R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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> x <- array(list(56
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+ ,72535)
+ ,dim=c(4
+ ,289)
+ ,dimnames=list(c('#logins'
+ ,'totaal#peer_reviews'
+ ,'totaal#karakterscompendium'
+ ,'AantalurenRFC')
+ ,1:289))
> y <- array(NA,dim=c(4,289),dimnames=list(c('#logins','totaal#peer_reviews','totaal#karakterscompendium','AantalurenRFC'),1:289))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '4'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '4'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
AantalurenRFC #logins totaal#peer_reviews totaal#karakterscompendium
1 210907 56 30 112285
2 120982 56 28 84786
3 176508 54 38 83123
4 179321 89 30 101193
5 123185 40 22 38361
6 52746 25 26 68504
7 385534 92 25 119182
8 33170 18 18 22807
9 101645 63 11 17140
10 149061 44 26 116174
11 165446 33 25 57635
12 237213 84 38 66198
13 173326 88 44 71701
14 133131 55 30 57793
15 258873 60 40 80444
16 180083 66 34 53855
17 324799 154 47 97668
18 230964 53 30 133824
19 236785 119 31 101481
20 135473 41 23 99645
21 202925 61 36 114789
22 215147 58 36 99052
23 344297 75 30 67654
24 153935 33 25 65553
25 132943 40 39 97500
26 174724 92 34 69112
27 174415 100 31 82753
28 225548 112 31 85323
29 223632 73 33 72654
30 124817 40 25 30727
31 221698 45 33 77873
32 210767 60 35 117478
33 170266 62 42 74007
34 260561 75 43 90183
35 84853 31 30 61542
36 294424 77 33 101494
37 101011 34 13 27570
38 215641 46 32 55813
39 325107 99 36 79215
40 7176 17 0 1423
41 167542 66 28 55461
42 106408 30 14 31081
43 96560 76 17 22996
44 265769 146 32 83122
45 269651 67 30 70106
46 149112 56 35 60578
47 175824 107 20 39992
48 152871 58 28 79892
49 111665 34 28 49810
50 116408 61 39 71570
51 362301 119 34 100708
52 78800 42 26 33032
53 183167 66 39 82875
54 277965 89 39 139077
55 150629 44 33 71595
56 168809 66 28 72260
57 24188 24 4 5950
58 329267 259 39 115762
59 65029 17 18 32551
60 101097 64 14 31701
61 218946 41 29 80670
62 244052 68 44 143558
63 341570 168 21 117105
64 103597 43 16 23789
65 233328 132 28 120733
66 256462 105 35 105195
67 206161 71 28 73107
68 311473 112 38 132068
69 235800 94 23 149193
70 177939 82 36 46821
71 207176 70 32 87011
72 196553 57 29 95260
73 174184 53 25 55183
74 143246 103 27 106671
75 187559 121 36 73511
76 187681 62 28 92945
77 119016 52 23 78664
78 182192 52 40 70054
79 73566 32 23 22618
80 194979 62 40 74011
81 167488 45 28 83737
82 143756 46 34 69094
83 275541 63 33 93133
84 243199 75 28 95536
85 182999 88 34 225920
86 135649 46 30 62133
87 152299 53 33 61370
88 120221 37 22 43836
89 346485 90 38 106117
90 145790 63 26 38692
91 193339 78 35 84651
92 80953 25 8 56622
93 122774 45 24 15986
94 130585 46 29 95364
95 112611 41 20 26706
96 286468 144 29 89691
97 241066 82 45 67267
98 148446 91 37 126846
99 204713 71 33 41140
100 182079 63 33 102860
101 140344 53 25 51715
102 220516 62 32 55801
103 243060 63 29 111813
104 162765 32 28 120293
105 182613 39 28 138599
106 232138 62 31 161647
107 265318 117 52 115929
108 85574 34 21 24266
109 310839 92 24 162901
110 225060 93 41 109825
111 232317 54 33 129838
112 144966 144 32 37510
113 43287 14 19 43750
114 155754 61 20 40652
115 164709 109 31 87771
116 201940 38 31 85872
117 235454 73 32 89275
118 220801 75 18 44418
119 99466 50 23 192565
120 92661 61 17 35232
121 133328 55 20 40909
122 61361 77 12 13294
123 125930 75 17 32387
124 100750 72 30 140867
125 224549 50 31 120662
126 82316 32 10 21233
127 102010 53 13 44332
128 101523 42 22 61056
129 243511 71 42 101338
130 22938 10 1 1168
131 41566 35 9 13497
132 152474 65 32 65567
133 61857 25 11 25162
134 99923 66 25 32334
135 132487 41 36 40735
136 317394 86 31 91413
137 21054 16 0 855
138 209641 42 24 97068
139 22648 19 13 44339
140 31414 19 8 14116
141 46698 45 13 10288
142 131698 65 19 65622
143 91735 35 18 16563
144 244749 95 33 76643
145 184510 49 40 110681
146 79863 37 22 29011
147 128423 64 38 92696
148 97839 38 24 94785
149 38214 34 8 8773
150 151101 32 35 83209
151 272458 65 43 93815
152 172494 52 43 86687
153 108043 62 14 34553
154 328107 65 41 105547
155 250579 83 38 103487
156 351067 95 45 213688
157 158015 29 31 71220
158 98866 18 13 23517
159 85439 33 28 56926
160 229242 247 31 91721
161 351619 139 40 115168
162 84207 29 30 111194
163 120445 118 16 51009
164 324598 110 37 135777
165 131069 67 30 51513
166 204271 42 35 74163
167 165543 65 32 51633
168 141722 94 27 75345
169 116048 64 20 33416
170 250047 81 18 83305
171 299775 95 31 98952
172 195838 67 31 102372
173 173260 63 21 37238
174 254488 83 39 103772
175 104389 45 41 123969
176 136084 30 13 27142
177 199476 70 32 135400
178 92499 32 18 21399
179 224330 83 39 130115
180 135781 31 14 24874
181 74408 67 7 34988
182 81240 66 17 45549
183 14688 10 0 6023
184 181633 70 30 64466
185 271856 103 37 54990
186 7199 5 0 1644
187 46660 20 5 6179
188 17547 5 1 3926
189 133368 36 16 32755
190 95227 34 32 34777
191 152601 48 24 73224
192 98146 40 17 27114
193 79619 43 11 20760
194 59194 31 24 37636
195 139942 42 22 65461
196 118612 46 12 30080
197 72880 33 19 24094
198 65475 18 13 69008
199 99643 55 17 54968
200 71965 35 15 46090
201 77272 59 16 27507
202 49289 19 24 10672
203 135131 66 15 34029
204 108446 60 17 46300
205 89746 36 18 24760
206 44296 25 20 18779
207 77648 47 16 21280
208 181528 54 16 40662
209 134019 53 18 28987
210 124064 40 22 22827
211 92630 40 8 18513
212 121848 39 17 30594
213 52915 14 18 24006
214 81872 45 16 27913
215 58981 36 23 42744
216 53515 28 22 12934
217 60812 44 13 22574
218 56375 30 13 41385
219 65490 22 16 18653
220 80949 17 16 18472
221 76302 31 20 30976
222 104011 55 22 63339
223 98104 54 17 25568
224 67989 21 18 33747
225 30989 14 17 4154
226 135458 81 12 19474
227 73504 35 7 35130
228 63123 43 17 39067
229 61254 46 14 13310
230 74914 30 23 65892
231 31774 23 17 4143
232 81437 38 14 28579
233 87186 54 15 51776
234 50090 20 17 21152
235 65745 53 21 38084
236 56653 45 18 27717
237 158399 39 18 32928
238 46455 20 17 11342
239 73624 24 17 19499
240 38395 31 16 16380
241 91899 35 15 36874
242 139526 151 21 48259
243 52164 52 16 16734
244 51567 30 14 28207
245 70551 31 15 30143
246 84856 29 17 41369
247 102538 57 15 45833
248 86678 40 15 29156
249 85709 44 10 35944
250 34662 25 6 36278
251 150580 77 22 45588
252 99611 35 21 45097
253 19349 11 1 3895
254 99373 63 18 28394
255 86230 44 17 18632
256 30837 19 4 2325
257 31706 13 10 25139
258 89806 42 16 27975
259 62088 38 16 14483
260 40151 29 9 13127
261 27634 20 16 5839
262 76990 27 17 24069
263 37460 20 7 3738
264 54157 19 15 18625
265 49862 37 14 36341
266 84337 26 14 24548
267 64175 42 18 21792
268 59382 49 12 26263
269 119308 30 16 23686
270 76702 49 21 49303
271 103425 67 19 25659
272 70344 28 16 28904
273 43410 19 1 2781
274 104838 49 16 29236
275 62215 27 10 19546
276 69304 30 19 22818
277 53117 22 12 32689
278 19764 12 2 5752
279 86680 31 14 22197
280 84105 20 17 20055
281 77945 20 19 25272
282 89113 39 14 82206
283 91005 29 11 32073
284 40248 16 4 5444
285 64187 27 16 20154
286 50857 21 20 36944
287 56613 19 12 8019
288 62792 35 15 30884
289 72535 14 16 19540
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `#logins`
-7081.372 902.659
`totaal#peer_reviews` `totaal#karakterscompendium`
2572.502 0.619
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-123153 -22381 -1671 18618 171489
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -7.081e+03 6.171e+03 -1.147 0.252
`#logins` 9.027e+02 8.976e+01 10.057 < 2e-16 ***
`totaal#peer_reviews` 2.573e+03 3.568e+02 7.209 5.07e-12 ***
`totaal#karakterscompendium` 6.190e-01 9.264e-02 6.681 1.24e-10 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 41920 on 285 degrees of freedom
Multiple R-squared: 0.7435, Adjusted R-squared: 0.7408
F-statistic: 275.4 on 3 and 285 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.9899473 2.010541e-02 1.005271e-02
[2,] 0.9771043 4.579146e-02 2.289573e-02
[3,] 0.9625446 7.491085e-02 3.745542e-02
[4,] 0.9543930 9.121410e-02 4.560705e-02
[5,] 0.9766615 4.667697e-02 2.333848e-02
[6,] 0.9650538 6.989240e-02 3.494620e-02
[7,] 0.9618477 7.630465e-02 3.815233e-02
[8,] 0.9406172 1.187655e-01 5.938275e-02
[9,] 0.9777685 4.446303e-02 2.223152e-02
[10,] 0.9665556 6.688880e-02 3.344440e-02
[11,] 0.9627130 7.457401e-02 3.728701e-02
[12,] 0.9458973 1.082054e-01 5.410272e-02
[13,] 0.9500246 9.995089e-02 4.997544e-02
[14,] 0.9379059 1.241882e-01 6.209412e-02
[15,] 0.9159830 1.680340e-01 8.401702e-02
[16,] 0.8928338 2.143323e-01 1.071662e-01
[17,] 0.9974658 5.068380e-03 2.534190e-03
[18,] 0.9965850 6.830040e-03 3.415020e-03
[19,] 0.9960781 7.843896e-03 3.921948e-03
[20,] 0.9959267 8.146653e-03 4.073326e-03
[21,] 0.9970174 5.965252e-03 2.982626e-03
[22,] 0.9960208 7.958466e-03 3.979233e-03
[23,] 0.9951397 9.720681e-03 4.860341e-03
[24,] 0.9932687 1.346265e-02 6.731325e-03
[25,] 0.9946708 1.065849e-02 5.329247e-03
[26,] 0.9923256 1.534877e-02 7.674384e-03
[27,] 0.9898099 2.038022e-02 1.019011e-02
[28,] 0.9888123 2.237533e-02 1.118767e-02
[29,] 0.9884455 2.310893e-02 1.155446e-02
[30,] 0.9929096 1.418070e-02 7.090351e-03
[31,] 0.9905751 1.884978e-02 9.424889e-03
[32,] 0.9938627 1.227462e-02 6.137311e-03
[33,] 0.9975376 4.924799e-03 2.462400e-03
[34,] 0.9966470 6.705988e-03 3.352994e-03
[35,] 0.9952784 9.443182e-03 4.721591e-03
[36,] 0.9940030 1.199392e-02 5.996960e-03
[37,] 0.9937039 1.259227e-02 6.296133e-03
[38,] 0.9924886 1.502287e-02 7.511436e-03
[39,] 0.9969278 6.144397e-03 3.072198e-03
[40,] 0.9960183 7.963353e-03 3.981677e-03
[41,] 0.9947450 1.051005e-02 5.255023e-03
[42,] 0.9934379 1.312410e-02 6.562050e-03
[43,] 0.9913225 1.735499e-02 8.677493e-03
[44,] 0.9947698 1.046036e-02 5.230180e-03
[45,] 0.9980410 3.918024e-03 1.959012e-03
[46,] 0.9977233 4.553403e-03 2.276701e-03
[47,] 0.9970425 5.914905e-03 2.957452e-03
[48,] 0.9961285 7.742964e-03 3.871482e-03
[49,] 0.9947849 1.043015e-02 5.215074e-03
[50,] 0.9931360 1.372803e-02 6.864015e-03
[51,] 0.9910236 1.795286e-02 8.976430e-03
[52,] 0.9980432 3.913685e-03 1.956843e-03
[53,] 0.9973722 5.255693e-03 2.627846e-03
[54,] 0.9965040 6.991963e-03 3.495982e-03
[55,] 0.9971655 5.669057e-03 2.834529e-03
[56,] 0.9965727 6.854615e-03 3.427308e-03
[57,] 0.9969368 6.126396e-03 3.063198e-03
[58,] 0.9959886 8.022814e-03 4.011407e-03
[59,] 0.9962249 7.550182e-03 3.775091e-03
[60,] 0.9950706 9.858712e-03 4.929356e-03
[61,] 0.9941459 1.170816e-02 5.854080e-03
[62,] 0.9932679 1.346420e-02 6.732099e-03
[63,] 0.9923583 1.528341e-02 7.641703e-03
[64,] 0.9901275 1.974503e-02 9.872517e-03
[65,] 0.9875362 2.492761e-02 1.246381e-02
[66,] 0.9844941 3.101189e-02 1.550595e-02
[67,] 0.9826734 3.465318e-02 1.732659e-02
[68,] 0.9922413 1.551740e-02 7.758698e-03
[69,] 0.9930349 1.393014e-02 6.965071e-03
[70,] 0.9910947 1.781057e-02 8.905284e-03
[71,] 0.9904429 1.911416e-02 9.557078e-03
[72,] 0.9877795 2.444100e-02 1.222050e-02
[73,] 0.9853073 2.938550e-02 1.469275e-02
[74,] 0.9814844 3.703128e-02 1.851564e-02
[75,] 0.9770347 4.593063e-02 2.296531e-02
[76,] 0.9729376 5.412489e-02 2.706245e-02
[77,] 0.9841463 3.170744e-02 1.585372e-02
[78,] 0.9847185 3.056308e-02 1.528154e-02
[79,] 0.9979143 4.171362e-03 2.085681e-03
[80,] 0.9973460 5.308079e-03 2.654040e-03
[81,] 0.9965884 6.823117e-03 3.411558e-03
[82,] 0.9955804 8.839131e-03 4.419565e-03
[83,] 0.9990235 1.953090e-03 9.765452e-04
[84,] 0.9986937 2.612584e-03 1.306292e-03
[85,] 0.9983089 3.382295e-03 1.691148e-03
[86,] 0.9977744 4.451290e-03 2.225645e-03
[87,] 0.9971698 5.660473e-03 2.830236e-03
[88,] 0.9970240 5.951935e-03 2.975968e-03
[89,] 0.9961983 7.603388e-03 3.801694e-03
[90,] 0.9958217 8.356553e-03 4.178276e-03
[91,] 0.9948702 1.025964e-02 5.129820e-03
[92,] 0.9984037 3.192647e-03 1.596324e-03
[93,] 0.9982853 3.429341e-03 1.714671e-03
[94,] 0.9978197 4.360689e-03 2.180344e-03
[95,] 0.9971562 5.687528e-03 2.843764e-03
[96,] 0.9976051 4.789766e-03 2.394883e-03
[97,] 0.9978416 4.316843e-03 2.158421e-03
[98,] 0.9971836 5.632833e-03 2.816416e-03
[99,] 0.9963406 7.318888e-03 3.659444e-03
[100,] 0.9952969 9.406212e-03 4.703106e-03
[101,] 0.9948346 1.033070e-02 5.165352e-03
[102,] 0.9935388 1.292241e-02 6.461204e-03
[103,] 0.9961022 7.795607e-03 3.897804e-03
[104,] 0.9953195 9.361093e-03 4.680546e-03
[105,] 0.9946465 1.070691e-02 5.353457e-03
[106,] 0.9974889 5.022293e-03 2.511147e-03
[107,] 0.9974743 5.051460e-03 2.525730e-03
[108,] 0.9971062 5.787608e-03 2.893804e-03
[109,] 0.9977776 4.444883e-03 2.222441e-03
[110,] 0.9977935 4.413011e-03 2.206505e-03
[111,] 0.9977662 4.467638e-03 2.233819e-03
[112,] 0.9990445 1.910985e-03 9.554926e-04
[113,] 0.9998743 2.513539e-04 1.256770e-04
[114,] 0.9998446 3.107481e-04 1.553740e-04
[115,] 0.9997933 4.134807e-04 2.067403e-04
[116,] 0.9998002 3.995061e-04 1.997531e-04
[117,] 0.9997288 5.424875e-04 2.712438e-04
[118,] 0.9999805 3.909969e-05 1.954985e-05
[119,] 0.9999767 4.651626e-05 2.325813e-05
[120,] 0.9999691 6.188377e-05 3.094189e-05
[121,] 0.9999561 8.776045e-05 4.388023e-05
[122,] 0.9999455 1.089579e-04 5.447893e-05
[123,] 0.9999288 1.424983e-04 7.124917e-05
[124,] 0.9999032 1.935745e-04 9.678725e-05
[125,] 0.9998736 2.528111e-04 1.264056e-04
[126,] 0.9998380 3.239008e-04 1.619504e-04
[127,] 0.9997772 4.455915e-04 2.227957e-04
[128,] 0.9997580 4.839560e-04 2.419780e-04
[129,] 0.9996793 6.413243e-04 3.206621e-04
[130,] 0.9999636 7.276843e-05 3.638421e-05
[131,] 0.9999492 1.016633e-04 5.083164e-05
[132,] 0.9999627 7.457778e-05 3.728889e-05
[133,] 0.9999696 6.076172e-05 3.038086e-05
[134,] 0.9999577 8.453410e-05 4.226705e-05
[135,] 0.9999486 1.028924e-04 5.144622e-05
[136,] 0.9999286 1.428075e-04 7.140375e-05
[137,] 0.9999029 1.942417e-04 9.712083e-05
[138,] 0.9999018 1.964063e-04 9.820314e-05
[139,] 0.9998743 2.513122e-04 1.256561e-04
[140,] 0.9998384 3.231039e-04 1.615520e-04
[141,] 0.9999257 1.486974e-04 7.434868e-05
[142,] 0.9999411 1.177356e-04 5.886780e-05
[143,] 0.9999195 1.609710e-04 8.048552e-05
[144,] 0.9998904 2.191939e-04 1.095969e-04
[145,] 0.9999215 1.569318e-04 7.846590e-05
[146,] 0.9999052 1.895684e-04 9.478418e-05
[147,] 0.9998681 2.637973e-04 1.318986e-04
[148,] 0.9999881 2.382869e-05 1.191434e-05
[149,] 0.9999860 2.806634e-05 1.403317e-05
[150,] 0.9999837 3.257177e-05 1.628589e-05
[151,] 0.9999788 4.240861e-05 2.120430e-05
[152,] 0.9999793 4.148120e-05 2.074060e-05
[153,] 0.9999792 4.162796e-05 2.081398e-05
[154,] 0.9999994 1.246772e-06 6.233862e-07
[155,] 0.9999997 5.788306e-07 2.894153e-07
[156,] 0.9999999 1.829092e-07 9.145459e-08
[157,] 1.0000000 9.415688e-08 4.707844e-08
[158,] 1.0000000 4.527018e-08 2.263509e-08
[159,] 1.0000000 6.095488e-08 3.047744e-08
[160,] 1.0000000 3.423980e-08 1.711990e-08
[161,] 1.0000000 5.261332e-08 2.630666e-08
[162,] 1.0000000 3.651903e-08 1.825951e-08
[163,] 1.0000000 5.974187e-08 2.987093e-08
[164,] 1.0000000 6.463137e-09 3.231569e-09
[165,] 1.0000000 2.610830e-10 1.305415e-10
[166,] 1.0000000 3.685311e-10 1.842656e-10
[167,] 1.0000000 1.882911e-10 9.414554e-11
[168,] 1.0000000 8.111219e-11 4.055609e-11
[169,] 1.0000000 6.488127e-12 3.244064e-12
[170,] 1.0000000 1.029214e-12 5.146069e-13
[171,] 1.0000000 1.906864e-12 9.534320e-13
[172,] 1.0000000 3.234438e-12 1.617219e-12
[173,] 1.0000000 5.625792e-12 2.812896e-12
[174,] 1.0000000 8.920633e-13 4.460317e-13
[175,] 1.0000000 1.347269e-12 6.736345e-13
[176,] 1.0000000 1.114220e-12 5.571098e-13
[177,] 1.0000000 2.219317e-12 1.109659e-12
[178,] 1.0000000 2.716543e-12 1.358272e-12
[179,] 1.0000000 2.974646e-14 1.487323e-14
[180,] 1.0000000 5.563017e-14 2.781509e-14
[181,] 1.0000000 1.139977e-13 5.699884e-14
[182,] 1.0000000 2.313338e-13 1.156669e-13
[183,] 1.0000000 6.649080e-14 3.324540e-14
[184,] 1.0000000 1.254419e-13 6.272097e-14
[185,] 1.0000000 1.110835e-13 5.554177e-14
[186,] 1.0000000 1.897118e-13 9.485588e-14
[187,] 1.0000000 3.939298e-13 1.969649e-13
[188,] 1.0000000 4.566605e-13 2.283302e-13
[189,] 1.0000000 3.928280e-13 1.964140e-13
[190,] 1.0000000 3.064611e-13 1.532306e-13
[191,] 1.0000000 6.326824e-13 3.163412e-13
[192,] 1.0000000 1.212269e-12 6.061347e-13
[193,] 1.0000000 2.403311e-12 1.201655e-12
[194,] 1.0000000 4.496488e-12 2.248244e-12
[195,] 1.0000000 7.078172e-12 3.539086e-12
[196,] 1.0000000 1.211886e-11 6.059431e-12
[197,] 1.0000000 1.212581e-11 6.062903e-12
[198,] 1.0000000 2.430032e-11 1.215016e-11
[199,] 1.0000000 4.443165e-11 2.221582e-11
[200,] 1.0000000 5.813169e-11 2.906584e-11
[201,] 1.0000000 1.145212e-10 5.726059e-11
[202,] 1.0000000 8.054944e-13 4.027472e-13
[203,] 1.0000000 3.524510e-13 1.762255e-13
[204,] 1.0000000 1.611436e-13 8.057179e-14
[205,] 1.0000000 1.737372e-13 8.686859e-14
[206,] 1.0000000 6.078063e-14 3.039031e-14
[207,] 1.0000000 1.368012e-13 6.840060e-14
[208,] 1.0000000 3.133732e-13 1.566866e-13
[209,] 1.0000000 2.841564e-13 1.420782e-13
[210,] 1.0000000 4.869957e-13 2.434978e-13
[211,] 1.0000000 9.466356e-13 4.733178e-13
[212,] 1.0000000 1.700602e-12 8.503012e-13
[213,] 1.0000000 3.832986e-12 1.916493e-12
[214,] 1.0000000 5.037279e-12 2.518640e-12
[215,] 1.0000000 1.129853e-11 5.649267e-12
[216,] 1.0000000 2.319850e-11 1.159925e-11
[217,] 1.0000000 4.592853e-11 2.296427e-11
[218,] 1.0000000 1.014001e-10 5.070006e-11
[219,] 1.0000000 1.615051e-10 8.075257e-11
[220,] 1.0000000 6.922730e-11 3.461365e-11
[221,] 1.0000000 1.410358e-10 7.051790e-11
[222,] 1.0000000 1.960134e-10 9.800669e-11
[223,] 1.0000000 4.031483e-10 2.015742e-10
[224,] 1.0000000 4.385276e-10 2.192638e-10
[225,] 1.0000000 5.149181e-10 2.574591e-10
[226,] 1.0000000 1.081216e-09 5.406081e-10
[227,] 1.0000000 2.220270e-09 1.110135e-09
[228,] 1.0000000 3.896877e-09 1.948438e-09
[229,] 1.0000000 2.801935e-09 1.400967e-09
[230,] 1.0000000 2.733969e-09 1.366985e-09
[231,] 1.0000000 1.132560e-11 5.662802e-12
[232,] 1.0000000 2.161369e-11 1.080684e-11
[233,] 1.0000000 5.343023e-11 2.671512e-11
[234,] 1.0000000 3.912031e-11 1.956015e-11
[235,] 1.0000000 7.548995e-11 3.774498e-11
[236,] 1.0000000 6.686227e-11 3.343114e-11
[237,] 1.0000000 2.848078e-11 1.424039e-11
[238,] 1.0000000 4.865984e-11 2.432992e-11
[239,] 1.0000000 1.329536e-10 6.647682e-11
[240,] 1.0000000 3.282544e-10 1.641272e-10
[241,] 1.0000000 8.544767e-10 4.272384e-10
[242,] 1.0000000 2.097188e-09 1.048594e-09
[243,] 1.0000000 4.553665e-09 2.276833e-09
[244,] 1.0000000 8.095559e-09 4.047779e-09
[245,] 1.0000000 7.232135e-09 3.616067e-09
[246,] 1.0000000 1.588716e-08 7.943579e-09
[247,] 1.0000000 3.832605e-08 1.916303e-08
[248,] 1.0000000 9.700223e-08 4.850112e-08
[249,] 0.9999999 2.312373e-07 1.156186e-07
[250,] 0.9999997 5.399013e-07 2.699507e-07
[251,] 0.9999996 8.323345e-07 4.161673e-07
[252,] 0.9999991 1.720237e-06 8.601183e-07
[253,] 0.9999981 3.717006e-06 1.858503e-06
[254,] 0.9999968 6.464127e-06 3.232064e-06
[255,] 0.9999984 3.262161e-06 1.631081e-06
[256,] 0.9999960 8.047741e-06 4.023870e-06
[257,] 0.9999918 1.641586e-05 8.207929e-06
[258,] 0.9999829 3.417352e-05 1.708676e-05
[259,] 0.9999816 3.680206e-05 1.840103e-05
[260,] 0.9999669 6.620903e-05 3.310452e-05
[261,] 0.9999521 9.580653e-05 4.790326e-05
[262,] 0.9999390 1.220725e-04 6.103624e-05
[263,] 0.9999945 1.102734e-05 5.513671e-06
[264,] 0.9999946 1.080066e-05 5.400329e-06
[265,] 0.9999890 2.207966e-05 1.103983e-05
[266,] 0.9999658 6.842003e-05 3.421002e-05
[267,] 0.9998975 2.049568e-04 1.024784e-04
[268,] 0.9997178 5.643016e-04 2.821508e-04
[269,] 0.9991801 1.639790e-03 8.198948e-04
[270,] 0.9982126 3.574724e-03 1.787362e-03
[271,] 0.9956564 8.687176e-03 4.343588e-03
[272,] 0.9931286 1.374279e-02 6.871393e-03
[273,] 0.9867322 2.653555e-02 1.326777e-02
[274,] 0.9780793 4.384149e-02 2.192075e-02
[275,] 0.9534419 9.311620e-02 4.655810e-02
[276,] 0.8804682 2.390637e-01 1.195318e-01
> postscript(file="/var/wessaorg/rcomp/tmp/1gn621352127979.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2za5b1352127979.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/373gv1352127979.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4r3iw1352127979.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5cqmp1352127979.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 289
Frequency = 1
1 2 3 4 5
2.076381e+04 -4.699524e+04 -1.435960e+04 -3.374436e+04 1.382081e+04
6 7 8 9 10
-7.202580e+04 1.714886e+05 -3.641829e+04 1.295226e+04 -2.236743e+04
11 12 13 14 15
4.275297e+04 2.974163e+04 -5.659719e+04 -2.238083e+04 5.910265e+04
16 17 18 19 20
6.789396e+03 1.151013e+04 3.019688e+04 -6.110887e+03 -1.529906e+04
21 22 23 24 25
-8.716384e+03 1.595426e+04 1.646284e+05 2.634100e+04 -5.675875e+04
26 27 28 29 30
-3.148230e+04 -3.973838e+04 -1.028024e+03 3.495635e+04 1.246049e+04
31 32 33 34 35
5.506641e+04 9.363774e+02 -3.247039e+04 3.350515e+04 -5.131553e+04
36 37 38 39 40
8.428673e+04 2.689455e+04 6.433364e+04 1.011837e+05 -1.968617e+03
41 42 43 44 45
8.689351e+03 3.115649e+04 -2.292698e+04 7.292417e+03 9.568593e+04
46 47 48 49 50
-2.188883e+04 1.011714e+04 -1.388233e+04 -1.480479e+04 -7.619980e+04
51 52 53 54 55
1.121661e+05 -3.936104e+04 -2.095151e+04 1.829822e+04 -1.121406e+04
56 57 58 59 60
-4.416575e+02 -4.367297e+03 -6.942060e+04 -9.687831e+03 -5.228667e+03
61 62 63 64 65
6.448381e+04 -1.229505e+04 7.049813e+04 1.597942e+04 -2.550128e+04
66 67 68 69 70
1.361449e+04 3.187278e+04 3.795590e+04 6.518501e+03 -1.058834e+04
71 72 73 74 75
1.489433e+04 1.861755e+04 3.495550e+04 -7.812977e+04 -5.269224e+04
76 77 78 79 80
9.237668e+03 -2.869878e+04 -3.926024e+03 -2.140504e+04 -2.614860e+03
81 82 83 84 85
1.008931e+04 -2.091685e+04 8.321613e+04 5.141736e+04 -1.166555e+05
86 87 88 89 90
-1.442522e+04 -1.133907e+04 1.017595e+04 1.088892e+05 5.169772e+03
91 92 93 94 95
-1.242069e+04 9.840793e+03 1.760088e+04 -3.748557e+04 1.470321e+04
96 97 98 99 100
3.344825e+04 1.673076e+04 -1.003105e+05 3.734876e+04 -1.626655e+04
101 102 103 104 105
3.262070e+03 5.477353e+04 4.946286e+04 -5.526047e+03 -3.327449e+03
106 107 108 109 110
3.452963e+03 -3.873794e+04 -7.077406e+03 7.230553e+04 -2.525643e+04
111 112 113 114 115
2.539692e+04 -8.347299e+04 -3.822616e+04 3.116093e+04 -6.067428e+04
116 117 118 119 120
4.182092e+04 3.906302e+04 8.638469e+04 -1.169443e+05 -2.085977e+04
121 122 123 124 125
1.399181e+04 -4.016092e+04 1.532968e+03 -1.215270e+05 3.206419e+04
126 127 128 129 130
2.164476e+04 3.679241e+02 -2.369394e+04 1.573372e+04 1.769733e+04
131 132 133 134 135
-1.445239e+04 -2.202127e+04 2.499954e+03 -3.689732e+04 -1.526430e+04
136 137 138 139 140
1.105176e+05 1.316361e+04 5.698886e+04 -4.830801e+04 -7.972488e+03
141 142 143 144 145
-2.665073e+04 -9.388781e+03 1.066634e+04 3.374580e+04 -2.404678e+04
146 147 148 149 150
-2.100588e+04 -7.739655e+04 -4.978941e+04 -1.140524e+04 -1.224383e+04
151 152 153 154 155
5.218065e+04 -3.163679e+04 1.757360e+03 1.057130e+05 2.092967e+04
156 157 158 159 160
2.436758e+04 1.508894e+04 4.170076e+04 -4.453269e+04 -1.231531e+05
161 162 163 164 165
5.904563e+04 -8.088910e+04 -5.172024e+04 5.316297e+04 -3.138764e+04
166 167 168 169 170
3.749875e+04 -3.275980e+02 -5.214011e+04 -6.774208e+03 8.614500e+04
171 172 173 174 175
8.010829e+04 -6.711257e+02 4.640226e+04 2.208976e+04 -1.113545e+05
176 177 178 179 180
6.584310e+04 -2.275681e+04 1.114499e+04 -2.437366e+04 6.346876e+04
181 182 183 184 185
-1.865267e+04 -4.317993e+04 9.014752e+03 8.450923e+03 5.674398e+04
186 187 188 189 190
8.749498e+03 1.900109e+04 1.511252e+04 4.651939e+04 -3.222788e+04
191 192 193 194 195
9.291528e+03 8.605835e+03 6.738782e+03 -4.674251e+04 1.199852e+04
196 197 198 199 200
3.468254e+04 -1.361728e+04 -1.984762e+04 -2.067772e+04 -1.966236e+04
201 202 203 204 205
-2.708943e+04 -2.912581e+04 2.298656e+04 -1.102282e+04 2.701014e+03
206 207 208 209 210
-3.426271e+04 -1.202723e+04 7.353736e+04 2.901244e+04 2.431483e+04
211 212 213 214 215
3.156608e+04 3.105649e+04 -1.380479e+04 -1.010351e+04 -5.205798e+04
216 217 218 219 220
-2.927883e+04 -1.923869e+04 -2.268183e+04 7.267538e+00 2.009159e+04
221 222 223 224 225
-1.522219e+04 -3.435360e+04 -3.116468e+03 -1.107875e+04 -2.087058e+04
226 227 228 229 230
2.650023e+04 9.240522e+03 -3.652364e+04 -1.744041e+04 -4.503685e+04
231 232 233 234 235
-2.820270e+04 5.128748e+02 -2.511132e+04 -1.770671e+04 -5.260980e+04
236 237 238 239 240
-4.034620e+04 6.359032e+04 -1.526966e+04 3.239802e+03 -3.380475e+04
241 242 243 244 245
5.976027e+03 -7.358734e+04 -3.921070e+04 -2.190560e+04 -7.595078e+03
246 247 248 249 250
-3.578277e+03 -8.788784e+03 1.018911e+03 5.100247e+03 -1.871296e+04
251 252 253 254 255
3.344169e+03 -6.836745e+03 1.151775e+04 -1.429310e+04 -1.670731e+03
256 257 258 259 260
9.038749e+03 -1.423240e+04 5.000900e+02 -1.525619e+04 -1.022242e+04
261 262 263 264 265
-2.811199e+04 1.069151e+03 6.166984e+03 -6.027922e+03 -3.496388e+04
266 267 268 269 270
1.673983e+04 -2.644885e+04 -2.489284e+04 4.348874e+04 -4.498634e+04
271 272 273 274 275
-1.473136e+04 -6.899705e+03 2.904701e+04 8.432962e+03 7.101251e+03
276 277 278 279 280
-1.369550e+04 -1.076353e+04 7.308169e+03 1.602473e+04 1.698729e+04
281 282 283 284 285
2.453143e+03 -2.590707e+04 2.375964e+04 1.922717e+04 -6.738095e+03
286 287 288 289
-3.533459e+04 1.071034e+04 -1.942337e+04 1.372452e+04
> postscript(file="/var/wessaorg/rcomp/tmp/6khea1352127979.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 289
Frequency = 1
lag(myerror, k = 1) myerror
0 2.076381e+04 NA
1 -4.699524e+04 2.076381e+04
2 -1.435960e+04 -4.699524e+04
3 -3.374436e+04 -1.435960e+04
4 1.382081e+04 -3.374436e+04
5 -7.202580e+04 1.382081e+04
6 1.714886e+05 -7.202580e+04
7 -3.641829e+04 1.714886e+05
8 1.295226e+04 -3.641829e+04
9 -2.236743e+04 1.295226e+04
10 4.275297e+04 -2.236743e+04
11 2.974163e+04 4.275297e+04
12 -5.659719e+04 2.974163e+04
13 -2.238083e+04 -5.659719e+04
14 5.910265e+04 -2.238083e+04
15 6.789396e+03 5.910265e+04
16 1.151013e+04 6.789396e+03
17 3.019688e+04 1.151013e+04
18 -6.110887e+03 3.019688e+04
19 -1.529906e+04 -6.110887e+03
20 -8.716384e+03 -1.529906e+04
21 1.595426e+04 -8.716384e+03
22 1.646284e+05 1.595426e+04
23 2.634100e+04 1.646284e+05
24 -5.675875e+04 2.634100e+04
25 -3.148230e+04 -5.675875e+04
26 -3.973838e+04 -3.148230e+04
27 -1.028024e+03 -3.973838e+04
28 3.495635e+04 -1.028024e+03
29 1.246049e+04 3.495635e+04
30 5.506641e+04 1.246049e+04
31 9.363774e+02 5.506641e+04
32 -3.247039e+04 9.363774e+02
33 3.350515e+04 -3.247039e+04
34 -5.131553e+04 3.350515e+04
35 8.428673e+04 -5.131553e+04
36 2.689455e+04 8.428673e+04
37 6.433364e+04 2.689455e+04
38 1.011837e+05 6.433364e+04
39 -1.968617e+03 1.011837e+05
40 8.689351e+03 -1.968617e+03
41 3.115649e+04 8.689351e+03
42 -2.292698e+04 3.115649e+04
43 7.292417e+03 -2.292698e+04
44 9.568593e+04 7.292417e+03
45 -2.188883e+04 9.568593e+04
46 1.011714e+04 -2.188883e+04
47 -1.388233e+04 1.011714e+04
48 -1.480479e+04 -1.388233e+04
49 -7.619980e+04 -1.480479e+04
50 1.121661e+05 -7.619980e+04
51 -3.936104e+04 1.121661e+05
52 -2.095151e+04 -3.936104e+04
53 1.829822e+04 -2.095151e+04
54 -1.121406e+04 1.829822e+04
55 -4.416575e+02 -1.121406e+04
56 -4.367297e+03 -4.416575e+02
57 -6.942060e+04 -4.367297e+03
58 -9.687831e+03 -6.942060e+04
59 -5.228667e+03 -9.687831e+03
60 6.448381e+04 -5.228667e+03
61 -1.229505e+04 6.448381e+04
62 7.049813e+04 -1.229505e+04
63 1.597942e+04 7.049813e+04
64 -2.550128e+04 1.597942e+04
65 1.361449e+04 -2.550128e+04
66 3.187278e+04 1.361449e+04
67 3.795590e+04 3.187278e+04
68 6.518501e+03 3.795590e+04
69 -1.058834e+04 6.518501e+03
70 1.489433e+04 -1.058834e+04
71 1.861755e+04 1.489433e+04
72 3.495550e+04 1.861755e+04
73 -7.812977e+04 3.495550e+04
74 -5.269224e+04 -7.812977e+04
75 9.237668e+03 -5.269224e+04
76 -2.869878e+04 9.237668e+03
77 -3.926024e+03 -2.869878e+04
78 -2.140504e+04 -3.926024e+03
79 -2.614860e+03 -2.140504e+04
80 1.008931e+04 -2.614860e+03
81 -2.091685e+04 1.008931e+04
82 8.321613e+04 -2.091685e+04
83 5.141736e+04 8.321613e+04
84 -1.166555e+05 5.141736e+04
85 -1.442522e+04 -1.166555e+05
86 -1.133907e+04 -1.442522e+04
87 1.017595e+04 -1.133907e+04
88 1.088892e+05 1.017595e+04
89 5.169772e+03 1.088892e+05
90 -1.242069e+04 5.169772e+03
91 9.840793e+03 -1.242069e+04
92 1.760088e+04 9.840793e+03
93 -3.748557e+04 1.760088e+04
94 1.470321e+04 -3.748557e+04
95 3.344825e+04 1.470321e+04
96 1.673076e+04 3.344825e+04
97 -1.003105e+05 1.673076e+04
98 3.734876e+04 -1.003105e+05
99 -1.626655e+04 3.734876e+04
100 3.262070e+03 -1.626655e+04
101 5.477353e+04 3.262070e+03
102 4.946286e+04 5.477353e+04
103 -5.526047e+03 4.946286e+04
104 -3.327449e+03 -5.526047e+03
105 3.452963e+03 -3.327449e+03
106 -3.873794e+04 3.452963e+03
107 -7.077406e+03 -3.873794e+04
108 7.230553e+04 -7.077406e+03
109 -2.525643e+04 7.230553e+04
110 2.539692e+04 -2.525643e+04
111 -8.347299e+04 2.539692e+04
112 -3.822616e+04 -8.347299e+04
113 3.116093e+04 -3.822616e+04
114 -6.067428e+04 3.116093e+04
115 4.182092e+04 -6.067428e+04
116 3.906302e+04 4.182092e+04
117 8.638469e+04 3.906302e+04
118 -1.169443e+05 8.638469e+04
119 -2.085977e+04 -1.169443e+05
120 1.399181e+04 -2.085977e+04
121 -4.016092e+04 1.399181e+04
122 1.532968e+03 -4.016092e+04
123 -1.215270e+05 1.532968e+03
124 3.206419e+04 -1.215270e+05
125 2.164476e+04 3.206419e+04
126 3.679241e+02 2.164476e+04
127 -2.369394e+04 3.679241e+02
128 1.573372e+04 -2.369394e+04
129 1.769733e+04 1.573372e+04
130 -1.445239e+04 1.769733e+04
131 -2.202127e+04 -1.445239e+04
132 2.499954e+03 -2.202127e+04
133 -3.689732e+04 2.499954e+03
134 -1.526430e+04 -3.689732e+04
135 1.105176e+05 -1.526430e+04
136 1.316361e+04 1.105176e+05
137 5.698886e+04 1.316361e+04
138 -4.830801e+04 5.698886e+04
139 -7.972488e+03 -4.830801e+04
140 -2.665073e+04 -7.972488e+03
141 -9.388781e+03 -2.665073e+04
142 1.066634e+04 -9.388781e+03
143 3.374580e+04 1.066634e+04
144 -2.404678e+04 3.374580e+04
145 -2.100588e+04 -2.404678e+04
146 -7.739655e+04 -2.100588e+04
147 -4.978941e+04 -7.739655e+04
148 -1.140524e+04 -4.978941e+04
149 -1.224383e+04 -1.140524e+04
150 5.218065e+04 -1.224383e+04
151 -3.163679e+04 5.218065e+04
152 1.757360e+03 -3.163679e+04
153 1.057130e+05 1.757360e+03
154 2.092967e+04 1.057130e+05
155 2.436758e+04 2.092967e+04
156 1.508894e+04 2.436758e+04
157 4.170076e+04 1.508894e+04
158 -4.453269e+04 4.170076e+04
159 -1.231531e+05 -4.453269e+04
160 5.904563e+04 -1.231531e+05
161 -8.088910e+04 5.904563e+04
162 -5.172024e+04 -8.088910e+04
163 5.316297e+04 -5.172024e+04
164 -3.138764e+04 5.316297e+04
165 3.749875e+04 -3.138764e+04
166 -3.275980e+02 3.749875e+04
167 -5.214011e+04 -3.275980e+02
168 -6.774208e+03 -5.214011e+04
169 8.614500e+04 -6.774208e+03
170 8.010829e+04 8.614500e+04
171 -6.711257e+02 8.010829e+04
172 4.640226e+04 -6.711257e+02
173 2.208976e+04 4.640226e+04
174 -1.113545e+05 2.208976e+04
175 6.584310e+04 -1.113545e+05
176 -2.275681e+04 6.584310e+04
177 1.114499e+04 -2.275681e+04
178 -2.437366e+04 1.114499e+04
179 6.346876e+04 -2.437366e+04
180 -1.865267e+04 6.346876e+04
181 -4.317993e+04 -1.865267e+04
182 9.014752e+03 -4.317993e+04
183 8.450923e+03 9.014752e+03
184 5.674398e+04 8.450923e+03
185 8.749498e+03 5.674398e+04
186 1.900109e+04 8.749498e+03
187 1.511252e+04 1.900109e+04
188 4.651939e+04 1.511252e+04
189 -3.222788e+04 4.651939e+04
190 9.291528e+03 -3.222788e+04
191 8.605835e+03 9.291528e+03
192 6.738782e+03 8.605835e+03
193 -4.674251e+04 6.738782e+03
194 1.199852e+04 -4.674251e+04
195 3.468254e+04 1.199852e+04
196 -1.361728e+04 3.468254e+04
197 -1.984762e+04 -1.361728e+04
198 -2.067772e+04 -1.984762e+04
199 -1.966236e+04 -2.067772e+04
200 -2.708943e+04 -1.966236e+04
201 -2.912581e+04 -2.708943e+04
202 2.298656e+04 -2.912581e+04
203 -1.102282e+04 2.298656e+04
204 2.701014e+03 -1.102282e+04
205 -3.426271e+04 2.701014e+03
206 -1.202723e+04 -3.426271e+04
207 7.353736e+04 -1.202723e+04
208 2.901244e+04 7.353736e+04
209 2.431483e+04 2.901244e+04
210 3.156608e+04 2.431483e+04
211 3.105649e+04 3.156608e+04
212 -1.380479e+04 3.105649e+04
213 -1.010351e+04 -1.380479e+04
214 -5.205798e+04 -1.010351e+04
215 -2.927883e+04 -5.205798e+04
216 -1.923869e+04 -2.927883e+04
217 -2.268183e+04 -1.923869e+04
218 7.267538e+00 -2.268183e+04
219 2.009159e+04 7.267538e+00
220 -1.522219e+04 2.009159e+04
221 -3.435360e+04 -1.522219e+04
222 -3.116468e+03 -3.435360e+04
223 -1.107875e+04 -3.116468e+03
224 -2.087058e+04 -1.107875e+04
225 2.650023e+04 -2.087058e+04
226 9.240522e+03 2.650023e+04
227 -3.652364e+04 9.240522e+03
228 -1.744041e+04 -3.652364e+04
229 -4.503685e+04 -1.744041e+04
230 -2.820270e+04 -4.503685e+04
231 5.128748e+02 -2.820270e+04
232 -2.511132e+04 5.128748e+02
233 -1.770671e+04 -2.511132e+04
234 -5.260980e+04 -1.770671e+04
235 -4.034620e+04 -5.260980e+04
236 6.359032e+04 -4.034620e+04
237 -1.526966e+04 6.359032e+04
238 3.239802e+03 -1.526966e+04
239 -3.380475e+04 3.239802e+03
240 5.976027e+03 -3.380475e+04
241 -7.358734e+04 5.976027e+03
242 -3.921070e+04 -7.358734e+04
243 -2.190560e+04 -3.921070e+04
244 -7.595078e+03 -2.190560e+04
245 -3.578277e+03 -7.595078e+03
246 -8.788784e+03 -3.578277e+03
247 1.018911e+03 -8.788784e+03
248 5.100247e+03 1.018911e+03
249 -1.871296e+04 5.100247e+03
250 3.344169e+03 -1.871296e+04
251 -6.836745e+03 3.344169e+03
252 1.151775e+04 -6.836745e+03
253 -1.429310e+04 1.151775e+04
254 -1.670731e+03 -1.429310e+04
255 9.038749e+03 -1.670731e+03
256 -1.423240e+04 9.038749e+03
257 5.000900e+02 -1.423240e+04
258 -1.525619e+04 5.000900e+02
259 -1.022242e+04 -1.525619e+04
260 -2.811199e+04 -1.022242e+04
261 1.069151e+03 -2.811199e+04
262 6.166984e+03 1.069151e+03
263 -6.027922e+03 6.166984e+03
264 -3.496388e+04 -6.027922e+03
265 1.673983e+04 -3.496388e+04
266 -2.644885e+04 1.673983e+04
267 -2.489284e+04 -2.644885e+04
268 4.348874e+04 -2.489284e+04
269 -4.498634e+04 4.348874e+04
270 -1.473136e+04 -4.498634e+04
271 -6.899705e+03 -1.473136e+04
272 2.904701e+04 -6.899705e+03
273 8.432962e+03 2.904701e+04
274 7.101251e+03 8.432962e+03
275 -1.369550e+04 7.101251e+03
276 -1.076353e+04 -1.369550e+04
277 7.308169e+03 -1.076353e+04
278 1.602473e+04 7.308169e+03
279 1.698729e+04 1.602473e+04
280 2.453143e+03 1.698729e+04
281 -2.590707e+04 2.453143e+03
282 2.375964e+04 -2.590707e+04
283 1.922717e+04 2.375964e+04
284 -6.738095e+03 1.922717e+04
285 -3.533459e+04 -6.738095e+03
286 1.071034e+04 -3.533459e+04
287 -1.942337e+04 1.071034e+04
288 1.372452e+04 -1.942337e+04
289 NA 1.372452e+04
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.699524e+04 2.076381e+04
[2,] -1.435960e+04 -4.699524e+04
[3,] -3.374436e+04 -1.435960e+04
[4,] 1.382081e+04 -3.374436e+04
[5,] -7.202580e+04 1.382081e+04
[6,] 1.714886e+05 -7.202580e+04
[7,] -3.641829e+04 1.714886e+05
[8,] 1.295226e+04 -3.641829e+04
[9,] -2.236743e+04 1.295226e+04
[10,] 4.275297e+04 -2.236743e+04
[11,] 2.974163e+04 4.275297e+04
[12,] -5.659719e+04 2.974163e+04
[13,] -2.238083e+04 -5.659719e+04
[14,] 5.910265e+04 -2.238083e+04
[15,] 6.789396e+03 5.910265e+04
[16,] 1.151013e+04 6.789396e+03
[17,] 3.019688e+04 1.151013e+04
[18,] -6.110887e+03 3.019688e+04
[19,] -1.529906e+04 -6.110887e+03
[20,] -8.716384e+03 -1.529906e+04
[21,] 1.595426e+04 -8.716384e+03
[22,] 1.646284e+05 1.595426e+04
[23,] 2.634100e+04 1.646284e+05
[24,] -5.675875e+04 2.634100e+04
[25,] -3.148230e+04 -5.675875e+04
[26,] -3.973838e+04 -3.148230e+04
[27,] -1.028024e+03 -3.973838e+04
[28,] 3.495635e+04 -1.028024e+03
[29,] 1.246049e+04 3.495635e+04
[30,] 5.506641e+04 1.246049e+04
[31,] 9.363774e+02 5.506641e+04
[32,] -3.247039e+04 9.363774e+02
[33,] 3.350515e+04 -3.247039e+04
[34,] -5.131553e+04 3.350515e+04
[35,] 8.428673e+04 -5.131553e+04
[36,] 2.689455e+04 8.428673e+04
[37,] 6.433364e+04 2.689455e+04
[38,] 1.011837e+05 6.433364e+04
[39,] -1.968617e+03 1.011837e+05
[40,] 8.689351e+03 -1.968617e+03
[41,] 3.115649e+04 8.689351e+03
[42,] -2.292698e+04 3.115649e+04
[43,] 7.292417e+03 -2.292698e+04
[44,] 9.568593e+04 7.292417e+03
[45,] -2.188883e+04 9.568593e+04
[46,] 1.011714e+04 -2.188883e+04
[47,] -1.388233e+04 1.011714e+04
[48,] -1.480479e+04 -1.388233e+04
[49,] -7.619980e+04 -1.480479e+04
[50,] 1.121661e+05 -7.619980e+04
[51,] -3.936104e+04 1.121661e+05
[52,] -2.095151e+04 -3.936104e+04
[53,] 1.829822e+04 -2.095151e+04
[54,] -1.121406e+04 1.829822e+04
[55,] -4.416575e+02 -1.121406e+04
[56,] -4.367297e+03 -4.416575e+02
[57,] -6.942060e+04 -4.367297e+03
[58,] -9.687831e+03 -6.942060e+04
[59,] -5.228667e+03 -9.687831e+03
[60,] 6.448381e+04 -5.228667e+03
[61,] -1.229505e+04 6.448381e+04
[62,] 7.049813e+04 -1.229505e+04
[63,] 1.597942e+04 7.049813e+04
[64,] -2.550128e+04 1.597942e+04
[65,] 1.361449e+04 -2.550128e+04
[66,] 3.187278e+04 1.361449e+04
[67,] 3.795590e+04 3.187278e+04
[68,] 6.518501e+03 3.795590e+04
[69,] -1.058834e+04 6.518501e+03
[70,] 1.489433e+04 -1.058834e+04
[71,] 1.861755e+04 1.489433e+04
[72,] 3.495550e+04 1.861755e+04
[73,] -7.812977e+04 3.495550e+04
[74,] -5.269224e+04 -7.812977e+04
[75,] 9.237668e+03 -5.269224e+04
[76,] -2.869878e+04 9.237668e+03
[77,] -3.926024e+03 -2.869878e+04
[78,] -2.140504e+04 -3.926024e+03
[79,] -2.614860e+03 -2.140504e+04
[80,] 1.008931e+04 -2.614860e+03
[81,] -2.091685e+04 1.008931e+04
[82,] 8.321613e+04 -2.091685e+04
[83,] 5.141736e+04 8.321613e+04
[84,] -1.166555e+05 5.141736e+04
[85,] -1.442522e+04 -1.166555e+05
[86,] -1.133907e+04 -1.442522e+04
[87,] 1.017595e+04 -1.133907e+04
[88,] 1.088892e+05 1.017595e+04
[89,] 5.169772e+03 1.088892e+05
[90,] -1.242069e+04 5.169772e+03
[91,] 9.840793e+03 -1.242069e+04
[92,] 1.760088e+04 9.840793e+03
[93,] -3.748557e+04 1.760088e+04
[94,] 1.470321e+04 -3.748557e+04
[95,] 3.344825e+04 1.470321e+04
[96,] 1.673076e+04 3.344825e+04
[97,] -1.003105e+05 1.673076e+04
[98,] 3.734876e+04 -1.003105e+05
[99,] -1.626655e+04 3.734876e+04
[100,] 3.262070e+03 -1.626655e+04
[101,] 5.477353e+04 3.262070e+03
[102,] 4.946286e+04 5.477353e+04
[103,] -5.526047e+03 4.946286e+04
[104,] -3.327449e+03 -5.526047e+03
[105,] 3.452963e+03 -3.327449e+03
[106,] -3.873794e+04 3.452963e+03
[107,] -7.077406e+03 -3.873794e+04
[108,] 7.230553e+04 -7.077406e+03
[109,] -2.525643e+04 7.230553e+04
[110,] 2.539692e+04 -2.525643e+04
[111,] -8.347299e+04 2.539692e+04
[112,] -3.822616e+04 -8.347299e+04
[113,] 3.116093e+04 -3.822616e+04
[114,] -6.067428e+04 3.116093e+04
[115,] 4.182092e+04 -6.067428e+04
[116,] 3.906302e+04 4.182092e+04
[117,] 8.638469e+04 3.906302e+04
[118,] -1.169443e+05 8.638469e+04
[119,] -2.085977e+04 -1.169443e+05
[120,] 1.399181e+04 -2.085977e+04
[121,] -4.016092e+04 1.399181e+04
[122,] 1.532968e+03 -4.016092e+04
[123,] -1.215270e+05 1.532968e+03
[124,] 3.206419e+04 -1.215270e+05
[125,] 2.164476e+04 3.206419e+04
[126,] 3.679241e+02 2.164476e+04
[127,] -2.369394e+04 3.679241e+02
[128,] 1.573372e+04 -2.369394e+04
[129,] 1.769733e+04 1.573372e+04
[130,] -1.445239e+04 1.769733e+04
[131,] -2.202127e+04 -1.445239e+04
[132,] 2.499954e+03 -2.202127e+04
[133,] -3.689732e+04 2.499954e+03
[134,] -1.526430e+04 -3.689732e+04
[135,] 1.105176e+05 -1.526430e+04
[136,] 1.316361e+04 1.105176e+05
[137,] 5.698886e+04 1.316361e+04
[138,] -4.830801e+04 5.698886e+04
[139,] -7.972488e+03 -4.830801e+04
[140,] -2.665073e+04 -7.972488e+03
[141,] -9.388781e+03 -2.665073e+04
[142,] 1.066634e+04 -9.388781e+03
[143,] 3.374580e+04 1.066634e+04
[144,] -2.404678e+04 3.374580e+04
[145,] -2.100588e+04 -2.404678e+04
[146,] -7.739655e+04 -2.100588e+04
[147,] -4.978941e+04 -7.739655e+04
[148,] -1.140524e+04 -4.978941e+04
[149,] -1.224383e+04 -1.140524e+04
[150,] 5.218065e+04 -1.224383e+04
[151,] -3.163679e+04 5.218065e+04
[152,] 1.757360e+03 -3.163679e+04
[153,] 1.057130e+05 1.757360e+03
[154,] 2.092967e+04 1.057130e+05
[155,] 2.436758e+04 2.092967e+04
[156,] 1.508894e+04 2.436758e+04
[157,] 4.170076e+04 1.508894e+04
[158,] -4.453269e+04 4.170076e+04
[159,] -1.231531e+05 -4.453269e+04
[160,] 5.904563e+04 -1.231531e+05
[161,] -8.088910e+04 5.904563e+04
[162,] -5.172024e+04 -8.088910e+04
[163,] 5.316297e+04 -5.172024e+04
[164,] -3.138764e+04 5.316297e+04
[165,] 3.749875e+04 -3.138764e+04
[166,] -3.275980e+02 3.749875e+04
[167,] -5.214011e+04 -3.275980e+02
[168,] -6.774208e+03 -5.214011e+04
[169,] 8.614500e+04 -6.774208e+03
[170,] 8.010829e+04 8.614500e+04
[171,] -6.711257e+02 8.010829e+04
[172,] 4.640226e+04 -6.711257e+02
[173,] 2.208976e+04 4.640226e+04
[174,] -1.113545e+05 2.208976e+04
[175,] 6.584310e+04 -1.113545e+05
[176,] -2.275681e+04 6.584310e+04
[177,] 1.114499e+04 -2.275681e+04
[178,] -2.437366e+04 1.114499e+04
[179,] 6.346876e+04 -2.437366e+04
[180,] -1.865267e+04 6.346876e+04
[181,] -4.317993e+04 -1.865267e+04
[182,] 9.014752e+03 -4.317993e+04
[183,] 8.450923e+03 9.014752e+03
[184,] 5.674398e+04 8.450923e+03
[185,] 8.749498e+03 5.674398e+04
[186,] 1.900109e+04 8.749498e+03
[187,] 1.511252e+04 1.900109e+04
[188,] 4.651939e+04 1.511252e+04
[189,] -3.222788e+04 4.651939e+04
[190,] 9.291528e+03 -3.222788e+04
[191,] 8.605835e+03 9.291528e+03
[192,] 6.738782e+03 8.605835e+03
[193,] -4.674251e+04 6.738782e+03
[194,] 1.199852e+04 -4.674251e+04
[195,] 3.468254e+04 1.199852e+04
[196,] -1.361728e+04 3.468254e+04
[197,] -1.984762e+04 -1.361728e+04
[198,] -2.067772e+04 -1.984762e+04
[199,] -1.966236e+04 -2.067772e+04
[200,] -2.708943e+04 -1.966236e+04
[201,] -2.912581e+04 -2.708943e+04
[202,] 2.298656e+04 -2.912581e+04
[203,] -1.102282e+04 2.298656e+04
[204,] 2.701014e+03 -1.102282e+04
[205,] -3.426271e+04 2.701014e+03
[206,] -1.202723e+04 -3.426271e+04
[207,] 7.353736e+04 -1.202723e+04
[208,] 2.901244e+04 7.353736e+04
[209,] 2.431483e+04 2.901244e+04
[210,] 3.156608e+04 2.431483e+04
[211,] 3.105649e+04 3.156608e+04
[212,] -1.380479e+04 3.105649e+04
[213,] -1.010351e+04 -1.380479e+04
[214,] -5.205798e+04 -1.010351e+04
[215,] -2.927883e+04 -5.205798e+04
[216,] -1.923869e+04 -2.927883e+04
[217,] -2.268183e+04 -1.923869e+04
[218,] 7.267538e+00 -2.268183e+04
[219,] 2.009159e+04 7.267538e+00
[220,] -1.522219e+04 2.009159e+04
[221,] -3.435360e+04 -1.522219e+04
[222,] -3.116468e+03 -3.435360e+04
[223,] -1.107875e+04 -3.116468e+03
[224,] -2.087058e+04 -1.107875e+04
[225,] 2.650023e+04 -2.087058e+04
[226,] 9.240522e+03 2.650023e+04
[227,] -3.652364e+04 9.240522e+03
[228,] -1.744041e+04 -3.652364e+04
[229,] -4.503685e+04 -1.744041e+04
[230,] -2.820270e+04 -4.503685e+04
[231,] 5.128748e+02 -2.820270e+04
[232,] -2.511132e+04 5.128748e+02
[233,] -1.770671e+04 -2.511132e+04
[234,] -5.260980e+04 -1.770671e+04
[235,] -4.034620e+04 -5.260980e+04
[236,] 6.359032e+04 -4.034620e+04
[237,] -1.526966e+04 6.359032e+04
[238,] 3.239802e+03 -1.526966e+04
[239,] -3.380475e+04 3.239802e+03
[240,] 5.976027e+03 -3.380475e+04
[241,] -7.358734e+04 5.976027e+03
[242,] -3.921070e+04 -7.358734e+04
[243,] -2.190560e+04 -3.921070e+04
[244,] -7.595078e+03 -2.190560e+04
[245,] -3.578277e+03 -7.595078e+03
[246,] -8.788784e+03 -3.578277e+03
[247,] 1.018911e+03 -8.788784e+03
[248,] 5.100247e+03 1.018911e+03
[249,] -1.871296e+04 5.100247e+03
[250,] 3.344169e+03 -1.871296e+04
[251,] -6.836745e+03 3.344169e+03
[252,] 1.151775e+04 -6.836745e+03
[253,] -1.429310e+04 1.151775e+04
[254,] -1.670731e+03 -1.429310e+04
[255,] 9.038749e+03 -1.670731e+03
[256,] -1.423240e+04 9.038749e+03
[257,] 5.000900e+02 -1.423240e+04
[258,] -1.525619e+04 5.000900e+02
[259,] -1.022242e+04 -1.525619e+04
[260,] -2.811199e+04 -1.022242e+04
[261,] 1.069151e+03 -2.811199e+04
[262,] 6.166984e+03 1.069151e+03
[263,] -6.027922e+03 6.166984e+03
[264,] -3.496388e+04 -6.027922e+03
[265,] 1.673983e+04 -3.496388e+04
[266,] -2.644885e+04 1.673983e+04
[267,] -2.489284e+04 -2.644885e+04
[268,] 4.348874e+04 -2.489284e+04
[269,] -4.498634e+04 4.348874e+04
[270,] -1.473136e+04 -4.498634e+04
[271,] -6.899705e+03 -1.473136e+04
[272,] 2.904701e+04 -6.899705e+03
[273,] 8.432962e+03 2.904701e+04
[274,] 7.101251e+03 8.432962e+03
[275,] -1.369550e+04 7.101251e+03
[276,] -1.076353e+04 -1.369550e+04
[277,] 7.308169e+03 -1.076353e+04
[278,] 1.602473e+04 7.308169e+03
[279,] 1.698729e+04 1.602473e+04
[280,] 2.453143e+03 1.698729e+04
[281,] -2.590707e+04 2.453143e+03
[282,] 2.375964e+04 -2.590707e+04
[283,] 1.922717e+04 2.375964e+04
[284,] -6.738095e+03 1.922717e+04
[285,] -3.533459e+04 -6.738095e+03
[286,] 1.071034e+04 -3.533459e+04
[287,] -1.942337e+04 1.071034e+04
[288,] 1.372452e+04 -1.942337e+04
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.699524e+04 2.076381e+04
2 -1.435960e+04 -4.699524e+04
3 -3.374436e+04 -1.435960e+04
4 1.382081e+04 -3.374436e+04
5 -7.202580e+04 1.382081e+04
6 1.714886e+05 -7.202580e+04
7 -3.641829e+04 1.714886e+05
8 1.295226e+04 -3.641829e+04
9 -2.236743e+04 1.295226e+04
10 4.275297e+04 -2.236743e+04
11 2.974163e+04 4.275297e+04
12 -5.659719e+04 2.974163e+04
13 -2.238083e+04 -5.659719e+04
14 5.910265e+04 -2.238083e+04
15 6.789396e+03 5.910265e+04
16 1.151013e+04 6.789396e+03
17 3.019688e+04 1.151013e+04
18 -6.110887e+03 3.019688e+04
19 -1.529906e+04 -6.110887e+03
20 -8.716384e+03 -1.529906e+04
21 1.595426e+04 -8.716384e+03
22 1.646284e+05 1.595426e+04
23 2.634100e+04 1.646284e+05
24 -5.675875e+04 2.634100e+04
25 -3.148230e+04 -5.675875e+04
26 -3.973838e+04 -3.148230e+04
27 -1.028024e+03 -3.973838e+04
28 3.495635e+04 -1.028024e+03
29 1.246049e+04 3.495635e+04
30 5.506641e+04 1.246049e+04
31 9.363774e+02 5.506641e+04
32 -3.247039e+04 9.363774e+02
33 3.350515e+04 -3.247039e+04
34 -5.131553e+04 3.350515e+04
35 8.428673e+04 -5.131553e+04
36 2.689455e+04 8.428673e+04
37 6.433364e+04 2.689455e+04
38 1.011837e+05 6.433364e+04
39 -1.968617e+03 1.011837e+05
40 8.689351e+03 -1.968617e+03
41 3.115649e+04 8.689351e+03
42 -2.292698e+04 3.115649e+04
43 7.292417e+03 -2.292698e+04
44 9.568593e+04 7.292417e+03
45 -2.188883e+04 9.568593e+04
46 1.011714e+04 -2.188883e+04
47 -1.388233e+04 1.011714e+04
48 -1.480479e+04 -1.388233e+04
49 -7.619980e+04 -1.480479e+04
50 1.121661e+05 -7.619980e+04
51 -3.936104e+04 1.121661e+05
52 -2.095151e+04 -3.936104e+04
53 1.829822e+04 -2.095151e+04
54 -1.121406e+04 1.829822e+04
55 -4.416575e+02 -1.121406e+04
56 -4.367297e+03 -4.416575e+02
57 -6.942060e+04 -4.367297e+03
58 -9.687831e+03 -6.942060e+04
59 -5.228667e+03 -9.687831e+03
60 6.448381e+04 -5.228667e+03
61 -1.229505e+04 6.448381e+04
62 7.049813e+04 -1.229505e+04
63 1.597942e+04 7.049813e+04
64 -2.550128e+04 1.597942e+04
65 1.361449e+04 -2.550128e+04
66 3.187278e+04 1.361449e+04
67 3.795590e+04 3.187278e+04
68 6.518501e+03 3.795590e+04
69 -1.058834e+04 6.518501e+03
70 1.489433e+04 -1.058834e+04
71 1.861755e+04 1.489433e+04
72 3.495550e+04 1.861755e+04
73 -7.812977e+04 3.495550e+04
74 -5.269224e+04 -7.812977e+04
75 9.237668e+03 -5.269224e+04
76 -2.869878e+04 9.237668e+03
77 -3.926024e+03 -2.869878e+04
78 -2.140504e+04 -3.926024e+03
79 -2.614860e+03 -2.140504e+04
80 1.008931e+04 -2.614860e+03
81 -2.091685e+04 1.008931e+04
82 8.321613e+04 -2.091685e+04
83 5.141736e+04 8.321613e+04
84 -1.166555e+05 5.141736e+04
85 -1.442522e+04 -1.166555e+05
86 -1.133907e+04 -1.442522e+04
87 1.017595e+04 -1.133907e+04
88 1.088892e+05 1.017595e+04
89 5.169772e+03 1.088892e+05
90 -1.242069e+04 5.169772e+03
91 9.840793e+03 -1.242069e+04
92 1.760088e+04 9.840793e+03
93 -3.748557e+04 1.760088e+04
94 1.470321e+04 -3.748557e+04
95 3.344825e+04 1.470321e+04
96 1.673076e+04 3.344825e+04
97 -1.003105e+05 1.673076e+04
98 3.734876e+04 -1.003105e+05
99 -1.626655e+04 3.734876e+04
100 3.262070e+03 -1.626655e+04
101 5.477353e+04 3.262070e+03
102 4.946286e+04 5.477353e+04
103 -5.526047e+03 4.946286e+04
104 -3.327449e+03 -5.526047e+03
105 3.452963e+03 -3.327449e+03
106 -3.873794e+04 3.452963e+03
107 -7.077406e+03 -3.873794e+04
108 7.230553e+04 -7.077406e+03
109 -2.525643e+04 7.230553e+04
110 2.539692e+04 -2.525643e+04
111 -8.347299e+04 2.539692e+04
112 -3.822616e+04 -8.347299e+04
113 3.116093e+04 -3.822616e+04
114 -6.067428e+04 3.116093e+04
115 4.182092e+04 -6.067428e+04
116 3.906302e+04 4.182092e+04
117 8.638469e+04 3.906302e+04
118 -1.169443e+05 8.638469e+04
119 -2.085977e+04 -1.169443e+05
120 1.399181e+04 -2.085977e+04
121 -4.016092e+04 1.399181e+04
122 1.532968e+03 -4.016092e+04
123 -1.215270e+05 1.532968e+03
124 3.206419e+04 -1.215270e+05
125 2.164476e+04 3.206419e+04
126 3.679241e+02 2.164476e+04
127 -2.369394e+04 3.679241e+02
128 1.573372e+04 -2.369394e+04
129 1.769733e+04 1.573372e+04
130 -1.445239e+04 1.769733e+04
131 -2.202127e+04 -1.445239e+04
132 2.499954e+03 -2.202127e+04
133 -3.689732e+04 2.499954e+03
134 -1.526430e+04 -3.689732e+04
135 1.105176e+05 -1.526430e+04
136 1.316361e+04 1.105176e+05
137 5.698886e+04 1.316361e+04
138 -4.830801e+04 5.698886e+04
139 -7.972488e+03 -4.830801e+04
140 -2.665073e+04 -7.972488e+03
141 -9.388781e+03 -2.665073e+04
142 1.066634e+04 -9.388781e+03
143 3.374580e+04 1.066634e+04
144 -2.404678e+04 3.374580e+04
145 -2.100588e+04 -2.404678e+04
146 -7.739655e+04 -2.100588e+04
147 -4.978941e+04 -7.739655e+04
148 -1.140524e+04 -4.978941e+04
149 -1.224383e+04 -1.140524e+04
150 5.218065e+04 -1.224383e+04
151 -3.163679e+04 5.218065e+04
152 1.757360e+03 -3.163679e+04
153 1.057130e+05 1.757360e+03
154 2.092967e+04 1.057130e+05
155 2.436758e+04 2.092967e+04
156 1.508894e+04 2.436758e+04
157 4.170076e+04 1.508894e+04
158 -4.453269e+04 4.170076e+04
159 -1.231531e+05 -4.453269e+04
160 5.904563e+04 -1.231531e+05
161 -8.088910e+04 5.904563e+04
162 -5.172024e+04 -8.088910e+04
163 5.316297e+04 -5.172024e+04
164 -3.138764e+04 5.316297e+04
165 3.749875e+04 -3.138764e+04
166 -3.275980e+02 3.749875e+04
167 -5.214011e+04 -3.275980e+02
168 -6.774208e+03 -5.214011e+04
169 8.614500e+04 -6.774208e+03
170 8.010829e+04 8.614500e+04
171 -6.711257e+02 8.010829e+04
172 4.640226e+04 -6.711257e+02
173 2.208976e+04 4.640226e+04
174 -1.113545e+05 2.208976e+04
175 6.584310e+04 -1.113545e+05
176 -2.275681e+04 6.584310e+04
177 1.114499e+04 -2.275681e+04
178 -2.437366e+04 1.114499e+04
179 6.346876e+04 -2.437366e+04
180 -1.865267e+04 6.346876e+04
181 -4.317993e+04 -1.865267e+04
182 9.014752e+03 -4.317993e+04
183 8.450923e+03 9.014752e+03
184 5.674398e+04 8.450923e+03
185 8.749498e+03 5.674398e+04
186 1.900109e+04 8.749498e+03
187 1.511252e+04 1.900109e+04
188 4.651939e+04 1.511252e+04
189 -3.222788e+04 4.651939e+04
190 9.291528e+03 -3.222788e+04
191 8.605835e+03 9.291528e+03
192 6.738782e+03 8.605835e+03
193 -4.674251e+04 6.738782e+03
194 1.199852e+04 -4.674251e+04
195 3.468254e+04 1.199852e+04
196 -1.361728e+04 3.468254e+04
197 -1.984762e+04 -1.361728e+04
198 -2.067772e+04 -1.984762e+04
199 -1.966236e+04 -2.067772e+04
200 -2.708943e+04 -1.966236e+04
201 -2.912581e+04 -2.708943e+04
202 2.298656e+04 -2.912581e+04
203 -1.102282e+04 2.298656e+04
204 2.701014e+03 -1.102282e+04
205 -3.426271e+04 2.701014e+03
206 -1.202723e+04 -3.426271e+04
207 7.353736e+04 -1.202723e+04
208 2.901244e+04 7.353736e+04
209 2.431483e+04 2.901244e+04
210 3.156608e+04 2.431483e+04
211 3.105649e+04 3.156608e+04
212 -1.380479e+04 3.105649e+04
213 -1.010351e+04 -1.380479e+04
214 -5.205798e+04 -1.010351e+04
215 -2.927883e+04 -5.205798e+04
216 -1.923869e+04 -2.927883e+04
217 -2.268183e+04 -1.923869e+04
218 7.267538e+00 -2.268183e+04
219 2.009159e+04 7.267538e+00
220 -1.522219e+04 2.009159e+04
221 -3.435360e+04 -1.522219e+04
222 -3.116468e+03 -3.435360e+04
223 -1.107875e+04 -3.116468e+03
224 -2.087058e+04 -1.107875e+04
225 2.650023e+04 -2.087058e+04
226 9.240522e+03 2.650023e+04
227 -3.652364e+04 9.240522e+03
228 -1.744041e+04 -3.652364e+04
229 -4.503685e+04 -1.744041e+04
230 -2.820270e+04 -4.503685e+04
231 5.128748e+02 -2.820270e+04
232 -2.511132e+04 5.128748e+02
233 -1.770671e+04 -2.511132e+04
234 -5.260980e+04 -1.770671e+04
235 -4.034620e+04 -5.260980e+04
236 6.359032e+04 -4.034620e+04
237 -1.526966e+04 6.359032e+04
238 3.239802e+03 -1.526966e+04
239 -3.380475e+04 3.239802e+03
240 5.976027e+03 -3.380475e+04
241 -7.358734e+04 5.976027e+03
242 -3.921070e+04 -7.358734e+04
243 -2.190560e+04 -3.921070e+04
244 -7.595078e+03 -2.190560e+04
245 -3.578277e+03 -7.595078e+03
246 -8.788784e+03 -3.578277e+03
247 1.018911e+03 -8.788784e+03
248 5.100247e+03 1.018911e+03
249 -1.871296e+04 5.100247e+03
250 3.344169e+03 -1.871296e+04
251 -6.836745e+03 3.344169e+03
252 1.151775e+04 -6.836745e+03
253 -1.429310e+04 1.151775e+04
254 -1.670731e+03 -1.429310e+04
255 9.038749e+03 -1.670731e+03
256 -1.423240e+04 9.038749e+03
257 5.000900e+02 -1.423240e+04
258 -1.525619e+04 5.000900e+02
259 -1.022242e+04 -1.525619e+04
260 -2.811199e+04 -1.022242e+04
261 1.069151e+03 -2.811199e+04
262 6.166984e+03 1.069151e+03
263 -6.027922e+03 6.166984e+03
264 -3.496388e+04 -6.027922e+03
265 1.673983e+04 -3.496388e+04
266 -2.644885e+04 1.673983e+04
267 -2.489284e+04 -2.644885e+04
268 4.348874e+04 -2.489284e+04
269 -4.498634e+04 4.348874e+04
270 -1.473136e+04 -4.498634e+04
271 -6.899705e+03 -1.473136e+04
272 2.904701e+04 -6.899705e+03
273 8.432962e+03 2.904701e+04
274 7.101251e+03 8.432962e+03
275 -1.369550e+04 7.101251e+03
276 -1.076353e+04 -1.369550e+04
277 7.308169e+03 -1.076353e+04
278 1.602473e+04 7.308169e+03
279 1.698729e+04 1.602473e+04
280 2.453143e+03 1.698729e+04
281 -2.590707e+04 2.453143e+03
282 2.375964e+04 -2.590707e+04
283 1.922717e+04 2.375964e+04
284 -6.738095e+03 1.922717e+04
285 -3.533459e+04 -6.738095e+03
286 1.071034e+04 -3.533459e+04
287 -1.942337e+04 1.071034e+04
288 1.372452e+04 -1.942337e+04
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/7x3w51352127979.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8rf5b1352127979.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9rlfh1352127979.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10bh0b1352127979.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11v88n1352127979.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/121hn71352127979.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/133xnr1352127979.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/14hw6m1352127979.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/15885c1352127979.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/1661k21352127979.tab")
+ }
>
> try(system("convert tmp/1gn621352127979.ps tmp/1gn621352127979.png",intern=TRUE))
character(0)
> try(system("convert tmp/2za5b1352127979.ps tmp/2za5b1352127979.png",intern=TRUE))
character(0)
> try(system("convert tmp/373gv1352127979.ps tmp/373gv1352127979.png",intern=TRUE))
character(0)
> try(system("convert tmp/4r3iw1352127979.ps tmp/4r3iw1352127979.png",intern=TRUE))
character(0)
> try(system("convert tmp/5cqmp1352127979.ps tmp/5cqmp1352127979.png",intern=TRUE))
character(0)
> try(system("convert tmp/6khea1352127979.ps tmp/6khea1352127979.png",intern=TRUE))
character(0)
> try(system("convert tmp/7x3w51352127979.ps tmp/7x3w51352127979.png",intern=TRUE))
character(0)
> try(system("convert tmp/8rf5b1352127979.ps tmp/8rf5b1352127979.png",intern=TRUE))
character(0)
> try(system("convert tmp/9rlfh1352127979.ps tmp/9rlfh1352127979.png",intern=TRUE))
character(0)
> try(system("convert tmp/10bh0b1352127979.ps tmp/10bh0b1352127979.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
14.677 1.156 15.837