 2.209685e-04 0.999889516
[162,] 7.959558e-05 1.591912e-04 0.999920404
[163,] 5.795793e-05 1.159159e-04 0.999942042
[164,] 4.174312e-05 8.348624e-05 0.999958257
[165,] 5.848712e-05 1.169742e-04 0.999941513
[166,] 4.143971e-05 8.287942e-05 0.999958560
[167,] 3.016799e-05 6.033598e-05 0.999969832
[168,] 2.100262e-05 4.200524e-05 0.999978997
[169,] 1.610773e-05 3.221546e-05 0.999983892
[170,] 4.514150e-04 9.028300e-04 0.999548585
[171,] 3.439754e-04 6.879507e-04 0.999656025
[172,] 2.827636e-04 5.655272e-04 0.999717236
[173,] 2.149618e-04 4.299237e-04 0.999785038
[174,] 1.811528e-04 3.623057e-04 0.999818847
[175,] 1.387695e-04 2.775389e-04 0.999861231
[176,] 1.207376e-04 2.414751e-04 0.999879262
[177,] 1.068313e-04 2.136625e-04 0.999893169
[178,] 7.620601e-05 1.524120e-04 0.999923794
[179,] 5.708401e-05 1.141680e-04 0.999942916
[180,] 7.685828e-05 1.537166e-04 0.999923142
[181,] 5.697683e-05 1.139537e-04 0.999943023
[182,] 5.827581e-05 1.165516e-04 0.999941724
[183,] 4.595561e-05 9.191122e-05 0.999954044
[184,] 3.514680e-05 7.029360e-05 0.999964853
[185,] 2.608441e-05 5.216882e-05 0.999973916
[186,] 2.302602e-05 4.605205e-05 0.999976974
[187,] 1.645963e-05 3.291925e-05 0.999983540
[188,] 1.595489e-05 3.190977e-05 0.999984045
[189,] 2.059068e-05 4.118137e-05 0.999979409
[190,] 1.459463e-05 2.918927e-05 0.999985405
[191,] 3.814217e-05 7.628433e-05 0.999961858
[192,] 3.835656e-05 7.671311e-05 0.999961643
[193,] 3.955971e-05 7.911941e-05 0.999960440
[194,] 2.696114e-04 5.392228e-04 0.999730389
[195,] 1.975820e-04 3.951640e-04 0.999802418
[196,] 1.410021e-04 2.820042e-04 0.999858998
[197,] 1.156255e-04 2.312510e-04 0.999884374
[198,] 8.183616e-05 1.636723e-04 0.999918164
[199,] 1.061000e-04 2.122000e-04 0.999893900
[200,] 1.224036e-04 2.448071e-04 0.999877596
[201,] 1.105372e-04 2.210743e-04 0.999889463
[202,] 2.154422e-04 4.308844e-04 0.999784558
[203,] 2.682382e-04 5.364764e-04 0.999731762
[204,] 1.893223e-04 3.786446e-04 0.999810678
[205,] 1.329148e-04 2.658296e-04 0.999867085
[206,] 5.537516e-04 1.107503e-03 0.999446248
[207,] 4.595203e-04 9.190407e-04 0.999540480
[208,] 3.828620e-04 7.657239e-04 0.999617138
[209,] 3.442513e-04 6.885026e-04 0.999655749
[210,] 3.044210e-04 6.088419e-04 0.999695579
[211,] 2.697302e-04 5.394605e-04 0.999730270
[212,] 3.898814e-04 7.797628e-04 0.999610119
[213,] 4.848801e-04 9.697602e-04 0.999515120
[214,] 1.040434e-02 2.080867e-02 0.989595664
[215,] 1.040541e-02 2.081081e-02 0.989594594
[216,] 1.421546e-02 2.843092e-02 0.985784540
[217,] 1.216919e-02 2.433838e-02 0.987830809
[218,] 1.032754e-02 2.065508e-02 0.989672461
[219,] 1.872188e-02 3.744376e-02 0.981278119
[220,] 1.452824e-02 2.905648e-02 0.985471761
[221,] 1.116820e-02 2.233640e-02 0.988831802
[222,] 1.072848e-02 2.145695e-02 0.989271524
[223,] 8.180308e-03 1.636062e-02 0.991819692
[224,] 6.567902e-03 1.313580e-02 0.993432098
[225,] 4.921625e-03 9.843250e-03 0.995078375
[226,] 3.638978e-03 7.277956e-03 0.996361022
[227,] 3.796337e-03 7.592673e-03 0.996203663
[228,] 2.921476e-03 5.842952e-03 0.997078524
[229,] 2.123176e-03 4.246353e-03 0.997876824
[230,] 3.201125e-03 6.402251e-03 0.996798875
[231,] 2.289930e-03 4.579860e-03 0.997710070
[232,] 2.415310e-03 4.830620e-03 0.997584690
[233,] 3.265354e-03 6.530708e-03 0.996734646
[234,] 3.879409e-02 7.758817e-02 0.961205915
[235,] 4.770321e-02 9.540641e-02 0.952296795
[236,] 3.958149e-02 7.916298e-02 0.960418510
[237,] 3.186032e-02 6.372064e-02 0.968139681
[238,] 4.598588e-02 9.197176e-02 0.954014120
[239,] 3.630724e-02 7.261447e-02 0.963692763
[240,] 2.887378e-02 5.774757e-02 0.971126217
[241,] 4.228940e-02 8.457881e-02 0.957710596
[242,] 3.341711e-02 6.683422e-02 0.966582889
[243,] 3.833945e-02 7.667889e-02 0.961660555
[244,] 3.294143e-02 6.588287e-02 0.967058566
[245,] 2.513459e-02 5.026919e-02 0.974865406
[246,] 1.899123e-02 3.798246e-02 0.981008771
[247,] 1.400931e-02 2.801862e-02 0.985990688
[248,] 1.044052e-02 2.088104e-02 0.989559479
[249,] 8.736914e-03 1.747383e-02 0.991263086
[250,] 6.499999e-03 1.300000e-02 0.993500001
[251,] 8.366170e-03 1.673234e-02 0.991633830
[252,] 6.751100e-03 1.350220e-02 0.993248900
[253,] 1.733203e-02 3.466407e-02 0.982667966
[254,] 1.210614e-02 2.421227e-02 0.987893863
[255,] 1.124019e-02 2.248038e-02 0.988759810
[256,] 9.084055e-03 1.816811e-02 0.990915945
[257,] 6.178472e-03 1.235694e-02 0.993821528
[258,] 6.165862e-01 7.668276e-01 0.383413782
[259,] 5.654606e-01 8.690788e-01 0.434539391
[260,] 5.179578e-01 9.640844e-01 0.482042191
[261,] 5.195766e-01 9.608468e-01 0.480423386
[262,] 5.061618e-01 9.876763e-01 0.493838155
[263,] 6.956367e-01 6.087267e-01 0.304363347
[264,] 6.215081e-01 7.569838e-01 0.378491923
[265,] 9.966716e-01 6.656753e-03 0.003328376
[266,] 9.979136e-01 4.172890e-03 0.002086445
[267,] 9.959499e-01 8.100102e-03 0.004050051
[268,] 9.894626e-01 2.107472e-02 0.010537360
[269,] 9.972199e-01 5.560244e-03 0.002780122
[270,] 9.942445e-01 1.151107e-02 0.005755536
[271,] 9.802455e-01 3.950898e-02 0.019754491
[272,] 9.896414e-01 2.071718e-02 0.010358588
> postscript(file="/var/fisher/rcomp/tmp/1bmlp1355997787.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/26n9b1355997787.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3jfld1355997787.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4hiah1355997787.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5tqjs1355997787.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 = 287
Frequency = 1
1 2 3 4 5 6
10711.0548 19796.6788 -19813.2003 -30242.9906 2230.8026 53763.9923
7 8 9 10 11 12
19433.5178 8983.9428 -1989.4430 78302.7669 -23733.1957 3025.5246
13 14 15 16 17 18
-47195.7335 2192.9067 7980.3375 1925.1896 -27882.4294 -4072.0206
19 20 21 22 23 24
-23860.0068 -32663.2274 -20922.4401 -19063.8706 37675.8233 -3213.0650
25 26 27 28 29 30
-14250.9334 37358.4654 -43456.6705 -12814.5477 100597.9653 61461.9671
31 32 33 34 35 36
20230.4403 41988.9545 -35147.9109 -61689.2782 41407.5442 28081.1213
37 38 39 40 41 42
-19467.4529 1551.6147 14406.4597 1313.7763 10583.0012 -1284.9064
43 44 45 46 47 48
-10839.9477 -18212.4633 -14823.2543 1747.3299 17159.9411 8359.3517
49 50 51 52 53 54
9931.1054 -5487.0974 -13212.9724 77576.9143 34683.4147 25698.2081
55 56 57 58 59 60
12636.2604 28136.9099 -177.4290 -10571.3953 3011.6567 8482.3483
61 62 63 64 65 66
-22713.5722 -4850.6544 172.1092 36748.0531 -2506.1111 -710.4707
67 68 69 70 71 72
-25329.9485 2821.3843 262.2763 4650.8220 -3563.4466 -33433.9593
73 74 75 76 77 78
-31499.3829 -20797.0348 -1007.0916 -10800.7957 -16138.0506 -2739.0104
79 80 81 82 83 84
-30186.3609 -42089.9381 78776.4007 -9546.3100 3213.5636 -21878.1774
85 86 87 88 89 90
19567.0129 -41985.9646 -42368.0730 -17038.1586 -1622.8551 4302.9623
91 92 93 94 95 96
-24638.5669 19130.5481 3137.1806 -29297.5713 31518.6700 211.5934
97 98 99 100 101 102
-17324.3084 13262.7492 9289.4302 -6565.7096 -27300.4141 5098.7500
103 104 105 106 107 108
-111.4564 -17428.3313 -5366.3012 -10087.1266 1961.4635 -19303.7144
109 110 111 112 113 114
-22871.7730 2164.1175 -29126.5390 -32614.4538 40507.3871 -29152.2056
115 116 117 118 119 120
9630.2227 4208.3805 6919.5122 -6154.8550 -4300.9916 -17698.6666
121 122 123 124 125 126
8686.6680 -15149.5596 2243.1263 30572.2723 11049.2402 -2296.5550
127 128 129 130 131 132
13475.7664 4284.3063 12320.9326 -6866.1394 9934.2980 20451.3799
133 134 135 136 137 138
-38257.2001 17324.3514 -65271.7630 1677.5546 -14331.6100 118849.0632
139 140 141 142 143 144
-14378.8494 5334.4101 22183.0974 39909.1779 -37523.6551 -1662.3641
145 146 147 148 149 150
48989.4646 17423.7426 -24835.1989 11563.0948 439.9476 -41784.9048
151 152 153 154 155 156
-30614.1820 4028.0106 151759.1648 28246.9720 -43859.8736 -77795.2600
157 158 159 160 161 162
-36056.7648 -4058.3903 4589.7336 7913.8423 23858.0335 -557.4635
163 164 165 166 167 168
24473.5597 24636.2420 -25168.0243 60608.1360 60217.5450 104937.8854
169 170 171 172 173 174
8602.5412 12415.9366 -6836.7591 55284.1271 -131.7195 -7472.5385
175 176 177 178 179 180
1946.0479 -17168.3817 127267.9387 -11853.7986 -18627.2758 13625.4774
181 182 183 184 185 186
-23140.0107 -13624.1831 -30208.5789 -28344.1616 -6082.5163 -17722.1545
187 188 189 190 191 192
54223.5833 10277.5443 -35819.7031 -18426.4565 20423.5798 16815.5584
193 194 195 196 197 198
-25313.8348 12966.4817 37884.1824 51118.3044 12179.9377 -71096.0819
199 200 201 202 203 204
-39202.5778 -38510.0682 -98593.3922 10865.8037 -7642.8817 25853.1671
205 206 207 208 209 210
5920.3769 -52046.1871 46349.8251 33107.3074 -64227.8862 -51525.6145
211 212 213 214 215 216
-1112.0744 -4855.9879 88867.2067 25514.6671 -28392.1785 -34226.5625
217 218 219 220 221 222
30969.1633 -33461.4109 54722.6203 48231.8120 -134761.7234 36797.6570
223 224 225 226 227 228
-58760.5716 20829.4440 23375.9307 69304.4697 999.0997 -4619.6075
229 230 231 232 233 234
-34429.8069 -9089.1271 20388.1948 -9703.7565 -3573.9873 -50716.0443
235 236 237 238 239 240
-20529.3669 -10187.3551 -63240.1114 2980.9036 -37780.0295 -58107.9493
241 242 243 244 245 246
-116330.6534 62789.3779 -12921.2809 -22695.3193 -58780.7166 -15514.9598
247 248 249 250 251 252
-13942.6067 69951.6444 -20900.2391 53614.4794 -32155.0381 13840.2309
253 254 255 256 257 258
16209.3576 -12357.7151 -14933.1509 -33763.7905 22608.7802 58378.0680
259 260 261 262 263 264
28634.4573 79454.9428 -13184.9177 35279.3306 24210.0826 -18352.9434
265 266 267 268 269 270
-93766.0496 75374.8477 -14875.9328 46278.0483 -14677.5124 23878.5324
271 272 273 274 275 276
-2999.4773 -4163.2813 69033.4038 -34327.1095 41791.5786 1236.8736
277 278 279 280 281 282
-140261.5676 -18432.8356 -49156.0266 -24040.1574 29219.5694 29781.6367
283 284 285 286 287
-29197.1302 -8781.8469 -12167.5721 -7480.9167 16392.1232
> postscript(file="/var/fisher/rcomp/tmp/6hqaz1355997787.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 = 287
Frequency = 1
lag(myerror, k = 1) myerror
0 10711.0548 NA
1 19796.6788 10711.0548
2 -19813.2003 19796.6788
3 -30242.9906 -19813.2003
4 2230.8026 -30242.9906
5 53763.9923 2230.8026
6 19433.5178 53763.9923
7 8983.9428 19433.5178
8 -1989.4430 8983.9428
9 78302.7669 -1989.4430
10 -23733.1957 78302.7669
11 3025.5246 -23733.1957
12 -47195.7335 3025.5246
13 2192.9067 -47195.7335
14 7980.3375 2192.9067
15 1925.1896 7980.3375
16 -27882.4294 1925.1896
17 -4072.0206 -27882.4294
18 -23860.0068 -4072.0206
19 -32663.2274 -23860.0068
20 -20922.4401 -32663.2274
21 -19063.8706 -20922.4401
22 37675.8233 -19063.8706
23 -3213.0650 37675.8233
24 -14250.9334 -3213.0650
25 37358.4654 -14250.9334
26 -43456.6705 37358.4654
27 -12814.5477 -43456.6705
28 100597.9653 -12814.5477
29 61461.9671 100597.9653
30 20230.4403 61461.9671
31 41988.9545 20230.4403
32 -35147.9109 41988.9545
33 -61689.2782 -35147.9109
34 41407.5442 -61689.2782
35 28081.1213 41407.5442
36 -19467.4529 28081.1213
37 1551.6147 -19467.4529
38 14406.4597 1551.6147
39 1313.7763 14406.4597
40 10583.0012 1313.7763
41 -1284.9064 10583.0012
42 -10839.9477 -1284.9064
43 -18212.4633 -10839.9477
44 -14823.2543 -18212.4633
45 1747.3299 -14823.2543
46 17159.9411 1747.3299
47 8359.3517 17159.9411
48 9931.1054 8359.3517
49 -5487.0974 9931.1054
50 -13212.9724 -5487.0974
51 77576.9143 -13212.9724
52 34683.4147 77576.9143
53 25698.2081 34683.4147
54 12636.2604 25698.2081
55 28136.9099 12636.2604
56 -177.4290 28136.9099
57 -10571.3953 -177.4290
58 3011.6567 -10571.3953
59 8482.3483 3011.6567
60 -22713.5722 8482.3483
61 -4850.6544 -22713.5722
62 172.1092 -4850.6544
63 36748.0531 172.1092
64 -2506.1111 36748.0531
65 -710.4707 -2506.1111
66 -25329.9485 -710.4707
67 2821.3843 -25329.9485
68 262.2763 2821.3843
69 4650.8220 262.2763
70 -3563.4466 4650.8220
71 -33433.9593 -3563.4466
72 -31499.3829 -33433.9593
73 -20797.0348 -31499.3829
74 -1007.0916 -20797.0348
75 -10800.7957 -1007.0916
76 -16138.0506 -10800.7957
77 -2739.0104 -16138.0506
78 -30186.3609 -2739.0104
79 -42089.9381 -30186.3609
80 78776.4007 -42089.9381
81 -9546.3100 78776.4007
82 3213.5636 -9546.3100
83 -21878.1774 3213.5636
84 19567.0129 -21878.1774
85 -41985.9646 19567.0129
86 -42368.0730 -41985.9646
87 -17038.1586 -42368.0730
88 -1622.8551 -17038.1586
89 4302.9623 -1622.8551
90 -24638.5669 4302.9623
91 19130.5481 -24638.5669
92 3137.1806 19130.5481
93 -29297.5713 3137.1806
94 31518.6700 -29297.5713
95 211.5934 31518.6700
96 -17324.3084 211.5934
97 13262.7492 -17324.3084
98 9289.4302 13262.7492
99 -6565.7096 9289.4302
100 -27300.4141 -6565.7096
101 5098.7500 -27300.4141
102 -111.4564 5098.7500
103 -17428.3313 -111.4564
104 -5366.3012 -17428.3313
105 -10087.1266 -5366.3012
106 1961.4635 -10087.1266
107 -19303.7144 1961.4635
108 -22871.7730 -19303.7144
109 2164.1175 -22871.7730
110 -29126.5390 2164.1175
111 -32614.4538 -29126.5390
112 40507.3871 -32614.4538
113 -29152.2056 40507.3871
114 9630.2227 -29152.2056
115 4208.3805 9630.2227
116 6919.5122 4208.3805
117 -6154.8550 6919.5122
118 -4300.9916 -6154.8550
119 -17698.6666 -4300.9916
120 8686.6680 -17698.6666
121 -15149.5596 8686.6680
122 2243.1263 -15149.5596
123 30572.2723 2243.1263
124 11049.2402 30572.2723
125 -2296.5550 11049.2402
126 13475.7664 -2296.5550
127 4284.3063 13475.7664
128 12320.9326 4284.3063
129 -6866.1394 12320.9326
130 9934.2980 -6866.1394
131 20451.3799 9934.2980
132 -38257.2001 20451.3799
133 17324.3514 -38257.2001
134 -65271.7630 17324.3514
135 1677.5546 -65271.7630
136 -14331.6100 1677.5546
137 118849.0632 -14331.6100
138 -14378.8494 118849.0632
139 5334.4101 -14378.8494
140 22183.0974 5334.4101
141 39909.1779 22183.0974
142 -37523.6551 39909.1779
143 -1662.3641 -37523.6551
144 48989.4646 -1662.3641
145 17423.7426 48989.4646
146 -24835.1989 17423.7426
147 11563.0948 -24835.1989
148 439.9476 11563.0948
149 -41784.9048 439.9476
150 -30614.1820 -41784.9048
151 4028.0106 -30614.1820
152 151759.1648 4028.0106
153 28246.9720 151759.1648
154 -43859.8736 28246.9720
155 -77795.2600 -43859.8736
156 -36056.7648 -77795.2600
157 -4058.3903 -36056.7648
158 4589.7336 -4058.3903
159 7913.8423 4589.7336
160 23858.0335 7913.8423
161 -557.4635 23858.0335
162 24473.5597 -557.4635
163 24636.2420 24473.5597
164 -25168.0243 24636.2420
165 60608.1360 -25168.0243
166 60217.5450 60608.1360
167 104937.8854 60217.5450
168 8602.5412 104937.8854
169 12415.9366 8602.5412
170 -6836.7591 12415.9366
171 55284.1271 -6836.7591
172 -131.7195 55284.1271
173 -7472.5385 -131.7195
174 1946.0479 -7472.5385
175 -17168.3817 1946.0479
176 127267.9387 -17168.3817
177 -11853.7986 127267.9387
178 -18627.2758 -11853.7986
179 13625.4774 -18627.2758
180 -23140.0107 13625.4774
181 -13624.1831 -23140.0107
182 -30208.5789 -13624.1831
183 -28344.1616 -30208.5789
184 -6082.5163 -28344.1616
185 -17722.1545 -6082.5163
186 54223.5833 -17722.1545
187 10277.5443 54223.5833
188 -35819.7031 10277.5443
189 -18426.4565 -35819.7031
190 20423.5798 -18426.4565
191 16815.5584 20423.5798
192 -25313.8348 16815.5584
193 12966.4817 -25313.8348
194 37884.1824 12966.4817
195 51118.3044 37884.1824
196 12179.9377 51118.3044
197 -71096.0819 12179.9377
198 -39202.5778 -71096.0819
199 -38510.0682 -39202.5778
200 -98593.3922 -38510.0682
201 10865.8037 -98593.3922
202 -7642.8817 10865.8037
203 25853.1671 -7642.8817
204 5920.3769 25853.1671
205 -52046.1871 5920.3769
206 46349.8251 -52046.1871
207 33107.3074 46349.8251
208 -64227.8862 33107.3074
209 -51525.6145 -64227.8862
210 -1112.0744 -51525.6145
211 -4855.9879 -1112.0744
212 88867.2067 -4855.9879
213 25514.6671 88867.2067
214 -28392.1785 25514.6671
215 -34226.5625 -28392.1785
216 30969.1633 -34226.5625
217 -33461.4109 30969.1633
218 54722.6203 -33461.4109
219 48231.8120 54722.6203
220 -134761.7234 48231.8120
221 36797.6570 -134761.7234
222 -58760.5716 36797.6570
223 20829.4440 -58760.5716
224 23375.9307 20829.4440
225 69304.4697 23375.9307
226 999.0997 69304.4697
227 -4619.6075 999.0997
228 -34429.8069 -4619.6075
229 -9089.1271 -34429.8069
230 20388.1948 -9089.1271
231 -9703.7565 20388.1948
232 -3573.9873 -9703.7565
233 -50716.0443 -3573.9873
234 -20529.3669 -50716.0443
235 -10187.3551 -20529.3669
236 -63240.1114 -10187.3551
237 2980.9036 -63240.1114
238 -37780.0295 2980.9036
239 -58107.9493 -37780.0295
240 -116330.6534 -58107.9493
241 62789.3779 -116330.6534
242 -12921.2809 62789.3779
243 -22695.3193 -12921.2809
244 -58780.7166 -22695.3193
245 -15514.9598 -58780.7166
246 -13942.6067 -15514.9598
247 69951.6444 -13942.6067
248 -20900.2391 69951.6444
249 53614.4794 -20900.2391
250 -32155.0381 53614.4794
251 13840.2309 -32155.0381
252 16209.3576 13840.2309
253 -12357.7151 16209.3576
254 -14933.1509 -12357.7151
255 -33763.7905 -14933.1509
256 22608.7802 -33763.7905
257 58378.0680 22608.7802
258 28634.4573 58378.0680
259 79454.9428 28634.4573
260 -13184.9177 79454.9428
261 35279.3306 -13184.9177
262 24210.0826 35279.3306
263 -18352.9434 24210.0826
264 -93766.0496 -18352.9434
265 75374.8477 -93766.0496
266 -14875.9328 75374.8477
267 46278.0483 -14875.9328
268 -14677.5124 46278.0483
269 23878.5324 -14677.5124
270 -2999.4773 23878.5324
271 -4163.2813 -2999.4773
272 69033.4038 -4163.2813
273 -34327.1095 69033.4038
274 41791.5786 -34327.1095
275 1236.8736 41791.5786
276 -140261.5676 1236.8736
277 -18432.8356 -140261.5676
278 -49156.0266 -18432.8356
279 -24040.1574 -49156.0266
280 29219.5694 -24040.1574
281 29781.6367 29219.5694
282 -29197.1302 29781.6367
283 -8781.8469 -29197.1302
284 -12167.5721 -8781.8469
285 -7480.9167 -12167.5721
286 16392.1232 -7480.9167
287 NA 16392.1232
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 19796.6788 10711.0548
[2,] -19813.2003 19796.6788
[3,] -30242.9906 -19813.2003
[4,] 2230.8026 -30242.9906
[5,] 53763.9923 2230.8026
[6,] 19433.5178 53763.9923
[7,] 8983.9428 19433.5178
[8,] -1989.4430 8983.9428
[9,] 78302.7669 -1989.4430
[10,] -23733.1957 78302.7669
[11,] 3025.5246 -23733.1957
[12,] -47195.7335 3025.5246
[13,] 2192.9067 -47195.7335
[14,] 7980.3375 2192.9067
[15,] 1925.1896 7980.3375
[16,] -27882.4294 1925.1896
[17,] -4072.0206 -27882.4294
[18,] -23860.0068 -4072.0206
[19,] -32663.2274 -23860.0068
[20,] -20922.4401 -32663.2274
[21,] -19063.8706 -20922.4401
[22,] 37675.8233 -19063.8706
[23,] -3213.0650 37675.8233
[24,] -14250.9334 -3213.0650
[25,] 37358.4654 -14250.9334
[26,] -43456.6705 37358.4654
[27,] -12814.5477 -43456.6705
[28,] 100597.9653 -12814.5477
[29,] 61461.9671 100597.9653
[30,] 20230.4403 61461.9671
[31,] 41988.9545 20230.4403
[32,] -35147.9109 41988.9545
[33,] -61689.2782 -35147.9109
[34,] 41407.5442 -61689.2782
[35,] 28081.1213 41407.5442
[36,] -19467.4529 28081.1213
[37,] 1551.6147 -19467.4529
[38,] 14406.4597 1551.6147
[39,] 1313.7763 14406.4597
[40,] 10583.0012 1313.7763
[41,] -1284.9064 10583.0012
[42,] -10839.9477 -1284.9064
[43,] -18212.4633 -10839.9477
[44,] -14823.2543 -18212.4633
[45,] 1747.3299 -14823.2543
[46,] 17159.9411 1747.3299
[47,] 8359.3517 17159.9411
[48,] 9931.1054 8359.3517
[49,] -5487.0974 9931.1054
[50,] -13212.9724 -5487.0974
[51,] 77576.9143 -13212.9724
[52,] 34683.4147 77576.9143
[53,] 25698.2081 34683.4147
[54,] 12636.2604 25698.2081
[55,] 28136.9099 12636.2604
[56,] -177.4290 28136.9099
[57,] -10571.3953 -177.4290
[58,] 3011.6567 -10571.3953
[59,] 8482.3483 3011.6567
[60,] -22713.5722 8482.3483
[61,] -4850.6544 -22713.5722
[62,] 172.1092 -4850.6544
[63,] 36748.0531 172.1092
[64,] -2506.1111 36748.0531
[65,] -710.4707 -2506.1111
[66,] -25329.9485 -710.4707
[67,] 2821.3843 -25329.9485
[68,] 262.2763 2821.3843
[69,] 4650.8220 262.2763
[70,] -3563.4466 4650.8220
[71,] -33433.9593 -3563.4466
[72,] -31499.3829 -33433.9593
[73,] -20797.0348 -31499.3829
[74,] -1007.0916 -20797.0348
[75,] -10800.7957 -1007.0916
[76,] -16138.0506 -10800.7957
[77,] -2739.0104 -16138.0506
[78,] -30186.3609 -2739.0104
[79,] -42089.9381 -30186.3609
[80,] 78776.4007 -42089.9381
[81,] -9546.3100 78776.4007
[82,] 3213.5636 -9546.3100
[83,] -21878.1774 3213.5636
[84,] 19567.0129 -21878.1774
[85,] -41985.9646 19567.0129
[86,] -42368.0730 -41985.9646
[87,] -17038.1586 -42368.0730
[88,] -1622.8551 -17038.1586
[89,] 4302.9623 -1622.8551
[90,] -24638.5669 4302.9623
[91,] 19130.5481 -24638.5669
[92,] 3137.1806 19130.5481
[93,] -29297.5713 3137.1806
[94,] 31518.6700 -29297.5713
[95,] 211.5934 31518.6700
[96,] -17324.3084 211.5934
[97,] 13262.7492 -17324.3084
[98,] 9289.4302 13262.7492
[99,] -6565.7096 9289.4302
[100,] -27300.4141 -6565.7096
[101,] 5098.7500 -27300.4141
[102,] -111.4564 5098.7500
[103,] -17428.3313 -111.4564
[104,] -5366.3012 -17428.3313
[105,] -10087.1266 -5366.3012
[106,] 1961.4635 -10087.1266
[107,] -19303.7144 1961.4635
[108,] -22871.7730 -19303.7144
[109,] 2164.1175 -22871.7730
[110,] -29126.5390 2164.1175
[111,] -32614.4538 -29126.5390
[112,] 40507.3871 -32614.4538
[113,] -29152.2056 40507.3871
[114,] 9630.2227 -29152.2056
[115,] 4208.3805 9630.2227
[116,] 6919.5122 4208.3805
[117,] -6154.8550 6919.5122
[118,] -4300.9916 -6154.8550
[119,] -17698.6666 -4300.9916
[120,] 8686.6680 -17698.6666
[121,] -15149.5596 8686.6680
[122,] 2243.1263 -15149.5596
[123,] 30572.2723 2243.1263
[124,] 11049.2402 30572.2723
[125,] -2296.5550 11049.2402
[126,] 13475.7664 -2296.5550
[127,] 4284.3063 13475.7664
[128,] 12320.9326 4284.3063
[129,] -6866.1394 12320.9326
[130,] 9934.2980 -6866.1394
[131,] 20451.3799 9934.2980
[132,] -38257.2001 20451.3799
[133,] 17324.3514 -38257.2001
[134,] -65271.7630 17324.3514
[135,] 1677.5546 -65271.7630
[136,] -14331.6100 1677.5546
[137,] 118849.0632 -14331.6100
[138,] -14378.8494 118849.0632
[139,] 5334.4101 -14378.8494
[140,] 22183.0974 5334.4101
[141,] 39909.1779 22183.0974
[142,] -37523.6551 39909.1779
[143,] -1662.3641 -37523.6551
[144,] 48989.4646 -1662.3641
[145,] 17423.7426 48989.4646
[146,] -24835.1989 17423.7426
[147,] 11563.0948 -24835.1989
[148,] 439.9476 11563.0948
[149,] -41784.9048 439.9476
[150,] -30614.1820 -41784.9048
[151,] 4028.0106 -30614.1820
[152,] 151759.1648 4028.0106
[153,] 28246.9720 151759.1648
[154,] -43859.8736 28246.9720
[155,] -77795.2600 -43859.8736
[156,] -36056.7648 -77795.2600
[157,] -4058.3903 -36056.7648
[158,] 4589.7336 -4058.3903
[159,] 7913.8423 4589.7336
[160,] 23858.0335 7913.8423
[161,] -557.4635 23858.0335
[162,] 24473.5597 -557.4635
[163,] 24636.2420 24473.5597
[164,] -25168.0243 24636.2420
[165,] 60608.1360 -25168.0243
[166,] 60217.5450 60608.1360
[167,] 104937.8854 60217.5450
[168,] 8602.5412 104937.8854
[169,] 12415.9366 8602.5412
[170,] -6836.7591 12415.9366
[171,] 55284.1271 -6836.7591
[172,] -131.7195 55284.1271
[173,] -7472.5385 -131.7195
[174,] 1946.0479 -7472.5385
[175,] -17168.3817 1946.0479
[176,] 127267.9387 -17168.3817
[177,] -11853.7986 127267.9387
[178,] -18627.2758 -11853.7986
[179,] 13625.4774 -18627.2758
[180,] -23140.0107 13625.4774
[181,] -13624.1831 -23140.0107
[182,] -30208.5789 -13624.1831
[183,] -28344.1616 -30208.5789
[184,] -6082.5163 -28344.1616
[185,] -17722.1545 -6082.5163
[186,] 54223.5833 -17722.1545
[187,] 10277.5443 54223.5833
[188,] -35819.7031 10277.5443
[189,] -18426.4565 -35819.7031
[190,] 20423.5798 -18426.4565
[191,] 16815.5584 20423.5798
[192,] -25313.8348 16815.5584
[193,] 12966.4817 -25313.8348
[194,] 37884.1824 12966.4817
[195,] 51118.3044 37884.1824
[196,] 12179.9377 51118.3044
[197,] -71096.0819 12179.9377
[198,] -39202.5778 -71096.0819
[199,] -38510.0682 -39202.5778
[200,] -98593.3922 -38510.0682
[201,] 10865.8037 -98593.3922
[202,] -7642.8817 10865.8037
[203,] 25853.1671 -7642.8817
[204,] 5920.3769 25853.1671
[205,] -52046.1871 5920.3769
[206,] 46349.8251 -52046.1871
[207,] 33107.3074 46349.8251
[208,] -64227.8862 33107.3074
[209,] -51525.6145 -64227.8862
[210,] -1112.0744 -51525.6145
[211,] -4855.9879 -1112.0744
[212,] 88867.2067 -4855.9879
[213,] 25514.6671 88867.2067
[214,] -28392.1785 25514.6671
[215,] -34226.5625 -28392.1785
[216,] 30969.1633 -34226.5625
[217,] -33461.4109 30969.1633
[218,] 54722.6203 -33461.4109
[219,] 48231.8120 54722.6203
[220,] -134761.7234 48231.8120
[221,] 36797.6570 -134761.7234
[222,] -58760.5716 36797.6570
[223,] 20829.4440 -58760.5716
[224,] 23375.9307 20829.4440
[225,] 69304.4697 23375.9307
[226,] 999.0997 69304.4697
[227,] -4619.6075 999.0997
[228,] -34429.8069 -4619.6075
[229,] -9089.1271 -34429.8069
[230,] 20388.1948 -9089.1271
[231,] -9703.7565 20388.1948
[232,] -3573.9873 -9703.7565
[233,] -50716.0443 -3573.9873
[234,] -20529.3669 -50716.0443
[235,] -10187.3551 -20529.3669
[236,] -63240.1114 -10187.3551
[237,] 2980.9036 -63240.1114
[238,] -37780.0295 2980.9036
[239,] -58107.9493 -37780.0295
[240,] -116330.6534 -58107.9493
[241,] 62789.3779 -116330.6534
[242,] -12921.2809 62789.3779
[243,] -22695.3193 -12921.2809
[244,] -58780.7166 -22695.3193
[245,] -15514.9598 -58780.7166
[246,] -13942.6067 -15514.9598
[247,] 69951.6444 -13942.6067
[248,] -20900.2391 69951.6444
[249,] 53614.4794 -20900.2391
[250,] -32155.0381 53614.4794
[251,] 13840.2309 -32155.0381
[252,] 16209.3576 13840.2309
[253,] -12357.7151 16209.3576
[254,] -14933.1509 -12357.7151
[255,] -33763.7905 -14933.1509
[256,] 22608.7802 -33763.7905
[257,] 58378.0680 22608.7802
[258,] 28634.4573 58378.0680
[259,] 79454.9428 28634.4573
[260,] -13184.9177 79454.9428
[261,] 35279.3306 -13184.9177
[262,] 24210.0826 35279.3306
[263,] -18352.9434 24210.0826
[264,] -93766.0496 -18352.9434
[265,] 75374.8477 -93766.0496
[266,] -14875.9328 75374.8477
[267,] 46278.0483 -14875.9328
[268,] -14677.5124 46278.0483
[269,] 23878.5324 -14677.5124
[270,] -2999.4773 23878.5324
[271,] -4163.2813 -2999.4773
[272,] 69033.4038 -4163.2813
[273,] -34327.1095 69033.4038
[274,] 41791.5786 -34327.1095
[275,] 1236.8736 41791.5786
[276,] -140261.5676 1236.8736
[277,] -18432.8356 -140261.5676
[278,] -49156.0266 -18432.8356
[279,] -24040.1574 -49156.0266
[280,] 29219.5694 -24040.1574
[281,] 29781.6367 29219.5694
[282,] -29197.1302 29781.6367
[283,] -8781.8469 -29197.1302
[284,] -12167.5721 -8781.8469
[285,] -7480.9167 -12167.5721
[286,] 16392.1232 -7480.9167
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 19796.6788 10711.0548
2 -19813.2003 19796.6788
3 -30242.9906 -19813.2003
4 2230.8026 -30242.9906
5 53763.9923 2230.8026
6 19433.5178 53763.9923
7 8983.9428 19433.5178
8 -1989.4430 8983.9428
9 78302.7669 -1989.4430
10 -23733.1957 78302.7669
11 3025.5246 -23733.1957
12 -47195.7335 3025.5246
13 2192.9067 -47195.7335
14 7980.3375 2192.9067
15 1925.1896 7980.3375
16 -27882.4294 1925.1896
17 -4072.0206 -27882.4294
18 -23860.0068 -4072.0206
19 -32663.2274 -23860.0068
20 -20922.4401 -32663.2274
21 -19063.8706 -20922.4401
22 37675.8233 -19063.8706
23 -3213.0650 37675.8233
24 -14250.9334 -3213.0650
25 37358.4654 -14250.9334
26 -43456.6705 37358.4654
27 -12814.5477 -43456.6705
28 100597.9653 -12814.5477
29 61461.9671 100597.9653
30 20230.4403 61461.9671
31 41988.9545 20230.4403
32 -35147.9109 41988.9545
33 -61689.2782 -35147.9109
34 41407.5442 -61689.2782
35 28081.1213 41407.5442
36 -19467.4529 28081.1213
37 1551.6147 -19467.4529
38 14406.4597 1551.6147
39 1313.7763 14406.4597
40 10583.0012 1313.7763
41 -1284.9064 10583.0012
42 -10839.9477 -1284.9064
43 -18212.4633 -10839.9477
44 -14823.2543 -18212.4633
45 1747.3299 -14823.2543
46 17159.9411 1747.3299
47 8359.3517 17159.9411
48 9931.1054 8359.3517
49 -5487.0974 9931.1054
50 -13212.9724 -5487.0974
51 77576.9143 -13212.9724
52 34683.4147 77576.9143
53 25698.2081 34683.4147
54 12636.2604 25698.2081
55 28136.9099 12636.2604
56 -177.4290 28136.9099
57 -10571.3953 -177.4290
58 3011.6567 -10571.3953
59 8482.3483 3011.6567
60 -22713.5722 8482.3483
61 -4850.6544 -22713.5722
62 172.1092 -4850.6544
63 36748.0531 172.1092
64 -2506.1111 36748.0531
65 -710.4707 -2506.1111
66 -25329.9485 -710.4707
67 2821.3843 -25329.9485
68 262.2763 2821.3843
69 4650.8220 262.2763
70 -3563.4466 4650.8220
71 -33433.9593 -3563.4466
72 -31499.3829 -33433.9593
73 -20797.0348 -31499.3829
74 -1007.0916 -20797.0348
75 -10800.7957 -1007.0916
76 -16138.0506 -10800.7957
77 -2739.0104 -16138.0506
78 -30186.3609 -2739.0104
79 -42089.9381 -30186.3609
80 78776.4007 -42089.9381
81 -9546.3100 78776.4007
82 3213.5636 -9546.3100
83 -21878.1774 3213.5636
84 19567.0129 -21878.1774
85 -41985.9646 19567.0129
86 -42368.0730 -41985.9646
87 -17038.1586 -42368.0730
88 -1622.8551 -17038.1586
89 4302.9623 -1622.8551
90 -24638.5669 4302.9623
91 19130.5481 -24638.5669
92 3137.1806 19130.5481
93 -29297.5713 3137.1806
94 31518.6700 -29297.5713
95 211.5934 31518.6700
96 -17324.3084 211.5934
97 13262.7492 -17324.3084
98 9289.4302 13262.7492
99 -6565.7096 9289.4302
100 -27300.4141 -6565.7096
101 5098.7500 -27300.4141
102 -111.4564 5098.7500
103 -17428.3313 -111.4564
104 -5366.3012 -17428.3313
105 -10087.1266 -5366.3012
106 1961.4635 -10087.1266
107 -19303.7144 1961.4635
108 -22871.7730 -19303.7144
109 2164.1175 -22871.7730
110 -29126.5390 2164.1175
111 -32614.4538 -29126.5390
112 40507.3871 -32614.4538
113 -29152.2056 40507.3871
114 9630.2227 -29152.2056
115 4208.3805 9630.2227
116 6919.5122 4208.3805
117 -6154.8550 6919.5122
118 -4300.9916 -6154.8550
119 -17698.6666 -4300.9916
120 8686.6680 -17698.6666
121 -15149.5596 8686.6680
122 2243.1263 -15149.5596
123 30572.2723 2243.1263
124 11049.2402 30572.2723
125 -2296.5550 11049.2402
126 13475.7664 -2296.5550
127 4284.3063 13475.7664
128 12320.9326 4284.3063
129 -6866.1394 12320.9326
130 9934.2980 -6866.1394
131 20451.3799 9934.2980
132 -38257.2001 20451.3799
133 17324.3514 -38257.2001
134 -65271.7630 17324.3514
135 1677.5546 -65271.7630
136 -14331.6100 1677.5546
137 118849.0632 -14331.6100
138 -14378.8494 118849.0632
139 5334.4101 -14378.8494
140 22183.0974 5334.4101
141 39909.1779 22183.0974
142 -37523.6551 39909.1779
143 -1662.3641 -37523.6551
144 48989.4646 -1662.3641
145 17423.7426 48989.4646
146 -24835.1989 17423.7426
147 11563.0948 -24835.1989
148 439.9476 11563.0948
149 -41784.9048 439.9476
150 -30614.1820 -41784.9048
151 4028.0106 -30614.1820
152 151759.1648 4028.0106
153 28246.9720 151759.1648
154 -43859.8736 28246.9720
155 -77795.2600 -43859.8736
156 -36056.7648 -77795.2600
157 -4058.3903 -36056.7648
158 4589.7336 -4058.3903
159 7913.8423 4589.7336
160 23858.0335 7913.8423
161 -557.4635 23858.0335
162 24473.5597 -557.4635
163 24636.2420 24473.5597
164 -25168.0243 24636.2420
165 60608.1360 -25168.0243
166 60217.5450 60608.1360
167 104937.8854 60217.5450
168 8602.5412 104937.8854
169 12415.9366 8602.5412
170 -6836.7591 12415.9366
171 55284.1271 -6836.7591
172 -131.7195 55284.1271
173 -7472.5385 -131.7195
174 1946.0479 -7472.5385
175 -17168.3817 1946.0479
176 127267.9387 -17168.3817
177 -11853.7986 127267.9387
178 -18627.2758 -11853.7986
179 13625.4774 -18627.2758
180 -23140.0107 13625.4774
181 -13624.1831 -23140.0107
182 -30208.5789 -13624.1831
183 -28344.1616 -30208.5789
184 -6082.5163 -28344.1616
185 -17722.1545 -6082.5163
186 54223.5833 -17722.1545
187 10277.5443 54223.5833
188 -35819.7031 10277.5443
189 -18426.4565 -35819.7031
190 20423.5798 -18426.4565
191 16815.5584 20423.5798
192 -25313.8348 16815.5584
193 12966.4817 -25313.8348
194 37884.1824 12966.4817
195 51118.3044 37884.1824
196 12179.9377 51118.3044
197 -71096.0819 12179.9377
198 -39202.5778 -71096.0819
199 -38510.0682 -39202.5778
200 -98593.3922 -38510.0682
201 10865.8037 -98593.3922
202 -7642.8817 10865.8037
203 25853.1671 -7642.8817
204 5920.3769 25853.1671
205 -52046.1871 5920.3769
206 46349.8251 -52046.1871
207 33107.3074 46349.8251
208 -64227.8862 33107.3074
209 -51525.6145 -64227.8862
210 -1112.0744 -51525.6145
211 -4855.9879 -1112.0744
212 88867.2067 -4855.9879
213 25514.6671 88867.2067
214 -28392.1785 25514.6671
215 -34226.5625 -28392.1785
216 30969.1633 -34226.5625
217 -33461.4109 30969.1633
218 54722.6203 -33461.4109
219 48231.8120 54722.6203
220 -134761.7234 48231.8120
221 36797.6570 -134761.7234
222 -58760.5716 36797.6570
223 20829.4440 -58760.5716
224 23375.9307 20829.4440
225 69304.4697 23375.9307
226 999.0997 69304.4697
227 -4619.6075 999.0997
228 -34429.8069 -4619.6075
229 -9089.1271 -34429.8069
230 20388.1948 -9089.1271
231 -9703.7565 20388.1948
232 -3573.9873 -9703.7565
233 -50716.0443 -3573.9873
234 -20529.3669 -50716.0443
235 -10187.3551 -20529.3669
236 -63240.1114 -10187.3551
237 2980.9036 -63240.1114
238 -37780.0295 2980.9036
239 -58107.9493 -37780.0295
240 -116330.6534 -58107.9493
241 62789.3779 -116330.6534
242 -12921.2809 62789.3779
243 -22695.3193 -12921.2809
244 -58780.7166 -22695.3193
245 -15514.9598 -58780.7166
246 -13942.6067 -15514.9598
247 69951.6444 -13942.6067
248 -20900.2391 69951.6444
249 53614.4794 -20900.2391
250 -32155.0381 53614.4794
251 13840.2309 -32155.0381
252 16209.3576 13840.2309
253 -12357.7151 16209.3576
254 -14933.1509 -12357.7151
255 -33763.7905 -14933.1509
256 22608.7802 -33763.7905
257 58378.0680 22608.7802
258 28634.4573 58378.0680
259 79454.9428 28634.4573
260 -13184.9177 79454.9428
261 35279.3306 -13184.9177
262 24210.0826 35279.3306
263 -18352.9434 24210.0826
264 -93766.0496 -18352.9434
265 75374.8477 -93766.0496
266 -14875.9328 75374.8477
267 46278.0483 -14875.9328
268 -14677.5124 46278.0483
269 23878.5324 -14677.5124
270 -2999.4773 23878.5324
271 -4163.2813 -2999.4773
272 69033.4038 -4163.2813
273 -34327.1095 69033.4038
274 41791.5786 -34327.1095
275 1236.8736 41791.5786
276 -140261.5676 1236.8736
277 -18432.8356 -140261.5676
278 -49156.0266 -18432.8356
279 -24040.1574 -49156.0266
280 29219.5694 -24040.1574
281 29781.6367 29219.5694
282 -29197.1302 29781.6367
283 -8781.8469 -29197.1302
284 -12167.5721 -8781.8469
285 -7480.9167 -12167.5721
286 16392.1232 -7480.9167
> 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/fisher/rcomp/tmp/7rioe1355997787.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/8mcni1355997787.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/9j92d1355997787.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10of6r1355997787.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/fisher/rcomp/tmp/11pt961355997787.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/fisher/rcomp/tmp/12s0yh1355997787.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/fisher/rcomp/tmp/13nygb1355997787.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/fisher/rcomp/tmp/14mie81355997788.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/fisher/rcomp/tmp/153okr1355997788.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/fisher/rcomp/tmp/16pstg1355997788.tab")
+ }
>
> try(system("convert tmp/1bmlp1355997787.ps tmp/1bmlp1355997787.png",intern=TRUE))
character(0)
> try(system("convert tmp/26n9b1355997787.ps tmp/26n9b1355997787.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jfld1355997787.ps tmp/3jfld1355997787.png",intern=TRUE))
character(0)
> try(system("convert tmp/4hiah1355997787.ps tmp/4hiah1355997787.png",intern=TRUE))
character(0)
> try(system("convert tmp/5tqjs1355997787.ps tmp/5tqjs1355997787.png",intern=TRUE))
character(0)
> try(system("convert tmp/6hqaz1355997787.ps tmp/6hqaz1355997787.png",intern=TRUE))
character(0)
> try(system("convert tmp/7rioe1355997787.ps tmp/7rioe1355997787.png",intern=TRUE))
character(0)
> try(system("convert tmp/8mcni1355997787.ps tmp/8mcni1355997787.png",intern=TRUE))
character(0)
> try(system("convert tmp/9j92d1355997787.ps tmp/9j92d1355997787.png",intern=TRUE))
character(0)
> try(system("convert tmp/10of6r1355997787.ps tmp/10of6r1355997787.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
11.849 1.815 13.676