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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+ ,46
+ ,0
+ ,28
+ ,15
+ ,894
+ ,72535
+ ,329
+ ,44
+ ,0
+ ,17
+ ,16)
+ ,dim=c(7
+ ,289)
+ ,dimnames=list(c('pageviews'
+ ,'time'
+ ,'compinfo'
+ ,'comppr'
+ ,'sharedcomp'
+ ,'bloggedcomp'
+ ,'compreviewed')
+ ,1:289))
> y <- array(NA,dim=c(7,289),dimnames=list(c('pageviews','time','compinfo','comppr','sharedcomp','bloggedcomp','compreviewed'),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 = '5'
> 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
sharedcomp pageviews time compinfo comppr bloggedcomp compreviewed
1 3 1418 210907 396 81 79 30
2 4 869 120982 297 55 58 28
3 12 1530 176508 559 50 60 38
4 2 2172 179321 967 125 108 30
5 1 901 123185 270 40 49 22
6 3 463 52746 143 37 0 26
7 0 3201 385534 1562 63 121 25
8 0 371 33170 109 44 1 18
9 0 1192 101645 371 88 20 11
10 5 1583 149061 656 66 43 26
11 0 1439 165446 511 57 69 25
12 0 1764 237213 655 74 78 38
13 7 1495 173326 465 49 86 44
14 7 1373 133131 525 52 44 30
15 3 2187 258873 885 88 104 40
16 9 1491 180083 497 36 63 34
17 0 4041 324799 1436 108 158 47
18 4 1706 230964 612 43 102 30
19 3 2152 236785 865 75 77 31
20 0 1036 135473 385 32 82 23
21 7 1882 202925 567 44 115 36
22 0 1929 215147 639 85 101 36
23 1 2242 344297 963 86 80 30
24 5 1220 153935 398 56 50 25
25 7 1289 132943 410 50 83 39
26 0 2515 174724 966 135 123 34
27 0 2147 174415 801 63 73 31
28 5 2352 225548 892 81 81 31
29 0 1638 223632 513 52 105 33
30 0 1222 124817 469 44 47 25
31 0 1812 221698 683 113 105 33
32 3 1677 210767 643 39 94 35
33 4 1579 170266 535 73 44 42
34 1 1731 260561 625 48 114 43
35 4 807 84853 264 33 38 30
36 2 2452 294424 992 59 107 33
37 0 829 101011 238 41 30 13
38 0 1940 215641 818 69 71 32
39 0 2662 325107 937 64 84 36
40 0 186 7176 70 1 0 0
41 2 1499 167542 507 59 59 28
42 1 865 106408 260 32 33 14
43 0 1793 96560 503 129 42 17
44 2 2527 265769 927 37 96 32
45 10 2747 269651 1269 31 106 30
46 6 1324 149112 537 65 56 35
47 0 2702 175824 910 107 57 20
48 5 1383 152871 532 74 59 28
49 4 1179 111665 345 54 39 28
50 1 2099 116408 918 76 34 39
51 2 4308 362301 1635 715 76 34
52 2 918 78800 330 57 20 26
53 0 1831 183167 557 66 91 39
54 8 3373 277965 1178 106 115 39
55 3 1713 150629 740 54 85 33
56 0 1438 168809 452 32 76 28
57 0 496 24188 218 20 8 4
58 8 2253 329267 764 71 79 39
59 5 744 65029 255 21 21 18
60 3 1161 101097 454 70 30 14
61 1 2352 218946 866 112 76 29
62 5 2144 244052 574 66 101 44
63 1 4691 341570 1276 190 94 21
64 1 1112 103597 379 66 27 16
65 5 2694 233328 825 165 92 28
66 0 1973 256462 798 56 123 35
67 12 1769 206161 663 61 75 28
68 8 3148 311473 1069 53 128 38
69 8 2474 235800 921 127 105 23
70 8 2084 177939 858 63 55 36
71 8 1954 207176 711 38 56 32
72 2 1226 196553 503 50 41 29
73 0 1389 174184 382 52 72 25
74 5 1496 143246 464 42 67 27
75 8 2269 187559 717 76 75 36
76 2 1833 187681 690 67 114 28
77 5 1268 119016 462 50 118 23
78 12 1943 182192 657 53 77 40
79 6 893 73566 385 39 22 23
80 7 1762 194979 577 50 66 40
81 2 1403 167488 619 77 69 28
82 0 1425 143756 479 57 105 34
83 4 1857 275541 817 73 116 33
84 3 1840 243199 752 34 88 28
85 6 1502 182999 430 39 73 34
86 2 1441 135649 451 46 99 30
87 0 1420 152299 537 63 62 33
88 1 1416 120221 519 35 53 22
89 0 2970 346485 1000 106 118 38
90 5 1317 145790 637 43 30 26
91 2 1644 193339 465 47 100 35
92 0 870 80953 437 31 49 8
93 0 1654 122774 711 162 24 24
94 5 1054 130585 299 57 67 29
95 0 937 112611 248 36 46 20
96 1 3004 286468 1162 263 57 29
97 0 2008 241066 714 78 75 45
98 1 2547 148446 905 63 135 37
99 1 1885 204713 649 54 68 33
100 2 1626 182079 512 63 124 33
101 6 1468 140344 472 77 33 25
102 1 2445 220516 905 79 98 32
103 4 1964 243060 786 110 58 29
104 2 1381 162765 489 56 68 28
105 3 1369 182613 479 56 81 28
106 0 1659 232138 617 43 131 31
107 10 2888 265318 925 111 110 52
108 0 1290 85574 351 71 37 21
109 9 2845 310839 1144 62 130 24
110 7 1982 225060 669 56 93 41
111 0 1904 232317 707 74 118 33
112 0 1391 144966 458 60 39 32
113 4 602 43287 214 43 13 19
114 4 1743 155754 599 68 74 20
115 0 1559 164709 572 53 81 31
116 0 2014 201940 897 87 109 31
117 0 2143 235454 819 46 151 32
118 1 2146 220801 720 105 51 18
119 0 874 99466 273 32 28 23
120 1 1590 92661 508 133 40 17
121 0 1590 133328 506 79 56 20
122 0 1210 61361 451 51 27 12
123 4 2072 125930 699 207 37 17
124 0 1281 100750 407 67 83 30
125 4 1401 224549 465 47 54 31
126 4 834 82316 245 34 27 10
127 3 1105 102010 370 66 28 13
128 0 1272 101523 316 76 59 22
129 0 1944 243511 603 65 133 42
130 0 391 22938 154 9 12 1
131 5 761 41566 229 42 0 9
132 0 1605 152474 577 45 106 32
133 4 530 61857 192 25 23 11
134 0 1988 99923 617 115 44 25
135 0 1386 132487 411 97 71 36
136 1 2395 317394 975 53 116 31
137 0 387 21054 146 2 4 0
138 5 1742 209641 705 52 62 24
139 0 620 22648 184 44 12 13
140 0 449 31414 200 22 18 8
141 0 800 46698 274 35 14 13
142 0 1684 131698 502 74 60 19
143 0 1050 91735 382 103 7 18
144 2 2699 244749 964 144 98 33
145 7 1606 184510 537 60 64 40
146 1 1502 79863 438 134 29 22
147 8 1204 128423 369 89 32 38
148 2 1138 97839 417 42 25 24
149 0 568 38214 276 52 16 8
150 2 1459 151101 514 98 48 35
151 0 2158 272458 822 99 100 43
152 0 1111 172494 389 52 46 43
153 1 1421 108043 466 29 45 14
154 3 2833 328107 1255 125 129 41
155 0 1955 250579 694 106 130 38
156 3 2922 351067 1024 95 136 45
157 0 1002 158015 400 40 59 31
158 0 1060 98866 397 140 25 13
159 0 956 85439 350 43 32 28
160 4 2186 229242 719 128 63 31
161 4 3604 351619 1277 142 95 40
162 11 1035 84207 356 73 14 30
163 0 1417 120445 457 72 36 16
164 0 3261 324598 1402 128 113 37
165 4 1587 131069 600 61 47 30
166 0 1424 204271 480 73 92 35
167 1 1701 165543 595 148 70 32
168 0 1249 141722 436 64 19 27
169 0 946 116048 230 45 50 20
170 0 1926 250047 651 58 41 18
171 9 3352 299775 1367 97 91 31
172 1 1641 195838 564 50 111 31
173 3 2035 173260 716 37 41 21
174 10 2312 254488 747 50 120 39
175 5 1369 104389 467 105 135 41
176 0 1577 136084 671 69 27 13
177 2 2201 199476 861 46 87 32
178 0 961 92499 319 57 25 18
179 1 1900 224330 612 52 131 39
180 2 1254 135781 433 98 45 14
181 4 1335 74408 434 61 29 7
182 0 1597 81240 503 89 58 17
183 0 207 14688 85 0 4 0
184 2 1645 181633 564 48 47 30
185 1 2429 271856 824 91 109 37
186 0 151 7199 74 0 7 0
187 0 474 46660 259 7 12 5
188 0 141 17547 69 3 0 1
189 1 1639 133368 535 54 37 16
190 0 872 95227 239 70 37 32
191 2 1318 152601 438 36 46 24
192 0 1018 98146 459 37 15 17
193 3 1383 79619 426 123 42 11
194 6 1314 59194 288 247 7 24
195 0 1335 139942 498 46 54 22
196 2 1403 118612 454 72 54 12
197 0 910 72880 376 41 14 19
198 2 616 65475 225 24 16 13
199 1 1407 99643 555 45 33 17
200 1 771 71965 252 33 32 15
201 2 766 77272 208 27 21 16
202 1 473 49289 130 36 15 24
203 0 1376 135131 481 87 38 15
204 1 1232 108446 389 90 22 17
205 3 1521 89746 565 114 28 18
206 0 572 44296 173 31 10 20
207 0 1059 77648 278 45 31 16
208 0 1544 181528 609 69 32 16
209 0 1230 134019 422 51 32 18
210 1 1206 124064 445 34 43 22
211 4 1205 92630 387 60 27 8
212 0 1255 121848 339 45 37 17
213 0 613 52915 181 54 20 18
214 0 721 81872 245 25 32 16
215 7 1109 58981 384 38 0 23
216 2 740 53515 212 52 5 22
217 0 1126 60812 399 67 26 13
218 7 728 56375 229 74 10 13
219 3 689 65490 224 38 27 16
220 0 592 80949 203 30 11 16
221 0 995 76302 333 26 29 20
222 6 1613 104011 384 67 25 22
223 2 2048 98104 636 132 55 17
224 0 705 67989 185 42 23 18
225 0 301 30989 93 35 5 17
226 3 1803 135458 581 118 43 12
227 0 799 73504 248 68 23 7
228 1 861 63123 304 43 34 17
229 1 1186 61254 344 76 36 14
230 0 1451 74914 407 64 35 23
231 1 628 31774 170 48 0 17
232 0 1161 81437 312 64 37 14
233 0 1463 87186 507 56 28 15
234 0 742 50090 224 71 16 17
235 0 979 65745 340 75 26 21
236 0 675 56653 168 39 38 18
237 0 1241 158399 443 42 23 18
238 0 676 46455 204 39 22 17
239 0 1049 73624 367 93 30 17
240 0 620 38395 210 38 16 16
241 0 1081 91899 335 60 18 15
242 0 1688 139526 364 71 28 21
243 0 736 52164 178 52 32 16
244 2 617 51567 206 27 21 14
245 0 812 70551 279 59 23 15
246 1 1051 84856 387 40 29 17
247 1 1656 102538 490 79 50 15
248 0 705 86678 238 44 12 15
249 0 945 85709 343 65 21 10
250 0 554 34662 232 10 18 6
251 0 1597 150580 530 124 27 22
252 0 982 99611 291 81 41 21
253 0 222 19349 67 15 13 1
254 1 1212 99373 397 92 12 18
255 0 1143 86230 467 42 21 17
256 0 435 30837 178 10 8 4
257 0 532 31706 175 24 26 10
258 0 882 89806 299 64 27 16
259 1 608 62088 154 45 13 16
260 0 459 40151 106 22 16 9
261 0 578 27634 189 56 2 16
262 0 826 76990 194 94 42 17
263 0 509 37460 135 19 5 7
264 0 717 54157 201 35 37 15
265 0 637 49862 207 32 17 14
266 0 857 84337 280 35 38 14
267 0 830 64175 260 48 37 18
268 0 652 59382 227 49 29 12
269 0 707 119308 239 48 32 16
270 0 954 76702 333 62 35 21
271 1 1461 103425 428 96 17 19
272 0 672 70344 230 45 20 16
273 0 778 43410 292 63 7 1
274 1 1141 104838 350 71 46 16
275 0 680 62215 186 26 24 10
276 6 1090 69304 326 48 40 19
277 3 616 53117 155 29 3 12
278 1 285 19764 75 19 10 2
279 2 1145 86680 361 45 37 14
280 0 733 84105 261 45 17 17
281 0 888 77945 299 67 28 19
282 0 849 89113 300 30 19 14
283 3 1182 91005 450 36 29 11
284 1 528 40248 183 34 8 4
285 0 642 64187 238 36 10 16
286 0 947 50857 165 34 15 20
287 1 819 56613 234 37 15 12
288 0 757 62792 176 46 28 15
289 0 894 72535 329 44 17 16
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) pageviews time compinfo comppr
-7.916e-01 1.462e-03 -4.226e-06 3.084e-04 -9.476e-03
bloggedcomp compreviewed
-2.296e-02 1.257e-01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-5.4472 -1.5357 -0.6333 1.2963 9.6507
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -7.916e-01 3.938e-01 -2.010 0.04534 *
pageviews 1.462e-03 8.270e-04 1.769 0.07806 .
time -4.226e-06 5.097e-06 -0.829 0.40779
compinfo 3.084e-04 1.982e-03 0.156 0.87642
comppr -9.476e-03 3.664e-03 -2.586 0.01020 *
bloggedcomp -2.296e-02 7.972e-03 -2.880 0.00429 **
compreviewed 1.257e-01 2.312e-02 5.437 1.17e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.48 on 282 degrees of freedom
Multiple R-squared: 0.1932, Adjusted R-squared: 0.1761
F-statistic: 11.26 on 6 and 282 DF, p-value: 2.852e-11
> 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,] 0.3174819 6.349637e-01 6.825181e-01
[2,] 0.4642394 9.284788e-01 5.357606e-01
[3,] 0.8850967 2.298065e-01 1.149033e-01
[4,] 0.8895601 2.208798e-01 1.104399e-01
[5,] 0.8444818 3.110363e-01 1.555182e-01
[6,] 0.7924622 4.150756e-01 2.075378e-01
[7,] 0.7627074 4.745853e-01 2.372926e-01
[8,] 0.9625009 7.499812e-02 3.749906e-02
[9,] 0.9479151 1.041698e-01 5.208490e-02
[10,] 0.9232768 1.534463e-01 7.672316e-02
[11,] 0.9095827 1.808346e-01 9.041729e-02
[12,] 0.9248479 1.503042e-01 7.515208e-02
[13,] 0.9239473 1.521054e-01 7.605268e-02
[14,] 0.8962905 2.074190e-01 1.037095e-01
[15,] 0.8922273 2.155454e-01 1.077727e-01
[16,] 0.8684120 2.631760e-01 1.315880e-01
[17,] 0.8352634 3.294731e-01 1.647366e-01
[18,] 0.8662945 2.674110e-01 1.337055e-01
[19,] 0.8721058 2.557883e-01 1.278942e-01
[20,] 0.8767729 2.464543e-01 1.232271e-01
[21,] 0.8959756 2.080489e-01 1.040244e-01
[22,] 0.8702905 2.594189e-01 1.297095e-01
[23,] 0.8481469 3.037062e-01 1.518531e-01
[24,] 0.8525679 2.948642e-01 1.474321e-01
[25,] 0.8838696 2.322608e-01 1.161304e-01
[26,] 0.8621229 2.757541e-01 1.378771e-01
[27,] 0.8313435 3.373129e-01 1.686565e-01
[28,] 0.7974283 4.051434e-01 2.025717e-01
[29,] 0.8144564 3.710872e-01 1.855436e-01
[30,] 0.8242368 3.515265e-01 1.757632e-01
[31,] 0.7896515 4.206971e-01 2.103485e-01
[32,] 0.7517846 4.964307e-01 2.482154e-01
[33,] 0.7098829 5.802341e-01 2.901171e-01
[34,] 0.6807591 6.384818e-01 3.192409e-01
[35,] 0.6412822 7.174357e-01 3.587178e-01
[36,] 0.8337282 3.325435e-01 1.662718e-01
[37,] 0.8170804 3.658392e-01 1.829196e-01
[38,] 0.7956384 4.087233e-01 2.043616e-01
[39,] 0.7987429 4.025142e-01 2.012571e-01
[40,] 0.7676554 4.646891e-01 2.323446e-01
[41,] 0.8847691 2.304619e-01 1.152309e-01
[42,] 0.9470375 1.059251e-01 5.296253e-02
[43,] 0.9381975 1.236050e-01 6.180251e-02
[44,] 0.9469201 1.061598e-01 5.307989e-02
[45,] 0.9742630 5.147393e-02 2.573697e-02
[46,] 0.9672236 6.555284e-02 3.277642e-02
[47,] 0.9645318 7.093631e-02 3.546816e-02
[48,] 0.9552913 8.941730e-02 4.470865e-02
[49,] 0.9690095 6.198105e-02 3.099052e-02
[50,] 0.9717701 5.645988e-02 2.822994e-02
[51,] 0.9686389 6.272221e-02 3.136111e-02
[52,] 0.9634365 7.312696e-02 3.656348e-02
[53,] 0.9557722 8.845560e-02 4.422780e-02
[54,] 0.9568248 8.635047e-02 4.317523e-02
[55,] 0.9468882 1.062237e-01 5.311185e-02
[56,] 0.9526418 9.471637e-02 4.735819e-02
[57,] 0.9499444 1.001112e-01 5.005560e-02
[58,] 0.9981812 3.637641e-03 1.818820e-03
[59,] 0.9989080 2.184078e-03 1.092039e-03
[60,] 0.9998445 3.109655e-04 1.554827e-04
[61,] 0.9998826 2.347131e-04 1.173565e-04
[62,] 0.9999279 1.441646e-04 7.208231e-05
[63,] 0.9999060 1.879650e-04 9.398248e-05
[64,] 0.9998880 2.239625e-04 1.119813e-04
[65,] 0.9998816 2.367613e-04 1.183807e-04
[66,] 0.9999205 1.590944e-04 7.954720e-05
[67,] 0.9998856 2.288292e-04 1.144146e-04
[68,] 0.9999433 1.134546e-04 5.672731e-05
[69,] 0.9999974 5.222376e-06 2.611188e-06
[70,] 0.9999982 3.590483e-06 1.795241e-06
[71,] 0.9999984 3.257718e-06 1.628859e-06
[72,] 0.9999976 4.844233e-06 2.422116e-06
[73,] 0.9999976 4.832109e-06 2.416054e-06
[74,] 0.9999975 5.086918e-06 2.543459e-06
[75,] 0.9999963 7.321678e-06 3.660839e-06
[76,] 0.9999969 6.247179e-06 3.123590e-06
[77,] 0.9999954 9.242138e-06 4.621069e-06
[78,] 0.9999965 7.056616e-06 3.528308e-06
[79,] 0.9999952 9.601749e-06 4.800875e-06
[80,] 0.9999967 6.654290e-06 3.327145e-06
[81,] 0.9999965 6.900073e-06 3.450036e-06
[82,] 0.9999951 9.847530e-06 4.923765e-06
[83,] 0.9999926 1.477459e-05 7.387295e-06
[84,] 0.9999926 1.470290e-05 7.351448e-06
[85,] 0.9999942 1.164895e-05 5.824474e-06
[86,] 0.9999926 1.484238e-05 7.421191e-06
[87,] 0.9999914 1.718828e-05 8.594141e-06
[88,] 0.9999967 6.643607e-06 3.321803e-06
[89,] 0.9999966 6.788278e-06 3.394139e-06
[90,] 0.9999965 7.064030e-06 3.532015e-06
[91,] 0.9999949 1.028444e-05 5.142218e-06
[92,] 0.9999963 7.432148e-06 3.716074e-06
[93,] 0.9999958 8.355228e-06 4.177614e-06
[94,] 0.9999947 1.069897e-05 5.349487e-06
[95,] 0.9999923 1.542569e-05 7.712847e-06
[96,] 0.9999903 1.945733e-05 9.728665e-06
[97,] 0.9999869 2.616735e-05 1.308368e-05
[98,] 0.9999955 9.090018e-06 4.545009e-06
[99,] 0.9999950 9.916922e-06 4.958461e-06
[100,] 0.9999999 2.804670e-07 1.402335e-07
[101,] 0.9999999 1.373642e-07 6.868212e-08
[102,] 0.9999999 1.726153e-07 8.630765e-08
[103,] 0.9999999 1.220646e-07 6.103229e-08
[104,] 0.9999999 1.190634e-07 5.953170e-08
[105,] 0.9999999 1.103249e-07 5.516247e-08
[106,] 0.9999999 1.170885e-07 5.854423e-08
[107,] 0.9999999 1.431462e-07 7.157312e-08
[108,] 0.9999999 2.013283e-07 1.006642e-07
[109,] 0.9999999 2.985147e-07 1.492574e-07
[110,] 0.9999998 3.385653e-07 1.692827e-07
[111,] 0.9999997 5.114395e-07 2.557197e-07
[112,] 0.9999997 6.439156e-07 3.219578e-07
[113,] 0.9999996 8.595481e-07 4.297741e-07
[114,] 0.9999995 9.311618e-07 4.655809e-07
[115,] 0.9999994 1.115645e-06 5.578225e-07
[116,] 0.9999994 1.167421e-06 5.837105e-07
[117,] 0.9999996 7.075792e-07 3.537896e-07
[118,] 0.9999996 7.952160e-07 3.976080e-07
[119,] 0.9999995 1.036052e-06 5.180262e-07
[120,] 0.9999995 1.092242e-06 5.461212e-07
[121,] 0.9999992 1.667137e-06 8.335683e-07
[122,] 0.9999996 8.267201e-07 4.133600e-07
[123,] 0.9999995 9.409346e-07 4.704673e-07
[124,] 0.9999998 4.915995e-07 2.457998e-07
[125,] 0.9999999 2.813626e-07 1.406813e-07
[126,] 0.9999999 2.497371e-07 1.248685e-07
[127,] 0.9999998 3.599573e-07 1.799786e-07
[128,] 0.9999997 5.495967e-07 2.747983e-07
[129,] 0.9999998 3.083378e-07 1.541689e-07
[130,] 0.9999998 4.216351e-07 2.108176e-07
[131,] 0.9999997 6.459722e-07 3.229861e-07
[132,] 0.9999996 8.561355e-07 4.280677e-07
[133,] 0.9999995 1.000116e-06 5.000579e-07
[134,] 0.9999994 1.235354e-06 6.176770e-07
[135,] 0.9999991 1.726144e-06 8.630718e-07
[136,] 0.9999996 7.554366e-07 3.777183e-07
[137,] 0.9999996 8.915540e-07 4.457770e-07
[138,] 0.9999999 1.406956e-07 7.034782e-08
[139,] 0.9999999 2.141525e-07 1.070763e-07
[140,] 0.9999998 3.378611e-07 1.689306e-07
[141,] 0.9999998 4.874814e-07 2.437407e-07
[142,] 0.9999998 4.025630e-07 2.012815e-07
[143,] 0.9999998 3.001256e-07 1.500628e-07
[144,] 0.9999998 4.605754e-07 2.302877e-07
[145,] 0.9999997 6.964811e-07 3.482405e-07
[146,] 0.9999995 9.111947e-07 4.555973e-07
[147,] 0.9999993 1.381511e-06 6.907555e-07
[148,] 0.9999991 1.752933e-06 8.764663e-07
[149,] 0.9999987 2.651545e-06 1.325772e-06
[150,] 0.9999987 2.678041e-06 1.339020e-06
[151,] 0.9999983 3.398294e-06 1.699147e-06
[152,] 0.9999975 5.068846e-06 2.534423e-06
[153,] 1.0000000 5.906303e-09 2.953151e-09
[154,] 1.0000000 7.655521e-09 3.827760e-09
[155,] 1.0000000 2.435396e-09 1.217698e-09
[156,] 1.0000000 3.391829e-09 1.695915e-09
[157,] 1.0000000 4.675401e-09 2.337701e-09
[158,] 1.0000000 6.616507e-09 3.308254e-09
[159,] 1.0000000 7.235814e-09 3.617907e-09
[160,] 1.0000000 1.147907e-08 5.739533e-09
[161,] 1.0000000 1.522014e-08 7.610069e-09
[162,] 1.0000000 1.486569e-09 7.432847e-10
[163,] 1.0000000 2.462357e-09 1.231179e-09
[164,] 1.0000000 3.836306e-09 1.918153e-09
[165,] 1.0000000 7.909958e-13 3.954979e-13
[166,] 1.0000000 1.480357e-13 7.401786e-14
[167,] 1.0000000 2.161754e-13 1.080877e-13
[168,] 1.0000000 3.439643e-13 1.719821e-13
[169,] 1.0000000 5.791684e-13 2.895842e-13
[170,] 1.0000000 6.290355e-13 3.145177e-13
[171,] 1.0000000 8.543336e-13 4.271668e-13
[172,] 1.0000000 5.441662e-13 2.720831e-13
[173,] 1.0000000 6.842393e-13 3.421196e-13
[174,] 1.0000000 1.389909e-12 6.949546e-13
[175,] 1.0000000 1.954189e-12 9.770947e-13
[176,] 1.0000000 2.652698e-12 1.326349e-12
[177,] 1.0000000 5.321983e-12 2.660991e-12
[178,] 1.0000000 1.051373e-11 5.256864e-12
[179,] 1.0000000 2.076277e-11 1.038138e-11
[180,] 1.0000000 3.890506e-11 1.945253e-11
[181,] 1.0000000 6.076975e-11 3.038488e-11
[182,] 1.0000000 5.813259e-11 2.906630e-11
[183,] 1.0000000 9.602032e-11 4.801016e-11
[184,] 1.0000000 1.288765e-10 6.443826e-11
[185,] 1.0000000 4.526147e-11 2.263074e-11
[186,] 1.0000000 8.200097e-11 4.100048e-11
[187,] 1.0000000 1.062751e-10 5.313754e-11
[188,] 1.0000000 1.498430e-10 7.492149e-11
[189,] 1.0000000 1.986385e-10 9.931924e-11
[190,] 1.0000000 3.587547e-10 1.793774e-10
[191,] 1.0000000 6.346174e-10 3.173087e-10
[192,] 1.0000000 8.794041e-10 4.397021e-10
[193,] 1.0000000 1.503513e-09 7.517563e-10
[194,] 1.0000000 2.709837e-09 1.354919e-09
[195,] 1.0000000 5.068682e-09 2.534341e-09
[196,] 1.0000000 7.654114e-09 3.827057e-09
[197,] 1.0000000 1.172747e-08 5.863733e-09
[198,] 1.0000000 1.781328e-08 8.906642e-09
[199,] 1.0000000 3.072150e-08 1.536075e-08
[200,] 1.0000000 5.130844e-08 2.565422e-08
[201,] 1.0000000 8.704214e-08 4.352107e-08
[202,] 1.0000000 4.008897e-08 2.004449e-08
[203,] 1.0000000 6.614719e-08 3.307359e-08
[204,] 0.9999999 1.142439e-07 5.712197e-08
[205,] 0.9999999 2.029813e-07 1.014907e-07
[206,] 1.0000000 7.396937e-09 3.698468e-09
[207,] 1.0000000 1.093702e-08 5.468511e-09
[208,] 1.0000000 1.717582e-08 8.587909e-09
[209,] 1.0000000 1.412275e-12 7.061373e-13
[210,] 1.0000000 3.305502e-13 1.652751e-13
[211,] 1.0000000 7.726329e-13 3.863164e-13
[212,] 1.0000000 1.340412e-12 6.702061e-13
[213,] 1.0000000 3.670693e-15 1.835347e-15
[214,] 1.0000000 9.978786e-15 4.989393e-15
[215,] 1.0000000 2.565271e-14 1.282636e-14
[216,] 1.0000000 6.415552e-14 3.207776e-14
[217,] 1.0000000 3.060710e-14 1.530355e-14
[218,] 1.0000000 8.319744e-14 4.159872e-14
[219,] 1.0000000 2.119591e-13 1.059795e-13
[220,] 1.0000000 5.533795e-13 2.766898e-13
[221,] 1.0000000 7.177489e-13 3.588745e-13
[222,] 1.0000000 1.544460e-12 7.722301e-13
[223,] 1.0000000 3.108636e-12 1.554318e-12
[224,] 1.0000000 3.147692e-12 1.573846e-12
[225,] 1.0000000 8.125883e-12 4.062941e-12
[226,] 1.0000000 1.877350e-11 9.386752e-12
[227,] 1.0000000 4.395879e-11 2.197940e-11
[228,] 1.0000000 1.031861e-10 5.159305e-11
[229,] 1.0000000 2.315541e-10 1.157771e-10
[230,] 1.0000000 5.512359e-10 2.756180e-10
[231,] 1.0000000 1.208549e-09 6.042747e-10
[232,] 1.0000000 2.637650e-09 1.318825e-09
[233,] 1.0000000 2.576242e-09 1.288121e-09
[234,] 1.0000000 5.742371e-09 2.871185e-09
[235,] 1.0000000 6.287976e-09 3.143988e-09
[236,] 1.0000000 1.529771e-08 7.648857e-09
[237,] 1.0000000 3.733693e-08 1.866846e-08
[238,] 1.0000000 4.379883e-08 2.189941e-08
[239,] 0.9999999 1.040940e-07 5.204701e-08
[240,] 0.9999999 2.367715e-07 1.183857e-07
[241,] 0.9999998 4.665874e-07 2.332937e-07
[242,] 0.9999995 9.232447e-07 4.616223e-07
[243,] 0.9999990 2.090657e-06 1.045329e-06
[244,] 0.9999976 4.751795e-06 2.375898e-06
[245,] 0.9999950 1.008205e-05 5.041025e-06
[246,] 0.9999933 1.338994e-05 6.694968e-06
[247,] 0.9999864 2.711960e-05 1.355980e-05
[248,] 0.9999744 5.125713e-05 2.562856e-05
[249,] 0.9999456 1.088022e-04 5.440112e-05
[250,] 0.9999232 1.536655e-04 7.683274e-05
[251,] 0.9998411 3.178322e-04 1.589161e-04
[252,] 0.9996837 6.325356e-04 3.162678e-04
[253,] 0.9994278 1.144460e-03 5.722300e-04
[254,] 0.9989604 2.079274e-03 1.039637e-03
[255,] 0.9983261 3.347784e-03 1.673892e-03
[256,] 0.9970226 5.954808e-03 2.977404e-03
[257,] 0.9960124 7.975177e-03 3.987589e-03
[258,] 0.9941087 1.178254e-02 5.891272e-03
[259,] 0.9896120 2.077600e-02 1.038800e-02
[260,] 0.9847432 3.051356e-02 1.525678e-02
[261,] 0.9804233 3.915330e-02 1.957665e-02
[262,] 0.9730544 5.389128e-02 2.694564e-02
[263,] 0.9524812 9.503770e-02 4.751885e-02
[264,] 0.9225485 1.549029e-01 7.745147e-02
[265,] 0.8771903 2.456195e-01 1.228097e-01
[266,] 0.8288572 3.422855e-01 1.711428e-01
[267,] 0.9837386 3.252278e-02 1.626139e-02
[268,] 0.9991619 1.676167e-03 8.380836e-04
[269,] 0.9955961 8.807814e-03 4.403907e-03
[270,] 0.9787626 4.247473e-02 2.123736e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1609x1354894070.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/2sw471354894070.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3lfpe1354894070.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4xyxf1354894070.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5nzki1354894070.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 6
1.296319932 2.272755534 8.201172592 -0.033315289 -0.350816690 0.375110740
7 8 9 10 11 12
-2.510829777 -1.467501359 -0.726484553 2.247804763 -1.790343373 -3.273500923
13 14 15 16 17 18
3.100945947 3.915414019 -0.393472150 5.731531921 -5.447221145 2.061141807
19 20 21 22 23 24
-0.040948287 -0.975785805 4.252701159 -2.719451856 -1.449652353 3.070515490
25 26 27 28 29 30
3.817760344 -2.617860058 -3.482994313 1.759421106 -2.062871302 -2.259936443
31 32 33 34 35 36
-1.799899019 0.158477855 -0.541696950 -2.165908319 1.301894302 -0.989690594
37 38 39 40 41 42
-0.624527229 -3.126067488 -4.007967179 0.537824778 -0.455778236 0.196701757
43 44 45 46 47 48
-1.528427594 -1.535688631 6.477629397 2.820954262 -2.889730952 2.786309233
49 50 51 52 53 54
1.319566152 -4.471877144 1.763504940 -0.589261662 -3.472752277 3.411122663
55 56 57 58 59 60
0.008769574 -2.209856914 -0.028505116 4.235517983 3.317747100 1.972754213
61 62 63 64 65 66
-1.830026669 0.922470252 -2.700950636 -0.280105516 2.738480008 -2.302315258
67 68 69 70 71 72
9.650672601 3.837307092 6.608009588 3.564631990 4.212585404 -0.556905816
73 74 75 76 77 78
-1.619019691 2.607477041 3.960520638 0.422792144 4.588608604 7.758186770
79 80 81 82 83 84
3.660727354 2.820664149 0.049981231 -2.156748908 2.193948602 0.718464805
85 86 87 88 89 90
3.006419822 0.055146746 -2.935749095 -1.148886168 -3.460451010 2.112485687
91 92 93 94 95 96
-0.598458850 0.139387236 -2.259071652 3.141989021 -1.296690842 -1.594785628
97 98 99 100 101 102
-4.543290368 -2.540879928 -2.376418732 0.319796784 3.436311034 -2.156289697
103 104 105 106 107 108
1.431837630 -0.119663479 1.283270267 -1.326703155 4.443227378 -1.959629147
109 110 111 112 113 114
7.145953619 3.148597573 -1.968126232 -3.330649780 2.345299499 2.544593085
115 116 117 118 119 120
-2.504544346 -2.147934151 -1.721019173 -0.733160491 -2.096092497 -0.257565421
121 122 123 124 125 126
-1.606694208 -1.263367823 2.751562712 -2.013049221 1.335733189 3.528968500
127 128 129 130 131 132
2.126326706 -1.428424030 -2.819701336 0.504268532 4.050190438 -2.252698532
133 134 135 136 137 138
3.600627392 -2.927105592 -2.779254004 -1.402827930 0.380366377 2.811090048
139 140 141 142 143 144
-1.018128778 -0.178061102 -1.246883275 -1.579657955 -1.600423692 -0.953324261
145 146 147 148 149 150
3.065763013 -1.033010314 4.260164120 -0.633309790 -0.108427710 -1.231914122
151 152 153 154 155 156
-3.638975489 -4.081614566 -0.426033397 -0.361004420 -2.011436715 -0.949384989
157 158 159 160 161 162
-2.293391210 -0.197097076 -2.731593588 1.103343402 -0.889702379 7.765448083
163 164 165 166 167 168
-1.415569155 -3.883095360 0.724747680 -2.172403955 -1.193780135 -2.922495846
169 170 171 172 173 174
-1.112667422 -1.941487595 4.845260172 -0.830209934 -0.021600811 6.580668571
175 176 177 178 179 180
3.025975649 -1.507350416 -1.440010995 -1.470303949 -1.631115530 1.599459188
181 182 183 184 185 186
3.383486342 -1.318272706 0.616576951 -1.258495194 -2.153341997 0.739090872
187 188 189 190 191 192
-0.071106216 0.541000271 -0.857309629 -2.665399016 -0.246410154 -1.866346184
193 194 195 196 197 198
2.720838584 4.515206281 -1.813415900 1.514184192 -2.026060704 1.058349073
199 200 201 202 203 204
-0.969524889 0.051894367 0.660107994 -1.063804296 -0.987170807 -0.451270949
205 206 207 208 209 210
1.232204720 -1.902222230 -1.388273194 -1.510320265 -1.616198367 -1.041733425
211 212 213 214 215 216
3.483997705 -1.494947315 -1.229270653 -1.032490622 3.768997122 -0.288217597
217 218 219 220 221 222
-1.123857775 6.190939931 1.959972487 -1.269467458 -2.046178405 3.196616143
223 224 225 226 227 228
0.390994034 -1.346203134 -1.237147660 2.144594349 0.149532551 -0.243904416
229 230 231 232 233 234
-0.003653324 -2.621101964 -0.727404790 -0.962692435 -1.848354399 -1.248137136
235 236 237 238 239 240
-1.799801493 -1.029077736 -1.827629379 -1.326309638 -1.111920519 -1.301808535
241 242 243 244 245 246
-1.408367621 -2.524329602 -0.903441573 1.021460695 -0.982590918 -0.598749665
247 248 249 250 251 252
-0.337514887 -1.139968778 -0.493228154 -0.190037429 -2.042166857 -1.244770401
253 254 255 256 257 258
0.842911954 -0.799158278 -1.916862875 0.006378718 -0.339349865 -0.996285870
259 260 261 262 263 264
-0.169399702 -0.298407983 -1.430189481 -0.433253151 -0.421346856 -0.794920324
265 266 267 268 269 270
-1.059744870 -0.747824673 -1.190024274 -0.359607997 -0.634015866 -1.631366969
271 272 273 274 275 276
-1.128797461 -1.090861403 0.379166736 0.175214718 -0.457228715 4.374188024
277 278 279 280 281 282
1.902395218 1.593375069 0.887700450 -1.326075720 -1.380966693 -1.205655221
283 284 285 286 287 288
1.932648937 1.136023393 -1.390317568 -2.277258183 -0.052803693 -0.911584400
289
-1.515156459
> postscript(file="/var/wessaorg/rcomp/tmp/6rqq41354894070.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 289
Frequency = 1
lag(myerror, k = 1) myerror
0 1.296319932 NA
1 2.272755534 1.296319932
2 8.201172592 2.272755534
3 -0.033315289 8.201172592
4 -0.350816690 -0.033315289
5 0.375110740 -0.350816690
6 -2.510829777 0.375110740
7 -1.467501359 -2.510829777
8 -0.726484553 -1.467501359
9 2.247804763 -0.726484553
10 -1.790343373 2.247804763
11 -3.273500923 -1.790343373
12 3.100945947 -3.273500923
13 3.915414019 3.100945947
14 -0.393472150 3.915414019
15 5.731531921 -0.393472150
16 -5.447221145 5.731531921
17 2.061141807 -5.447221145
18 -0.040948287 2.061141807
19 -0.975785805 -0.040948287
20 4.252701159 -0.975785805
21 -2.719451856 4.252701159
22 -1.449652353 -2.719451856
23 3.070515490 -1.449652353
24 3.817760344 3.070515490
25 -2.617860058 3.817760344
26 -3.482994313 -2.617860058
27 1.759421106 -3.482994313
28 -2.062871302 1.759421106
29 -2.259936443 -2.062871302
30 -1.799899019 -2.259936443
31 0.158477855 -1.799899019
32 -0.541696950 0.158477855
33 -2.165908319 -0.541696950
34 1.301894302 -2.165908319
35 -0.989690594 1.301894302
36 -0.624527229 -0.989690594
37 -3.126067488 -0.624527229
38 -4.007967179 -3.126067488
39 0.537824778 -4.007967179
40 -0.455778236 0.537824778
41 0.196701757 -0.455778236
42 -1.528427594 0.196701757
43 -1.535688631 -1.528427594
44 6.477629397 -1.535688631
45 2.820954262 6.477629397
46 -2.889730952 2.820954262
47 2.786309233 -2.889730952
48 1.319566152 2.786309233
49 -4.471877144 1.319566152
50 1.763504940 -4.471877144
51 -0.589261662 1.763504940
52 -3.472752277 -0.589261662
53 3.411122663 -3.472752277
54 0.008769574 3.411122663
55 -2.209856914 0.008769574
56 -0.028505116 -2.209856914
57 4.235517983 -0.028505116
58 3.317747100 4.235517983
59 1.972754213 3.317747100
60 -1.830026669 1.972754213
61 0.922470252 -1.830026669
62 -2.700950636 0.922470252
63 -0.280105516 -2.700950636
64 2.738480008 -0.280105516
65 -2.302315258 2.738480008
66 9.650672601 -2.302315258
67 3.837307092 9.650672601
68 6.608009588 3.837307092
69 3.564631990 6.608009588
70 4.212585404 3.564631990
71 -0.556905816 4.212585404
72 -1.619019691 -0.556905816
73 2.607477041 -1.619019691
74 3.960520638 2.607477041
75 0.422792144 3.960520638
76 4.588608604 0.422792144
77 7.758186770 4.588608604
78 3.660727354 7.758186770
79 2.820664149 3.660727354
80 0.049981231 2.820664149
81 -2.156748908 0.049981231
82 2.193948602 -2.156748908
83 0.718464805 2.193948602
84 3.006419822 0.718464805
85 0.055146746 3.006419822
86 -2.935749095 0.055146746
87 -1.148886168 -2.935749095
88 -3.460451010 -1.148886168
89 2.112485687 -3.460451010
90 -0.598458850 2.112485687
91 0.139387236 -0.598458850
92 -2.259071652 0.139387236
93 3.141989021 -2.259071652
94 -1.296690842 3.141989021
95 -1.594785628 -1.296690842
96 -4.543290368 -1.594785628
97 -2.540879928 -4.543290368
98 -2.376418732 -2.540879928
99 0.319796784 -2.376418732
100 3.436311034 0.319796784
101 -2.156289697 3.436311034
102 1.431837630 -2.156289697
103 -0.119663479 1.431837630
104 1.283270267 -0.119663479
105 -1.326703155 1.283270267
106 4.443227378 -1.326703155
107 -1.959629147 4.443227378
108 7.145953619 -1.959629147
109 3.148597573 7.145953619
110 -1.968126232 3.148597573
111 -3.330649780 -1.968126232
112 2.345299499 -3.330649780
113 2.544593085 2.345299499
114 -2.504544346 2.544593085
115 -2.147934151 -2.504544346
116 -1.721019173 -2.147934151
117 -0.733160491 -1.721019173
118 -2.096092497 -0.733160491
119 -0.257565421 -2.096092497
120 -1.606694208 -0.257565421
121 -1.263367823 -1.606694208
122 2.751562712 -1.263367823
123 -2.013049221 2.751562712
124 1.335733189 -2.013049221
125 3.528968500 1.335733189
126 2.126326706 3.528968500
127 -1.428424030 2.126326706
128 -2.819701336 -1.428424030
129 0.504268532 -2.819701336
130 4.050190438 0.504268532
131 -2.252698532 4.050190438
132 3.600627392 -2.252698532
133 -2.927105592 3.600627392
134 -2.779254004 -2.927105592
135 -1.402827930 -2.779254004
136 0.380366377 -1.402827930
137 2.811090048 0.380366377
138 -1.018128778 2.811090048
139 -0.178061102 -1.018128778
140 -1.246883275 -0.178061102
141 -1.579657955 -1.246883275
142 -1.600423692 -1.579657955
143 -0.953324261 -1.600423692
144 3.065763013 -0.953324261
145 -1.033010314 3.065763013
146 4.260164120 -1.033010314
147 -0.633309790 4.260164120
148 -0.108427710 -0.633309790
149 -1.231914122 -0.108427710
150 -3.638975489 -1.231914122
151 -4.081614566 -3.638975489
152 -0.426033397 -4.081614566
153 -0.361004420 -0.426033397
154 -2.011436715 -0.361004420
155 -0.949384989 -2.011436715
156 -2.293391210 -0.949384989
157 -0.197097076 -2.293391210
158 -2.731593588 -0.197097076
159 1.103343402 -2.731593588
160 -0.889702379 1.103343402
161 7.765448083 -0.889702379
162 -1.415569155 7.765448083
163 -3.883095360 -1.415569155
164 0.724747680 -3.883095360
165 -2.172403955 0.724747680
166 -1.193780135 -2.172403955
167 -2.922495846 -1.193780135
168 -1.112667422 -2.922495846
169 -1.941487595 -1.112667422
170 4.845260172 -1.941487595
171 -0.830209934 4.845260172
172 -0.021600811 -0.830209934
173 6.580668571 -0.021600811
174 3.025975649 6.580668571
175 -1.507350416 3.025975649
176 -1.440010995 -1.507350416
177 -1.470303949 -1.440010995
178 -1.631115530 -1.470303949
179 1.599459188 -1.631115530
180 3.383486342 1.599459188
181 -1.318272706 3.383486342
182 0.616576951 -1.318272706
183 -1.258495194 0.616576951
184 -2.153341997 -1.258495194
185 0.739090872 -2.153341997
186 -0.071106216 0.739090872
187 0.541000271 -0.071106216
188 -0.857309629 0.541000271
189 -2.665399016 -0.857309629
190 -0.246410154 -2.665399016
191 -1.866346184 -0.246410154
192 2.720838584 -1.866346184
193 4.515206281 2.720838584
194 -1.813415900 4.515206281
195 1.514184192 -1.813415900
196 -2.026060704 1.514184192
197 1.058349073 -2.026060704
198 -0.969524889 1.058349073
199 0.051894367 -0.969524889
200 0.660107994 0.051894367
201 -1.063804296 0.660107994
202 -0.987170807 -1.063804296
203 -0.451270949 -0.987170807
204 1.232204720 -0.451270949
205 -1.902222230 1.232204720
206 -1.388273194 -1.902222230
207 -1.510320265 -1.388273194
208 -1.616198367 -1.510320265
209 -1.041733425 -1.616198367
210 3.483997705 -1.041733425
211 -1.494947315 3.483997705
212 -1.229270653 -1.494947315
213 -1.032490622 -1.229270653
214 3.768997122 -1.032490622
215 -0.288217597 3.768997122
216 -1.123857775 -0.288217597
217 6.190939931 -1.123857775
218 1.959972487 6.190939931
219 -1.269467458 1.959972487
220 -2.046178405 -1.269467458
221 3.196616143 -2.046178405
222 0.390994034 3.196616143
223 -1.346203134 0.390994034
224 -1.237147660 -1.346203134
225 2.144594349 -1.237147660
226 0.149532551 2.144594349
227 -0.243904416 0.149532551
228 -0.003653324 -0.243904416
229 -2.621101964 -0.003653324
230 -0.727404790 -2.621101964
231 -0.962692435 -0.727404790
232 -1.848354399 -0.962692435
233 -1.248137136 -1.848354399
234 -1.799801493 -1.248137136
235 -1.029077736 -1.799801493
236 -1.827629379 -1.029077736
237 -1.326309638 -1.827629379
238 -1.111920519 -1.326309638
239 -1.301808535 -1.111920519
240 -1.408367621 -1.301808535
241 -2.524329602 -1.408367621
242 -0.903441573 -2.524329602
243 1.021460695 -0.903441573
244 -0.982590918 1.021460695
245 -0.598749665 -0.982590918
246 -0.337514887 -0.598749665
247 -1.139968778 -0.337514887
248 -0.493228154 -1.139968778
249 -0.190037429 -0.493228154
250 -2.042166857 -0.190037429
251 -1.244770401 -2.042166857
252 0.842911954 -1.244770401
253 -0.799158278 0.842911954
254 -1.916862875 -0.799158278
255 0.006378718 -1.916862875
256 -0.339349865 0.006378718
257 -0.996285870 -0.339349865
258 -0.169399702 -0.996285870
259 -0.298407983 -0.169399702
260 -1.430189481 -0.298407983
261 -0.433253151 -1.430189481
262 -0.421346856 -0.433253151
263 -0.794920324 -0.421346856
264 -1.059744870 -0.794920324
265 -0.747824673 -1.059744870
266 -1.190024274 -0.747824673
267 -0.359607997 -1.190024274
268 -0.634015866 -0.359607997
269 -1.631366969 -0.634015866
270 -1.128797461 -1.631366969
271 -1.090861403 -1.128797461
272 0.379166736 -1.090861403
273 0.175214718 0.379166736
274 -0.457228715 0.175214718
275 4.374188024 -0.457228715
276 1.902395218 4.374188024
277 1.593375069 1.902395218
278 0.887700450 1.593375069
279 -1.326075720 0.887700450
280 -1.380966693 -1.326075720
281 -1.205655221 -1.380966693
282 1.932648937 -1.205655221
283 1.136023393 1.932648937
284 -1.390317568 1.136023393
285 -2.277258183 -1.390317568
286 -0.052803693 -2.277258183
287 -0.911584400 -0.052803693
288 -1.515156459 -0.911584400
289 NA -1.515156459
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.272755534 1.296319932
[2,] 8.201172592 2.272755534
[3,] -0.033315289 8.201172592
[4,] -0.350816690 -0.033315289
[5,] 0.375110740 -0.350816690
[6,] -2.510829777 0.375110740
[7,] -1.467501359 -2.510829777
[8,] -0.726484553 -1.467501359
[9,] 2.247804763 -0.726484553
[10,] -1.790343373 2.247804763
[11,] -3.273500923 -1.790343373
[12,] 3.100945947 -3.273500923
[13,] 3.915414019 3.100945947
[14,] -0.393472150 3.915414019
[15,] 5.731531921 -0.393472150
[16,] -5.447221145 5.731531921
[17,] 2.061141807 -5.447221145
[18,] -0.040948287 2.061141807
[19,] -0.975785805 -0.040948287
[20,] 4.252701159 -0.975785805
[21,] -2.719451856 4.252701159
[22,] -1.449652353 -2.719451856
[23,] 3.070515490 -1.449652353
[24,] 3.817760344 3.070515490
[25,] -2.617860058 3.817760344
[26,] -3.482994313 -2.617860058
[27,] 1.759421106 -3.482994313
[28,] -2.062871302 1.759421106
[29,] -2.259936443 -2.062871302
[30,] -1.799899019 -2.259936443
[31,] 0.158477855 -1.799899019
[32,] -0.541696950 0.158477855
[33,] -2.165908319 -0.541696950
[34,] 1.301894302 -2.165908319
[35,] -0.989690594 1.301894302
[36,] -0.624527229 -0.989690594
[37,] -3.126067488 -0.624527229
[38,] -4.007967179 -3.126067488
[39,] 0.537824778 -4.007967179
[40,] -0.455778236 0.537824778
[41,] 0.196701757 -0.455778236
[42,] -1.528427594 0.196701757
[43,] -1.535688631 -1.528427594
[44,] 6.477629397 -1.535688631
[45,] 2.820954262 6.477629397
[46,] -2.889730952 2.820954262
[47,] 2.786309233 -2.889730952
[48,] 1.319566152 2.786309233
[49,] -4.471877144 1.319566152
[50,] 1.763504940 -4.471877144
[51,] -0.589261662 1.763504940
[52,] -3.472752277 -0.589261662
[53,] 3.411122663 -3.472752277
[54,] 0.008769574 3.411122663
[55,] -2.209856914 0.008769574
[56,] -0.028505116 -2.209856914
[57,] 4.235517983 -0.028505116
[58,] 3.317747100 4.235517983
[59,] 1.972754213 3.317747100
[60,] -1.830026669 1.972754213
[61,] 0.922470252 -1.830026669
[62,] -2.700950636 0.922470252
[63,] -0.280105516 -2.700950636
[64,] 2.738480008 -0.280105516
[65,] -2.302315258 2.738480008
[66,] 9.650672601 -2.302315258
[67,] 3.837307092 9.650672601
[68,] 6.608009588 3.837307092
[69,] 3.564631990 6.608009588
[70,] 4.212585404 3.564631990
[71,] -0.556905816 4.212585404
[72,] -1.619019691 -0.556905816
[73,] 2.607477041 -1.619019691
[74,] 3.960520638 2.607477041
[75,] 0.422792144 3.960520638
[76,] 4.588608604 0.422792144
[77,] 7.758186770 4.588608604
[78,] 3.660727354 7.758186770
[79,] 2.820664149 3.660727354
[80,] 0.049981231 2.820664149
[81,] -2.156748908 0.049981231
[82,] 2.193948602 -2.156748908
[83,] 0.718464805 2.193948602
[84,] 3.006419822 0.718464805
[85,] 0.055146746 3.006419822
[86,] -2.935749095 0.055146746
[87,] -1.148886168 -2.935749095
[88,] -3.460451010 -1.148886168
[89,] 2.112485687 -3.460451010
[90,] -0.598458850 2.112485687
[91,] 0.139387236 -0.598458850
[92,] -2.259071652 0.139387236
[93,] 3.141989021 -2.259071652
[94,] -1.296690842 3.141989021
[95,] -1.594785628 -1.296690842
[96,] -4.543290368 -1.594785628
[97,] -2.540879928 -4.543290368
[98,] -2.376418732 -2.540879928
[99,] 0.319796784 -2.376418732
[100,] 3.436311034 0.319796784
[101,] -2.156289697 3.436311034
[102,] 1.431837630 -2.156289697
[103,] -0.119663479 1.431837630
[104,] 1.283270267 -0.119663479
[105,] -1.326703155 1.283270267
[106,] 4.443227378 -1.326703155
[107,] -1.959629147 4.443227378
[108,] 7.145953619 -1.959629147
[109,] 3.148597573 7.145953619
[110,] -1.968126232 3.148597573
[111,] -3.330649780 -1.968126232
[112,] 2.345299499 -3.330649780
[113,] 2.544593085 2.345299499
[114,] -2.504544346 2.544593085
[115,] -2.147934151 -2.504544346
[116,] -1.721019173 -2.147934151
[117,] -0.733160491 -1.721019173
[118,] -2.096092497 -0.733160491
[119,] -0.257565421 -2.096092497
[120,] -1.606694208 -0.257565421
[121,] -1.263367823 -1.606694208
[122,] 2.751562712 -1.263367823
[123,] -2.013049221 2.751562712
[124,] 1.335733189 -2.013049221
[125,] 3.528968500 1.335733189
[126,] 2.126326706 3.528968500
[127,] -1.428424030 2.126326706
[128,] -2.819701336 -1.428424030
[129,] 0.504268532 -2.819701336
[130,] 4.050190438 0.504268532
[131,] -2.252698532 4.050190438
[132,] 3.600627392 -2.252698532
[133,] -2.927105592 3.600627392
[134,] -2.779254004 -2.927105592
[135,] -1.402827930 -2.779254004
[136,] 0.380366377 -1.402827930
[137,] 2.811090048 0.380366377
[138,] -1.018128778 2.811090048
[139,] -0.178061102 -1.018128778
[140,] -1.246883275 -0.178061102
[141,] -1.579657955 -1.246883275
[142,] -1.600423692 -1.579657955
[143,] -0.953324261 -1.600423692
[144,] 3.065763013 -0.953324261
[145,] -1.033010314 3.065763013
[146,] 4.260164120 -1.033010314
[147,] -0.633309790 4.260164120
[148,] -0.108427710 -0.633309790
[149,] -1.231914122 -0.108427710
[150,] -3.638975489 -1.231914122
[151,] -4.081614566 -3.638975489
[152,] -0.426033397 -4.081614566
[153,] -0.361004420 -0.426033397
[154,] -2.011436715 -0.361004420
[155,] -0.949384989 -2.011436715
[156,] -2.293391210 -0.949384989
[157,] -0.197097076 -2.293391210
[158,] -2.731593588 -0.197097076
[159,] 1.103343402 -2.731593588
[160,] -0.889702379 1.103343402
[161,] 7.765448083 -0.889702379
[162,] -1.415569155 7.765448083
[163,] -3.883095360 -1.415569155
[164,] 0.724747680 -3.883095360
[165,] -2.172403955 0.724747680
[166,] -1.193780135 -2.172403955
[167,] -2.922495846 -1.193780135
[168,] -1.112667422 -2.922495846
[169,] -1.941487595 -1.112667422
[170,] 4.845260172 -1.941487595
[171,] -0.830209934 4.845260172
[172,] -0.021600811 -0.830209934
[173,] 6.580668571 -0.021600811
[174,] 3.025975649 6.580668571
[175,] -1.507350416 3.025975649
[176,] -1.440010995 -1.507350416
[177,] -1.470303949 -1.440010995
[178,] -1.631115530 -1.470303949
[179,] 1.599459188 -1.631115530
[180,] 3.383486342 1.599459188
[181,] -1.318272706 3.383486342
[182,] 0.616576951 -1.318272706
[183,] -1.258495194 0.616576951
[184,] -2.153341997 -1.258495194
[185,] 0.739090872 -2.153341997
[186,] -0.071106216 0.739090872
[187,] 0.541000271 -0.071106216
[188,] -0.857309629 0.541000271
[189,] -2.665399016 -0.857309629
[190,] -0.246410154 -2.665399016
[191,] -1.866346184 -0.246410154
[192,] 2.720838584 -1.866346184
[193,] 4.515206281 2.720838584
[194,] -1.813415900 4.515206281
[195,] 1.514184192 -1.813415900
[196,] -2.026060704 1.514184192
[197,] 1.058349073 -2.026060704
[198,] -0.969524889 1.058349073
[199,] 0.051894367 -0.969524889
[200,] 0.660107994 0.051894367
[201,] -1.063804296 0.660107994
[202,] -0.987170807 -1.063804296
[203,] -0.451270949 -0.987170807
[204,] 1.232204720 -0.451270949
[205,] -1.902222230 1.232204720
[206,] -1.388273194 -1.902222230
[207,] -1.510320265 -1.388273194
[208,] -1.616198367 -1.510320265
[209,] -1.041733425 -1.616198367
[210,] 3.483997705 -1.041733425
[211,] -1.494947315 3.483997705
[212,] -1.229270653 -1.494947315
[213,] -1.032490622 -1.229270653
[214,] 3.768997122 -1.032490622
[215,] -0.288217597 3.768997122
[216,] -1.123857775 -0.288217597
[217,] 6.190939931 -1.123857775
[218,] 1.959972487 6.190939931
[219,] -1.269467458 1.959972487
[220,] -2.046178405 -1.269467458
[221,] 3.196616143 -2.046178405
[222,] 0.390994034 3.196616143
[223,] -1.346203134 0.390994034
[224,] -1.237147660 -1.346203134
[225,] 2.144594349 -1.237147660
[226,] 0.149532551 2.144594349
[227,] -0.243904416 0.149532551
[228,] -0.003653324 -0.243904416
[229,] -2.621101964 -0.003653324
[230,] -0.727404790 -2.621101964
[231,] -0.962692435 -0.727404790
[232,] -1.848354399 -0.962692435
[233,] -1.248137136 -1.848354399
[234,] -1.799801493 -1.248137136
[235,] -1.029077736 -1.799801493
[236,] -1.827629379 -1.029077736
[237,] -1.326309638 -1.827629379
[238,] -1.111920519 -1.326309638
[239,] -1.301808535 -1.111920519
[240,] -1.408367621 -1.301808535
[241,] -2.524329602 -1.408367621
[242,] -0.903441573 -2.524329602
[243,] 1.021460695 -0.903441573
[244,] -0.982590918 1.021460695
[245,] -0.598749665 -0.982590918
[246,] -0.337514887 -0.598749665
[247,] -1.139968778 -0.337514887
[248,] -0.493228154 -1.139968778
[249,] -0.190037429 -0.493228154
[250,] -2.042166857 -0.190037429
[251,] -1.244770401 -2.042166857
[252,] 0.842911954 -1.244770401
[253,] -0.799158278 0.842911954
[254,] -1.916862875 -0.799158278
[255,] 0.006378718 -1.916862875
[256,] -0.339349865 0.006378718
[257,] -0.996285870 -0.339349865
[258,] -0.169399702 -0.996285870
[259,] -0.298407983 -0.169399702
[260,] -1.430189481 -0.298407983
[261,] -0.433253151 -1.430189481
[262,] -0.421346856 -0.433253151
[263,] -0.794920324 -0.421346856
[264,] -1.059744870 -0.794920324
[265,] -0.747824673 -1.059744870
[266,] -1.190024274 -0.747824673
[267,] -0.359607997 -1.190024274
[268,] -0.634015866 -0.359607997
[269,] -1.631366969 -0.634015866
[270,] -1.128797461 -1.631366969
[271,] -1.090861403 -1.128797461
[272,] 0.379166736 -1.090861403
[273,] 0.175214718 0.379166736
[274,] -0.457228715 0.175214718
[275,] 4.374188024 -0.457228715
[276,] 1.902395218 4.374188024
[277,] 1.593375069 1.902395218
[278,] 0.887700450 1.593375069
[279,] -1.326075720 0.887700450
[280,] -1.380966693 -1.326075720
[281,] -1.205655221 -1.380966693
[282,] 1.932648937 -1.205655221
[283,] 1.136023393 1.932648937
[284,] -1.390317568 1.136023393
[285,] -2.277258183 -1.390317568
[286,] -0.052803693 -2.277258183
[287,] -0.911584400 -0.052803693
[288,] -1.515156459 -0.911584400
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.272755534 1.296319932
2 8.201172592 2.272755534
3 -0.033315289 8.201172592
4 -0.350816690 -0.033315289
5 0.375110740 -0.350816690
6 -2.510829777 0.375110740
7 -1.467501359 -2.510829777
8 -0.726484553 -1.467501359
9 2.247804763 -0.726484553
10 -1.790343373 2.247804763
11 -3.273500923 -1.790343373
12 3.100945947 -3.273500923
13 3.915414019 3.100945947
14 -0.393472150 3.915414019
15 5.731531921 -0.393472150
16 -5.447221145 5.731531921
17 2.061141807 -5.447221145
18 -0.040948287 2.061141807
19 -0.975785805 -0.040948287
20 4.252701159 -0.975785805
21 -2.719451856 4.252701159
22 -1.449652353 -2.719451856
23 3.070515490 -1.449652353
24 3.817760344 3.070515490
25 -2.617860058 3.817760344
26 -3.482994313 -2.617860058
27 1.759421106 -3.482994313
28 -2.062871302 1.759421106
29 -2.259936443 -2.062871302
30 -1.799899019 -2.259936443
31 0.158477855 -1.799899019
32 -0.541696950 0.158477855
33 -2.165908319 -0.541696950
34 1.301894302 -2.165908319
35 -0.989690594 1.301894302
36 -0.624527229 -0.989690594
37 -3.126067488 -0.624527229
38 -4.007967179 -3.126067488
39 0.537824778 -4.007967179
40 -0.455778236 0.537824778
41 0.196701757 -0.455778236
42 -1.528427594 0.196701757
43 -1.535688631 -1.528427594
44 6.477629397 -1.535688631
45 2.820954262 6.477629397
46 -2.889730952 2.820954262
47 2.786309233 -2.889730952
48 1.319566152 2.786309233
49 -4.471877144 1.319566152
50 1.763504940 -4.471877144
51 -0.589261662 1.763504940
52 -3.472752277 -0.589261662
53 3.411122663 -3.472752277
54 0.008769574 3.411122663
55 -2.209856914 0.008769574
56 -0.028505116 -2.209856914
57 4.235517983 -0.028505116
58 3.317747100 4.235517983
59 1.972754213 3.317747100
60 -1.830026669 1.972754213
61 0.922470252 -1.830026669
62 -2.700950636 0.922470252
63 -0.280105516 -2.700950636
64 2.738480008 -0.280105516
65 -2.302315258 2.738480008
66 9.650672601 -2.302315258
67 3.837307092 9.650672601
68 6.608009588 3.837307092
69 3.564631990 6.608009588
70 4.212585404 3.564631990
71 -0.556905816 4.212585404
72 -1.619019691 -0.556905816
73 2.607477041 -1.619019691
74 3.960520638 2.607477041
75 0.422792144 3.960520638
76 4.588608604 0.422792144
77 7.758186770 4.588608604
78 3.660727354 7.758186770
79 2.820664149 3.660727354
80 0.049981231 2.820664149
81 -2.156748908 0.049981231
82 2.193948602 -2.156748908
83 0.718464805 2.193948602
84 3.006419822 0.718464805
85 0.055146746 3.006419822
86 -2.935749095 0.055146746
87 -1.148886168 -2.935749095
88 -3.460451010 -1.148886168
89 2.112485687 -3.460451010
90 -0.598458850 2.112485687
91 0.139387236 -0.598458850
92 -2.259071652 0.139387236
93 3.141989021 -2.259071652
94 -1.296690842 3.141989021
95 -1.594785628 -1.296690842
96 -4.543290368 -1.594785628
97 -2.540879928 -4.543290368
98 -2.376418732 -2.540879928
99 0.319796784 -2.376418732
100 3.436311034 0.319796784
101 -2.156289697 3.436311034
102 1.431837630 -2.156289697
103 -0.119663479 1.431837630
104 1.283270267 -0.119663479
105 -1.326703155 1.283270267
106 4.443227378 -1.326703155
107 -1.959629147 4.443227378
108 7.145953619 -1.959629147
109 3.148597573 7.145953619
110 -1.968126232 3.148597573
111 -3.330649780 -1.968126232
112 2.345299499 -3.330649780
113 2.544593085 2.345299499
114 -2.504544346 2.544593085
115 -2.147934151 -2.504544346
116 -1.721019173 -2.147934151
117 -0.733160491 -1.721019173
118 -2.096092497 -0.733160491
119 -0.257565421 -2.096092497
120 -1.606694208 -0.257565421
121 -1.263367823 -1.606694208
122 2.751562712 -1.263367823
123 -2.013049221 2.751562712
124 1.335733189 -2.013049221
125 3.528968500 1.335733189
126 2.126326706 3.528968500
127 -1.428424030 2.126326706
128 -2.819701336 -1.428424030
129 0.504268532 -2.819701336
130 4.050190438 0.504268532
131 -2.252698532 4.050190438
132 3.600627392 -2.252698532
133 -2.927105592 3.600627392
134 -2.779254004 -2.927105592
135 -1.402827930 -2.779254004
136 0.380366377 -1.402827930
137 2.811090048 0.380366377
138 -1.018128778 2.811090048
139 -0.178061102 -1.018128778
140 -1.246883275 -0.178061102
141 -1.579657955 -1.246883275
142 -1.600423692 -1.579657955
143 -0.953324261 -1.600423692
144 3.065763013 -0.953324261
145 -1.033010314 3.065763013
146 4.260164120 -1.033010314
147 -0.633309790 4.260164120
148 -0.108427710 -0.633309790
149 -1.231914122 -0.108427710
150 -3.638975489 -1.231914122
151 -4.081614566 -3.638975489
152 -0.426033397 -4.081614566
153 -0.361004420 -0.426033397
154 -2.011436715 -0.361004420
155 -0.949384989 -2.011436715
156 -2.293391210 -0.949384989
157 -0.197097076 -2.293391210
158 -2.731593588 -0.197097076
159 1.103343402 -2.731593588
160 -0.889702379 1.103343402
161 7.765448083 -0.889702379
162 -1.415569155 7.765448083
163 -3.883095360 -1.415569155
164 0.724747680 -3.883095360
165 -2.172403955 0.724747680
166 -1.193780135 -2.172403955
167 -2.922495846 -1.193780135
168 -1.112667422 -2.922495846
169 -1.941487595 -1.112667422
170 4.845260172 -1.941487595
171 -0.830209934 4.845260172
172 -0.021600811 -0.830209934
173 6.580668571 -0.021600811
174 3.025975649 6.580668571
175 -1.507350416 3.025975649
176 -1.440010995 -1.507350416
177 -1.470303949 -1.440010995
178 -1.631115530 -1.470303949
179 1.599459188 -1.631115530
180 3.383486342 1.599459188
181 -1.318272706 3.383486342
182 0.616576951 -1.318272706
183 -1.258495194 0.616576951
184 -2.153341997 -1.258495194
185 0.739090872 -2.153341997
186 -0.071106216 0.739090872
187 0.541000271 -0.071106216
188 -0.857309629 0.541000271
189 -2.665399016 -0.857309629
190 -0.246410154 -2.665399016
191 -1.866346184 -0.246410154
192 2.720838584 -1.866346184
193 4.515206281 2.720838584
194 -1.813415900 4.515206281
195 1.514184192 -1.813415900
196 -2.026060704 1.514184192
197 1.058349073 -2.026060704
198 -0.969524889 1.058349073
199 0.051894367 -0.969524889
200 0.660107994 0.051894367
201 -1.063804296 0.660107994
202 -0.987170807 -1.063804296
203 -0.451270949 -0.987170807
204 1.232204720 -0.451270949
205 -1.902222230 1.232204720
206 -1.388273194 -1.902222230
207 -1.510320265 -1.388273194
208 -1.616198367 -1.510320265
209 -1.041733425 -1.616198367
210 3.483997705 -1.041733425
211 -1.494947315 3.483997705
212 -1.229270653 -1.494947315
213 -1.032490622 -1.229270653
214 3.768997122 -1.032490622
215 -0.288217597 3.768997122
216 -1.123857775 -0.288217597
217 6.190939931 -1.123857775
218 1.959972487 6.190939931
219 -1.269467458 1.959972487
220 -2.046178405 -1.269467458
221 3.196616143 -2.046178405
222 0.390994034 3.196616143
223 -1.346203134 0.390994034
224 -1.237147660 -1.346203134
225 2.144594349 -1.237147660
226 0.149532551 2.144594349
227 -0.243904416 0.149532551
228 -0.003653324 -0.243904416
229 -2.621101964 -0.003653324
230 -0.727404790 -2.621101964
231 -0.962692435 -0.727404790
232 -1.848354399 -0.962692435
233 -1.248137136 -1.848354399
234 -1.799801493 -1.248137136
235 -1.029077736 -1.799801493
236 -1.827629379 -1.029077736
237 -1.326309638 -1.827629379
238 -1.111920519 -1.326309638
239 -1.301808535 -1.111920519
240 -1.408367621 -1.301808535
241 -2.524329602 -1.408367621
242 -0.903441573 -2.524329602
243 1.021460695 -0.903441573
244 -0.982590918 1.021460695
245 -0.598749665 -0.982590918
246 -0.337514887 -0.598749665
247 -1.139968778 -0.337514887
248 -0.493228154 -1.139968778
249 -0.190037429 -0.493228154
250 -2.042166857 -0.190037429
251 -1.244770401 -2.042166857
252 0.842911954 -1.244770401
253 -0.799158278 0.842911954
254 -1.916862875 -0.799158278
255 0.006378718 -1.916862875
256 -0.339349865 0.006378718
257 -0.996285870 -0.339349865
258 -0.169399702 -0.996285870
259 -0.298407983 -0.169399702
260 -1.430189481 -0.298407983
261 -0.433253151 -1.430189481
262 -0.421346856 -0.433253151
263 -0.794920324 -0.421346856
264 -1.059744870 -0.794920324
265 -0.747824673 -1.059744870
266 -1.190024274 -0.747824673
267 -0.359607997 -1.190024274
268 -0.634015866 -0.359607997
269 -1.631366969 -0.634015866
270 -1.128797461 -1.631366969
271 -1.090861403 -1.128797461
272 0.379166736 -1.090861403
273 0.175214718 0.379166736
274 -0.457228715 0.175214718
275 4.374188024 -0.457228715
276 1.902395218 4.374188024
277 1.593375069 1.902395218
278 0.887700450 1.593375069
279 -1.326075720 0.887700450
280 -1.380966693 -1.326075720
281 -1.205655221 -1.380966693
282 1.932648937 -1.205655221
283 1.136023393 1.932648937
284 -1.390317568 1.136023393
285 -2.277258183 -1.390317568
286 -0.052803693 -2.277258183
287 -0.911584400 -0.052803693
288 -1.515156459 -0.911584400
> 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/7opp81354894070.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/8u8231354894070.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/92gco1354894070.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/10b61l1354894070.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/114bpl1354894070.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12xe011354894070.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13w5fv1354894070.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14ir2q1354894070.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/15imy81354894070.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/16whfo1354894070.tab")
+ }
>
> try(system("convert tmp/1609x1354894070.ps tmp/1609x1354894070.png",intern=TRUE))
character(0)
> try(system("convert tmp/2sw471354894070.ps tmp/2sw471354894070.png",intern=TRUE))
character(0)
> try(system("convert tmp/3lfpe1354894070.ps tmp/3lfpe1354894070.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xyxf1354894070.ps tmp/4xyxf1354894070.png",intern=TRUE))
character(0)
> try(system("convert tmp/5nzki1354894070.ps tmp/5nzki1354894070.png",intern=TRUE))
character(0)
> try(system("convert tmp/6rqq41354894070.ps tmp/6rqq41354894070.png",intern=TRUE))
character(0)
> try(system("convert tmp/7opp81354894070.ps tmp/7opp81354894070.png",intern=TRUE))
character(0)
> try(system("convert tmp/8u8231354894070.ps tmp/8u8231354894070.png",intern=TRUE))
character(0)
> try(system("convert tmp/92gco1354894070.ps tmp/92gco1354894070.png",intern=TRUE))
character(0)
> try(system("convert tmp/10b61l1354894070.ps tmp/10b61l1354894070.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
12.525 1.098 13.672