R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(210907
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+ ,dim=c(4
+ ,289)
+ ,dimnames=list(c('time_in_rfc'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'Forecast')
+ ,1:289))
> y <- array(NA,dim=c(4,289),dimnames=list(c('time_in_rfc','blogged_computations','compendiums_reviewed','Forecast'),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'
> #'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
> 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
Forecast time_in_rfc blogged_computations compendiums_reviewed
1 12.332070 210907 79 30
2 9.279507 120982 58 28
3 13.286685 176508 60 38
4 8.610039 179321 108 30
5 9.182673 123185 49 22
6 10.076060 52746 0 26
7 16.857858 385534 121 25
8 7.874590 33170 1 18
9 8.714737 101645 20 11
10 11.477456 149061 43 26
11 10.154135 165446 69 25
12 14.858889 237213 78 38
13 12.049427 173326 86 44
14 11.221369 133131 44 30
15 14.232859 258873 104 40
16 12.642727 180083 63 34
17 14.364536 324799 158 47
18 11.560768 230964 102 30
19 13.881901 236785 77 31
20 7.426300 135473 82 23
21 10.105845 202925 115 36
22 11.756381 215147 101 36
23 18.704849 344297 80 30
24 11.035808 153935 50 25
25 9.587133 132943 83 39
26 7.842134 174724 123 34
27 11.169518 174415 73 31
28 13.035903 225548 81 31
29 11.421522 223632 105 33
30 9.855234 124817 47 25
31 11.328027 221698 105 33
32 11.927057 210767 94 35
33 14.785710 170266 44 42
34 13.999822 260561 114 43
35 9.341618 84853 38 30
36 14.692435 294424 107 33
37 8.222021 101011 30 13
38 13.461316 215641 71 32
39 18.358941 325107 84 36
40 4.039968 7176 0 0
41 11.454664 167542 59 28
42 8.403279 106408 33 14
43 7.688250 96560 42 17
44 13.992352 265769 96 32
45 13.128245 269651 106 30
46 11.822768 149112 56 35
47 10.827008 175824 57 20
48 10.745424 152871 59 28
49 10.267244 111665 39 28
50 12.496693 116408 34 39
51 20.467692 362301 76 34
52 9.821747 78800 20 26
53 11.409575 183167 91 39
54 14.175783 277965 115 39
55 9.406181 150629 85 33
56 10.229149 168809 76 28
57 4.846550 24188 8 4
58 19.380789 329267 79 39
59 7.900908 65029 21 18
60 8.373606 101097 30 14
61 12.800349 218946 76 29
62 14.333152 244052 101 44
63 16.186485 341570 94 21
64 9.016393 103597 27 16
65 12.137117 233328 92 28
66 11.941019 256462 123 35
67 12.110549 206161 75 28
68 14.664236 311473 128 38
69 10.535489 235800 105 23
70 13.439470 177939 55 36
71 14.187474 207176 56 32
72 14.367026 196553 41 29
73 10.349480 174184 72 25
74 9.527159 143246 67 27
75 12.390689 187559 75 36
76 8.265180 187681 114 28
77 3.905806 119016 118 23
78 12.569556 182192 77 40
79 8.975055 73566 22 23
80 14.020330 194979 66 40
81 10.695133 167488 69 28
82 7.707505 143756 105 34
83 13.098346 275541 116 33
84 12.917079 243199 88 28
85 12.026775 182999 73 34
86 7.180033 135649 99 30
87 11.227831 152299 62 33
88 8.736616 120221 53 22
89 17.113741 346485 118 38
90 12.303323 145790 30 26
91 10.630383 193339 100 35
92 5.077073 80953 49 8
93 11.349959 122774 24 24
94 9.209943 130585 67 29
95 8.603716 112611 46 20
96 17.502713 286468 57 29
97 16.304220 241066 75 45
98 6.105753 148446 135 37
99 13.307528 204713 68 33
100 7.974577 182079 124 33
101 11.665544 140344 33 25
102 11.653303 220516 98 32
103 15.328548 243060 58 29
104 10.542501 162765 68 28
105 10.518016 182613 81 28
106 9.569880 232138 131 31
107 15.859401 265318 110 52
108 8.125322 85574 37 21
109 12.418224 310839 130 24
110 13.578277 225060 93 41
111 10.857384 232317 118 33
112 12.466822 144966 39 32
113 7.602798 43287 13 19
114 8.570000 155754 74 20
115 10.094764 164709 81 31
116 9.775244 201940 109 31
117 8.363771 235454 151 32
118 13.160629 220801 51 18
119 9.772986 99466 28 23
120 7.651145 92661 40 17
121 8.848317 133328 56 20
122 6.384871 61361 27 12
123 9.486544 125930 37 17
124 6.703984 100750 83 30
125 15.031294 224549 54 31
126 7.103044 82316 27 10
127 8.421700 102010 28 13
128 7.378546 101523 59 22
129 11.589998 243511 133 42
130 4.041072 22938 12 1
131 7.029326 41566 0 9
132 7.758413 152474 106 32
133 6.564190 61857 23 11
134 8.878860 99923 44 25
135 10.031112 132487 71 36
136 14.826790 317394 116 31
137 4.408103 21054 4 0
138 12.673071 209641 62 24
139 5.796177 22648 12 13
140 5.028664 31414 18 8
141 6.807442 46698 14 13
142 8.319323 131698 60 19
143 10.251644 91735 7 18
144 12.972225 244749 98 33
145 13.665612 184510 64 40
146 8.602199 79863 29 22
147 13.081491 128423 32 38
148 10.068835 97839 25 24
149 5.508780 38214 16 8
150 12.524459 151101 48 35
151 15.634647 272458 100 43
152 14.889461 172494 46 43
153 7.574015 108043 45 14
154 15.834962 328107 129 41
155 11.569054 250579 130 38
156 17.004781 351067 136 45
157 11.436381 158015 59 31
158 8.496786 98866 25 13
159 9.529246 85439 32 28
160 14.576939 229242 63 31
161 19.397705 351619 95 40
162 11.126998 84207 14 30
163 9.149647 120445 36 16
164 16.286691 324598 113 37
165 10.894609 131069 47 30
166 11.764405 204271 92 35
167 11.115122 165543 70 32
168 13.086703 141722 19 27
169 8.467103 116048 50 20
170 15.331388 250047 41 18
171 15.867337 299775 91 31
172 9.328871 195838 111 31
173 12.061557 173260 41 21
174 12.662375 254488 120 39
175 4.565615 104389 135 41
176 10.144631 136084 27 13
177 11.468779 199476 87 32
178 8.926121 92499 25 18
179 10.371834 224330 131 39
180 8.914953 135781 45 14
181 6.127083 74408 29 7
182 5.736563 81240 58 17
183 4.100352 14688 4 0
184 13.339024 181633 47 30
185 14.039754 271856 109 37
186 3.511235 7199 7 0
187 5.777572 46660 12 5
188 4.688760 17547 0 1
189 9.698692 133368 37 16
190 10.213675 95227 37 32
191 11.126660 152601 46 24
192 9.808607 98146 15 17
193 5.984709 79619 42 11
194 9.563077 59194 7 24
195 9.614296 139942 54 22
196 7.108869 118612 54 12
197 8.957720 72880 14 19
198 7.563794 65475 16 13
199 8.518520 99643 33 17
200 6.961321 71965 32 15
201 8.197917 77272 21 16
202 8.478704 49289 15 24
203 9.560801 135131 38 15
204 9.776696 108446 22 17
205 8.565957 89746 28 18
206 8.026079 44296 10 20
207 7.459173 77648 31 16
208 12.405350 181528 32 16
209 10.403477 134019 32 18
210 9.679318 124064 43 22
211 7.306799 92630 27 8
212 9.289208 121848 37 17
213 7.390973 52915 20 18
214 7.587682 81872 32 16
215 9.935198 58981 0 23
216 9.145068 53515 5 22
217 6.581450 60812 26 13
218 7.578025 56375 10 13
219 7.174187 65490 27 16
220 9.132594 80949 11 16
221 8.135196 76302 29 20
222 10.072354 104011 25 22
223 6.778895 98104 55 17
224 7.892619 67989 23 18
225 7.318958 30989 5 17
226 8.755868 135458 43 12
227 6.537533 73504 23 7
228 6.677342 63123 34 17
229 5.993324 61254 36 14
230 8.056224 74914 35 23
231 7.735368 31774 0 17
232 6.893338 81437 37 14
233 7.999918 87186 28 15
234 7.409745 50090 16 17
235 7.999342 65745 26 21
236 6.209222 56653 38 18
237 12.263308 158399 23 18
238 6.779866 46455 22 17
239 7.487760 73624 30 17
240 6.696947 38395 16 16
241 8.984679 91899 18 15
242 11.414751 139526 28 21
243 6.151508 52164 32 16
244 6.660406 51567 21 14
245 7.574192 70551 23 15
246 8.106440 84856 29 17
247 7.076854 102538 50 15
248 9.186432 86678 12 15
249 7.721224 85709 21 10
250 4.890828 34662 18 6
251 12.172254 150580 27 22
252 8.501145 99611 41 21
253 3.791877 19349 13 1
254 10.242427 99373 12 18
255 8.778400 86230 21 17
256 5.167983 30837 8 4
257 4.732098 31706 26 10
258 8.349695 89806 27 16
259 8.069413 62088 13 16
260 5.749848 40151 16 9
261 7.236417 27634 2 16
262 6.742178 76990 42 17
263 6.157515 37460 5 7
264 5.721969 54157 37 15
265 6.880750 49862 17 14
266 6.957841 84337 38 14
267 6.648550 64175 37 18
268 6.137816 59382 29 12
269 9.397450 119308 32 16
270 7.847808 76702 35 21
271 10.207280 103425 17 19
272 7.938689 70344 20 16
273 5.409210 43410 7 1
274 7.638238 104838 46 16
275 6.358378 62215 24 10
276 6.816852 69304 40 19
277 7.802941 53117 3 12
278 4.186443 19764 10 2
279 7.146800 86680 37 14
280 8.978440 84105 17 17
281 8.142888 77945 28 19
282 8.626876 89113 19 14
283 7.519139 91005 29 11
284 5.622938 40248 8 4
285 8.397961 64187 10 16
286 7.964797 50857 15 20
287 7.063643 56613 15 12
288 6.820639 62792 28 15
289 8.271684 72535 17 16
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time_in_rfc blogged_computations
3.693e+00 4.834e-05 -7.569e-02
compendiums_reviewed
1.474e-01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4.972e-09 -4.697e-10 -1.310e-11 4.238e-10 5.463e-09
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.693e+00 2.759e-10 1.339e+10 <2e-16 ***
time_in_rfc 4.834e-05 2.600e-15 1.860e+10 <2e-16 ***
blogged_computations -7.569e-02 5.846e-12 -1.295e+10 <2e-16 ***
compendiums_reviewed 1.474e-01 1.737e-11 8.488e+09 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.896e-09 on 285 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 2.772e+20 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,] 0.016751620 3.350324e-02 9.832484e-01
[2,] 0.010866555 2.173311e-02 9.891334e-01
[3,] 0.002552116 5.104231e-03 9.974479e-01
[4,] 0.238627236 4.772545e-01 7.613728e-01
[5,] 0.643517426 7.129651e-01 3.564826e-01
[6,] 0.576881525 8.462369e-01 4.231185e-01
[7,] 0.953099587 9.380083e-02 4.690041e-02
[8,] 0.991780982 1.643804e-02 8.219018e-03
[9,] 0.988014851 2.397030e-02 1.198515e-02
[10,] 0.980819567 3.836087e-02 1.918043e-02
[11,] 0.983291677 3.341665e-02 1.670832e-02
[12,] 0.984759701 3.048060e-02 1.524030e-02
[13,] 0.991978069 1.604386e-02 8.021931e-03
[14,] 0.987465289 2.506942e-02 1.253471e-02
[15,] 0.988027997 2.394401e-02 1.197200e-02
[16,] 0.995342931 9.314137e-03 4.657069e-03
[17,] 0.995680813 8.638375e-03 4.319187e-03
[18,] 0.999594357 8.112852e-04 4.056426e-04
[19,] 0.999421856 1.156289e-03 5.781445e-04
[20,] 0.999310692 1.378616e-03 6.893081e-04
[21,] 0.999786581 4.268373e-04 2.134186e-04
[22,] 0.999739235 5.215303e-04 2.607652e-04
[23,] 0.999812468 3.750637e-04 1.875319e-04
[24,] 0.999693556 6.128874e-04 3.064437e-04
[25,] 0.999522449 9.551018e-04 4.775509e-04
[26,] 0.999291290 1.417420e-03 7.087099e-04
[27,] 0.998909978 2.180044e-03 1.090022e-03
[28,] 0.998397745 3.204509e-03 1.602255e-03
[29,] 0.997670347 4.659306e-03 2.329653e-03
[30,] 0.998806470 2.387060e-03 1.193530e-03
[31,] 0.998328162 3.343675e-03 1.671838e-03
[32,] 0.999013196 1.973609e-03 9.868045e-04
[33,] 0.998804979 2.390043e-03 1.195021e-03
[34,] 0.998286477 3.427046e-03 1.713523e-03
[35,] 0.997657076 4.685847e-03 2.342924e-03
[36,] 0.996667847 6.664306e-03 3.332153e-03
[37,] 0.995320786 9.358428e-03 4.679214e-03
[38,] 0.995205422 9.589157e-03 4.794578e-03
[39,] 0.994392176 1.121565e-02 5.607824e-03
[40,] 0.998068234 3.863532e-03 1.931766e-03
[41,] 0.997949648 4.100704e-03 2.050352e-03
[42,] 0.999165254 1.669491e-03 8.347457e-04
[43,] 0.999045512 1.908977e-03 9.544885e-04
[44,] 0.999827214 3.455712e-04 1.727856e-04
[45,] 0.999992689 1.462168e-05 7.310839e-06
[46,] 0.999988549 2.290114e-05 1.145057e-05
[47,] 0.999996347 7.305334e-06 3.652667e-06
[48,] 0.999996132 7.736814e-06 3.868407e-06
[49,] 0.999994005 1.198985e-05 5.994923e-06
[50,] 0.999991995 1.600989e-05 8.004947e-06
[51,] 0.999987748 2.450394e-05 1.225197e-05
[52,] 0.999981502 3.699585e-05 1.849793e-05
[53,] 0.999971696 5.660852e-05 2.830426e-05
[54,] 0.999957496 8.500828e-05 4.250414e-05
[55,] 0.999993401 1.319881e-05 6.599404e-06
[56,] 0.999991618 1.676415e-05 8.382073e-06
[57,] 0.999990469 1.906272e-05 9.531358e-06
[58,] 0.999985395 2.920929e-05 1.460464e-05
[59,] 0.999982130 3.573934e-05 1.786967e-05
[60,] 0.999982788 3.442341e-05 1.721170e-05
[61,] 0.999977869 4.426245e-05 2.213123e-05
[62,] 0.999987574 2.485292e-05 1.242646e-05
[63,] 0.999991936 1.612722e-05 8.063609e-06
[64,] 0.999991433 1.713482e-05 8.567410e-06
[65,] 0.999987026 2.594785e-05 1.297392e-05
[66,] 0.999982362 3.527556e-05 1.763778e-05
[67,] 0.999989442 2.111598e-05 1.055799e-05
[68,] 0.999984130 3.173952e-05 1.586976e-05
[69,] 0.999981503 3.699492e-05 1.849746e-05
[70,] 0.999972957 5.408670e-05 2.704335e-05
[71,] 0.999960272 7.945616e-05 3.972808e-05
[72,] 0.999958582 8.283628e-05 4.141814e-05
[73,] 0.999939659 1.206828e-04 6.034139e-05
[74,] 0.999958728 8.254390e-05 4.127195e-05
[75,] 0.999969281 6.143790e-05 3.071895e-05
[76,] 0.999955317 8.936552e-05 4.468276e-05
[77,] 0.999991677 1.664671e-05 8.323357e-06
[78,] 0.999990506 1.898833e-05 9.494166e-06
[79,] 0.999986189 2.762211e-05 1.381106e-05
[80,] 0.999979797 4.040660e-05 2.020330e-05
[81,] 0.999992542 1.491524e-05 7.457622e-06
[82,] 0.999989158 2.168323e-05 1.084161e-05
[83,] 0.999996464 7.072362e-06 3.536181e-06
[84,] 0.999994723 1.055406e-05 5.277029e-06
[85,] 0.999995758 8.484280e-06 4.242140e-06
[86,] 0.999993709 1.258213e-05 6.291064e-06
[87,] 0.999995408 9.183672e-06 4.591836e-06
[88,] 0.999993186 1.362708e-05 6.813539e-06
[89,] 0.999989896 2.020741e-05 1.010370e-05
[90,] 0.999996087 7.825984e-06 3.912992e-06
[91,] 0.999998693 2.613926e-06 1.306963e-06
[92,] 0.999998008 3.983252e-06 1.991626e-06
[93,] 0.999999771 4.585472e-07 2.292736e-07
[94,] 0.999999645 7.097802e-07 3.548901e-07
[95,] 0.999999551 8.980759e-07 4.490379e-07
[96,] 0.999999346 1.307182e-06 6.535912e-07
[97,] 0.999999775 4.490758e-07 2.245379e-07
[98,] 0.999999850 3.005650e-07 1.502825e-07
[99,] 0.999999806 3.881862e-07 1.940931e-07
[100,] 0.999999702 5.958740e-07 2.979370e-07
[101,] 0.999999569 8.616968e-07 4.308484e-07
[102,] 0.999999358 1.284870e-06 6.424351e-07
[103,] 0.999999538 9.231829e-07 4.615915e-07
[104,] 0.999999784 4.326635e-07 2.163318e-07
[105,] 0.999999969 6.276173e-08 3.138086e-08
[106,] 0.999999981 3.731983e-08 1.865992e-08
[107,] 0.999999970 5.912753e-08 2.956377e-08
[108,] 0.999999953 9.398857e-08 4.699429e-08
[109,] 0.999999997 6.587902e-09 3.293951e-09
[110,] 0.999999995 1.072519e-08 5.362595e-09
[111,] 0.999999992 1.685663e-08 8.428315e-09
[112,] 0.999999987 2.543268e-08 1.271634e-08
[113,] 0.999999980 4.015513e-08 2.007756e-08
[114,] 0.999999968 6.471487e-08 3.235744e-08
[115,] 0.999999949 1.020823e-07 5.104114e-08
[116,] 0.999999919 1.611389e-07 8.056943e-08
[117,] 0.999999873 2.534462e-07 1.267231e-07
[118,] 0.999999802 3.954915e-07 1.977458e-07
[119,] 0.999999848 3.036193e-07 1.518096e-07
[120,] 0.999999768 4.648755e-07 2.324377e-07
[121,] 0.999999643 7.143769e-07 3.571884e-07
[122,] 0.999999452 1.095632e-06 5.478159e-07
[123,] 0.999999704 5.925750e-07 2.962875e-07
[124,] 0.999999558 8.845882e-07 4.422941e-07
[125,] 0.999999325 1.349826e-06 6.749131e-07
[126,] 0.999999004 1.991508e-06 9.957540e-07
[127,] 0.999998502 2.995303e-06 1.497651e-06
[128,] 0.999997782 4.436918e-06 2.218459e-06
[129,] 0.999996703 6.594009e-06 3.297005e-06
[130,] 0.999996060 7.879677e-06 3.939839e-06
[131,] 0.999994255 1.149060e-05 5.745300e-06
[132,] 0.999995895 8.210478e-06 4.105239e-06
[133,] 0.999994019 1.196148e-05 5.980739e-06
[134,] 0.999991230 1.754041e-05 8.770203e-06
[135,] 0.999987165 2.566910e-05 1.283455e-05
[136,] 0.999981842 3.631576e-05 1.815788e-05
[137,] 0.999990622 1.875516e-05 9.377579e-06
[138,] 0.999997547 4.905118e-06 2.452559e-06
[139,] 0.999997799 4.401195e-06 2.200598e-06
[140,] 0.999996709 6.582295e-06 3.291147e-06
[141,] 0.999999252 1.496550e-06 7.482750e-07
[142,] 0.999998885 2.230590e-06 1.115295e-06
[143,] 0.999998328 3.344776e-06 1.672388e-06
[144,] 0.999999387 1.226391e-06 6.131957e-07
[145,] 0.999999129 1.742339e-06 8.711696e-07
[146,] 0.999999322 1.356788e-06 6.783939e-07
[147,] 0.999998956 2.087456e-06 1.043728e-06
[148,] 0.999999628 7.434807e-07 3.717403e-07
[149,] 0.999999915 1.692260e-07 8.461298e-08
[150,] 0.999999866 2.674586e-07 1.337293e-07
[151,] 0.999999810 3.794218e-07 1.897109e-07
[152,] 0.999999704 5.916088e-07 2.958044e-07
[153,] 0.999999539 9.214568e-07 4.607284e-07
[154,] 0.999999817 3.650715e-07 1.825357e-07
[155,] 0.999999859 2.818348e-07 1.409174e-07
[156,] 0.999999944 1.120824e-07 5.604121e-08
[157,] 0.999999909 1.812456e-07 9.062282e-08
[158,] 0.999999952 9.697732e-08 4.848866e-08
[159,] 0.999999998 3.082348e-09 1.541174e-09
[160,] 1.000000000 3.211135e-11 1.605567e-11
[161,] 1.000000000 4.205917e-13 2.102958e-13
[162,] 1.000000000 8.511714e-14 4.255857e-14
[163,] 1.000000000 1.681031e-13 8.405155e-14
[164,] 1.000000000 3.267632e-13 1.633816e-13
[165,] 1.000000000 1.419589e-17 7.097947e-18
[166,] 1.000000000 1.423977e-17 7.119885e-18
[167,] 1.000000000 1.066536e-17 5.332680e-18
[168,] 1.000000000 9.976573e-18 4.988286e-18
[169,] 1.000000000 2.228678e-17 1.114339e-17
[170,] 1.000000000 1.782913e-19 8.914566e-20
[171,] 1.000000000 3.885668e-21 1.942834e-21
[172,] 1.000000000 9.816086e-21 4.908043e-21
[173,] 1.000000000 1.462880e-20 7.314400e-21
[174,] 1.000000000 3.327993e-20 1.663996e-20
[175,] 1.000000000 7.370177e-20 3.685089e-20
[176,] 1.000000000 1.603115e-19 8.015576e-20
[177,] 1.000000000 3.132516e-19 1.566258e-19
[178,] 1.000000000 5.690475e-23 2.845238e-23
[179,] 1.000000000 9.812884e-23 4.906442e-23
[180,] 1.000000000 2.227802e-22 1.113901e-22
[181,] 1.000000000 5.012004e-22 2.506002e-22
[182,] 1.000000000 1.304326e-21 6.521630e-22
[183,] 1.000000000 3.508128e-21 1.754064e-21
[184,] 1.000000000 2.613721e-22 1.306861e-22
[185,] 1.000000000 1.266242e-22 6.331211e-23
[186,] 1.000000000 3.481228e-22 1.740614e-22
[187,] 1.000000000 9.719163e-22 4.859581e-22
[188,] 1.000000000 2.591988e-21 1.295994e-21
[189,] 1.000000000 6.255311e-21 3.127655e-21
[190,] 1.000000000 1.699595e-20 8.497976e-21
[191,] 1.000000000 4.388400e-20 2.194200e-20
[192,] 1.000000000 1.059874e-19 5.299370e-20
[193,] 1.000000000 2.596215e-19 1.298107e-19
[194,] 1.000000000 6.050587e-19 3.025294e-19
[195,] 1.000000000 1.337622e-18 6.688112e-19
[196,] 1.000000000 3.476746e-18 1.738373e-18
[197,] 1.000000000 8.132803e-18 4.066402e-18
[198,] 1.000000000 2.069796e-17 1.034898e-17
[199,] 1.000000000 4.368607e-17 2.184304e-17
[200,] 1.000000000 1.070491e-16 5.352455e-17
[201,] 1.000000000 2.694016e-16 1.347008e-16
[202,] 1.000000000 5.494472e-16 2.747236e-16
[203,] 1.000000000 8.330033e-16 4.165017e-16
[204,] 1.000000000 2.070654e-15 1.035327e-15
[205,] 1.000000000 5.076037e-15 2.538019e-15
[206,] 1.000000000 1.099854e-14 5.499272e-15
[207,] 1.000000000 2.517389e-14 1.258695e-14
[208,] 1.000000000 5.328249e-14 2.664125e-14
[209,] 1.000000000 1.260340e-13 6.301701e-14
[210,] 1.000000000 2.929065e-13 1.464532e-13
[211,] 1.000000000 6.847843e-13 3.423921e-13
[212,] 1.000000000 1.488853e-12 7.444264e-13
[213,] 1.000000000 3.427616e-12 1.713808e-12
[214,] 1.000000000 7.786859e-12 3.893430e-12
[215,] 1.000000000 1.727815e-11 8.639076e-12
[216,] 1.000000000 6.116567e-14 3.058284e-14
[217,] 1.000000000 1.317968e-13 6.589839e-14
[218,] 1.000000000 3.298739e-13 1.649370e-13
[219,] 1.000000000 7.978486e-13 3.989243e-13
[220,] 1.000000000 1.963623e-12 9.818113e-13
[221,] 1.000000000 4.481205e-12 2.240602e-12
[222,] 1.000000000 1.077050e-11 5.385250e-12
[223,] 1.000000000 2.570773e-11 1.285387e-11
[224,] 1.000000000 5.916752e-11 2.958376e-11
[225,] 1.000000000 1.342928e-10 6.714639e-11
[226,] 1.000000000 2.798900e-10 1.399450e-10
[227,] 1.000000000 6.194568e-10 3.097284e-10
[228,] 0.999999999 1.227604e-09 6.138019e-10
[229,] 0.999999999 2.755245e-09 1.377623e-09
[230,] 0.999999997 5.842563e-09 2.921281e-09
[231,] 1.000000000 1.302247e-10 6.511236e-11
[232,] 1.000000000 3.088674e-10 1.544337e-10
[233,] 1.000000000 7.104475e-10 3.552238e-10
[234,] 0.999999999 1.668578e-09 8.342889e-10
[235,] 0.999999998 3.913391e-09 1.956696e-09
[236,] 0.999999996 7.417124e-09 3.708562e-09
[237,] 0.999999991 1.720345e-08 8.601724e-09
[238,] 0.999999981 3.838507e-08 1.919253e-08
[239,] 0.999999959 8.247957e-08 4.123978e-08
[240,] 0.999999920 1.593848e-07 7.969240e-08
[241,] 0.999999840 3.204919e-07 1.602459e-07
[242,] 0.999999701 5.973702e-07 2.986851e-07
[243,] 0.999999364 1.272623e-06 6.363116e-07
[244,] 0.999998754 2.491119e-06 1.245559e-06
[245,] 0.999999990 2.044882e-08 1.022441e-08
[246,] 0.999999976 4.881806e-08 2.440903e-08
[247,] 0.999999953 9.482323e-08 4.741162e-08
[248,] 1.000000000 1.167395e-14 5.836977e-15
[249,] 1.000000000 5.129827e-14 2.564914e-14
[250,] 1.000000000 1.806309e-13 9.031544e-14
[251,] 1.000000000 3.838005e-13 1.919003e-13
[252,] 1.000000000 1.640667e-12 8.203335e-13
[253,] 1.000000000 6.998490e-12 3.499245e-12
[254,] 1.000000000 1.790545e-11 8.952724e-12
[255,] 1.000000000 7.519399e-11 3.759700e-11
[256,] 1.000000000 1.959676e-10 9.798379e-11
[257,] 1.000000000 4.650233e-10 2.325116e-10
[258,] 0.999999999 1.868583e-09 9.342914e-10
[259,] 0.999999996 7.308143e-09 3.654072e-09
[260,] 0.999999986 2.870829e-08 1.435415e-08
[261,] 0.999999966 6.824036e-08 3.412018e-08
[262,] 0.999999922 1.551454e-07 7.757272e-08
[263,] 0.999999843 3.139267e-07 1.569634e-07
[264,] 0.999999423 1.153256e-06 5.766281e-07
[265,] 1.000000000 9.311795e-10 4.655897e-10
[266,] 0.999999998 3.335084e-09 1.667542e-09
[267,] 0.999999989 2.283135e-08 1.141568e-08
[268,] 0.999999930 1.402997e-07 7.014983e-08
[269,] 0.999999889 2.223289e-07 1.111644e-07
[270,] 0.999999241 1.518036e-06 7.590181e-07
[271,] 0.999997081 5.837427e-06 2.918714e-06
[272,] 0.999980217 3.956551e-05 1.978276e-05
[273,] 0.999927800 1.444002e-04 7.220010e-05
[274,] 0.999555836 8.883288e-04 4.441644e-04
[275,] 0.997555948 4.888105e-03 2.444052e-03
[276,] 0.999570956 8.580875e-04 4.290438e-04
> postscript(file="/var/wessaorg/rcomp/tmp/13rf81324377885.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2crsz1324377885.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3qfcm1324377885.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/42avf1324377885.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/58y311324377885.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
-1.723658e-09 2.513310e-10 -2.648560e-09 -5.243379e-10 2.809621e-10
6 7 8 9 10
-8.760340e-10 -3.110440e-09 -1.052950e-10 4.974967e-10 -4.822442e-09
11 12 13 14 15
-4.971467e-09 -4.783487e-09 3.920942e-09 3.698974e-09 -2.683328e-09
16 17 18 19 20
-1.220391e-09 1.881239e-09 -3.231178e-09 1.364957e-09 3.260586e-11
21 22 23 24 25
2.884083e-09 3.950829e-09 -2.012340e-09 4.582295e-09 1.534437e-10
26 27 28 29 30
-5.815418e-10 3.923316e-09 -2.300497e-09 2.816908e-09 -5.916274e-12
31 32 33 34 35
-4.465197e-10 8.414600e-10 6.853917e-11 7.212087e-10 9.091482e-11
36 37 38 39 40
2.708661e-09 2.080735e-10 2.858394e-09 4.476643e-10 -2.804743e-11
41 42 43 44 45
7.550635e-10 -3.626207e-10 1.453607e-10 1.759655e-09 1.388458e-09
46 47 48 49 50
4.537400e-09 -2.195264e-09 -3.747391e-09 1.809202e-09 -4.573344e-09
51 52 53 54 55
5.462522e-09 2.946459e-10 -3.644545e-09 2.187576e-09 -3.944447e-10
56 57 58 59 60
1.306459e-09 2.961169e-11 -4.127258e-10 -8.963341e-11 1.321169e-10
61 62 63 64 65
4.831236e-09 -1.164504e-09 1.843473e-09 -2.399883e-10 1.602057e-09
66 67 68 69 70
-1.862566e-09 -1.194826e-09 -2.976864e-09 -2.878579e-09 1.952208e-09
71 72 73 74 75
1.745904e-10 1.075164e-09 3.019715e-09 -1.530986e-10 -1.525082e-09
76 77 78 79 80
-4.697420e-10 -2.369375e-11 -1.848224e-09 -9.524303e-11 -2.812008e-09
81 82 83 84 85
-2.670920e-09 -2.395063e-10 -4.590185e-09 -1.639336e-09 -4.931258e-10
86 87 88 89 90
1.831333e-10 -3.729469e-09 4.605640e-10 3.852897e-09 3.098437e-10
91 92 93 94 95
2.404649e-09 2.637339e-10 2.602415e-09 -2.944468e-10 1.012892e-10
96 97 98 99 100
-3.573387e-09 -3.705930e-09 1.899201e-11 -4.707999e-09 -2.748707e-10
101 102 103 104 105
1.322273e-09 7.545778e-10 -3.493673e-09 2.656792e-09 -1.220147e-09
106 107 108 109 110
-3.491743e-10 -5.621469e-10 -5.223846e-10 -2.408706e-09 -2.968359e-09
111 112 113 114 115
4.400340e-09 -2.575913e-09 3.884963e-10 3.097206e-10 -4.603330e-09
116 117 118 119 120
-1.908564e-10 -4.139530e-10 8.420013e-10 4.854191e-10 -5.845436e-11
121 122 123 124 125
4.016015e-10 2.295474e-10 -1.185041e-10 -3.866618e-11 2.476043e-09
126 127 128 129 130
-4.011473e-10 3.115312e-10 -1.326857e-10 3.046867e-09 -6.066200e-10
131 132 133 134 135
2.228780e-10 -4.366569e-10 -3.060961e-10 4.238254e-10 1.007507e-10
136 137 138 139 140
-1.178942e-09 2.387568e-10 2.607375e-09 3.773298e-10 -2.332181e-10
141 142 143 144 145
2.722463e-12 -4.513889e-10 3.069921e-09 3.960932e-09 -1.809372e-09
146 147 148 149 150
2.556451e-10 4.033462e-09 5.080333e-10 -3.577091e-10 3.356768e-09
151 152 153 154 155
8.620957e-10 2.160285e-09 1.193607e-10 -3.058441e-09 3.829188e-09
156 157 158 159 160
-1.042799e-10 -8.867856e-10 3.180825e-10 -2.714169e-10 -2.951773e-09
161 162 163 164 165
2.390367e-09 -3.028565e-09 -4.062767e-11 -2.357174e-09 4.769255e-09
166 167 168 169 170
-4.714538e-09 -4.155172e-09 -2.622208e-09 -7.009511e-12 5.378812e-10
171 172 173 174 175
-4.330061e-09 -3.394392e-10 2.516432e-09 2.900964e-09 1.332398e-10
176 177 178 179 180
4.041107e-09 4.009010e-09 5.769308e-12 1.320693e-10 -1.221313e-10
181 182 183 184 185
-5.471911e-10 -2.967870e-10 1.648266e-10 4.723731e-09 1.752518e-09
186 187 188 189 190
2.823562e-10 3.503683e-10 -5.733146e-10 1.456788e-10 2.400455e-09
191 192 193 194 195
1.679498e-09 5.528211e-11 1.172303e-10 -1.278692e-10 -4.023659e-10
196 197 198 199 200
1.191590e-10 -4.741438e-10 -5.166900e-10 3.562249e-10 4.239185e-10
201 202 203 204 205
4.301459e-10 -2.829631e-10 4.910831e-10 -2.494929e-10 4.767596e-10
206 207 208 209 210
-5.256026e-10 -1.554674e-10 -5.122886e-10 9.482624e-10 -2.703763e-11
211 212 213 214 215
-5.362783e-11 4.526887e-10 -5.251040e-10 4.183464e-10 -2.585923e-10
216 217 218 219 220
-4.991062e-10 1.951004e-11 2.240465e-10 -6.079533e-11 -8.420245e-11
221 222 223 224 225
-3.854907e-10 -3.667259e-09 -4.760364e-10 -6.995709e-12 -4.898263e-12
226 227 228 229 230
1.648114e-10 -3.653729e-10 2.771226e-11 -6.728787e-12 -2.903898e-10
231 232 233 234 235
-4.709772e-10 -4.458185e-10 -2.686964e-10 3.860761e-10 -1.872863e-10
236 237 238 239 240
-3.630736e-10 -2.523802e-09 -5.572199e-10 2.733718e-10 -2.097014e-10
241 242 243 244 245
1.067746e-10 1.204149e-09 -2.599948e-10 2.823228e-11 -3.608922e-10
246 247 248 249 250
-4.847545e-10 -1.203170e-10 -4.250662e-10 1.296625e-10 2.769796e-10
251 252 253 254 255
3.556443e-09 -3.564669e-10 -4.904898e-10 -3.883933e-09 1.210625e-10
256 257 258 259 260
2.635993e-10 2.497773e-10 3.029637e-10 1.270516e-10 3.163892e-10
261 262 263 264 265
-2.015676e-10 3.173983e-10 4.238408e-10 -4.974539e-10 -2.831913e-10
266 267 268 269 270
-1.304819e-11 2.328233e-10 2.573405e-10 4.529499e-12 -4.009811e-10
271 272 273 274 275
2.133153e-09 -4.468262e-10 -1.114259e-10 -5.093834e-11 4.213594e-10
276 277 278 279 280
-2.244267e-10 -4.274300e-10 -2.352386e-10 1.519844e-10 1.516028e-10
281 282 283 284 285
-3.398185e-10 5.083690e-10 -5.032963e-10 -1.417166e-10 -2.685936e-10
286 287 288 289
-1.168468e-10 -1.305996e-11 -5.466121e-11 -1.649965e-10
> postscript(file="/var/wessaorg/rcomp/tmp/6sqly1324377885.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 -1.723658e-09 NA
1 2.513310e-10 -1.723658e-09
2 -2.648560e-09 2.513310e-10
3 -5.243379e-10 -2.648560e-09
4 2.809621e-10 -5.243379e-10
5 -8.760340e-10 2.809621e-10
6 -3.110440e-09 -8.760340e-10
7 -1.052950e-10 -3.110440e-09
8 4.974967e-10 -1.052950e-10
9 -4.822442e-09 4.974967e-10
10 -4.971467e-09 -4.822442e-09
11 -4.783487e-09 -4.971467e-09
12 3.920942e-09 -4.783487e-09
13 3.698974e-09 3.920942e-09
14 -2.683328e-09 3.698974e-09
15 -1.220391e-09 -2.683328e-09
16 1.881239e-09 -1.220391e-09
17 -3.231178e-09 1.881239e-09
18 1.364957e-09 -3.231178e-09
19 3.260586e-11 1.364957e-09
20 2.884083e-09 3.260586e-11
21 3.950829e-09 2.884083e-09
22 -2.012340e-09 3.950829e-09
23 4.582295e-09 -2.012340e-09
24 1.534437e-10 4.582295e-09
25 -5.815418e-10 1.534437e-10
26 3.923316e-09 -5.815418e-10
27 -2.300497e-09 3.923316e-09
28 2.816908e-09 -2.300497e-09
29 -5.916274e-12 2.816908e-09
30 -4.465197e-10 -5.916274e-12
31 8.414600e-10 -4.465197e-10
32 6.853917e-11 8.414600e-10
33 7.212087e-10 6.853917e-11
34 9.091482e-11 7.212087e-10
35 2.708661e-09 9.091482e-11
36 2.080735e-10 2.708661e-09
37 2.858394e-09 2.080735e-10
38 4.476643e-10 2.858394e-09
39 -2.804743e-11 4.476643e-10
40 7.550635e-10 -2.804743e-11
41 -3.626207e-10 7.550635e-10
42 1.453607e-10 -3.626207e-10
43 1.759655e-09 1.453607e-10
44 1.388458e-09 1.759655e-09
45 4.537400e-09 1.388458e-09
46 -2.195264e-09 4.537400e-09
47 -3.747391e-09 -2.195264e-09
48 1.809202e-09 -3.747391e-09
49 -4.573344e-09 1.809202e-09
50 5.462522e-09 -4.573344e-09
51 2.946459e-10 5.462522e-09
52 -3.644545e-09 2.946459e-10
53 2.187576e-09 -3.644545e-09
54 -3.944447e-10 2.187576e-09
55 1.306459e-09 -3.944447e-10
56 2.961169e-11 1.306459e-09
57 -4.127258e-10 2.961169e-11
58 -8.963341e-11 -4.127258e-10
59 1.321169e-10 -8.963341e-11
60 4.831236e-09 1.321169e-10
61 -1.164504e-09 4.831236e-09
62 1.843473e-09 -1.164504e-09
63 -2.399883e-10 1.843473e-09
64 1.602057e-09 -2.399883e-10
65 -1.862566e-09 1.602057e-09
66 -1.194826e-09 -1.862566e-09
67 -2.976864e-09 -1.194826e-09
68 -2.878579e-09 -2.976864e-09
69 1.952208e-09 -2.878579e-09
70 1.745904e-10 1.952208e-09
71 1.075164e-09 1.745904e-10
72 3.019715e-09 1.075164e-09
73 -1.530986e-10 3.019715e-09
74 -1.525082e-09 -1.530986e-10
75 -4.697420e-10 -1.525082e-09
76 -2.369375e-11 -4.697420e-10
77 -1.848224e-09 -2.369375e-11
78 -9.524303e-11 -1.848224e-09
79 -2.812008e-09 -9.524303e-11
80 -2.670920e-09 -2.812008e-09
81 -2.395063e-10 -2.670920e-09
82 -4.590185e-09 -2.395063e-10
83 -1.639336e-09 -4.590185e-09
84 -4.931258e-10 -1.639336e-09
85 1.831333e-10 -4.931258e-10
86 -3.729469e-09 1.831333e-10
87 4.605640e-10 -3.729469e-09
88 3.852897e-09 4.605640e-10
89 3.098437e-10 3.852897e-09
90 2.404649e-09 3.098437e-10
91 2.637339e-10 2.404649e-09
92 2.602415e-09 2.637339e-10
93 -2.944468e-10 2.602415e-09
94 1.012892e-10 -2.944468e-10
95 -3.573387e-09 1.012892e-10
96 -3.705930e-09 -3.573387e-09
97 1.899201e-11 -3.705930e-09
98 -4.707999e-09 1.899201e-11
99 -2.748707e-10 -4.707999e-09
100 1.322273e-09 -2.748707e-10
101 7.545778e-10 1.322273e-09
102 -3.493673e-09 7.545778e-10
103 2.656792e-09 -3.493673e-09
104 -1.220147e-09 2.656792e-09
105 -3.491743e-10 -1.220147e-09
106 -5.621469e-10 -3.491743e-10
107 -5.223846e-10 -5.621469e-10
108 -2.408706e-09 -5.223846e-10
109 -2.968359e-09 -2.408706e-09
110 4.400340e-09 -2.968359e-09
111 -2.575913e-09 4.400340e-09
112 3.884963e-10 -2.575913e-09
113 3.097206e-10 3.884963e-10
114 -4.603330e-09 3.097206e-10
115 -1.908564e-10 -4.603330e-09
116 -4.139530e-10 -1.908564e-10
117 8.420013e-10 -4.139530e-10
118 4.854191e-10 8.420013e-10
119 -5.845436e-11 4.854191e-10
120 4.016015e-10 -5.845436e-11
121 2.295474e-10 4.016015e-10
122 -1.185041e-10 2.295474e-10
123 -3.866618e-11 -1.185041e-10
124 2.476043e-09 -3.866618e-11
125 -4.011473e-10 2.476043e-09
126 3.115312e-10 -4.011473e-10
127 -1.326857e-10 3.115312e-10
128 3.046867e-09 -1.326857e-10
129 -6.066200e-10 3.046867e-09
130 2.228780e-10 -6.066200e-10
131 -4.366569e-10 2.228780e-10
132 -3.060961e-10 -4.366569e-10
133 4.238254e-10 -3.060961e-10
134 1.007507e-10 4.238254e-10
135 -1.178942e-09 1.007507e-10
136 2.387568e-10 -1.178942e-09
137 2.607375e-09 2.387568e-10
138 3.773298e-10 2.607375e-09
139 -2.332181e-10 3.773298e-10
140 2.722463e-12 -2.332181e-10
141 -4.513889e-10 2.722463e-12
142 3.069921e-09 -4.513889e-10
143 3.960932e-09 3.069921e-09
144 -1.809372e-09 3.960932e-09
145 2.556451e-10 -1.809372e-09
146 4.033462e-09 2.556451e-10
147 5.080333e-10 4.033462e-09
148 -3.577091e-10 5.080333e-10
149 3.356768e-09 -3.577091e-10
150 8.620957e-10 3.356768e-09
151 2.160285e-09 8.620957e-10
152 1.193607e-10 2.160285e-09
153 -3.058441e-09 1.193607e-10
154 3.829188e-09 -3.058441e-09
155 -1.042799e-10 3.829188e-09
156 -8.867856e-10 -1.042799e-10
157 3.180825e-10 -8.867856e-10
158 -2.714169e-10 3.180825e-10
159 -2.951773e-09 -2.714169e-10
160 2.390367e-09 -2.951773e-09
161 -3.028565e-09 2.390367e-09
162 -4.062767e-11 -3.028565e-09
163 -2.357174e-09 -4.062767e-11
164 4.769255e-09 -2.357174e-09
165 -4.714538e-09 4.769255e-09
166 -4.155172e-09 -4.714538e-09
167 -2.622208e-09 -4.155172e-09
168 -7.009511e-12 -2.622208e-09
169 5.378812e-10 -7.009511e-12
170 -4.330061e-09 5.378812e-10
171 -3.394392e-10 -4.330061e-09
172 2.516432e-09 -3.394392e-10
173 2.900964e-09 2.516432e-09
174 1.332398e-10 2.900964e-09
175 4.041107e-09 1.332398e-10
176 4.009010e-09 4.041107e-09
177 5.769308e-12 4.009010e-09
178 1.320693e-10 5.769308e-12
179 -1.221313e-10 1.320693e-10
180 -5.471911e-10 -1.221313e-10
181 -2.967870e-10 -5.471911e-10
182 1.648266e-10 -2.967870e-10
183 4.723731e-09 1.648266e-10
184 1.752518e-09 4.723731e-09
185 2.823562e-10 1.752518e-09
186 3.503683e-10 2.823562e-10
187 -5.733146e-10 3.503683e-10
188 1.456788e-10 -5.733146e-10
189 2.400455e-09 1.456788e-10
190 1.679498e-09 2.400455e-09
191 5.528211e-11 1.679498e-09
192 1.172303e-10 5.528211e-11
193 -1.278692e-10 1.172303e-10
194 -4.023659e-10 -1.278692e-10
195 1.191590e-10 -4.023659e-10
196 -4.741438e-10 1.191590e-10
197 -5.166900e-10 -4.741438e-10
198 3.562249e-10 -5.166900e-10
199 4.239185e-10 3.562249e-10
200 4.301459e-10 4.239185e-10
201 -2.829631e-10 4.301459e-10
202 4.910831e-10 -2.829631e-10
203 -2.494929e-10 4.910831e-10
204 4.767596e-10 -2.494929e-10
205 -5.256026e-10 4.767596e-10
206 -1.554674e-10 -5.256026e-10
207 -5.122886e-10 -1.554674e-10
208 9.482624e-10 -5.122886e-10
209 -2.703763e-11 9.482624e-10
210 -5.362783e-11 -2.703763e-11
211 4.526887e-10 -5.362783e-11
212 -5.251040e-10 4.526887e-10
213 4.183464e-10 -5.251040e-10
214 -2.585923e-10 4.183464e-10
215 -4.991062e-10 -2.585923e-10
216 1.951004e-11 -4.991062e-10
217 2.240465e-10 1.951004e-11
218 -6.079533e-11 2.240465e-10
219 -8.420245e-11 -6.079533e-11
220 -3.854907e-10 -8.420245e-11
221 -3.667259e-09 -3.854907e-10
222 -4.760364e-10 -3.667259e-09
223 -6.995709e-12 -4.760364e-10
224 -4.898263e-12 -6.995709e-12
225 1.648114e-10 -4.898263e-12
226 -3.653729e-10 1.648114e-10
227 2.771226e-11 -3.653729e-10
228 -6.728787e-12 2.771226e-11
229 -2.903898e-10 -6.728787e-12
230 -4.709772e-10 -2.903898e-10
231 -4.458185e-10 -4.709772e-10
232 -2.686964e-10 -4.458185e-10
233 3.860761e-10 -2.686964e-10
234 -1.872863e-10 3.860761e-10
235 -3.630736e-10 -1.872863e-10
236 -2.523802e-09 -3.630736e-10
237 -5.572199e-10 -2.523802e-09
238 2.733718e-10 -5.572199e-10
239 -2.097014e-10 2.733718e-10
240 1.067746e-10 -2.097014e-10
241 1.204149e-09 1.067746e-10
242 -2.599948e-10 1.204149e-09
243 2.823228e-11 -2.599948e-10
244 -3.608922e-10 2.823228e-11
245 -4.847545e-10 -3.608922e-10
246 -1.203170e-10 -4.847545e-10
247 -4.250662e-10 -1.203170e-10
248 1.296625e-10 -4.250662e-10
249 2.769796e-10 1.296625e-10
250 3.556443e-09 2.769796e-10
251 -3.564669e-10 3.556443e-09
252 -4.904898e-10 -3.564669e-10
253 -3.883933e-09 -4.904898e-10
254 1.210625e-10 -3.883933e-09
255 2.635993e-10 1.210625e-10
256 2.497773e-10 2.635993e-10
257 3.029637e-10 2.497773e-10
258 1.270516e-10 3.029637e-10
259 3.163892e-10 1.270516e-10
260 -2.015676e-10 3.163892e-10
261 3.173983e-10 -2.015676e-10
262 4.238408e-10 3.173983e-10
263 -4.974539e-10 4.238408e-10
264 -2.831913e-10 -4.974539e-10
265 -1.304819e-11 -2.831913e-10
266 2.328233e-10 -1.304819e-11
267 2.573405e-10 2.328233e-10
268 4.529499e-12 2.573405e-10
269 -4.009811e-10 4.529499e-12
270 2.133153e-09 -4.009811e-10
271 -4.468262e-10 2.133153e-09
272 -1.114259e-10 -4.468262e-10
273 -5.093834e-11 -1.114259e-10
274 4.213594e-10 -5.093834e-11
275 -2.244267e-10 4.213594e-10
276 -4.274300e-10 -2.244267e-10
277 -2.352386e-10 -4.274300e-10
278 1.519844e-10 -2.352386e-10
279 1.516028e-10 1.519844e-10
280 -3.398185e-10 1.516028e-10
281 5.083690e-10 -3.398185e-10
282 -5.032963e-10 5.083690e-10
283 -1.417166e-10 -5.032963e-10
284 -2.685936e-10 -1.417166e-10
285 -1.168468e-10 -2.685936e-10
286 -1.305996e-11 -1.168468e-10
287 -5.466121e-11 -1.305996e-11
288 -1.649965e-10 -5.466121e-11
289 NA -1.649965e-10
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.513310e-10 -1.723658e-09
[2,] -2.648560e-09 2.513310e-10
[3,] -5.243379e-10 -2.648560e-09
[4,] 2.809621e-10 -5.243379e-10
[5,] -8.760340e-10 2.809621e-10
[6,] -3.110440e-09 -8.760340e-10
[7,] -1.052950e-10 -3.110440e-09
[8,] 4.974967e-10 -1.052950e-10
[9,] -4.822442e-09 4.974967e-10
[10,] -4.971467e-09 -4.822442e-09
[11,] -4.783487e-09 -4.971467e-09
[12,] 3.920942e-09 -4.783487e-09
[13,] 3.698974e-09 3.920942e-09
[14,] -2.683328e-09 3.698974e-09
[15,] -1.220391e-09 -2.683328e-09
[16,] 1.881239e-09 -1.220391e-09
[17,] -3.231178e-09 1.881239e-09
[18,] 1.364957e-09 -3.231178e-09
[19,] 3.260586e-11 1.364957e-09
[20,] 2.884083e-09 3.260586e-11
[21,] 3.950829e-09 2.884083e-09
[22,] -2.012340e-09 3.950829e-09
[23,] 4.582295e-09 -2.012340e-09
[24,] 1.534437e-10 4.582295e-09
[25,] -5.815418e-10 1.534437e-10
[26,] 3.923316e-09 -5.815418e-10
[27,] -2.300497e-09 3.923316e-09
[28,] 2.816908e-09 -2.300497e-09
[29,] -5.916274e-12 2.816908e-09
[30,] -4.465197e-10 -5.916274e-12
[31,] 8.414600e-10 -4.465197e-10
[32,] 6.853917e-11 8.414600e-10
[33,] 7.212087e-10 6.853917e-11
[34,] 9.091482e-11 7.212087e-10
[35,] 2.708661e-09 9.091482e-11
[36,] 2.080735e-10 2.708661e-09
[37,] 2.858394e-09 2.080735e-10
[38,] 4.476643e-10 2.858394e-09
[39,] -2.804743e-11 4.476643e-10
[40,] 7.550635e-10 -2.804743e-11
[41,] -3.626207e-10 7.550635e-10
[42,] 1.453607e-10 -3.626207e-10
[43,] 1.759655e-09 1.453607e-10
[44,] 1.388458e-09 1.759655e-09
[45,] 4.537400e-09 1.388458e-09
[46,] -2.195264e-09 4.537400e-09
[47,] -3.747391e-09 -2.195264e-09
[48,] 1.809202e-09 -3.747391e-09
[49,] -4.573344e-09 1.809202e-09
[50,] 5.462522e-09 -4.573344e-09
[51,] 2.946459e-10 5.462522e-09
[52,] -3.644545e-09 2.946459e-10
[53,] 2.187576e-09 -3.644545e-09
[54,] -3.944447e-10 2.187576e-09
[55,] 1.306459e-09 -3.944447e-10
[56,] 2.961169e-11 1.306459e-09
[57,] -4.127258e-10 2.961169e-11
[58,] -8.963341e-11 -4.127258e-10
[59,] 1.321169e-10 -8.963341e-11
[60,] 4.831236e-09 1.321169e-10
[61,] -1.164504e-09 4.831236e-09
[62,] 1.843473e-09 -1.164504e-09
[63,] -2.399883e-10 1.843473e-09
[64,] 1.602057e-09 -2.399883e-10
[65,] -1.862566e-09 1.602057e-09
[66,] -1.194826e-09 -1.862566e-09
[67,] -2.976864e-09 -1.194826e-09
[68,] -2.878579e-09 -2.976864e-09
[69,] 1.952208e-09 -2.878579e-09
[70,] 1.745904e-10 1.952208e-09
[71,] 1.075164e-09 1.745904e-10
[72,] 3.019715e-09 1.075164e-09
[73,] -1.530986e-10 3.019715e-09
[74,] -1.525082e-09 -1.530986e-10
[75,] -4.697420e-10 -1.525082e-09
[76,] -2.369375e-11 -4.697420e-10
[77,] -1.848224e-09 -2.369375e-11
[78,] -9.524303e-11 -1.848224e-09
[79,] -2.812008e-09 -9.524303e-11
[80,] -2.670920e-09 -2.812008e-09
[81,] -2.395063e-10 -2.670920e-09
[82,] -4.590185e-09 -2.395063e-10
[83,] -1.639336e-09 -4.590185e-09
[84,] -4.931258e-10 -1.639336e-09
[85,] 1.831333e-10 -4.931258e-10
[86,] -3.729469e-09 1.831333e-10
[87,] 4.605640e-10 -3.729469e-09
[88,] 3.852897e-09 4.605640e-10
[89,] 3.098437e-10 3.852897e-09
[90,] 2.404649e-09 3.098437e-10
[91,] 2.637339e-10 2.404649e-09
[92,] 2.602415e-09 2.637339e-10
[93,] -2.944468e-10 2.602415e-09
[94,] 1.012892e-10 -2.944468e-10
[95,] -3.573387e-09 1.012892e-10
[96,] -3.705930e-09 -3.573387e-09
[97,] 1.899201e-11 -3.705930e-09
[98,] -4.707999e-09 1.899201e-11
[99,] -2.748707e-10 -4.707999e-09
[100,] 1.322273e-09 -2.748707e-10
[101,] 7.545778e-10 1.322273e-09
[102,] -3.493673e-09 7.545778e-10
[103,] 2.656792e-09 -3.493673e-09
[104,] -1.220147e-09 2.656792e-09
[105,] -3.491743e-10 -1.220147e-09
[106,] -5.621469e-10 -3.491743e-10
[107,] -5.223846e-10 -5.621469e-10
[108,] -2.408706e-09 -5.223846e-10
[109,] -2.968359e-09 -2.408706e-09
[110,] 4.400340e-09 -2.968359e-09
[111,] -2.575913e-09 4.400340e-09
[112,] 3.884963e-10 -2.575913e-09
[113,] 3.097206e-10 3.884963e-10
[114,] -4.603330e-09 3.097206e-10
[115,] -1.908564e-10 -4.603330e-09
[116,] -4.139530e-10 -1.908564e-10
[117,] 8.420013e-10 -4.139530e-10
[118,] 4.854191e-10 8.420013e-10
[119,] -5.845436e-11 4.854191e-10
[120,] 4.016015e-10 -5.845436e-11
[121,] 2.295474e-10 4.016015e-10
[122,] -1.185041e-10 2.295474e-10
[123,] -3.866618e-11 -1.185041e-10
[124,] 2.476043e-09 -3.866618e-11
[125,] -4.011473e-10 2.476043e-09
[126,] 3.115312e-10 -4.011473e-10
[127,] -1.326857e-10 3.115312e-10
[128,] 3.046867e-09 -1.326857e-10
[129,] -6.066200e-10 3.046867e-09
[130,] 2.228780e-10 -6.066200e-10
[131,] -4.366569e-10 2.228780e-10
[132,] -3.060961e-10 -4.366569e-10
[133,] 4.238254e-10 -3.060961e-10
[134,] 1.007507e-10 4.238254e-10
[135,] -1.178942e-09 1.007507e-10
[136,] 2.387568e-10 -1.178942e-09
[137,] 2.607375e-09 2.387568e-10
[138,] 3.773298e-10 2.607375e-09
[139,] -2.332181e-10 3.773298e-10
[140,] 2.722463e-12 -2.332181e-10
[141,] -4.513889e-10 2.722463e-12
[142,] 3.069921e-09 -4.513889e-10
[143,] 3.960932e-09 3.069921e-09
[144,] -1.809372e-09 3.960932e-09
[145,] 2.556451e-10 -1.809372e-09
[146,] 4.033462e-09 2.556451e-10
[147,] 5.080333e-10 4.033462e-09
[148,] -3.577091e-10 5.080333e-10
[149,] 3.356768e-09 -3.577091e-10
[150,] 8.620957e-10 3.356768e-09
[151,] 2.160285e-09 8.620957e-10
[152,] 1.193607e-10 2.160285e-09
[153,] -3.058441e-09 1.193607e-10
[154,] 3.829188e-09 -3.058441e-09
[155,] -1.042799e-10 3.829188e-09
[156,] -8.867856e-10 -1.042799e-10
[157,] 3.180825e-10 -8.867856e-10
[158,] -2.714169e-10 3.180825e-10
[159,] -2.951773e-09 -2.714169e-10
[160,] 2.390367e-09 -2.951773e-09
[161,] -3.028565e-09 2.390367e-09
[162,] -4.062767e-11 -3.028565e-09
[163,] -2.357174e-09 -4.062767e-11
[164,] 4.769255e-09 -2.357174e-09
[165,] -4.714538e-09 4.769255e-09
[166,] -4.155172e-09 -4.714538e-09
[167,] -2.622208e-09 -4.155172e-09
[168,] -7.009511e-12 -2.622208e-09
[169,] 5.378812e-10 -7.009511e-12
[170,] -4.330061e-09 5.378812e-10
[171,] -3.394392e-10 -4.330061e-09
[172,] 2.516432e-09 -3.394392e-10
[173,] 2.900964e-09 2.516432e-09
[174,] 1.332398e-10 2.900964e-09
[175,] 4.041107e-09 1.332398e-10
[176,] 4.009010e-09 4.041107e-09
[177,] 5.769308e-12 4.009010e-09
[178,] 1.320693e-10 5.769308e-12
[179,] -1.221313e-10 1.320693e-10
[180,] -5.471911e-10 -1.221313e-10
[181,] -2.967870e-10 -5.471911e-10
[182,] 1.648266e-10 -2.967870e-10
[183,] 4.723731e-09 1.648266e-10
[184,] 1.752518e-09 4.723731e-09
[185,] 2.823562e-10 1.752518e-09
[186,] 3.503683e-10 2.823562e-10
[187,] -5.733146e-10 3.503683e-10
[188,] 1.456788e-10 -5.733146e-10
[189,] 2.400455e-09 1.456788e-10
[190,] 1.679498e-09 2.400455e-09
[191,] 5.528211e-11 1.679498e-09
[192,] 1.172303e-10 5.528211e-11
[193,] -1.278692e-10 1.172303e-10
[194,] -4.023659e-10 -1.278692e-10
[195,] 1.191590e-10 -4.023659e-10
[196,] -4.741438e-10 1.191590e-10
[197,] -5.166900e-10 -4.741438e-10
[198,] 3.562249e-10 -5.166900e-10
[199,] 4.239185e-10 3.562249e-10
[200,] 4.301459e-10 4.239185e-10
[201,] -2.829631e-10 4.301459e-10
[202,] 4.910831e-10 -2.829631e-10
[203,] -2.494929e-10 4.910831e-10
[204,] 4.767596e-10 -2.494929e-10
[205,] -5.256026e-10 4.767596e-10
[206,] -1.554674e-10 -5.256026e-10
[207,] -5.122886e-10 -1.554674e-10
[208,] 9.482624e-10 -5.122886e-10
[209,] -2.703763e-11 9.482624e-10
[210,] -5.362783e-11 -2.703763e-11
[211,] 4.526887e-10 -5.362783e-11
[212,] -5.251040e-10 4.526887e-10
[213,] 4.183464e-10 -5.251040e-10
[214,] -2.585923e-10 4.183464e-10
[215,] -4.991062e-10 -2.585923e-10
[216,] 1.951004e-11 -4.991062e-10
[217,] 2.240465e-10 1.951004e-11
[218,] -6.079533e-11 2.240465e-10
[219,] -8.420245e-11 -6.079533e-11
[220,] -3.854907e-10 -8.420245e-11
[221,] -3.667259e-09 -3.854907e-10
[222,] -4.760364e-10 -3.667259e-09
[223,] -6.995709e-12 -4.760364e-10
[224,] -4.898263e-12 -6.995709e-12
[225,] 1.648114e-10 -4.898263e-12
[226,] -3.653729e-10 1.648114e-10
[227,] 2.771226e-11 -3.653729e-10
[228,] -6.728787e-12 2.771226e-11
[229,] -2.903898e-10 -6.728787e-12
[230,] -4.709772e-10 -2.903898e-10
[231,] -4.458185e-10 -4.709772e-10
[232,] -2.686964e-10 -4.458185e-10
[233,] 3.860761e-10 -2.686964e-10
[234,] -1.872863e-10 3.860761e-10
[235,] -3.630736e-10 -1.872863e-10
[236,] -2.523802e-09 -3.630736e-10
[237,] -5.572199e-10 -2.523802e-09
[238,] 2.733718e-10 -5.572199e-10
[239,] -2.097014e-10 2.733718e-10
[240,] 1.067746e-10 -2.097014e-10
[241,] 1.204149e-09 1.067746e-10
[242,] -2.599948e-10 1.204149e-09
[243,] 2.823228e-11 -2.599948e-10
[244,] -3.608922e-10 2.823228e-11
[245,] -4.847545e-10 -3.608922e-10
[246,] -1.203170e-10 -4.847545e-10
[247,] -4.250662e-10 -1.203170e-10
[248,] 1.296625e-10 -4.250662e-10
[249,] 2.769796e-10 1.296625e-10
[250,] 3.556443e-09 2.769796e-10
[251,] -3.564669e-10 3.556443e-09
[252,] -4.904898e-10 -3.564669e-10
[253,] -3.883933e-09 -4.904898e-10
[254,] 1.210625e-10 -3.883933e-09
[255,] 2.635993e-10 1.210625e-10
[256,] 2.497773e-10 2.635993e-10
[257,] 3.029637e-10 2.497773e-10
[258,] 1.270516e-10 3.029637e-10
[259,] 3.163892e-10 1.270516e-10
[260,] -2.015676e-10 3.163892e-10
[261,] 3.173983e-10 -2.015676e-10
[262,] 4.238408e-10 3.173983e-10
[263,] -4.974539e-10 4.238408e-10
[264,] -2.831913e-10 -4.974539e-10
[265,] -1.304819e-11 -2.831913e-10
[266,] 2.328233e-10 -1.304819e-11
[267,] 2.573405e-10 2.328233e-10
[268,] 4.529499e-12 2.573405e-10
[269,] -4.009811e-10 4.529499e-12
[270,] 2.133153e-09 -4.009811e-10
[271,] -4.468262e-10 2.133153e-09
[272,] -1.114259e-10 -4.468262e-10
[273,] -5.093834e-11 -1.114259e-10
[274,] 4.213594e-10 -5.093834e-11
[275,] -2.244267e-10 4.213594e-10
[276,] -4.274300e-10 -2.244267e-10
[277,] -2.352386e-10 -4.274300e-10
[278,] 1.519844e-10 -2.352386e-10
[279,] 1.516028e-10 1.519844e-10
[280,] -3.398185e-10 1.516028e-10
[281,] 5.083690e-10 -3.398185e-10
[282,] -5.032963e-10 5.083690e-10
[283,] -1.417166e-10 -5.032963e-10
[284,] -2.685936e-10 -1.417166e-10
[285,] -1.168468e-10 -2.685936e-10
[286,] -1.305996e-11 -1.168468e-10
[287,] -5.466121e-11 -1.305996e-11
[288,] -1.649965e-10 -5.466121e-11
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.513310e-10 -1.723658e-09
2 -2.648560e-09 2.513310e-10
3 -5.243379e-10 -2.648560e-09
4 2.809621e-10 -5.243379e-10
5 -8.760340e-10 2.809621e-10
6 -3.110440e-09 -8.760340e-10
7 -1.052950e-10 -3.110440e-09
8 4.974967e-10 -1.052950e-10
9 -4.822442e-09 4.974967e-10
10 -4.971467e-09 -4.822442e-09
11 -4.783487e-09 -4.971467e-09
12 3.920942e-09 -4.783487e-09
13 3.698974e-09 3.920942e-09
14 -2.683328e-09 3.698974e-09
15 -1.220391e-09 -2.683328e-09
16 1.881239e-09 -1.220391e-09
17 -3.231178e-09 1.881239e-09
18 1.364957e-09 -3.231178e-09
19 3.260586e-11 1.364957e-09
20 2.884083e-09 3.260586e-11
21 3.950829e-09 2.884083e-09
22 -2.012340e-09 3.950829e-09
23 4.582295e-09 -2.012340e-09
24 1.534437e-10 4.582295e-09
25 -5.815418e-10 1.534437e-10
26 3.923316e-09 -5.815418e-10
27 -2.300497e-09 3.923316e-09
28 2.816908e-09 -2.300497e-09
29 -5.916274e-12 2.816908e-09
30 -4.465197e-10 -5.916274e-12
31 8.414600e-10 -4.465197e-10
32 6.853917e-11 8.414600e-10
33 7.212087e-10 6.853917e-11
34 9.091482e-11 7.212087e-10
35 2.708661e-09 9.091482e-11
36 2.080735e-10 2.708661e-09
37 2.858394e-09 2.080735e-10
38 4.476643e-10 2.858394e-09
39 -2.804743e-11 4.476643e-10
40 7.550635e-10 -2.804743e-11
41 -3.626207e-10 7.550635e-10
42 1.453607e-10 -3.626207e-10
43 1.759655e-09 1.453607e-10
44 1.388458e-09 1.759655e-09
45 4.537400e-09 1.388458e-09
46 -2.195264e-09 4.537400e-09
47 -3.747391e-09 -2.195264e-09
48 1.809202e-09 -3.747391e-09
49 -4.573344e-09 1.809202e-09
50 5.462522e-09 -4.573344e-09
51 2.946459e-10 5.462522e-09
52 -3.644545e-09 2.946459e-10
53 2.187576e-09 -3.644545e-09
54 -3.944447e-10 2.187576e-09
55 1.306459e-09 -3.944447e-10
56 2.961169e-11 1.306459e-09
57 -4.127258e-10 2.961169e-11
58 -8.963341e-11 -4.127258e-10
59 1.321169e-10 -8.963341e-11
60 4.831236e-09 1.321169e-10
61 -1.164504e-09 4.831236e-09
62 1.843473e-09 -1.164504e-09
63 -2.399883e-10 1.843473e-09
64 1.602057e-09 -2.399883e-10
65 -1.862566e-09 1.602057e-09
66 -1.194826e-09 -1.862566e-09
67 -2.976864e-09 -1.194826e-09
68 -2.878579e-09 -2.976864e-09
69 1.952208e-09 -2.878579e-09
70 1.745904e-10 1.952208e-09
71 1.075164e-09 1.745904e-10
72 3.019715e-09 1.075164e-09
73 -1.530986e-10 3.019715e-09
74 -1.525082e-09 -1.530986e-10
75 -4.697420e-10 -1.525082e-09
76 -2.369375e-11 -4.697420e-10
77 -1.848224e-09 -2.369375e-11
78 -9.524303e-11 -1.848224e-09
79 -2.812008e-09 -9.524303e-11
80 -2.670920e-09 -2.812008e-09
81 -2.395063e-10 -2.670920e-09
82 -4.590185e-09 -2.395063e-10
83 -1.639336e-09 -4.590185e-09
84 -4.931258e-10 -1.639336e-09
85 1.831333e-10 -4.931258e-10
86 -3.729469e-09 1.831333e-10
87 4.605640e-10 -3.729469e-09
88 3.852897e-09 4.605640e-10
89 3.098437e-10 3.852897e-09
90 2.404649e-09 3.098437e-10
91 2.637339e-10 2.404649e-09
92 2.602415e-09 2.637339e-10
93 -2.944468e-10 2.602415e-09
94 1.012892e-10 -2.944468e-10
95 -3.573387e-09 1.012892e-10
96 -3.705930e-09 -3.573387e-09
97 1.899201e-11 -3.705930e-09
98 -4.707999e-09 1.899201e-11
99 -2.748707e-10 -4.707999e-09
100 1.322273e-09 -2.748707e-10
101 7.545778e-10 1.322273e-09
102 -3.493673e-09 7.545778e-10
103 2.656792e-09 -3.493673e-09
104 -1.220147e-09 2.656792e-09
105 -3.491743e-10 -1.220147e-09
106 -5.621469e-10 -3.491743e-10
107 -5.223846e-10 -5.621469e-10
108 -2.408706e-09 -5.223846e-10
109 -2.968359e-09 -2.408706e-09
110 4.400340e-09 -2.968359e-09
111 -2.575913e-09 4.400340e-09
112 3.884963e-10 -2.575913e-09
113 3.097206e-10 3.884963e-10
114 -4.603330e-09 3.097206e-10
115 -1.908564e-10 -4.603330e-09
116 -4.139530e-10 -1.908564e-10
117 8.420013e-10 -4.139530e-10
118 4.854191e-10 8.420013e-10
119 -5.845436e-11 4.854191e-10
120 4.016015e-10 -5.845436e-11
121 2.295474e-10 4.016015e-10
122 -1.185041e-10 2.295474e-10
123 -3.866618e-11 -1.185041e-10
124 2.476043e-09 -3.866618e-11
125 -4.011473e-10 2.476043e-09
126 3.115312e-10 -4.011473e-10
127 -1.326857e-10 3.115312e-10
128 3.046867e-09 -1.326857e-10
129 -6.066200e-10 3.046867e-09
130 2.228780e-10 -6.066200e-10
131 -4.366569e-10 2.228780e-10
132 -3.060961e-10 -4.366569e-10
133 4.238254e-10 -3.060961e-10
134 1.007507e-10 4.238254e-10
135 -1.178942e-09 1.007507e-10
136 2.387568e-10 -1.178942e-09
137 2.607375e-09 2.387568e-10
138 3.773298e-10 2.607375e-09
139 -2.332181e-10 3.773298e-10
140 2.722463e-12 -2.332181e-10
141 -4.513889e-10 2.722463e-12
142 3.069921e-09 -4.513889e-10
143 3.960932e-09 3.069921e-09
144 -1.809372e-09 3.960932e-09
145 2.556451e-10 -1.809372e-09
146 4.033462e-09 2.556451e-10
147 5.080333e-10 4.033462e-09
148 -3.577091e-10 5.080333e-10
149 3.356768e-09 -3.577091e-10
150 8.620957e-10 3.356768e-09
151 2.160285e-09 8.620957e-10
152 1.193607e-10 2.160285e-09
153 -3.058441e-09 1.193607e-10
154 3.829188e-09 -3.058441e-09
155 -1.042799e-10 3.829188e-09
156 -8.867856e-10 -1.042799e-10
157 3.180825e-10 -8.867856e-10
158 -2.714169e-10 3.180825e-10
159 -2.951773e-09 -2.714169e-10
160 2.390367e-09 -2.951773e-09
161 -3.028565e-09 2.390367e-09
162 -4.062767e-11 -3.028565e-09
163 -2.357174e-09 -4.062767e-11
164 4.769255e-09 -2.357174e-09
165 -4.714538e-09 4.769255e-09
166 -4.155172e-09 -4.714538e-09
167 -2.622208e-09 -4.155172e-09
168 -7.009511e-12 -2.622208e-09
169 5.378812e-10 -7.009511e-12
170 -4.330061e-09 5.378812e-10
171 -3.394392e-10 -4.330061e-09
172 2.516432e-09 -3.394392e-10
173 2.900964e-09 2.516432e-09
174 1.332398e-10 2.900964e-09
175 4.041107e-09 1.332398e-10
176 4.009010e-09 4.041107e-09
177 5.769308e-12 4.009010e-09
178 1.320693e-10 5.769308e-12
179 -1.221313e-10 1.320693e-10
180 -5.471911e-10 -1.221313e-10
181 -2.967870e-10 -5.471911e-10
182 1.648266e-10 -2.967870e-10
183 4.723731e-09 1.648266e-10
184 1.752518e-09 4.723731e-09
185 2.823562e-10 1.752518e-09
186 3.503683e-10 2.823562e-10
187 -5.733146e-10 3.503683e-10
188 1.456788e-10 -5.733146e-10
189 2.400455e-09 1.456788e-10
190 1.679498e-09 2.400455e-09
191 5.528211e-11 1.679498e-09
192 1.172303e-10 5.528211e-11
193 -1.278692e-10 1.172303e-10
194 -4.023659e-10 -1.278692e-10
195 1.191590e-10 -4.023659e-10
196 -4.741438e-10 1.191590e-10
197 -5.166900e-10 -4.741438e-10
198 3.562249e-10 -5.166900e-10
199 4.239185e-10 3.562249e-10
200 4.301459e-10 4.239185e-10
201 -2.829631e-10 4.301459e-10
202 4.910831e-10 -2.829631e-10
203 -2.494929e-10 4.910831e-10
204 4.767596e-10 -2.494929e-10
205 -5.256026e-10 4.767596e-10
206 -1.554674e-10 -5.256026e-10
207 -5.122886e-10 -1.554674e-10
208 9.482624e-10 -5.122886e-10
209 -2.703763e-11 9.482624e-10
210 -5.362783e-11 -2.703763e-11
211 4.526887e-10 -5.362783e-11
212 -5.251040e-10 4.526887e-10
213 4.183464e-10 -5.251040e-10
214 -2.585923e-10 4.183464e-10
215 -4.991062e-10 -2.585923e-10
216 1.951004e-11 -4.991062e-10
217 2.240465e-10 1.951004e-11
218 -6.079533e-11 2.240465e-10
219 -8.420245e-11 -6.079533e-11
220 -3.854907e-10 -8.420245e-11
221 -3.667259e-09 -3.854907e-10
222 -4.760364e-10 -3.667259e-09
223 -6.995709e-12 -4.760364e-10
224 -4.898263e-12 -6.995709e-12
225 1.648114e-10 -4.898263e-12
226 -3.653729e-10 1.648114e-10
227 2.771226e-11 -3.653729e-10
228 -6.728787e-12 2.771226e-11
229 -2.903898e-10 -6.728787e-12
230 -4.709772e-10 -2.903898e-10
231 -4.458185e-10 -4.709772e-10
232 -2.686964e-10 -4.458185e-10
233 3.860761e-10 -2.686964e-10
234 -1.872863e-10 3.860761e-10
235 -3.630736e-10 -1.872863e-10
236 -2.523802e-09 -3.630736e-10
237 -5.572199e-10 -2.523802e-09
238 2.733718e-10 -5.572199e-10
239 -2.097014e-10 2.733718e-10
240 1.067746e-10 -2.097014e-10
241 1.204149e-09 1.067746e-10
242 -2.599948e-10 1.204149e-09
243 2.823228e-11 -2.599948e-10
244 -3.608922e-10 2.823228e-11
245 -4.847545e-10 -3.608922e-10
246 -1.203170e-10 -4.847545e-10
247 -4.250662e-10 -1.203170e-10
248 1.296625e-10 -4.250662e-10
249 2.769796e-10 1.296625e-10
250 3.556443e-09 2.769796e-10
251 -3.564669e-10 3.556443e-09
252 -4.904898e-10 -3.564669e-10
253 -3.883933e-09 -4.904898e-10
254 1.210625e-10 -3.883933e-09
255 2.635993e-10 1.210625e-10
256 2.497773e-10 2.635993e-10
257 3.029637e-10 2.497773e-10
258 1.270516e-10 3.029637e-10
259 3.163892e-10 1.270516e-10
260 -2.015676e-10 3.163892e-10
261 3.173983e-10 -2.015676e-10
262 4.238408e-10 3.173983e-10
263 -4.974539e-10 4.238408e-10
264 -2.831913e-10 -4.974539e-10
265 -1.304819e-11 -2.831913e-10
266 2.328233e-10 -1.304819e-11
267 2.573405e-10 2.328233e-10
268 4.529499e-12 2.573405e-10
269 -4.009811e-10 4.529499e-12
270 2.133153e-09 -4.009811e-10
271 -4.468262e-10 2.133153e-09
272 -1.114259e-10 -4.468262e-10
273 -5.093834e-11 -1.114259e-10
274 4.213594e-10 -5.093834e-11
275 -2.244267e-10 4.213594e-10
276 -4.274300e-10 -2.244267e-10
277 -2.352386e-10 -4.274300e-10
278 1.519844e-10 -2.352386e-10
279 1.516028e-10 1.519844e-10
280 -3.398185e-10 1.516028e-10
281 5.083690e-10 -3.398185e-10
282 -5.032963e-10 5.083690e-10
283 -1.417166e-10 -5.032963e-10
284 -2.685936e-10 -1.417166e-10
285 -1.168468e-10 -2.685936e-10
286 -1.305996e-11 -1.168468e-10
287 -5.466121e-11 -1.305996e-11
288 -1.649965e-10 -5.466121e-11
> 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/7gudo1324377885.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8oiqr1324377885.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9a5zm1324377885.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10xrmn1324377885.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/117y991324377885.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/1295oh1324377885.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/134sjw1324377885.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/14i4uz1324377885.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/15y8nm1324377885.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/16qde01324377885.tab")
+ }
>
> try(system("convert tmp/13rf81324377885.ps tmp/13rf81324377885.png",intern=TRUE))
character(0)
> try(system("convert tmp/2crsz1324377885.ps tmp/2crsz1324377885.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qfcm1324377885.ps tmp/3qfcm1324377885.png",intern=TRUE))
character(0)
> try(system("convert tmp/42avf1324377885.ps tmp/42avf1324377885.png",intern=TRUE))
character(0)
> try(system("convert tmp/58y311324377885.ps tmp/58y311324377885.png",intern=TRUE))
character(0)
> try(system("convert tmp/6sqly1324377885.ps tmp/6sqly1324377885.png",intern=TRUE))
character(0)
> try(system("convert tmp/7gudo1324377885.ps tmp/7gudo1324377885.png",intern=TRUE))
character(0)
> try(system("convert tmp/8oiqr1324377885.ps tmp/8oiqr1324377885.png",intern=TRUE))
character(0)
> try(system("convert tmp/9a5zm1324377885.ps tmp/9a5zm1324377885.png",intern=TRUE))
character(0)
> try(system("convert tmp/10xrmn1324377885.ps tmp/10xrmn1324377885.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
7.918 0.639 8.571