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)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
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(609
+ ,59
+ ,32
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+ ,73
+ ,39
+ ,263
+ ,338
+ ,217
+ ,213
+ ,77
+ ,35
+ ,234
+ ,110
+ ,62)
+ ,dim=c(3
+ ,310)
+ ,dimnames=list(c('dichtheid'
+ ,'huwelijken'
+ ,'echtscheidingen')
+ ,1:310))
> y <- array(NA,dim=c(3,310),dimnames=list(c('dichtheid','huwelijken','echtscheidingen'),1:310))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> 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
dichtheid huwelijken echtscheidingen
1 609.000 59.000 32.000
2 985.000 2.110 1.106
3 1.308 59.000 15.000
4 2.364 65.000 51.000
5 617.000 36.000 30.000
6 2.269 134.000 94.000
7 2.584 109.000 46.000
8 960.000 92.000 62.000
9 304.000 88.000 33.000
10 2.447 33.000 19.000
11 375.000 21.000 15.000
12 1.869 61.000 33.000
13 1.369 101.000 57.000
14 298.000 75.000 50.000
15 712.000 37.000 16.000
16 866.000 83.000 58.000
17 1.501 46.000 19.000
18 3.178 64.000 38.000
19 1.758 61.000 28.000
20 419.000 21.000 14.000
21 734.000 49.000 45.000
22 1.039 158.000 84.000
23 542.000 93.000 42.000
24 1.128 47.000 18.000
25 835.000 44.000 35.000
26 1.143 82.000 42.000
27 948.000 52.000 25.000
28 215.000 69.000 48.000
29 309.000 84.000 42.000
30 550.000 59.000 18.000
31 1.042 42.000 34.000
32 280.000 37.000 24.000
33 636.000 79.000 51.000
34 443.000 76.000 45.000
35 501.000 144.000 101.000
36 449.000 178.000 84.000
37 730.000 380.000 206.000
38 461.000 87.000 45.000
39 683.000 56.000 34.000
40 1.242 54.000 35.000
41 552.000 36.000 14.000
42 468.000 75.000 45.000
43 495.000 89.000 65.000
44 518.000 51.000 28.000
45 558.000 7.000 2.000
46 883.000 78.000 49.000
47 321.000 79.000 39.000
48 230.000 31.000 22.000
49 335.000 158.000 72.000
50 288.000 30.000 21.000
51 454.000 115.000 76.000
52 337.000 31.000 20.000
53 337.000 57.000 45.000
54 387.000 62.000 34.000
55 551.000 47.000 27.000
56 370.000 41.000 37.000
57 272.000 69.000 35.000
58 188.000 47.000 26.000
59 569.000 37.000 13.000
60 254.000 154.000 59.000
61 273.000 49.000 25.000
62 268.000 48.000 22.000
63 190.000 44.000 33.000
64 299.000 45.000 29.000
65 507.000 37.000 30.000
66 332.000 150.000 117.000
67 152.000 27.000 17.000
68 222.000 35.000 25.000
69 241.000 100.000 47.000
70 727.000 63.000 47.000
71 272.000 398.000 230.000
72 869.000 127.000 69.000
73 433.000 88.000 32.000
74 361.000 797.000 4.600
75 511.000 212.000 122.000
76 629.000 147.000 105.000
77 609.000 206.000 113.000
78 797.000 109.000 67.000
79 108.000 386.000 270.000
80 971.000 219.000 126.000
81 240.000 86.000 43.000
82 227.000 534.000 254.000
83 911.000 204.000 144.000
84 811.000 133.000 112.000
85 147.000 676.000 412.000
86 504.000 303.000 179.000
87 335.000 95.000 75.000
88 592.000 226.000 119.000
89 1.226 124.000 101.000
90 486.000 96.000 71.000
91 1.150 67.000 30.000
92 528.000 7.000 3.000
93 418.000 122.000 72.000
94 674.000 34.000 22.000
95 550.000 26.000 24.000
96 122.000 99.000 76.000
97 782.000 118.000 98.000
98 487.000 25.000 6.000
99 613.000 34.000 20.000
100 1.846 45.000 23.000
101 1.102 39.000 23.000
102 512.000 37.000 21.000
103 515.000 55.000 36.000
104 1.988 43.000 29.000
105 2.303 48.000 35.000
106 1.146 59.000 40.000
107 792.000 44.000 30.000
108 1.733 57.000 29.000
109 2.007 17.000 3.000
110 286.000 102.000 62.000
111 701.000 31.000 29.000
112 416.000 47.000 30.000
113 454.000 144.000 96.000
114 557.000 72.000 37.000
115 161.000 69.000 40.000
116 322.000 32.000 27.000
117 238.000 22.000 13.000
118 632.000 39.000 24.000
119 250.000 13.000 11.000
120 396.000 23.000 20.000
121 168.000 52.000 39.000
122 463.000 39.000 26.000
123 612.000 27.000 27.000
124 193.000 48.000 23.000
125 251.000 117.000 74.000
126 237.000 40.000 27.000
127 688.000 30.000 14.000
128 158.000 28.000 16.000
129 549.000 42.000 15.000
130 284.000 47.000 24.000
131 1.686 34.000 14.000
132 299.000 99.000 73.000
133 355.000 26.000 12.000
134 413.000 45.000 25.000
135 643.000 80.000 40.000
136 454.000 23.000 10.000
137 666.000 37.000 18.000
138 175.000 31.000 16.000
139 195.000 41.000 27.000
140 447.000 17.000 14.000
141 235.000 74.000 36.000
142 196.000 68.000 29.000
143 369.000 569.000 255.000
144 418.000 52.000 29.000
145 210.000 39.000 15.000
146 1.086 55.000 36.000
147 843.000 49.000 28.000
148 121.000 145.000 95.000
149 253.000 62.000 25.000
150 282.000 43.000 21.000
151 440.000 31.000 10.000
152 368.000 97.000 55.000
153 57.000 35.000 26.000
154 599.000 19.000 12.000
155 137.000 15.000 15.000
156 109.000 130.000 89.000
157 172.000 38.000 26.000
158 215.000 48.000 18.000
159 219.000 40.000 20.000
160 53.000 71.000 40.000
161 193.000 49.000 27.000
162 268.000 19.000 7.000
163 265.000 28.000 20.000
164 167.000 50.000 33.000
165 416.000 20.000 12.000
166 180.000 32.000 24.000
167 86.000 119.000 86.000
168 149.000 29.000 21.000
169 96.000 68.000 62.000
170 698.000 94.000 53.000
171 341.000 25.000 22.000
172 442.000 87.000 52.000
173 670.000 135.000 67.000
174 912.000 17.000 18.000
175 936.000 13.000 7.000
176 1.289 49.000 37.000
177 425.000 37.000 21.000
178 984.000 140.000 71.000
179 819.000 16.000 20.000
180 799.000 38.000 28.000
181 381.000 23.000 16.000
182 196.000 63.000 37.000
183 517.000 75.000 45.000
184 1.239 474.000 360.000
185 278.000 43.000 35.000
186 305.000 52.000 26.000
187 246.000 97.000 54.000
188 1.831 102.000 54.000
189 254.000 89.000 55.000
190 294.000 8.000 7.000
191 534.000 116.000 87.000
192 263.000 60.000 28.000
193 659.000 44.000 21.000
194 1.064 36.000 21.000
195 385.000 53.000 31.000
196 328.000 17.000 1.000
197 306.000 149.000 86.000
198 960.000 10.000 6.000
199 239.000 89.000 68.000
200 274.000 57.000 47.000
201 318.000 51.000 33.000
202 377.000 40.000 21.000
203 455.000 28.000 16.000
204 194.000 10.000 8.000
205 171.000 45.000 19.000
206 287.000 35.000 19.000
207 421.000 41.000 33.000
208 200.000 109.000 72.000
209 262.000 299.000 217.000
210 219.000 44.000 31.000
211 61.000 18.000 10.000
212 444.000 138.000 91.000
213 497.000 152.000 87.000
214 363.000 142.000 73.000
215 121.000 94.000 57.000
216 480.000 9.000 4.000
217 583.000 86.000 43.000
218 1.025 42.000 32.000
219 1.342 55.000 39.000
220 402.000 48.000 48.000
221 583.000 297.000 239.000
222 362.000 42.000 24.000
223 594.000 40.000 23.000
224 505.000 40.000 23.000
225 364.000 30.000 25.000
226 439.000 126.000 75.000
227 567.000 35.000 25.000
228 562.000 44.000 19.000
229 385.000 36.000 28.000
230 558.000 253.000 127.000
231 792.000 36.000 35.000
232 594.000 18.000 17.000
233 378.000 47.000 25.000
234 668.000 26.000 18.000
235 326.000 38.000 22.000
236 642.000 28.000 15.000
237 492.000 69.000 51.000
238 621.000 44.000 30.000
239 245.000 58.000 31.000
240 158.000 37.000 27.000
241 667.000 24.000 14.000
242 183.000 34.000 24.000
243 241.000 66.000 62.000
244 89.000 48.000 28.000
245 912.000 50.000 25.000
246 559.000 355.000 210.000
247 238.000 81.000 36.000
248 388.000 106.000 81.000
249 569.000 64.000 39.000
250 665.000 70.000 36.000
251 441.000 68.000 38.000
252 397.000 137.000 88.000
253 1.558 29.000 19.000
254 219.000 76.000 71.000
255 354.000 74.000 47.000
256 484.000 57.000 38.000
257 708.000 40.000 28.000
258 631.000 181.000 130.000
259 159.000 85.000 73.000
260 318.000 49.000 22.000
261 227.000 84.000 52.000
262 309.000 46.000 31.000
263 580.000 100.000 58.000
264 360.000 40.000 37.000
265 205.000 86.000 56.000
266 211.000 57.000 33.000
267 460.000 86.000 67.000
268 287.000 21.000 14.000
269 174.000 75.000 59.000
270 436.000 30.000 11.000
271 729.000 64.000 34.000
272 298.000 85.000 44.000
273 250.000 110.000 79.000
274 212.000 35.000 18.000
275 149.000 47.000 47.000
276 183.000 157.000 75.000
277 250.000 50.000 23.000
278 141.000 1.105 664.000
279 238.000 22.000 19.000
280 500.000 86.000 35.000
281 308.000 29.000 20.000
282 473.000 38.000 39.000
283 580.000 79.000 57.000
284 336.000 24.000 21.000
285 857.000 34.000 23.000
286 387.000 55.000 20.000
287 705.000 36.000 37.000
288 346.000 39.000 18.000
289 451.000 31.000 16.000
290 353.000 30.000 16.000
291 546.000 40.000 26.000
292 442.000 57.000 30.000
293 737.000 31.000 11.000
294 144.000 139.000 63.000
295 252.000 104.000 68.000
296 715.000 28.000 14.000
297 285.000 44.000 26.000
298 663.000 23.000 16.000
299 268.000 17.000 8.000
300 300.000 6.000 5.000
301 402.000 20.000 14.000
302 368.000 24.000 15.000
303 344.000 27.000 14.000
304 523.000 181.000 100.000
305 219.000 65.000 35.000
306 313.000 155.000 86.000
307 592.000 73.000 39.000
308 263.000 338.000 217.000
309 213.000 77.000 35.000
310 234.000 110.000 62.000
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) huwelijken echtscheidingen
384.05362 0.06617 -0.25169
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-382.87 -166.17 -36.28 165.92 608.55
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 384.05362 18.55769 20.695 <2e-16 ***
huwelijken 0.06617 0.19867 0.333 0.739
echtscheidingen -0.25169 0.29958 -0.840 0.401
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 241.6 on 307 degrees of freedom
Multiple R-squared: 0.002605, Adjusted R-squared: -0.003892
F-statistic: 0.401 on 2 and 307 DF, p-value: 0.67
> 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,] 0.8734583 0.2530833656 0.1265416828
[2,] 0.8092448 0.3815103421 0.1907551710
[3,] 0.9897845 0.0204309688 0.0102154844
[4,] 0.9831921 0.0336157821 0.0168078910
[5,] 0.9961827 0.0076345009 0.0038172504
[6,] 0.9940476 0.0119047442 0.0059523721
[7,] 0.9948688 0.0102624812 0.0051312406
[8,] 0.9926870 0.0146260831 0.0073130415
[9,] 0.9876047 0.0247905954 0.0123952977
[10,] 0.9884850 0.0230300490 0.0115150245
[11,] 0.9964622 0.0070755845 0.0035377922
[12,] 0.9972985 0.0054030045 0.0027015023
[13,] 0.9978466 0.0043067917 0.0021533959
[14,] 0.9977186 0.0045628930 0.0022814465
[15,] 0.9963760 0.0072479865 0.0036239933
[16,] 0.9954927 0.0090145941 0.0045072971
[17,] 0.9939902 0.0120196835 0.0060098418
[18,] 0.9964151 0.0071697879 0.0035848939
[19,] 0.9967005 0.0065990329 0.0032995164
[20,] 0.9974914 0.0050171695 0.0025085847
[21,] 0.9972706 0.0054587065 0.0027293533
[22,] 0.9995583 0.0008833110 0.0004416555
[23,] 0.9994502 0.0010995756 0.0005497878
[24,] 0.9991757 0.0016485573 0.0008242787
[25,] 0.9992650 0.0014700195 0.0007350098
[26,] 0.9997144 0.0005712972 0.0002856486
[27,] 0.9996087 0.0007826860 0.0003913430
[28,] 0.9996324 0.0007352841 0.0003676420
[29,] 0.9994700 0.0010600542 0.0005300271
[30,] 0.9993550 0.0012900056 0.0006450028
[31,] 0.9996055 0.0007889609 0.0003944805
[32,] 0.9998573 0.0002854321 0.0001427161
[33,] 0.9997940 0.0004119828 0.0002059914
[34,] 0.9998164 0.0003672397 0.0001836199
[35,] 0.9998797 0.0002405104 0.0001202552
[36,] 0.9998614 0.0002771792 0.0001385896
[37,] 0.9997964 0.0004071359 0.0002035680
[38,] 0.9996998 0.0006003914 0.0003001957
[39,] 0.9996064 0.0007872697 0.0003936349
[40,] 0.9995327 0.0009345978 0.0004672989
[41,] 0.9998055 0.0003889376 0.0001944688
[42,] 0.9997121 0.0005757808 0.0002878904
[43,] 0.9996344 0.0007312494 0.0003656247
[44,] 0.9994688 0.0010623433 0.0005311716
[45,] 0.9992735 0.0014529020 0.0007264510
[46,] 0.9989719 0.0020562144 0.0010281072
[47,] 0.9985631 0.0028738763 0.0014369381
[48,] 0.9980816 0.0038367168 0.0019183584
[49,] 0.9973532 0.0052936535 0.0026468268
[50,] 0.9968525 0.0062950144 0.0031475072
[51,] 0.9958121 0.0083758067 0.0041879033
[52,] 0.9945788 0.0108424249 0.0054212124
[53,] 0.9937364 0.0125272309 0.0062636154
[54,] 0.9933400 0.0133200511 0.0066600255
[55,] 0.9913804 0.0172391462 0.0086195731
[56,] 0.9891376 0.0217248320 0.0108624160
[57,] 0.9863786 0.0272427683 0.0136213842
[58,] 0.9852366 0.0295267385 0.0147633692
[59,] 0.9816294 0.0367411953 0.0183705976
[60,] 0.9777035 0.0445929248 0.0222964624
[61,] 0.9747511 0.0504978515 0.0252489258
[62,] 0.9733016 0.0533967844 0.0266983922
[63,] 0.9694358 0.0611284131 0.0305642066
[64,] 0.9636442 0.0727115910 0.0363557955
[65,] 0.9683651 0.0632697071 0.0316348535
[66,] 0.9634227 0.0731545619 0.0365772810
[67,] 0.9808050 0.0383900012 0.0191950006
[68,] 0.9768944 0.0462111917 0.0231055958
[69,] 0.9767223 0.0465553888 0.0232776944
[70,] 0.9723545 0.0552910034 0.0276455017
[71,] 0.9714120 0.0571760509 0.0285880255
[72,] 0.9692811 0.0614377607 0.0307188803
[73,] 0.9780652 0.0438696000 0.0219348000
[74,] 0.9813966 0.0372067228 0.0186033614
[75,] 0.9932210 0.0135580067 0.0067790033
[76,] 0.9919889 0.0160222659 0.0080111330
[77,] 0.9909973 0.0180053768 0.0090026884
[78,] 0.9959924 0.0080152392 0.0040076196
[79,] 0.9974485 0.0051030103 0.0025515052
[80,] 0.9975774 0.0048451750 0.0024225875
[81,] 0.9970298 0.0059404414 0.0029702207
[82,] 0.9961814 0.0076371701 0.0038185851
[83,] 0.9958777 0.0082446327 0.0041223163
[84,] 0.9971321 0.0057357998 0.0028678999
[85,] 0.9964214 0.0071572297 0.0035786148
[86,] 0.9975069 0.0049862164 0.0024931082
[87,] 0.9970028 0.0059943851 0.0029971925
[88,] 0.9961316 0.0077367126 0.0038683563
[89,] 0.9964263 0.0071474235 0.0035737118
[90,] 0.9958455 0.0083089374 0.0041544687
[91,] 0.9959751 0.0080497053 0.0040248526
[92,] 0.9973134 0.0053732851 0.0026866426
[93,] 0.9966475 0.0067050212 0.0033525106
[94,] 0.9964739 0.0070522839 0.0035261420
[95,] 0.9975741 0.0048518408 0.0024259204
[96,] 0.9983435 0.0033129252 0.0016564626
[97,] 0.9979743 0.0040514343 0.0020257171
[98,] 0.9975433 0.0049133363 0.0024566681
[99,] 0.9983101 0.0033798758 0.0016899379
[100,] 0.9988416 0.0023167995 0.0011583997
[101,] 0.9992125 0.0015750374 0.0007875187
[102,] 0.9995284 0.0009432940 0.0004716470
[103,] 0.9996878 0.0006244309 0.0003122154
[104,] 0.9997960 0.0004080130 0.0002040065
[105,] 0.9997329 0.0005341106 0.0002670553
[106,] 0.9997849 0.0004302367 0.0002151184
[107,] 0.9997085 0.0005829301 0.0002914650
[108,] 0.9996177 0.0007645715 0.0003822858
[109,] 0.9995590 0.0008820561 0.0004410280
[110,] 0.9995311 0.0009378784 0.0004689392
[111,] 0.9993822 0.0012356787 0.0006178393
[112,] 0.9992533 0.0014934848 0.0007467424
[113,] 0.9992651 0.0014698424 0.0007349212
[114,] 0.9991016 0.0017967752 0.0008983876
[115,] 0.9988163 0.0023674789 0.0011837394
[116,] 0.9987320 0.0025360029 0.0012680015
[117,] 0.9983917 0.0032166772 0.0016083386
[118,] 0.9983480 0.0033039598 0.0016519799
[119,] 0.9981580 0.0036840136 0.0018420068
[120,] 0.9977712 0.0044576507 0.0022288253
[121,] 0.9973633 0.0052733108 0.0026366554
[122,] 0.9977346 0.0045308410 0.0022654205
[123,] 0.9976375 0.0047249838 0.0023624919
[124,] 0.9973053 0.0053893305 0.0026946652
[125,] 0.9966730 0.0066540378 0.0033270189
[126,] 0.9976773 0.0046453199 0.0023226600
[127,] 0.9970863 0.0058274509 0.0029137255
[128,] 0.9962815 0.0074369153 0.0037184576
[129,] 0.9952920 0.0094160585 0.0047080293
[130,] 0.9955077 0.0089846226 0.0044923113
[131,] 0.9944339 0.0111322485 0.0055661243
[132,] 0.9949221 0.0101558566 0.0050779283
[133,] 0.9945806 0.0108387731 0.0054193866
[134,] 0.9940297 0.0119406915 0.0059703457
[135,] 0.9926256 0.0147487893 0.0073743946
[136,] 0.9914765 0.0170470591 0.0085235296
[137,] 0.9906375 0.0187249700 0.0093624850
[138,] 0.9884796 0.0230408015 0.0115204008
[139,] 0.9858613 0.0282773036 0.0141386518
[140,] 0.9843369 0.0313261823 0.0156630912
[141,] 0.9884389 0.0231221297 0.0115610649
[142,] 0.9936337 0.0127326930 0.0063663465
[143,] 0.9937547 0.0124906883 0.0062453442
[144,] 0.9926424 0.0147152859 0.0073576430
[145,] 0.9911479 0.0177042066 0.0088521033
[146,] 0.9891375 0.0217250273 0.0108625137
[147,] 0.9865779 0.0268441676 0.0134220838
[148,] 0.9887137 0.0225725025 0.0112862513
[149,] 0.9882499 0.0235001882 0.0117500941
[150,] 0.9883832 0.0232335263 0.0116167631
[151,] 0.9888874 0.0222251073 0.0111125536
[152,] 0.9883245 0.0233510948 0.0116755474
[153,] 0.9870118 0.0259763611 0.0129881805
[154,] 0.9855097 0.0289805020 0.0144902510
[155,] 0.9879601 0.0240798402 0.0120399201
[156,] 0.9870105 0.0259790853 0.0129895427
[157,] 0.9848427 0.0303146918 0.0151573459
[158,] 0.9823840 0.0352320235 0.0176160117
[159,] 0.9817848 0.0364303092 0.0182151546
[160,] 0.9778951 0.0442097831 0.0221048916
[161,] 0.9768377 0.0463246044 0.0231623022
[162,] 0.9789160 0.0421679698 0.0210839849
[163,] 0.9790266 0.0419467264 0.0209733632
[164,] 0.9808320 0.0383360059 0.0191680030
[165,] 0.9835939 0.0328122171 0.0164061086
[166,] 0.9801311 0.0397378534 0.0198689267
[167,] 0.9761136 0.0477727410 0.0238863705
[168,] 0.9784022 0.0431956291 0.0215978146
[169,] 0.9903569 0.0192861817 0.0096430909
[170,] 0.9965356 0.0069287202 0.0034643601
[171,] 0.9977453 0.0045094715 0.0022547357
[172,] 0.9971018 0.0057964076 0.0028982038
[173,] 0.9994133 0.0011734865 0.0005867432
[174,] 0.9997206 0.0005588786 0.0002794393
[175,] 0.9998632 0.0002735301 0.0001367650
[176,] 0.9998109 0.0003782211 0.0001891105
[177,] 0.9997887 0.0004225252 0.0002112626
[178,] 0.9997407 0.0005185591 0.0002592795
[179,] 0.9998076 0.0003848970 0.0001924485
[180,] 0.9997512 0.0004975555 0.0002487777
[181,] 0.9996717 0.0006566009 0.0003283004
[182,] 0.9995987 0.0008025033 0.0004012517
[183,] 0.9997719 0.0004561306 0.0002280653
[184,] 0.9997171 0.0005657444 0.0002828722
[185,] 0.9996321 0.0007358083 0.0003679041
[186,] 0.9995645 0.0008709934 0.0004354967
[187,] 0.9994605 0.0010789455 0.0005394727
[188,] 0.9995231 0.0009538875 0.0004769438
[189,] 0.9997364 0.0005271705 0.0002635852
[190,] 0.9996373 0.0007254686 0.0003627343
[191,] 0.9995166 0.0009667538 0.0004833769
[192,] 0.9993666 0.0012667194 0.0006333597
[193,] 0.9998899 0.0002201028 0.0001100514
[194,] 0.9998648 0.0002704145 0.0001352073
[195,] 0.9998245 0.0003510024 0.0001755012
[196,] 0.9997622 0.0004755751 0.0002377875
[197,] 0.9996701 0.0006597620 0.0003298810
[198,] 0.9995578 0.0008843636 0.0004421818
[199,] 0.9995186 0.0009627424 0.0004813712
[200,] 0.9995130 0.0009740543 0.0004870271
[201,] 0.9993766 0.0012468150 0.0006234075
[202,] 0.9991556 0.0016887457 0.0008443728
[203,] 0.9990741 0.0018517411 0.0009258705
[204,] 0.9988529 0.0022942225 0.0011471112
[205,] 0.9987003 0.0025994752 0.0012997376
[206,] 0.9990974 0.0018051492 0.0009025746
[207,] 0.9987948 0.0024103169 0.0012051585
[208,] 0.9984702 0.0030595967 0.0015297984
[209,] 0.9979664 0.0040671021 0.0020335511
[210,] 0.9982458 0.0035084856 0.0017542428
[211,] 0.9977395 0.0045209891 0.0022604945
[212,] 0.9975055 0.0049889099 0.0024944549
[213,] 0.9986663 0.0026673130 0.0013336565
[214,] 0.9993412 0.0013176354 0.0006588177
[215,] 0.9990909 0.0018181251 0.0009090626
[216,] 0.9990875 0.0018249175 0.0009124587
[217,] 0.9987660 0.0024679677 0.0012339839
[218,] 0.9986493 0.0027014194 0.0013507097
[219,] 0.9982710 0.0034580645 0.0017290323
[220,] 0.9976846 0.0046307177 0.0023153588
[221,] 0.9969263 0.0061474750 0.0030737375
[222,] 0.9964797 0.0070405918 0.0035202959
[223,] 0.9959274 0.0081451862 0.0040725931
[224,] 0.9946087 0.0107826496 0.0053913248
[225,] 0.9940764 0.0118472691 0.0059236345
[226,] 0.9967724 0.0064551622 0.0032275811
[227,] 0.9965371 0.0069258937 0.0034629469
[228,] 0.9953656 0.0092688719 0.0046344360
[229,] 0.9959804 0.0080391316 0.0040195658
[230,] 0.9947606 0.0104787170 0.0052393585
[231,] 0.9951036 0.0097927745 0.0048963872
[232,] 0.9938861 0.0122278209 0.0061139105
[233,] 0.9940699 0.0118601778 0.0059300889
[234,] 0.9929636 0.0140727318 0.0070363659
[235,] 0.9931037 0.0137925871 0.0068962935
[236,] 0.9941080 0.0117839921 0.0058919961
[237,] 0.9938502 0.0122995807 0.0061497904
[238,] 0.9926646 0.0146707748 0.0073353874
[239,] 0.9943887 0.0112226259 0.0056113129
[240,] 0.9987919 0.0024161018 0.0012080509
[241,] 0.9988648 0.0022704493 0.0011352246
[242,] 0.9986266 0.0027468653 0.0013734326
[243,] 0.9980478 0.0039043944 0.0019521972
[244,] 0.9978453 0.0043093872 0.0021546936
[245,] 0.9983320 0.0033359947 0.0016679974
[246,] 0.9976831 0.0046337890 0.0023168945
[247,] 0.9967721 0.0064558611 0.0032279306
[248,] 0.9986528 0.0026944827 0.0013472413
[249,] 0.9983881 0.0032237279 0.0016118639
[250,] 0.9976825 0.0046350197 0.0023175099
[251,] 0.9969002 0.0061996243 0.0030998122
[252,] 0.9979961 0.0040078704 0.0020039352
[253,] 0.9987982 0.0024035511 0.0012017756
[254,] 0.9987533 0.0024934376 0.0012467188
[255,] 0.9982367 0.0035266531 0.0017633265
[256,] 0.9978309 0.0043382377 0.0021691188
[257,] 0.9970115 0.0059770470 0.0029885235
[258,] 0.9970950 0.0058100628 0.0029050314
[259,] 0.9957909 0.0084181276 0.0042090638
[260,] 0.9951168 0.0097664914 0.0048832457
[261,] 0.9946331 0.0107338908 0.0053669454
[262,] 0.9927644 0.0144711992 0.0072355996
[263,] 0.9909769 0.0180462499 0.0090231249
[264,] 0.9907995 0.0184010065 0.0092005032
[265,] 0.9869281 0.0261438063 0.0130719032
[266,] 0.9924958 0.0150084812 0.0075042406
[267,] 0.9896445 0.0207109063 0.0103554532
[268,] 0.9863811 0.0272378362 0.0136189181
[269,] 0.9860194 0.0279611220 0.0139805610
[270,] 0.9883439 0.0233121903 0.0116560952
[271,] 0.9867330 0.0265340901 0.0132670450
[272,] 0.9850913 0.0298174604 0.0149087302
[273,] 0.9843976 0.0312047799 0.0156023899
[274,] 0.9861361 0.0277278682 0.0138639341
[275,] 0.9843596 0.0312808531 0.0156404265
[276,] 0.9817061 0.0365877112 0.0182938556
[277,] 0.9749001 0.0501997218 0.0250998609
[278,] 0.9665913 0.0668174254 0.0334087127
[279,] 0.9627770 0.0744460408 0.0372230204
[280,] 0.9869878 0.0260243868 0.0130121934
[281,] 0.9799977 0.0400046022 0.0200023011
[282,] 0.9799478 0.0401043518 0.0200521759
[283,] 0.9700844 0.0598311363 0.0299155681
[284,] 0.9550649 0.0898702636 0.0449351318
[285,] 0.9362964 0.1274072943 0.0637036471
[286,] 0.9178290 0.1643419104 0.0821709552
[287,] 0.8844035 0.2311930646 0.1155965323
[288,] 0.9432728 0.1134543568 0.0567271784
[289,] 0.9322883 0.1354233375 0.0677116688
[290,] 0.9090941 0.1818117363 0.0909058681
[291,] 0.9608122 0.0783755368 0.0391877684
[292,] 0.9393764 0.1212472184 0.0606236092
[293,] 0.9787915 0.0424170898 0.0212085449
[294,] 0.9621082 0.0757835584 0.0378917792
[295,] 0.9298194 0.1403611469 0.0701805735
[296,] 0.8801194 0.2397612399 0.1198806200
[297,] 0.7997440 0.4005120409 0.2002560204
[298,] 0.6795021 0.6409958445 0.3204979222
[299,] 0.6507848 0.6984304089 0.3492152044
> postscript(file="/var/wessaorg/rcomp/tmp/1w61s1321909558.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/2hudq1321909558.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3r4nc1321909558.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4c5gr1321909558.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5c8o61321909558.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 310
Frequency = 1
1 2 3 4 5 6
229.0962896 601.0851283 -382.8745080 -373.1545724 238.1149172 -366.9927782
7 8 9 10 11 12
-377.1047243 585.4633473 -77.5710796 -379.0081928 -6.6678736 -377.9153656
13 14 15 16 17 18
-375.0216939 -78.4320123 329.5250269 491.0521428 -380.8144624 -375.5464195
19 20 21 22 23 24
-379.2848355 37.0804325 358.0300572 -372.3279082 162.3632932 -381.5053310
25 26 27 28 29 30
456.8439904 -377.7657863 566.7976539 -161.5383527 -70.0411355 166.5725739
31 32 33 34 35 36
-377.2333544 -100.4614212 259.5549833 65.2433432 132.8383337 74.3096000
37 38 39 40 41 42
372.6489977 82.5154227 303.7982013 -377.5757556 169.0878136 90.3095178
43 44 45 46 47 48
121.4169531 137.6189104 173.9865490 506.1177699 -58.4653444 -150.5677616
49 50 51 52 53 54
-41.3872359 -92.7532810 81.4650474 -44.0711496 -39.4993396 7.4011537
55 56 57 58 59 60
170.6319148 -7.4540979 -107.8103744 -192.6197792 185.7699450 -125.3945593
61 62 63 64 65 66
-108.0038224 -113.6927297 -188.6593976 -80.7323481 128.0487426 -32.5316102
67 68 69 70 71 72
-229.5615332 -158.0773781 -137.8414590 350.6070008 -80.5014895 493.9090945
73 74 75 76 77 78
51.1772264 -74.6369739 143.6240350 261.6465858 239.7558367 422.5968492
79 80 81 82 83 84
-233.6396354 604.1675888 -138.9217907 -128.4605785 549.6906992 446.3348879
85 86 87 88 89 90
-178.0897222 144.9487038 -36.4631547 222.9425088 -365.6121745 113.4638948
91 92 93 94 95 96
-379.7864951 144.2382430 43.9950494 293.2337146 170.2664993 -249.4761591
97 98 99 100 101 102
414.8037911 102.8021823 231.7303266 -379.3965119 -379.7434644 130.7834968
103 104 105 106 107 108
136.3677638 -377.6119989 -376.1177080 -376.7441586 412.5855205 -378.7934432
109 110 111 112 113 114
-382.4165029 -89.1983986 322.1940962 36.3869967 84.5798638 177.4944898
115 116 117 118 119 120
-217.5519045 -57.3754664 -144.2374361 251.4062296 -132.1452527 15.4582471
121 122 123 124 125 126
-209.6786305 82.9096175 232.9554066 -188.4410357 -122.1706897 -142.9048631
127 128 129 130 131 132
305.4848611 -223.8794017 165.9424600 -97.1231672 -381.0938372 -73.2312410
133 134 135 136 137 138
-27.7538285 32.2608760 263.7201750 70.9413074 284.0284149 -207.0779255
139 140 141 142 143 144
-184.9710377 65.3451308 -144.8895534 -185.2543637 11.4750048 37.8044298
145 146 147 148 149 150
-172.8590162 -377.5462362 462.7512596 -248.7380048 -128.8640921 -99.6135507
151 152 153 154 155 156
56.4119106 -8.6293834 -322.8256841 216.7093937 -244.2708260 -261.2555498
157 158 159 160 161 162
-208.0242079 -167.6995056 -162.6667209 -325.6842537 -187.5004344 -115.5490762
163 164 165 166 167 168
-115.8726258 -212.0564451 33.6432191 -200.1305483 -284.2827112 -231.6871064
169 170 171 172 173 174
-276.9484625 321.0657524 -39.1707141 65.2772805 293.8763098 531.3519067
175 176 177 178 179 180
552.8479713 -376.6944946 43.7834968 608.5522127 438.9214693 419.4791801
181 182 183 184 185 186
-0.5485288 -182.9099389 139.3095178 -323.5715415 -100.0898350 -75.9506522
187 188 189 190 191 192
-130.8810774 -375.3809504 -122.0999867 -88.8211557 164.1675066 -117.9766609
193 194 195 196 197 198
277.3202747 -380.0863286 5.2416431 -56.9268909 -66.2679489 576.7948011
199 200 201 202 203 204
-133.8279650 -101.9959516 -61.1226197 -4.4150269 73.1205983 -188.7018109
205 206 207 208 209 210
-211.2492879 -94.5875419 42.5391262 -173.1446809 -87.2222267 -160.1627855
211 212 213 214 215 216
-321.7278197 73.7184415 124.7852213 -12.0767485 -254.9274717 96.3575878
217 218 219 220 221 222
204.0782093 -377.7537424 -376.5351542 26.8513137 239.4473900 -18.7922942
223 224 225 226 227 228
213.0883610 124.0883610 -15.7465051 65.4854329 186.9226219 179.8168867
229 230 231 232 233 234
5.6115293 189.1693466 414.3733871 213.0340382 -2.8714732 286.7563354
235 236 237 238 239 240
-55.0309838 259.8689043 116.2167292 241.5855205 -135.0892298 -221.7063393
241 242 243 244 245 246
284.8819087 -197.2628975 -131.8161133 -291.1825658 530.9300030 204.3101384
247 248 249 250 251 252
-142.3527755 17.3190886 190.5272744 285.3751450 62.0108821 26.0295341
253 254 255 256 257 258
-379.6324944 -152.2126134 -23.1209197 105.7388026 328.3468309 267.6889991
259 260 261 262 263 264
-212.3047968 -63.7589043 -149.5241957 -70.2951347 203.9271747 -17.3879233
265 266 267 268 269 270
-170.6497690 -168.5196673 87.1188648 -94.9195675 -200.1667665 52.7297792
271 272 273 274 275 276
349.2688046 -80.6039221 -121.4489977 -169.8392359 -226.3342057 -192.5659794
277 278 279 280 281 282
-131.5733849 -76.0019391 -142.7272723 119.0646575 -72.9388004 96.2478138
283 284 285 286 287 288
205.0651472 -44.3562335 476.4854086 4.3406602 327.8767750 -36.1039343
289 290 291 292 293 294
68.9220745 -29.0117509 165.8434429 61.7252508 353.6636046 -233.3951645
295 296 297 298 299 300
-121.8205839 332.6172103 -95.4212554 281.4514712 -115.1650330 -83.1921945
301 302 303 304 305 306
20.1466070 -13.8663973 -38.3166151 152.1381798 -160.5456761 -59.6649965
307 308 309 310
212.9317031 -88.8030357 -167.3397712 -141.7277953
> postscript(file="/var/wessaorg/rcomp/tmp/6nd6q1321909558.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 = 310
Frequency = 1
lag(myerror, k = 1) myerror
0 229.0962896 NA
1 601.0851283 229.0962896
2 -382.8745080 601.0851283
3 -373.1545724 -382.8745080
4 238.1149172 -373.1545724
5 -366.9927782 238.1149172
6 -377.1047243 -366.9927782
7 585.4633473 -377.1047243
8 -77.5710796 585.4633473
9 -379.0081928 -77.5710796
10 -6.6678736 -379.0081928
11 -377.9153656 -6.6678736
12 -375.0216939 -377.9153656
13 -78.4320123 -375.0216939
14 329.5250269 -78.4320123
15 491.0521428 329.5250269
16 -380.8144624 491.0521428
17 -375.5464195 -380.8144624
18 -379.2848355 -375.5464195
19 37.0804325 -379.2848355
20 358.0300572 37.0804325
21 -372.3279082 358.0300572
22 162.3632932 -372.3279082
23 -381.5053310 162.3632932
24 456.8439904 -381.5053310
25 -377.7657863 456.8439904
26 566.7976539 -377.7657863
27 -161.5383527 566.7976539
28 -70.0411355 -161.5383527
29 166.5725739 -70.0411355
30 -377.2333544 166.5725739
31 -100.4614212 -377.2333544
32 259.5549833 -100.4614212
33 65.2433432 259.5549833
34 132.8383337 65.2433432
35 74.3096000 132.8383337
36 372.6489977 74.3096000
37 82.5154227 372.6489977
38 303.7982013 82.5154227
39 -377.5757556 303.7982013
40 169.0878136 -377.5757556
41 90.3095178 169.0878136
42 121.4169531 90.3095178
43 137.6189104 121.4169531
44 173.9865490 137.6189104
45 506.1177699 173.9865490
46 -58.4653444 506.1177699
47 -150.5677616 -58.4653444
48 -41.3872359 -150.5677616
49 -92.7532810 -41.3872359
50 81.4650474 -92.7532810
51 -44.0711496 81.4650474
52 -39.4993396 -44.0711496
53 7.4011537 -39.4993396
54 170.6319148 7.4011537
55 -7.4540979 170.6319148
56 -107.8103744 -7.4540979
57 -192.6197792 -107.8103744
58 185.7699450 -192.6197792
59 -125.3945593 185.7699450
60 -108.0038224 -125.3945593
61 -113.6927297 -108.0038224
62 -188.6593976 -113.6927297
63 -80.7323481 -188.6593976
64 128.0487426 -80.7323481
65 -32.5316102 128.0487426
66 -229.5615332 -32.5316102
67 -158.0773781 -229.5615332
68 -137.8414590 -158.0773781
69 350.6070008 -137.8414590
70 -80.5014895 350.6070008
71 493.9090945 -80.5014895
72 51.1772264 493.9090945
73 -74.6369739 51.1772264
74 143.6240350 -74.6369739
75 261.6465858 143.6240350
76 239.7558367 261.6465858
77 422.5968492 239.7558367
78 -233.6396354 422.5968492
79 604.1675888 -233.6396354
80 -138.9217907 604.1675888
81 -128.4605785 -138.9217907
82 549.6906992 -128.4605785
83 446.3348879 549.6906992
84 -178.0897222 446.3348879
85 144.9487038 -178.0897222
86 -36.4631547 144.9487038
87 222.9425088 -36.4631547
88 -365.6121745 222.9425088
89 113.4638948 -365.6121745
90 -379.7864951 113.4638948
91 144.2382430 -379.7864951
92 43.9950494 144.2382430
93 293.2337146 43.9950494
94 170.2664993 293.2337146
95 -249.4761591 170.2664993
96 414.8037911 -249.4761591
97 102.8021823 414.8037911
98 231.7303266 102.8021823
99 -379.3965119 231.7303266
100 -379.7434644 -379.3965119
101 130.7834968 -379.7434644
102 136.3677638 130.7834968
103 -377.6119989 136.3677638
104 -376.1177080 -377.6119989
105 -376.7441586 -376.1177080
106 412.5855205 -376.7441586
107 -378.7934432 412.5855205
108 -382.4165029 -378.7934432
109 -89.1983986 -382.4165029
110 322.1940962 -89.1983986
111 36.3869967 322.1940962
112 84.5798638 36.3869967
113 177.4944898 84.5798638
114 -217.5519045 177.4944898
115 -57.3754664 -217.5519045
116 -144.2374361 -57.3754664
117 251.4062296 -144.2374361
118 -132.1452527 251.4062296
119 15.4582471 -132.1452527
120 -209.6786305 15.4582471
121 82.9096175 -209.6786305
122 232.9554066 82.9096175
123 -188.4410357 232.9554066
124 -122.1706897 -188.4410357
125 -142.9048631 -122.1706897
126 305.4848611 -142.9048631
127 -223.8794017 305.4848611
128 165.9424600 -223.8794017
129 -97.1231672 165.9424600
130 -381.0938372 -97.1231672
131 -73.2312410 -381.0938372
132 -27.7538285 -73.2312410
133 32.2608760 -27.7538285
134 263.7201750 32.2608760
135 70.9413074 263.7201750
136 284.0284149 70.9413074
137 -207.0779255 284.0284149
138 -184.9710377 -207.0779255
139 65.3451308 -184.9710377
140 -144.8895534 65.3451308
141 -185.2543637 -144.8895534
142 11.4750048 -185.2543637
143 37.8044298 11.4750048
144 -172.8590162 37.8044298
145 -377.5462362 -172.8590162
146 462.7512596 -377.5462362
147 -248.7380048 462.7512596
148 -128.8640921 -248.7380048
149 -99.6135507 -128.8640921
150 56.4119106 -99.6135507
151 -8.6293834 56.4119106
152 -322.8256841 -8.6293834
153 216.7093937 -322.8256841
154 -244.2708260 216.7093937
155 -261.2555498 -244.2708260
156 -208.0242079 -261.2555498
157 -167.6995056 -208.0242079
158 -162.6667209 -167.6995056
159 -325.6842537 -162.6667209
160 -187.5004344 -325.6842537
161 -115.5490762 -187.5004344
162 -115.8726258 -115.5490762
163 -212.0564451 -115.8726258
164 33.6432191 -212.0564451
165 -200.1305483 33.6432191
166 -284.2827112 -200.1305483
167 -231.6871064 -284.2827112
168 -276.9484625 -231.6871064
169 321.0657524 -276.9484625
170 -39.1707141 321.0657524
171 65.2772805 -39.1707141
172 293.8763098 65.2772805
173 531.3519067 293.8763098
174 552.8479713 531.3519067
175 -376.6944946 552.8479713
176 43.7834968 -376.6944946
177 608.5522127 43.7834968
178 438.9214693 608.5522127
179 419.4791801 438.9214693
180 -0.5485288 419.4791801
181 -182.9099389 -0.5485288
182 139.3095178 -182.9099389
183 -323.5715415 139.3095178
184 -100.0898350 -323.5715415
185 -75.9506522 -100.0898350
186 -130.8810774 -75.9506522
187 -375.3809504 -130.8810774
188 -122.0999867 -375.3809504
189 -88.8211557 -122.0999867
190 164.1675066 -88.8211557
191 -117.9766609 164.1675066
192 277.3202747 -117.9766609
193 -380.0863286 277.3202747
194 5.2416431 -380.0863286
195 -56.9268909 5.2416431
196 -66.2679489 -56.9268909
197 576.7948011 -66.2679489
198 -133.8279650 576.7948011
199 -101.9959516 -133.8279650
200 -61.1226197 -101.9959516
201 -4.4150269 -61.1226197
202 73.1205983 -4.4150269
203 -188.7018109 73.1205983
204 -211.2492879 -188.7018109
205 -94.5875419 -211.2492879
206 42.5391262 -94.5875419
207 -173.1446809 42.5391262
208 -87.2222267 -173.1446809
209 -160.1627855 -87.2222267
210 -321.7278197 -160.1627855
211 73.7184415 -321.7278197
212 124.7852213 73.7184415
213 -12.0767485 124.7852213
214 -254.9274717 -12.0767485
215 96.3575878 -254.9274717
216 204.0782093 96.3575878
217 -377.7537424 204.0782093
218 -376.5351542 -377.7537424
219 26.8513137 -376.5351542
220 239.4473900 26.8513137
221 -18.7922942 239.4473900
222 213.0883610 -18.7922942
223 124.0883610 213.0883610
224 -15.7465051 124.0883610
225 65.4854329 -15.7465051
226 186.9226219 65.4854329
227 179.8168867 186.9226219
228 5.6115293 179.8168867
229 189.1693466 5.6115293
230 414.3733871 189.1693466
231 213.0340382 414.3733871
232 -2.8714732 213.0340382
233 286.7563354 -2.8714732
234 -55.0309838 286.7563354
235 259.8689043 -55.0309838
236 116.2167292 259.8689043
237 241.5855205 116.2167292
238 -135.0892298 241.5855205
239 -221.7063393 -135.0892298
240 284.8819087 -221.7063393
241 -197.2628975 284.8819087
242 -131.8161133 -197.2628975
243 -291.1825658 -131.8161133
244 530.9300030 -291.1825658
245 204.3101384 530.9300030
246 -142.3527755 204.3101384
247 17.3190886 -142.3527755
248 190.5272744 17.3190886
249 285.3751450 190.5272744
250 62.0108821 285.3751450
251 26.0295341 62.0108821
252 -379.6324944 26.0295341
253 -152.2126134 -379.6324944
254 -23.1209197 -152.2126134
255 105.7388026 -23.1209197
256 328.3468309 105.7388026
257 267.6889991 328.3468309
258 -212.3047968 267.6889991
259 -63.7589043 -212.3047968
260 -149.5241957 -63.7589043
261 -70.2951347 -149.5241957
262 203.9271747 -70.2951347
263 -17.3879233 203.9271747
264 -170.6497690 -17.3879233
265 -168.5196673 -170.6497690
266 87.1188648 -168.5196673
267 -94.9195675 87.1188648
268 -200.1667665 -94.9195675
269 52.7297792 -200.1667665
270 349.2688046 52.7297792
271 -80.6039221 349.2688046
272 -121.4489977 -80.6039221
273 -169.8392359 -121.4489977
274 -226.3342057 -169.8392359
275 -192.5659794 -226.3342057
276 -131.5733849 -192.5659794
277 -76.0019391 -131.5733849
278 -142.7272723 -76.0019391
279 119.0646575 -142.7272723
280 -72.9388004 119.0646575
281 96.2478138 -72.9388004
282 205.0651472 96.2478138
283 -44.3562335 205.0651472
284 476.4854086 -44.3562335
285 4.3406602 476.4854086
286 327.8767750 4.3406602
287 -36.1039343 327.8767750
288 68.9220745 -36.1039343
289 -29.0117509 68.9220745
290 165.8434429 -29.0117509
291 61.7252508 165.8434429
292 353.6636046 61.7252508
293 -233.3951645 353.6636046
294 -121.8205839 -233.3951645
295 332.6172103 -121.8205839
296 -95.4212554 332.6172103
297 281.4514712 -95.4212554
298 -115.1650330 281.4514712
299 -83.1921945 -115.1650330
300 20.1466070 -83.1921945
301 -13.8663973 20.1466070
302 -38.3166151 -13.8663973
303 152.1381798 -38.3166151
304 -160.5456761 152.1381798
305 -59.6649965 -160.5456761
306 212.9317031 -59.6649965
307 -88.8030357 212.9317031
308 -167.3397712 -88.8030357
309 -141.7277953 -167.3397712
310 NA -141.7277953
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 601.0851283 229.0962896
[2,] -382.8745080 601.0851283
[3,] -373.1545724 -382.8745080
[4,] 238.1149172 -373.1545724
[5,] -366.9927782 238.1149172
[6,] -377.1047243 -366.9927782
[7,] 585.4633473 -377.1047243
[8,] -77.5710796 585.4633473
[9,] -379.0081928 -77.5710796
[10,] -6.6678736 -379.0081928
[11,] -377.9153656 -6.6678736
[12,] -375.0216939 -377.9153656
[13,] -78.4320123 -375.0216939
[14,] 329.5250269 -78.4320123
[15,] 491.0521428 329.5250269
[16,] -380.8144624 491.0521428
[17,] -375.5464195 -380.8144624
[18,] -379.2848355 -375.5464195
[19,] 37.0804325 -379.2848355
[20,] 358.0300572 37.0804325
[21,] -372.3279082 358.0300572
[22,] 162.3632932 -372.3279082
[23,] -381.5053310 162.3632932
[24,] 456.8439904 -381.5053310
[25,] -377.7657863 456.8439904
[26,] 566.7976539 -377.7657863
[27,] -161.5383527 566.7976539
[28,] -70.0411355 -161.5383527
[29,] 166.5725739 -70.0411355
[30,] -377.2333544 166.5725739
[31,] -100.4614212 -377.2333544
[32,] 259.5549833 -100.4614212
[33,] 65.2433432 259.5549833
[34,] 132.8383337 65.2433432
[35,] 74.3096000 132.8383337
[36,] 372.6489977 74.3096000
[37,] 82.5154227 372.6489977
[38,] 303.7982013 82.5154227
[39,] -377.5757556 303.7982013
[40,] 169.0878136 -377.5757556
[41,] 90.3095178 169.0878136
[42,] 121.4169531 90.3095178
[43,] 137.6189104 121.4169531
[44,] 173.9865490 137.6189104
[45,] 506.1177699 173.9865490
[46,] -58.4653444 506.1177699
[47,] -150.5677616 -58.4653444
[48,] -41.3872359 -150.5677616
[49,] -92.7532810 -41.3872359
[50,] 81.4650474 -92.7532810
[51,] -44.0711496 81.4650474
[52,] -39.4993396 -44.0711496
[53,] 7.4011537 -39.4993396
[54,] 170.6319148 7.4011537
[55,] -7.4540979 170.6319148
[56,] -107.8103744 -7.4540979
[57,] -192.6197792 -107.8103744
[58,] 185.7699450 -192.6197792
[59,] -125.3945593 185.7699450
[60,] -108.0038224 -125.3945593
[61,] -113.6927297 -108.0038224
[62,] -188.6593976 -113.6927297
[63,] -80.7323481 -188.6593976
[64,] 128.0487426 -80.7323481
[65,] -32.5316102 128.0487426
[66,] -229.5615332 -32.5316102
[67,] -158.0773781 -229.5615332
[68,] -137.8414590 -158.0773781
[69,] 350.6070008 -137.8414590
[70,] -80.5014895 350.6070008
[71,] 493.9090945 -80.5014895
[72,] 51.1772264 493.9090945
[73,] -74.6369739 51.1772264
[74,] 143.6240350 -74.6369739
[75,] 261.6465858 143.6240350
[76,] 239.7558367 261.6465858
[77,] 422.5968492 239.7558367
[78,] -233.6396354 422.5968492
[79,] 604.1675888 -233.6396354
[80,] -138.9217907 604.1675888
[81,] -128.4605785 -138.9217907
[82,] 549.6906992 -128.4605785
[83,] 446.3348879 549.6906992
[84,] -178.0897222 446.3348879
[85,] 144.9487038 -178.0897222
[86,] -36.4631547 144.9487038
[87,] 222.9425088 -36.4631547
[88,] -365.6121745 222.9425088
[89,] 113.4638948 -365.6121745
[90,] -379.7864951 113.4638948
[91,] 144.2382430 -379.7864951
[92,] 43.9950494 144.2382430
[93,] 293.2337146 43.9950494
[94,] 170.2664993 293.2337146
[95,] -249.4761591 170.2664993
[96,] 414.8037911 -249.4761591
[97,] 102.8021823 414.8037911
[98,] 231.7303266 102.8021823
[99,] -379.3965119 231.7303266
[100,] -379.7434644 -379.3965119
[101,] 130.7834968 -379.7434644
[102,] 136.3677638 130.7834968
[103,] -377.6119989 136.3677638
[104,] -376.1177080 -377.6119989
[105,] -376.7441586 -376.1177080
[106,] 412.5855205 -376.7441586
[107,] -378.7934432 412.5855205
[108,] -382.4165029 -378.7934432
[109,] -89.1983986 -382.4165029
[110,] 322.1940962 -89.1983986
[111,] 36.3869967 322.1940962
[112,] 84.5798638 36.3869967
[113,] 177.4944898 84.5798638
[114,] -217.5519045 177.4944898
[115,] -57.3754664 -217.5519045
[116,] -144.2374361 -57.3754664
[117,] 251.4062296 -144.2374361
[118,] -132.1452527 251.4062296
[119,] 15.4582471 -132.1452527
[120,] -209.6786305 15.4582471
[121,] 82.9096175 -209.6786305
[122,] 232.9554066 82.9096175
[123,] -188.4410357 232.9554066
[124,] -122.1706897 -188.4410357
[125,] -142.9048631 -122.1706897
[126,] 305.4848611 -142.9048631
[127,] -223.8794017 305.4848611
[128,] 165.9424600 -223.8794017
[129,] -97.1231672 165.9424600
[130,] -381.0938372 -97.1231672
[131,] -73.2312410 -381.0938372
[132,] -27.7538285 -73.2312410
[133,] 32.2608760 -27.7538285
[134,] 263.7201750 32.2608760
[135,] 70.9413074 263.7201750
[136,] 284.0284149 70.9413074
[137,] -207.0779255 284.0284149
[138,] -184.9710377 -207.0779255
[139,] 65.3451308 -184.9710377
[140,] -144.8895534 65.3451308
[141,] -185.2543637 -144.8895534
[142,] 11.4750048 -185.2543637
[143,] 37.8044298 11.4750048
[144,] -172.8590162 37.8044298
[145,] -377.5462362 -172.8590162
[146,] 462.7512596 -377.5462362
[147,] -248.7380048 462.7512596
[148,] -128.8640921 -248.7380048
[149,] -99.6135507 -128.8640921
[150,] 56.4119106 -99.6135507
[151,] -8.6293834 56.4119106
[152,] -322.8256841 -8.6293834
[153,] 216.7093937 -322.8256841
[154,] -244.2708260 216.7093937
[155,] -261.2555498 -244.2708260
[156,] -208.0242079 -261.2555498
[157,] -167.6995056 -208.0242079
[158,] -162.6667209 -167.6995056
[159,] -325.6842537 -162.6667209
[160,] -187.5004344 -325.6842537
[161,] -115.5490762 -187.5004344
[162,] -115.8726258 -115.5490762
[163,] -212.0564451 -115.8726258
[164,] 33.6432191 -212.0564451
[165,] -200.1305483 33.6432191
[166,] -284.2827112 -200.1305483
[167,] -231.6871064 -284.2827112
[168,] -276.9484625 -231.6871064
[169,] 321.0657524 -276.9484625
[170,] -39.1707141 321.0657524
[171,] 65.2772805 -39.1707141
[172,] 293.8763098 65.2772805
[173,] 531.3519067 293.8763098
[174,] 552.8479713 531.3519067
[175,] -376.6944946 552.8479713
[176,] 43.7834968 -376.6944946
[177,] 608.5522127 43.7834968
[178,] 438.9214693 608.5522127
[179,] 419.4791801 438.9214693
[180,] -0.5485288 419.4791801
[181,] -182.9099389 -0.5485288
[182,] 139.3095178 -182.9099389
[183,] -323.5715415 139.3095178
[184,] -100.0898350 -323.5715415
[185,] -75.9506522 -100.0898350
[186,] -130.8810774 -75.9506522
[187,] -375.3809504 -130.8810774
[188,] -122.0999867 -375.3809504
[189,] -88.8211557 -122.0999867
[190,] 164.1675066 -88.8211557
[191,] -117.9766609 164.1675066
[192,] 277.3202747 -117.9766609
[193,] -380.0863286 277.3202747
[194,] 5.2416431 -380.0863286
[195,] -56.9268909 5.2416431
[196,] -66.2679489 -56.9268909
[197,] 576.7948011 -66.2679489
[198,] -133.8279650 576.7948011
[199,] -101.9959516 -133.8279650
[200,] -61.1226197 -101.9959516
[201,] -4.4150269 -61.1226197
[202,] 73.1205983 -4.4150269
[203,] -188.7018109 73.1205983
[204,] -211.2492879 -188.7018109
[205,] -94.5875419 -211.2492879
[206,] 42.5391262 -94.5875419
[207,] -173.1446809 42.5391262
[208,] -87.2222267 -173.1446809
[209,] -160.1627855 -87.2222267
[210,] -321.7278197 -160.1627855
[211,] 73.7184415 -321.7278197
[212,] 124.7852213 73.7184415
[213,] -12.0767485 124.7852213
[214,] -254.9274717 -12.0767485
[215,] 96.3575878 -254.9274717
[216,] 204.0782093 96.3575878
[217,] -377.7537424 204.0782093
[218,] -376.5351542 -377.7537424
[219,] 26.8513137 -376.5351542
[220,] 239.4473900 26.8513137
[221,] -18.7922942 239.4473900
[222,] 213.0883610 -18.7922942
[223,] 124.0883610 213.0883610
[224,] -15.7465051 124.0883610
[225,] 65.4854329 -15.7465051
[226,] 186.9226219 65.4854329
[227,] 179.8168867 186.9226219
[228,] 5.6115293 179.8168867
[229,] 189.1693466 5.6115293
[230,] 414.3733871 189.1693466
[231,] 213.0340382 414.3733871
[232,] -2.8714732 213.0340382
[233,] 286.7563354 -2.8714732
[234,] -55.0309838 286.7563354
[235,] 259.8689043 -55.0309838
[236,] 116.2167292 259.8689043
[237,] 241.5855205 116.2167292
[238,] -135.0892298 241.5855205
[239,] -221.7063393 -135.0892298
[240,] 284.8819087 -221.7063393
[241,] -197.2628975 284.8819087
[242,] -131.8161133 -197.2628975
[243,] -291.1825658 -131.8161133
[244,] 530.9300030 -291.1825658
[245,] 204.3101384 530.9300030
[246,] -142.3527755 204.3101384
[247,] 17.3190886 -142.3527755
[248,] 190.5272744 17.3190886
[249,] 285.3751450 190.5272744
[250,] 62.0108821 285.3751450
[251,] 26.0295341 62.0108821
[252,] -379.6324944 26.0295341
[253,] -152.2126134 -379.6324944
[254,] -23.1209197 -152.2126134
[255,] 105.7388026 -23.1209197
[256,] 328.3468309 105.7388026
[257,] 267.6889991 328.3468309
[258,] -212.3047968 267.6889991
[259,] -63.7589043 -212.3047968
[260,] -149.5241957 -63.7589043
[261,] -70.2951347 -149.5241957
[262,] 203.9271747 -70.2951347
[263,] -17.3879233 203.9271747
[264,] -170.6497690 -17.3879233
[265,] -168.5196673 -170.6497690
[266,] 87.1188648 -168.5196673
[267,] -94.9195675 87.1188648
[268,] -200.1667665 -94.9195675
[269,] 52.7297792 -200.1667665
[270,] 349.2688046 52.7297792
[271,] -80.6039221 349.2688046
[272,] -121.4489977 -80.6039221
[273,] -169.8392359 -121.4489977
[274,] -226.3342057 -169.8392359
[275,] -192.5659794 -226.3342057
[276,] -131.5733849 -192.5659794
[277,] -76.0019391 -131.5733849
[278,] -142.7272723 -76.0019391
[279,] 119.0646575 -142.7272723
[280,] -72.9388004 119.0646575
[281,] 96.2478138 -72.9388004
[282,] 205.0651472 96.2478138
[283,] -44.3562335 205.0651472
[284,] 476.4854086 -44.3562335
[285,] 4.3406602 476.4854086
[286,] 327.8767750 4.3406602
[287,] -36.1039343 327.8767750
[288,] 68.9220745 -36.1039343
[289,] -29.0117509 68.9220745
[290,] 165.8434429 -29.0117509
[291,] 61.7252508 165.8434429
[292,] 353.6636046 61.7252508
[293,] -233.3951645 353.6636046
[294,] -121.8205839 -233.3951645
[295,] 332.6172103 -121.8205839
[296,] -95.4212554 332.6172103
[297,] 281.4514712 -95.4212554
[298,] -115.1650330 281.4514712
[299,] -83.1921945 -115.1650330
[300,] 20.1466070 -83.1921945
[301,] -13.8663973 20.1466070
[302,] -38.3166151 -13.8663973
[303,] 152.1381798 -38.3166151
[304,] -160.5456761 152.1381798
[305,] -59.6649965 -160.5456761
[306,] 212.9317031 -59.6649965
[307,] -88.8030357 212.9317031
[308,] -167.3397712 -88.8030357
[309,] -141.7277953 -167.3397712
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 601.0851283 229.0962896
2 -382.8745080 601.0851283
3 -373.1545724 -382.8745080
4 238.1149172 -373.1545724
5 -366.9927782 238.1149172
6 -377.1047243 -366.9927782
7 585.4633473 -377.1047243
8 -77.5710796 585.4633473
9 -379.0081928 -77.5710796
10 -6.6678736 -379.0081928
11 -377.9153656 -6.6678736
12 -375.0216939 -377.9153656
13 -78.4320123 -375.0216939
14 329.5250269 -78.4320123
15 491.0521428 329.5250269
16 -380.8144624 491.0521428
17 -375.5464195 -380.8144624
18 -379.2848355 -375.5464195
19 37.0804325 -379.2848355
20 358.0300572 37.0804325
21 -372.3279082 358.0300572
22 162.3632932 -372.3279082
23 -381.5053310 162.3632932
24 456.8439904 -381.5053310
25 -377.7657863 456.8439904
26 566.7976539 -377.7657863
27 -161.5383527 566.7976539
28 -70.0411355 -161.5383527
29 166.5725739 -70.0411355
30 -377.2333544 166.5725739
31 -100.4614212 -377.2333544
32 259.5549833 -100.4614212
33 65.2433432 259.5549833
34 132.8383337 65.2433432
35 74.3096000 132.8383337
36 372.6489977 74.3096000
37 82.5154227 372.6489977
38 303.7982013 82.5154227
39 -377.5757556 303.7982013
40 169.0878136 -377.5757556
41 90.3095178 169.0878136
42 121.4169531 90.3095178
43 137.6189104 121.4169531
44 173.9865490 137.6189104
45 506.1177699 173.9865490
46 -58.4653444 506.1177699
47 -150.5677616 -58.4653444
48 -41.3872359 -150.5677616
49 -92.7532810 -41.3872359
50 81.4650474 -92.7532810
51 -44.0711496 81.4650474
52 -39.4993396 -44.0711496
53 7.4011537 -39.4993396
54 170.6319148 7.4011537
55 -7.4540979 170.6319148
56 -107.8103744 -7.4540979
57 -192.6197792 -107.8103744
58 185.7699450 -192.6197792
59 -125.3945593 185.7699450
60 -108.0038224 -125.3945593
61 -113.6927297 -108.0038224
62 -188.6593976 -113.6927297
63 -80.7323481 -188.6593976
64 128.0487426 -80.7323481
65 -32.5316102 128.0487426
66 -229.5615332 -32.5316102
67 -158.0773781 -229.5615332
68 -137.8414590 -158.0773781
69 350.6070008 -137.8414590
70 -80.5014895 350.6070008
71 493.9090945 -80.5014895
72 51.1772264 493.9090945
73 -74.6369739 51.1772264
74 143.6240350 -74.6369739
75 261.6465858 143.6240350
76 239.7558367 261.6465858
77 422.5968492 239.7558367
78 -233.6396354 422.5968492
79 604.1675888 -233.6396354
80 -138.9217907 604.1675888
81 -128.4605785 -138.9217907
82 549.6906992 -128.4605785
83 446.3348879 549.6906992
84 -178.0897222 446.3348879
85 144.9487038 -178.0897222
86 -36.4631547 144.9487038
87 222.9425088 -36.4631547
88 -365.6121745 222.9425088
89 113.4638948 -365.6121745
90 -379.7864951 113.4638948
91 144.2382430 -379.7864951
92 43.9950494 144.2382430
93 293.2337146 43.9950494
94 170.2664993 293.2337146
95 -249.4761591 170.2664993
96 414.8037911 -249.4761591
97 102.8021823 414.8037911
98 231.7303266 102.8021823
99 -379.3965119 231.7303266
100 -379.7434644 -379.3965119
101 130.7834968 -379.7434644
102 136.3677638 130.7834968
103 -377.6119989 136.3677638
104 -376.1177080 -377.6119989
105 -376.7441586 -376.1177080
106 412.5855205 -376.7441586
107 -378.7934432 412.5855205
108 -382.4165029 -378.7934432
109 -89.1983986 -382.4165029
110 322.1940962 -89.1983986
111 36.3869967 322.1940962
112 84.5798638 36.3869967
113 177.4944898 84.5798638
114 -217.5519045 177.4944898
115 -57.3754664 -217.5519045
116 -144.2374361 -57.3754664
117 251.4062296 -144.2374361
118 -132.1452527 251.4062296
119 15.4582471 -132.1452527
120 -209.6786305 15.4582471
121 82.9096175 -209.6786305
122 232.9554066 82.9096175
123 -188.4410357 232.9554066
124 -122.1706897 -188.4410357
125 -142.9048631 -122.1706897
126 305.4848611 -142.9048631
127 -223.8794017 305.4848611
128 165.9424600 -223.8794017
129 -97.1231672 165.9424600
130 -381.0938372 -97.1231672
131 -73.2312410 -381.0938372
132 -27.7538285 -73.2312410
133 32.2608760 -27.7538285
134 263.7201750 32.2608760
135 70.9413074 263.7201750
136 284.0284149 70.9413074
137 -207.0779255 284.0284149
138 -184.9710377 -207.0779255
139 65.3451308 -184.9710377
140 -144.8895534 65.3451308
141 -185.2543637 -144.8895534
142 11.4750048 -185.2543637
143 37.8044298 11.4750048
144 -172.8590162 37.8044298
145 -377.5462362 -172.8590162
146 462.7512596 -377.5462362
147 -248.7380048 462.7512596
148 -128.8640921 -248.7380048
149 -99.6135507 -128.8640921
150 56.4119106 -99.6135507
151 -8.6293834 56.4119106
152 -322.8256841 -8.6293834
153 216.7093937 -322.8256841
154 -244.2708260 216.7093937
155 -261.2555498 -244.2708260
156 -208.0242079 -261.2555498
157 -167.6995056 -208.0242079
158 -162.6667209 -167.6995056
159 -325.6842537 -162.6667209
160 -187.5004344 -325.6842537
161 -115.5490762 -187.5004344
162 -115.8726258 -115.5490762
163 -212.0564451 -115.8726258
164 33.6432191 -212.0564451
165 -200.1305483 33.6432191
166 -284.2827112 -200.1305483
167 -231.6871064 -284.2827112
168 -276.9484625 -231.6871064
169 321.0657524 -276.9484625
170 -39.1707141 321.0657524
171 65.2772805 -39.1707141
172 293.8763098 65.2772805
173 531.3519067 293.8763098
174 552.8479713 531.3519067
175 -376.6944946 552.8479713
176 43.7834968 -376.6944946
177 608.5522127 43.7834968
178 438.9214693 608.5522127
179 419.4791801 438.9214693
180 -0.5485288 419.4791801
181 -182.9099389 -0.5485288
182 139.3095178 -182.9099389
183 -323.5715415 139.3095178
184 -100.0898350 -323.5715415
185 -75.9506522 -100.0898350
186 -130.8810774 -75.9506522
187 -375.3809504 -130.8810774
188 -122.0999867 -375.3809504
189 -88.8211557 -122.0999867
190 164.1675066 -88.8211557
191 -117.9766609 164.1675066
192 277.3202747 -117.9766609
193 -380.0863286 277.3202747
194 5.2416431 -380.0863286
195 -56.9268909 5.2416431
196 -66.2679489 -56.9268909
197 576.7948011 -66.2679489
198 -133.8279650 576.7948011
199 -101.9959516 -133.8279650
200 -61.1226197 -101.9959516
201 -4.4150269 -61.1226197
202 73.1205983 -4.4150269
203 -188.7018109 73.1205983
204 -211.2492879 -188.7018109
205 -94.5875419 -211.2492879
206 42.5391262 -94.5875419
207 -173.1446809 42.5391262
208 -87.2222267 -173.1446809
209 -160.1627855 -87.2222267
210 -321.7278197 -160.1627855
211 73.7184415 -321.7278197
212 124.7852213 73.7184415
213 -12.0767485 124.7852213
214 -254.9274717 -12.0767485
215 96.3575878 -254.9274717
216 204.0782093 96.3575878
217 -377.7537424 204.0782093
218 -376.5351542 -377.7537424
219 26.8513137 -376.5351542
220 239.4473900 26.8513137
221 -18.7922942 239.4473900
222 213.0883610 -18.7922942
223 124.0883610 213.0883610
224 -15.7465051 124.0883610
225 65.4854329 -15.7465051
226 186.9226219 65.4854329
227 179.8168867 186.9226219
228 5.6115293 179.8168867
229 189.1693466 5.6115293
230 414.3733871 189.1693466
231 213.0340382 414.3733871
232 -2.8714732 213.0340382
233 286.7563354 -2.8714732
234 -55.0309838 286.7563354
235 259.8689043 -55.0309838
236 116.2167292 259.8689043
237 241.5855205 116.2167292
238 -135.0892298 241.5855205
239 -221.7063393 -135.0892298
240 284.8819087 -221.7063393
241 -197.2628975 284.8819087
242 -131.8161133 -197.2628975
243 -291.1825658 -131.8161133
244 530.9300030 -291.1825658
245 204.3101384 530.9300030
246 -142.3527755 204.3101384
247 17.3190886 -142.3527755
248 190.5272744 17.3190886
249 285.3751450 190.5272744
250 62.0108821 285.3751450
251 26.0295341 62.0108821
252 -379.6324944 26.0295341
253 -152.2126134 -379.6324944
254 -23.1209197 -152.2126134
255 105.7388026 -23.1209197
256 328.3468309 105.7388026
257 267.6889991 328.3468309
258 -212.3047968 267.6889991
259 -63.7589043 -212.3047968
260 -149.5241957 -63.7589043
261 -70.2951347 -149.5241957
262 203.9271747 -70.2951347
263 -17.3879233 203.9271747
264 -170.6497690 -17.3879233
265 -168.5196673 -170.6497690
266 87.1188648 -168.5196673
267 -94.9195675 87.1188648
268 -200.1667665 -94.9195675
269 52.7297792 -200.1667665
270 349.2688046 52.7297792
271 -80.6039221 349.2688046
272 -121.4489977 -80.6039221
273 -169.8392359 -121.4489977
274 -226.3342057 -169.8392359
275 -192.5659794 -226.3342057
276 -131.5733849 -192.5659794
277 -76.0019391 -131.5733849
278 -142.7272723 -76.0019391
279 119.0646575 -142.7272723
280 -72.9388004 119.0646575
281 96.2478138 -72.9388004
282 205.0651472 96.2478138
283 -44.3562335 205.0651472
284 476.4854086 -44.3562335
285 4.3406602 476.4854086
286 327.8767750 4.3406602
287 -36.1039343 327.8767750
288 68.9220745 -36.1039343
289 -29.0117509 68.9220745
290 165.8434429 -29.0117509
291 61.7252508 165.8434429
292 353.6636046 61.7252508
293 -233.3951645 353.6636046
294 -121.8205839 -233.3951645
295 332.6172103 -121.8205839
296 -95.4212554 332.6172103
297 281.4514712 -95.4212554
298 -115.1650330 281.4514712
299 -83.1921945 -115.1650330
300 20.1466070 -83.1921945
301 -13.8663973 20.1466070
302 -38.3166151 -13.8663973
303 152.1381798 -38.3166151
304 -160.5456761 152.1381798
305 -59.6649965 -160.5456761
306 212.9317031 -59.6649965
307 -88.8030357 212.9317031
308 -167.3397712 -88.8030357
309 -141.7277953 -167.3397712
> 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/7r1qa1321909558.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/8ztav1321909558.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/9zboh1321909558.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/10617x1321909558.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/115vai1321909558.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/120q9d1321909558.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13yxjm1321909558.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14bqd21321909558.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/15s3dr1321909558.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/16wnmw1321909558.tab")
+ }
>
> try(system("convert tmp/1w61s1321909558.ps tmp/1w61s1321909558.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hudq1321909558.ps tmp/2hudq1321909558.png",intern=TRUE))
character(0)
> try(system("convert tmp/3r4nc1321909558.ps tmp/3r4nc1321909558.png",intern=TRUE))
character(0)
> try(system("convert tmp/4c5gr1321909558.ps tmp/4c5gr1321909558.png",intern=TRUE))
character(0)
> try(system("convert tmp/5c8o61321909558.ps tmp/5c8o61321909558.png",intern=TRUE))
character(0)
> try(system("convert tmp/6nd6q1321909558.ps tmp/6nd6q1321909558.png",intern=TRUE))
character(0)
> try(system("convert tmp/7r1qa1321909558.ps tmp/7r1qa1321909558.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ztav1321909558.ps tmp/8ztav1321909558.png",intern=TRUE))
character(0)
> try(system("convert tmp/9zboh1321909558.ps tmp/9zboh1321909558.png",intern=TRUE))
character(0)
> try(system("convert tmp/10617x1321909558.ps tmp/10617x1321909558.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
8.161 0.543 8.799