R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(1418
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+ ,72535
+ ,14
+ ,329
+ ,44
+ ,0
+ ,17
+ ,16)
+ ,dim=c(8
+ ,289)
+ ,dimnames=list(c('pageviews'
+ ,'time_in_rfc'
+ ,'logins'
+ ,'compendium_views_info'
+ ,'compendium_views_pr'
+ ,'shared_compendiums'
+ ,'blogged_computations'
+ ,'compendiums_reviewed')
+ ,1:289))
> y <- array(NA,dim=c(8,289),dimnames=list(c('pageviews','time_in_rfc','logins','compendium_views_info','compendium_views_pr','shared_compendiums','blogged_computations','compendiums_reviewed'),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 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> 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
pageviews time_in_rfc logins compendium_views_info compendium_views_pr
1 1418 210907 56 396 81
2 869 120982 56 297 55
3 1530 176508 54 559 50
4 2172 179321 89 967 125
5 901 123185 40 270 40
6 463 52746 25 143 37
7 3201 385534 92 1562 63
8 371 33170 18 109 44
9 1192 101645 63 371 88
10 1583 149061 44 656 66
11 1439 165446 33 511 57
12 1764 237213 84 655 74
13 1495 173326 88 465 49
14 1373 133131 55 525 52
15 2187 258873 60 885 88
16 1491 180083 66 497 36
17 4041 324799 154 1436 108
18 1706 230964 53 612 43
19 2152 236785 119 865 75
20 1036 135473 41 385 32
21 1882 202925 61 567 44
22 1929 215147 58 639 85
23 2242 344297 75 963 86
24 1220 153935 33 398 56
25 1289 132943 40 410 50
26 2515 174724 92 966 135
27 2147 174415 100 801 63
28 2352 225548 112 892 81
29 1638 223632 73 513 52
30 1222 124817 40 469 44
31 1812 221698 45 683 113
32 1677 210767 60 643 39
33 1579 170266 62 535 73
34 1731 260561 75 625 48
35 807 84853 31 264 33
36 2452 294424 77 992 59
37 829 101011 34 238 41
38 1940 215641 46 818 69
39 2662 325107 99 937 64
40 186 7176 17 70 1
41 1499 167542 66 507 59
42 865 106408 30 260 32
43 1793 96560 76 503 129
44 2527 265769 146 927 37
45 2747 269651 67 1269 31
46 1324 149112 56 537 65
47 2702 175824 107 910 107
48 1383 152871 58 532 74
49 1179 111665 34 345 54
50 2099 116408 61 918 76
51 4308 362301 119 1635 715
52 918 78800 42 330 57
53 1831 183167 66 557 66
54 3373 277965 89 1178 106
55 1713 150629 44 740 54
56 1438 168809 66 452 32
57 496 24188 24 218 20
58 2253 329267 259 764 71
59 744 65029 17 255 21
60 1161 101097 64 454 70
61 2352 218946 41 866 112
62 2144 244052 68 574 66
63 4691 341570 168 1276 190
64 1112 103597 43 379 66
65 2694 233328 132 825 165
66 1973 256462 105 798 56
67 1769 206161 71 663 61
68 3148 311473 112 1069 53
69 2474 235800 94 921 127
70 2084 177939 82 858 63
71 1954 207176 70 711 38
72 1226 196553 57 503 50
73 1389 174184 53 382 52
74 1496 143246 103 464 42
75 2269 187559 121 717 76
76 1833 187681 62 690 67
77 1268 119016 52 462 50
78 1943 182192 52 657 53
79 893 73566 32 385 39
80 1762 194979 62 577 50
81 1403 167488 45 619 77
82 1425 143756 46 479 57
83 1857 275541 63 817 73
84 1840 243199 75 752 34
85 1502 182999 88 430 39
86 1441 135649 46 451 46
87 1420 152299 53 537 63
88 1416 120221 37 519 35
89 2970 346485 90 1000 106
90 1317 145790 63 637 43
91 1644 193339 78 465 47
92 870 80953 25 437 31
93 1654 122774 45 711 162
94 1054 130585 46 299 57
95 937 112611 41 248 36
96 3004 286468 144 1162 263
97 2008 241066 82 714 78
98 2547 148446 91 905 63
99 1885 204713 71 649 54
100 1626 182079 63 512 63
101 1468 140344 53 472 77
102 2445 220516 62 905 79
103 1964 243060 63 786 110
104 1381 162765 32 489 56
105 1369 182613 39 479 56
106 1659 232138 62 617 43
107 2888 265318 117 925 111
108 1290 85574 34 351 71
109 2845 310839 92 1144 62
110 1982 225060 93 669 56
111 1904 232317 54 707 74
112 1391 144966 144 458 60
113 602 43287 14 214 43
114 1743 155754 61 599 68
115 1559 164709 109 572 53
116 2014 201940 38 897 87
117 2143 235454 73 819 46
118 2146 220801 75 720 105
119 874 99466 50 273 32
120 1590 92661 61 508 133
121 1590 133328 55 506 79
122 1210 61361 77 451 51
123 2072 125930 75 699 207
124 1281 100750 72 407 67
125 1401 224549 50 465 47
126 834 82316 32 245 34
127 1105 102010 53 370 66
128 1272 101523 42 316 76
129 1944 243511 71 603 65
130 391 22938 10 154 9
131 761 41566 35 229 42
132 1605 152474 65 577 45
133 530 61857 25 192 25
134 1988 99923 66 617 115
135 1386 132487 41 411 97
136 2395 317394 86 975 53
137 387 21054 16 146 2
138 1742 209641 42 705 52
139 620 22648 19 184 44
140 449 31414 19 200 22
141 800 46698 45 274 35
142 1684 131698 65 502 74
143 1050 91735 35 382 103
144 2699 244749 95 964 144
145 1606 184510 49 537 60
146 1502 79863 37 438 134
147 1204 128423 64 369 89
148 1138 97839 38 417 42
149 568 38214 34 276 52
150 1459 151101 32 514 98
151 2158 272458 65 822 99
152 1111 172494 52 389 52
153 1421 108043 62 466 29
154 2833 328107 65 1255 125
155 1955 250579 83 694 106
156 2922 351067 95 1024 95
157 1002 158015 29 400 40
158 1060 98866 18 397 140
159 956 85439 33 350 43
160 2186 229242 247 719 128
161 3604 351619 139 1277 142
162 1035 84207 29 356 73
163 1417 120445 118 457 72
164 3261 324598 110 1402 128
165 1587 131069 67 600 61
166 1424 204271 42 480 73
167 1701 165543 65 595 148
168 1249 141722 94 436 64
169 946 116048 64 230 45
170 1926 250047 81 651 58
171 3352 299775 95 1367 97
172 1641 195838 67 564 50
173 2035 173260 63 716 37
174 2312 254488 83 747 50
175 1369 104389 45 467 105
176 1577 136084 30 671 69
177 2201 199476 70 861 46
178 961 92499 32 319 57
179 1900 224330 83 612 52
180 1254 135781 31 433 98
181 1335 74408 67 434 61
182 1597 81240 66 503 89
183 207 14688 10 85 0
184 1645 181633 70 564 48
185 2429 271856 103 824 91
186 151 7199 5 74 0
187 474 46660 20 259 7
188 141 17547 5 69 3
189 1639 133368 36 535 54
190 872 95227 34 239 70
191 1318 152601 48 438 36
192 1018 98146 40 459 37
193 1383 79619 43 426 123
194 1314 59194 31 288 247
195 1335 139942 42 498 46
196 1403 118612 46 454 72
197 910 72880 33 376 41
198 616 65475 18 225 24
199 1407 99643 55 555 45
200 771 71965 35 252 33
201 766 77272 59 208 27
202 473 49289 19 130 36
203 1376 135131 66 481 87
204 1232 108446 60 389 90
205 1521 89746 36 565 114
206 572 44296 25 173 31
207 1059 77648 47 278 45
208 1544 181528 54 609 69
209 1230 134019 53 422 51
210 1206 124064 40 445 34
211 1205 92630 40 387 60
212 1255 121848 39 339 45
213 613 52915 14 181 54
214 721 81872 45 245 25
215 1109 58981 36 384 38
216 740 53515 28 212 52
217 1126 60812 44 399 67
218 728 56375 30 229 74
219 689 65490 22 224 38
220 592 80949 17 203 30
221 995 76302 31 333 26
222 1613 104011 55 384 67
223 2048 98104 54 636 132
224 705 67989 21 185 42
225 301 30989 14 93 35
226 1803 135458 81 581 118
227 799 73504 35 248 68
228 861 63123 43 304 43
229 1186 61254 46 344 76
230 1451 74914 30 407 64
231 628 31774 23 170 48
232 1161 81437 38 312 64
233 1463 87186 54 507 56
234 742 50090 20 224 71
235 979 65745 53 340 75
236 675 56653 45 168 39
237 1241 158399 39 443 42
238 676 46455 20 204 39
239 1049 73624 24 367 93
240 620 38395 31 210 38
241 1081 91899 35 335 60
242 1688 139526 151 364 71
243 736 52164 52 178 52
244 617 51567 30 206 27
245 812 70551 31 279 59
246 1051 84856 29 387 40
247 1656 102538 57 490 79
248 705 86678 40 238 44
249 945 85709 44 343 65
250 554 34662 25 232 10
251 1597 150580 77 530 124
252 982 99611 35 291 81
253 222 19349 11 67 15
254 1212 99373 63 397 92
255 1143 86230 44 467 42
256 435 30837 19 178 10
257 532 31706 13 175 24
258 882 89806 42 299 64
259 608 62088 38 154 45
260 459 40151 29 106 22
261 578 27634 20 189 56
262 826 76990 27 194 94
263 509 37460 20 135 19
264 717 54157 19 201 35
265 637 49862 37 207 32
266 857 84337 26 280 35
267 830 64175 42 260 48
268 652 59382 49 227 49
269 707 119308 30 239 48
270 954 76702 49 333 62
271 1461 103425 67 428 96
272 672 70344 28 230 45
273 778 43410 19 292 63
274 1141 104838 49 350 71
275 680 62215 27 186 26
276 1090 69304 30 326 48
277 616 53117 22 155 29
278 285 19764 12 75 19
279 1145 86680 31 361 45
280 733 84105 20 261 45
281 888 77945 20 299 67
282 849 89113 39 300 30
283 1182 91005 29 450 36
284 528 40248 16 183 34
285 642 64187 27 238 36
286 947 50857 21 165 34
287 819 56613 19 234 37
288 757 62792 35 176 46
289 894 72535 14 329 44
shared_compendiums blogged_computations compendiums_reviewed
1 3 79 30
2 4 58 28
3 12 60 38
4 2 108 30
5 1 49 22
6 3 0 26
7 0 121 25
8 0 1 18
9 0 20 11
10 5 43 26
11 0 69 25
12 0 78 38
13 7 86 44
14 7 44 30
15 3 104 40
16 9 63 34
17 0 158 47
18 4 102 30
19 3 77 31
20 0 82 23
21 7 115 36
22 0 101 36
23 1 80 30
24 5 50 25
25 7 83 39
26 0 123 34
27 0 73 31
28 5 81 31
29 0 105 33
30 0 47 25
31 0 105 33
32 3 94 35
33 4 44 42
34 1 114 43
35 4 38 30
36 2 107 33
37 0 30 13
38 0 71 32
39 0 84 36
40 0 0 0
41 2 59 28
42 1 33 14
43 0 42 17
44 2 96 32
45 10 106 30
46 6 56 35
47 0 57 20
48 5 59 28
49 4 39 28
50 1 34 39
51 2 76 34
52 2 20 26
53 0 91 39
54 8 115 39
55 3 85 33
56 0 76 28
57 0 8 4
58 8 79 39
59 5 21 18
60 3 30 14
61 1 76 29
62 5 101 44
63 1 94 21
64 1 27 16
65 5 92 28
66 0 123 35
67 12 75 28
68 8 128 38
69 8 105 23
70 8 55 36
71 8 56 32
72 2 41 29
73 0 72 25
74 5 67 27
75 8 75 36
76 2 114 28
77 5 118 23
78 12 77 40
79 6 22 23
80 7 66 40
81 2 69 28
82 0 105 34
83 4 116 33
84 3 88 28
85 6 73 34
86 2 99 30
87 0 62 33
88 1 53 22
89 0 118 38
90 5 30 26
91 2 100 35
92 0 49 8
93 0 24 24
94 5 67 29
95 0 46 20
96 1 57 29
97 0 75 45
98 1 135 37
99 1 68 33
100 2 124 33
101 6 33 25
102 1 98 32
103 4 58 29
104 2 68 28
105 3 81 28
106 0 131 31
107 10 110 52
108 0 37 21
109 9 130 24
110 7 93 41
111 0 118 33
112 0 39 32
113 4 13 19
114 4 74 20
115 0 81 31
116 0 109 31
117 0 151 32
118 1 51 18
119 0 28 23
120 1 40 17
121 0 56 20
122 0 27 12
123 4 37 17
124 0 83 30
125 4 54 31
126 4 27 10
127 3 28 13
128 0 59 22
129 0 133 42
130 0 12 1
131 5 0 9
132 0 106 32
133 4 23 11
134 0 44 25
135 0 71 36
136 1 116 31
137 0 4 0
138 5 62 24
139 0 12 13
140 0 18 8
141 0 14 13
142 0 60 19
143 0 7 18
144 2 98 33
145 7 64 40
146 1 29 22
147 8 32 38
148 2 25 24
149 0 16 8
150 2 48 35
151 0 100 43
152 0 46 43
153 1 45 14
154 3 129 41
155 0 130 38
156 3 136 45
157 0 59 31
158 0 25 13
159 0 32 28
160 4 63 31
161 4 95 40
162 11 14 30
163 0 36 16
164 0 113 37
165 4 47 30
166 0 92 35
167 1 70 32
168 0 19 27
169 0 50 20
170 0 41 18
171 9 91 31
172 1 111 31
173 3 41 21
174 10 120 39
175 5 135 41
176 0 27 13
177 2 87 32
178 0 25 18
179 1 131 39
180 2 45 14
181 4 29 7
182 0 58 17
183 0 4 0
184 2 47 30
185 1 109 37
186 0 7 0
187 0 12 5
188 0 0 1
189 1 37 16
190 0 37 32
191 2 46 24
192 0 15 17
193 3 42 11
194 6 7 24
195 0 54 22
196 2 54 12
197 0 14 19
198 2 16 13
199 1 33 17
200 1 32 15
201 2 21 16
202 1 15 24
203 0 38 15
204 1 22 17
205 3 28 18
206 0 10 20
207 0 31 16
208 0 32 16
209 0 32 18
210 1 43 22
211 4 27 8
212 0 37 17
213 0 20 18
214 0 32 16
215 7 0 23
216 2 5 22
217 0 26 13
218 7 10 13
219 3 27 16
220 0 11 16
221 0 29 20
222 6 25 22
223 2 55 17
224 0 23 18
225 0 5 17
226 3 43 12
227 0 23 7
228 1 34 17
229 1 36 14
230 0 35 23
231 1 0 17
232 0 37 14
233 0 28 15
234 0 16 17
235 0 26 21
236 0 38 18
237 0 23 18
238 0 22 17
239 0 30 17
240 0 16 16
241 0 18 15
242 0 28 21
243 0 32 16
244 2 21 14
245 0 23 15
246 1 29 17
247 1 50 15
248 0 12 15
249 0 21 10
250 0 18 6
251 0 27 22
252 0 41 21
253 0 13 1
254 1 12 18
255 0 21 17
256 0 8 4
257 0 26 10
258 0 27 16
259 1 13 16
260 0 16 9
261 0 2 16
262 0 42 17
263 0 5 7
264 0 37 15
265 0 17 14
266 0 38 14
267 0 37 18
268 0 29 12
269 0 32 16
270 0 35 21
271 1 17 19
272 0 20 16
273 0 7 1
274 1 46 16
275 0 24 10
276 6 40 19
277 3 3 12
278 1 10 2
279 2 37 14
280 0 17 17
281 0 28 19
282 0 19 14
283 3 29 11
284 1 8 4
285 0 10 16
286 0 15 20
287 1 15 12
288 0 28 15
289 0 17 16
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time_in_rfc logins
9.859e+01 4.561e-04 3.274e+00
compendium_views_info compendium_views_pr shared_compendiums
1.741e+00 1.534e+00 6.164e+00
blogged_computations compendiums_reviewed
1.823e+00 2.565e-01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-486.47 -82.46 -11.44 75.54 1190.20
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.859e+01 2.502e+01 3.940 0.000103 ***
time_in_rfc 4.561e-04 3.367e-04 1.355 0.176567
logins 3.274e+00 4.106e-01 7.975 3.87e-14 ***
compendium_views_info 1.741e+00 8.345e-02 20.869 < 2e-16 ***
compendium_views_pr 1.534e+00 2.230e-01 6.878 3.93e-11 ***
shared_compendiums 6.164e+00 3.840e+00 1.605 0.109607
blogged_computations 1.823e+00 5.187e-01 3.514 0.000514 ***
compendiums_reviewed 2.565e-01 1.576e+00 0.163 0.870801
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 160.6 on 281 degrees of freedom
Multiple R-squared: 0.9535, Adjusted R-squared: 0.9524
F-statistic: 823.9 on 7 and 281 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.10139824 2.027965e-01 8.986018e-01
[2,] 0.13866979 2.773396e-01 8.613302e-01
[3,] 0.21700799 4.340160e-01 7.829920e-01
[4,] 0.13460093 2.692019e-01 8.653991e-01
[5,] 0.07616359 1.523272e-01 9.238364e-01
[6,] 0.04651772 9.303543e-02 9.534823e-01
[7,] 0.81707783 3.658443e-01 1.829222e-01
[8,] 0.76693897 4.661221e-01 2.330610e-01
[9,] 0.78860887 4.227823e-01 2.113911e-01
[10,] 0.74309127 5.138175e-01 2.569087e-01
[11,] 0.76505519 4.698896e-01 2.349448e-01
[12,] 0.72084973 5.583005e-01 2.791503e-01
[13,] 0.67154375 6.569125e-01 3.284562e-01
[14,] 0.64922022 7.015596e-01 3.507798e-01
[15,] 0.58338107 8.332379e-01 4.166189e-01
[16,] 0.51878437 9.624313e-01 4.812156e-01
[17,] 0.46203265 9.240653e-01 5.379673e-01
[18,] 0.39955195 7.991039e-01 6.004480e-01
[19,] 0.33993091 6.798618e-01 6.600691e-01
[20,] 0.28360187 5.672037e-01 7.163981e-01
[21,] 0.23612424 4.722485e-01 7.638758e-01
[22,] 0.20305668 4.061134e-01 7.969433e-01
[23,] 0.16583062 3.316612e-01 8.341694e-01
[24,] 0.18049146 3.609829e-01 8.195085e-01
[25,] 0.14408736 2.881747e-01 8.559126e-01
[26,] 0.11761592 2.352318e-01 8.823841e-01
[27,] 0.10753279 2.150656e-01 8.924672e-01
[28,] 0.08570886 1.714177e-01 9.142911e-01
[29,] 0.13196775 2.639355e-01 8.680322e-01
[30,] 0.10550448 2.110090e-01 8.944955e-01
[31,] 0.08334484 1.666897e-01 9.166552e-01
[32,] 0.07487350 1.497470e-01 9.251265e-01
[33,] 0.13422269 2.684454e-01 8.657773e-01
[34,] 0.10996552 2.199310e-01 8.900345e-01
[35,] 0.10021501 2.004300e-01 8.997850e-01
[36,] 0.10549856 2.109971e-01 8.945014e-01
[37,] 0.22567042 4.513408e-01 7.743296e-01
[38,] 0.21380634 4.276127e-01 7.861937e-01
[39,] 0.22446825 4.489365e-01 7.755317e-01
[40,] 0.19184325 3.836865e-01 8.081568e-01
[41,] 0.28052616 5.610523e-01 7.194738e-01
[42,] 0.24863405 4.972681e-01 7.513659e-01
[43,] 0.25138800 5.027760e-01 7.486120e-01
[44,] 0.63634671 7.273066e-01 3.636533e-01
[45,] 0.61373777 7.725245e-01 3.862622e-01
[46,] 0.57427636 8.514473e-01 4.257236e-01
[47,] 0.53915067 9.216987e-01 4.608493e-01
[48,] 0.80716529 3.856694e-01 1.928347e-01
[49,] 0.77937999 4.412400e-01 2.206200e-01
[50,] 0.76266259 4.746748e-01 2.373374e-01
[51,] 0.78884439 4.223112e-01 2.111556e-01
[52,] 0.90206705 1.958659e-01 9.793295e-02
[53,] 1.00000000 1.189432e-10 5.947161e-11
[54,] 1.00000000 2.219062e-10 1.109531e-10
[55,] 1.00000000 2.577365e-10 1.288683e-10
[56,] 1.00000000 5.604024e-11 2.802012e-11
[57,] 1.00000000 7.868171e-11 3.934085e-11
[58,] 1.00000000 1.941078e-11 9.705391e-12
[59,] 1.00000000 3.012224e-11 1.506112e-11
[60,] 1.00000000 4.539575e-11 2.269788e-11
[61,] 1.00000000 6.806008e-11 3.403004e-11
[62,] 1.00000000 6.103779e-11 3.051889e-11
[63,] 1.00000000 6.875274e-11 3.437637e-11
[64,] 1.00000000 1.236969e-10 6.184843e-11
[65,] 1.00000000 1.526238e-10 7.631188e-11
[66,] 1.00000000 2.256570e-10 1.128285e-10
[67,] 1.00000000 1.843026e-10 9.215131e-11
[68,] 1.00000000 1.913720e-10 9.568602e-11
[69,] 1.00000000 2.131199e-10 1.065599e-10
[70,] 1.00000000 2.791986e-10 1.395993e-10
[71,] 1.00000000 1.222334e-10 6.111670e-11
[72,] 1.00000000 2.203453e-10 1.101726e-10
[73,] 1.00000000 2.337361e-11 1.168680e-11
[74,] 1.00000000 2.416461e-11 1.208231e-11
[75,] 1.00000000 4.261100e-11 2.130550e-11
[76,] 1.00000000 6.815355e-11 3.407677e-11
[77,] 1.00000000 1.102733e-10 5.513667e-11
[78,] 1.00000000 1.675462e-10 8.377309e-11
[79,] 1.00000000 5.021133e-11 2.510567e-11
[80,] 1.00000000 8.570727e-12 4.285364e-12
[81,] 1.00000000 1.158871e-11 5.794356e-12
[82,] 1.00000000 6.133063e-12 3.066531e-12
[83,] 1.00000000 4.375706e-12 2.187853e-12
[84,] 1.00000000 7.841616e-12 3.920808e-12
[85,] 1.00000000 1.164001e-11 5.820004e-12
[86,] 1.00000000 3.417445e-12 1.708723e-12
[87,] 1.00000000 6.329527e-12 3.164764e-12
[88,] 1.00000000 6.740792e-12 3.370396e-12
[89,] 1.00000000 8.981568e-12 4.490784e-12
[90,] 1.00000000 1.611595e-11 8.057973e-12
[91,] 1.00000000 2.258343e-11 1.129172e-11
[92,] 1.00000000 2.356554e-11 1.178277e-11
[93,] 1.00000000 2.289926e-11 1.144963e-11
[94,] 1.00000000 4.035617e-11 2.017809e-11
[95,] 1.00000000 6.988697e-11 3.494348e-11
[96,] 1.00000000 8.282571e-11 4.141286e-11
[97,] 1.00000000 5.617595e-11 2.808798e-11
[98,] 1.00000000 2.006146e-11 1.003073e-11
[99,] 1.00000000 2.908460e-11 1.454230e-11
[100,] 1.00000000 5.225618e-11 2.612809e-11
[101,] 1.00000000 8.822030e-11 4.411015e-11
[102,] 1.00000000 6.248565e-11 3.124283e-11
[103,] 1.00000000 9.803611e-11 4.901806e-11
[104,] 1.00000000 1.560620e-10 7.803101e-11
[105,] 1.00000000 1.208954e-10 6.044768e-11
[106,] 1.00000000 7.045171e-11 3.522586e-11
[107,] 1.00000000 1.077482e-10 5.387411e-11
[108,] 1.00000000 9.027797e-11 4.513898e-11
[109,] 1.00000000 1.594722e-10 7.973609e-11
[110,] 1.00000000 2.395494e-10 1.197747e-10
[111,] 1.00000000 2.553346e-10 1.276673e-10
[112,] 1.00000000 3.989121e-10 1.994560e-10
[113,] 1.00000000 5.928354e-10 2.964177e-10
[114,] 1.00000000 9.387291e-10 4.693646e-10
[115,] 1.00000000 1.588326e-09 7.941632e-10
[116,] 1.00000000 2.555220e-09 1.277610e-09
[117,] 1.00000000 4.144739e-09 2.072369e-09
[118,] 1.00000000 2.514603e-09 1.257302e-09
[119,] 1.00000000 3.106210e-09 1.553105e-09
[120,] 1.00000000 5.066491e-09 2.533246e-09
[121,] 1.00000000 8.057020e-09 4.028510e-09
[122,] 0.99999999 1.301977e-08 6.509887e-09
[123,] 0.99999999 1.567036e-08 7.835179e-09
[124,] 1.00000000 4.437917e-09 2.218959e-09
[125,] 1.00000000 6.161962e-09 3.080981e-09
[126,] 1.00000000 6.839332e-09 3.419666e-09
[127,] 0.99999999 1.118057e-08 5.590287e-09
[128,] 0.99999999 1.531821e-08 7.659107e-09
[129,] 0.99999999 2.412422e-08 1.206211e-08
[130,] 0.99999999 2.678827e-08 1.339413e-08
[131,] 0.99999998 4.372472e-08 2.186236e-08
[132,] 0.99999999 2.534177e-08 1.267088e-08
[133,] 0.99999998 3.750180e-08 1.875090e-08
[134,] 0.99999997 5.634534e-08 2.817267e-08
[135,] 0.99999996 8.688688e-08 4.344344e-08
[136,] 0.99999997 5.916542e-08 2.958271e-08
[137,] 0.99999996 7.359633e-08 3.679817e-08
[138,] 0.99999994 1.180776e-07 5.903881e-08
[139,] 0.99999997 5.136883e-08 2.568442e-08
[140,] 0.99999996 8.259592e-08 4.129796e-08
[141,] 0.99999994 1.242635e-07 6.213174e-08
[142,] 0.99999992 1.691481e-07 8.457407e-08
[143,] 0.99999991 1.850022e-07 9.250112e-08
[144,] 0.99999999 2.529147e-08 1.264573e-08
[145,] 0.99999999 2.312807e-08 1.156404e-08
[146,] 0.99999998 3.122197e-08 1.561099e-08
[147,] 0.99999999 2.843816e-08 1.421908e-08
[148,] 0.99999999 2.579791e-08 1.289896e-08
[149,] 0.99999998 4.166098e-08 2.083049e-08
[150,] 1.00000000 4.944128e-10 2.472064e-10
[151,] 1.00000000 4.495402e-10 2.247701e-10
[152,] 1.00000000 3.863869e-10 1.931934e-10
[153,] 1.00000000 4.007405e-10 2.003702e-10
[154,] 1.00000000 9.174965e-11 4.587483e-11
[155,] 1.00000000 1.077554e-10 5.387772e-11
[156,] 1.00000000 1.873356e-10 9.366780e-11
[157,] 1.00000000 1.403549e-10 7.017745e-11
[158,] 1.00000000 7.063039e-11 3.531519e-11
[159,] 1.00000000 1.293400e-10 6.467000e-11
[160,] 1.00000000 1.779292e-10 8.896458e-11
[161,] 1.00000000 1.229748e-10 6.148739e-11
[162,] 1.00000000 2.004190e-10 1.002095e-10
[163,] 1.00000000 1.318358e-10 6.591790e-11
[164,] 1.00000000 2.107761e-10 1.053880e-10
[165,] 1.00000000 1.558363e-11 7.791816e-12
[166,] 1.00000000 2.907805e-11 1.453903e-11
[167,] 1.00000000 3.920393e-11 1.960196e-11
[168,] 1.00000000 7.330712e-11 3.665356e-11
[169,] 1.00000000 7.186452e-11 3.593226e-11
[170,] 1.00000000 1.155673e-10 5.778364e-11
[171,] 1.00000000 2.050783e-10 1.025391e-10
[172,] 1.00000000 3.335556e-10 1.667778e-10
[173,] 1.00000000 6.040472e-10 3.020236e-10
[174,] 1.00000000 1.037576e-09 5.187880e-10
[175,] 1.00000000 8.799753e-10 4.399877e-10
[176,] 1.00000000 1.558497e-09 7.792485e-10
[177,] 1.00000000 1.398944e-09 6.994722e-10
[178,] 1.00000000 2.495331e-09 1.247666e-09
[179,] 1.00000000 6.911327e-10 3.455663e-10
[180,] 1.00000000 1.113510e-09 5.567551e-10
[181,] 1.00000000 1.978909e-09 9.894543e-10
[182,] 1.00000000 1.684269e-09 8.421347e-10
[183,] 1.00000000 2.891708e-09 1.445854e-09
[184,] 1.00000000 4.338464e-09 2.169232e-09
[185,] 1.00000000 6.276217e-09 3.138109e-09
[186,] 0.99999999 1.092430e-08 5.462150e-09
[187,] 0.99999999 1.450166e-08 7.250829e-09
[188,] 0.99999999 2.427000e-08 1.213500e-08
[189,] 0.99999998 3.060661e-08 1.530330e-08
[190,] 0.99999998 4.785759e-08 2.392880e-08
[191,] 0.99999996 7.672116e-08 3.836058e-08
[192,] 0.99999994 1.172472e-07 5.862358e-08
[193,] 0.99999992 1.532845e-07 7.664224e-08
[194,] 0.99999987 2.582340e-07 1.291170e-07
[195,] 0.99999983 3.422361e-07 1.711181e-07
[196,] 0.99999970 5.902024e-07 2.951012e-07
[197,] 0.99999971 5.886698e-07 2.943349e-07
[198,] 0.99999964 7.111143e-07 3.555571e-07
[199,] 0.99999942 1.159944e-06 5.799719e-07
[200,] 0.99999932 1.368261e-06 6.841303e-07
[201,] 0.99999889 2.211606e-06 1.105803e-06
[202,] 0.99999947 1.059852e-06 5.299261e-07
[203,] 0.99999908 1.831287e-06 9.156433e-07
[204,] 0.99999892 2.153589e-06 1.076795e-06
[205,] 0.99999855 2.892079e-06 1.446040e-06
[206,] 0.99999758 4.849120e-06 2.424560e-06
[207,] 0.99999610 7.801240e-06 3.900620e-06
[208,] 0.99999801 3.983857e-06 1.991929e-06
[209,] 0.99999783 4.338271e-06 2.169136e-06
[210,] 0.99999628 7.431713e-06 3.715857e-06
[211,] 0.99999403 1.193350e-05 5.966749e-06
[212,] 0.99999848 3.037630e-06 1.518815e-06
[213,] 0.99999898 2.034307e-06 1.017153e-06
[214,] 0.99999843 3.139130e-06 1.569565e-06
[215,] 0.99999773 4.533708e-06 2.266854e-06
[216,] 0.99999612 7.765456e-06 3.882728e-06
[217,] 0.99999323 1.353164e-05 6.765820e-06
[218,] 0.99999338 1.324959e-05 6.624795e-06
[219,] 0.99999031 1.937907e-05 9.689535e-06
[220,] 0.99999910 1.808389e-06 9.041943e-07
[221,] 0.99999848 3.049617e-06 1.524808e-06
[222,] 0.99999923 1.538288e-06 7.691440e-07
[223,] 0.99999912 1.763808e-06 8.819041e-07
[224,] 0.99999838 3.233219e-06 1.616609e-06
[225,] 0.99999819 3.622945e-06 1.811473e-06
[226,] 0.99999690 6.192186e-06 3.096093e-06
[227,] 0.99999465 1.070215e-05 5.351075e-06
[228,] 0.99999038 1.923160e-05 9.615800e-06
[229,] 0.99998250 3.500993e-05 1.750497e-05
[230,] 0.99997333 5.333661e-05 2.666830e-05
[231,] 0.99997125 5.749628e-05 2.874814e-05
[232,] 0.99999106 1.787620e-05 8.938099e-06
[233,] 0.99998314 3.371508e-05 1.685754e-05
[234,] 0.99997804 4.391586e-05 2.195793e-05
[235,] 0.99996408 7.184980e-05 3.592490e-05
[236,] 0.99993558 1.288350e-04 6.441748e-05
[237,] 0.99999324 1.352936e-05 6.764679e-06
[238,] 0.99998894 2.211245e-05 1.105622e-05
[239,] 0.99997851 4.298368e-05 2.149184e-05
[240,] 0.99996040 7.919271e-05 3.959635e-05
[241,] 0.99992756 1.448842e-04 7.244210e-05
[242,] 0.99986470 2.706025e-04 1.353012e-04
[243,] 0.99976080 4.784078e-04 2.392039e-04
[244,] 0.99956042 8.791530e-04 4.395765e-04
[245,] 0.99927064 1.458720e-03 7.293599e-04
[246,] 0.99878988 2.420234e-03 1.210117e-03
[247,] 0.99792417 4.151657e-03 2.075828e-03
[248,] 0.99680729 6.385429e-03 3.192714e-03
[249,] 0.99508676 9.826485e-03 4.913243e-03
[250,] 0.99184245 1.631509e-02 8.157545e-03
[251,] 0.99138150 1.723699e-02 8.618496e-03
[252,] 0.98582507 2.834986e-02 1.417493e-02
[253,] 0.97907734 4.184531e-02 2.092266e-02
[254,] 0.96835321 6.329358e-02 3.164679e-02
[255,] 0.95543855 8.912291e-02 4.456145e-02
[256,] 0.93760180 1.247964e-01 6.239820e-02
[257,] 0.91033631 1.793274e-01 8.966369e-02
[258,] 0.91875195 1.624961e-01 8.124805e-02
[259,] 0.88265948 2.346810e-01 1.173405e-01
[260,] 0.95437348 9.125304e-02 4.562652e-02
[261,] 0.93316226 1.336755e-01 6.683774e-02
[262,] 0.92844295 1.431141e-01 7.155705e-02
[263,] 0.90800362 1.839928e-01 9.199638e-02
[264,] 0.87839688 2.432062e-01 1.216031e-01
[265,] 0.80333433 3.933313e-01 1.966657e-01
[266,] 0.89947559 2.010488e-01 1.005244e-01
[267,] 0.81515174 3.696965e-01 1.848483e-01
[268,] 0.92448471 1.510306e-01 7.551529e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1u1ez1323901908.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2r9841323901908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3z8c31323901908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4lkgq1323901908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/51ny51323901908.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
55.840307 -207.241781 -69.122740 -392.325496 -17.400532 -72.433300
7 8 9 10 11 12
-418.355672 -65.390173 20.465817 -87.102977 47.431208 -123.869728
13 14 15 16 17 18
-66.885281 -91.435799 -120.555659 -5.559519 323.660621 -21.442222
19 20 21 22 23 24
-232.380114 -133.517689 174.256706 105.911585 -227.760734 35.808926
25 26 27 28 29 30
3.698886 -86.685854 8.917283 -80.171941 25.429861 -40.780498
31 32 33 34 35 36
-97.593446 -92.536268 40.499363 -119.000869 -43.755811 -66.802883
37 38 39 40 41 42
37.656124 -75.488542 198.756867 -94.961211 7.450642 47.894314
43 44 45 46 47 48
246.836494 -37.425838 -213.908233 -208.824803 315.048810 -160.692354
49 50 51 52 53 54
131.622115 -45.733094 -448.783835 -71.588472 185.695695 373.329069
55 56 57 58 59 60
-151.717976 64.397086 -118.116276 -486.473608 10.104148 -167.979801
61 62 63 64 65 66
187.336637 384.442509 1190.204992 4.664242 161.366561 -295.084000
67 68 69 70 71 72
-122.065327 305.388000 -85.140185 -113.794543 75.691509 -195.992252
73 74 75 76 77 78
154.800070 -37.483613 128.265114 -85.836858 -188.159686 141.074300
79 80 81 82 83 84
-157.161877 116.280619 -260.633157 -11.444297 -352.803584 -162.859289
85 86 87 88 89 90
44.411963 73.517452 -74.829728 75.539626 289.869320 -321.769061
91 92 93 94 95 96
116.404917 -247.280901 -184.422712 -23.253475 76.738583 -241.115185
97 98 99 100 101 102
19.716804 148.411356 108.987454 3.039718 88.275031 152.681350
103 104 105 106 107 108
-126.999826 22.499025 -33.920353 -135.615731 228.777501 248.099847
109 110 111 112 113 114
-82.462131 2.172147 -45.587191 -214.099124 -54.006621 61.570440
115 116 117 118 119 120
-204.587662 -203.228249 -82.223882 182.533819 -15.095522 77.370837
121 122 123 124 125 126
140.992554 -84.587062 39.238314 -69.788202 23.396330 37.860334
127 128 129 130 131 132
-32.063432 209.554464 98.901950 -54.907108 32.526279 -51.199139
133 134 135 136 137 138
-120.755556 290.297567 89.602082 -134.672372 -38.189082 -47.165897
139 140 141 142 143 144
35.761080 -143.015777 -26.912885 210.591399 -45.590347 78.728846
145 146 147 148 149 150
65.588950 212.926308 -59.181466 15.724283 -250.941593 32.534266
151 152 153 154 155 156
-54.271613 -88.569516 122.365726 -269.397612 -147.464734 145.386664
157 158 159 160 161 162
-137.025746 -97.569294 -30.564608 -421.734867 240.260224 -29.864553
163 164 165 166 167 168
-98.870231 -199.050219 -47.172713 -29.789095 -91.007204 -120.987137
169 170 171 172 173 174
19.112940 146.173694 47.044084 -41.578293 248.890078 157.671059
175 176 177 178 179 180
-186.223906 -8.747637 33.200036 22.327454 26.873733 -10.294528
181 182 183 184 185 186
54.455755 122.746477 -86.345883 72.894617 80.333460 -108.870823
187 188 189 190 191 192
-196.278288 -106.981732 269.519885 19.447190 72.355446 -144.085599
193 194 195 196 197 198
78.955645 150.688827 -6.786257 84.832667 -77.927547 -44.844661
199 200 201 202 203 204
-23.301262 -32.802695 -19.354283 -31.539402 -44.488898 21.426032
205 206 207 208 209 210
30.725843 -0.817536 157.363281 -42.976619 20.703692 2.589295
211 212 213 214 215 216
91.320628 241.977638 5.351047 -89.699616 89.605462 49.307782
217 218 219 220 221 222
7.299845 -71.511835 -31.660909 -22.847146 82.346567 427.230630
223 224 225 226 227 228
300.936260 73.523555 -86.667797 84.729443 -27.593365 -75.011941
229 230 231 232 233 234
117.877351 343.408111 59.429946 188.334867 124.164265 22.589706
235 236 237 238 239 240
-82.996533 -23.026928 60.061293 31.213485 -2.521478 -54.849838
241 242 243 244 245 246
113.843544 232.157000 -8.800747 -57.677113 -42.382535 20.093070
247 248 249 250 251 252
248.406203 -71.756169 -74.587157 -95.952925 9.630227 12.280751
253 254 255 256 257 258
-85.065648 -3.285809 -59.283361 -80.785224 -15.129688 -67.226986
259 260 261 262 263 264
-14.488883 -2.662823 -21.439254 40.977753 52.696911 56.504726
265 266 267 268 269 270
-49.610692 20.680125 -33.824178 -160.504388 -96.483729 -84.175637
271 272 273 274 275 276
161.280173 -60.454152 -20.727912 21.652739 54.535856 105.488411
277 278 279 280 281 282
79.714578 -46.546755 124.344937 -28.308199 9.026223 -24.593025
283 284 285 286 287 288
33.925050 -33.931149 -66.272984 384.503980 131.557181 83.247213
289
40.989463
> postscript(file="/var/wessaorg/rcomp/tmp/63jwm1323901908.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 55.840307 NA
1 -207.241781 55.840307
2 -69.122740 -207.241781
3 -392.325496 -69.122740
4 -17.400532 -392.325496
5 -72.433300 -17.400532
6 -418.355672 -72.433300
7 -65.390173 -418.355672
8 20.465817 -65.390173
9 -87.102977 20.465817
10 47.431208 -87.102977
11 -123.869728 47.431208
12 -66.885281 -123.869728
13 -91.435799 -66.885281
14 -120.555659 -91.435799
15 -5.559519 -120.555659
16 323.660621 -5.559519
17 -21.442222 323.660621
18 -232.380114 -21.442222
19 -133.517689 -232.380114
20 174.256706 -133.517689
21 105.911585 174.256706
22 -227.760734 105.911585
23 35.808926 -227.760734
24 3.698886 35.808926
25 -86.685854 3.698886
26 8.917283 -86.685854
27 -80.171941 8.917283
28 25.429861 -80.171941
29 -40.780498 25.429861
30 -97.593446 -40.780498
31 -92.536268 -97.593446
32 40.499363 -92.536268
33 -119.000869 40.499363
34 -43.755811 -119.000869
35 -66.802883 -43.755811
36 37.656124 -66.802883
37 -75.488542 37.656124
38 198.756867 -75.488542
39 -94.961211 198.756867
40 7.450642 -94.961211
41 47.894314 7.450642
42 246.836494 47.894314
43 -37.425838 246.836494
44 -213.908233 -37.425838
45 -208.824803 -213.908233
46 315.048810 -208.824803
47 -160.692354 315.048810
48 131.622115 -160.692354
49 -45.733094 131.622115
50 -448.783835 -45.733094
51 -71.588472 -448.783835
52 185.695695 -71.588472
53 373.329069 185.695695
54 -151.717976 373.329069
55 64.397086 -151.717976
56 -118.116276 64.397086
57 -486.473608 -118.116276
58 10.104148 -486.473608
59 -167.979801 10.104148
60 187.336637 -167.979801
61 384.442509 187.336637
62 1190.204992 384.442509
63 4.664242 1190.204992
64 161.366561 4.664242
65 -295.084000 161.366561
66 -122.065327 -295.084000
67 305.388000 -122.065327
68 -85.140185 305.388000
69 -113.794543 -85.140185
70 75.691509 -113.794543
71 -195.992252 75.691509
72 154.800070 -195.992252
73 -37.483613 154.800070
74 128.265114 -37.483613
75 -85.836858 128.265114
76 -188.159686 -85.836858
77 141.074300 -188.159686
78 -157.161877 141.074300
79 116.280619 -157.161877
80 -260.633157 116.280619
81 -11.444297 -260.633157
82 -352.803584 -11.444297
83 -162.859289 -352.803584
84 44.411963 -162.859289
85 73.517452 44.411963
86 -74.829728 73.517452
87 75.539626 -74.829728
88 289.869320 75.539626
89 -321.769061 289.869320
90 116.404917 -321.769061
91 -247.280901 116.404917
92 -184.422712 -247.280901
93 -23.253475 -184.422712
94 76.738583 -23.253475
95 -241.115185 76.738583
96 19.716804 -241.115185
97 148.411356 19.716804
98 108.987454 148.411356
99 3.039718 108.987454
100 88.275031 3.039718
101 152.681350 88.275031
102 -126.999826 152.681350
103 22.499025 -126.999826
104 -33.920353 22.499025
105 -135.615731 -33.920353
106 228.777501 -135.615731
107 248.099847 228.777501
108 -82.462131 248.099847
109 2.172147 -82.462131
110 -45.587191 2.172147
111 -214.099124 -45.587191
112 -54.006621 -214.099124
113 61.570440 -54.006621
114 -204.587662 61.570440
115 -203.228249 -204.587662
116 -82.223882 -203.228249
117 182.533819 -82.223882
118 -15.095522 182.533819
119 77.370837 -15.095522
120 140.992554 77.370837
121 -84.587062 140.992554
122 39.238314 -84.587062
123 -69.788202 39.238314
124 23.396330 -69.788202
125 37.860334 23.396330
126 -32.063432 37.860334
127 209.554464 -32.063432
128 98.901950 209.554464
129 -54.907108 98.901950
130 32.526279 -54.907108
131 -51.199139 32.526279
132 -120.755556 -51.199139
133 290.297567 -120.755556
134 89.602082 290.297567
135 -134.672372 89.602082
136 -38.189082 -134.672372
137 -47.165897 -38.189082
138 35.761080 -47.165897
139 -143.015777 35.761080
140 -26.912885 -143.015777
141 210.591399 -26.912885
142 -45.590347 210.591399
143 78.728846 -45.590347
144 65.588950 78.728846
145 212.926308 65.588950
146 -59.181466 212.926308
147 15.724283 -59.181466
148 -250.941593 15.724283
149 32.534266 -250.941593
150 -54.271613 32.534266
151 -88.569516 -54.271613
152 122.365726 -88.569516
153 -269.397612 122.365726
154 -147.464734 -269.397612
155 145.386664 -147.464734
156 -137.025746 145.386664
157 -97.569294 -137.025746
158 -30.564608 -97.569294
159 -421.734867 -30.564608
160 240.260224 -421.734867
161 -29.864553 240.260224
162 -98.870231 -29.864553
163 -199.050219 -98.870231
164 -47.172713 -199.050219
165 -29.789095 -47.172713
166 -91.007204 -29.789095
167 -120.987137 -91.007204
168 19.112940 -120.987137
169 146.173694 19.112940
170 47.044084 146.173694
171 -41.578293 47.044084
172 248.890078 -41.578293
173 157.671059 248.890078
174 -186.223906 157.671059
175 -8.747637 -186.223906
176 33.200036 -8.747637
177 22.327454 33.200036
178 26.873733 22.327454
179 -10.294528 26.873733
180 54.455755 -10.294528
181 122.746477 54.455755
182 -86.345883 122.746477
183 72.894617 -86.345883
184 80.333460 72.894617
185 -108.870823 80.333460
186 -196.278288 -108.870823
187 -106.981732 -196.278288
188 269.519885 -106.981732
189 19.447190 269.519885
190 72.355446 19.447190
191 -144.085599 72.355446
192 78.955645 -144.085599
193 150.688827 78.955645
194 -6.786257 150.688827
195 84.832667 -6.786257
196 -77.927547 84.832667
197 -44.844661 -77.927547
198 -23.301262 -44.844661
199 -32.802695 -23.301262
200 -19.354283 -32.802695
201 -31.539402 -19.354283
202 -44.488898 -31.539402
203 21.426032 -44.488898
204 30.725843 21.426032
205 -0.817536 30.725843
206 157.363281 -0.817536
207 -42.976619 157.363281
208 20.703692 -42.976619
209 2.589295 20.703692
210 91.320628 2.589295
211 241.977638 91.320628
212 5.351047 241.977638
213 -89.699616 5.351047
214 89.605462 -89.699616
215 49.307782 89.605462
216 7.299845 49.307782
217 -71.511835 7.299845
218 -31.660909 -71.511835
219 -22.847146 -31.660909
220 82.346567 -22.847146
221 427.230630 82.346567
222 300.936260 427.230630
223 73.523555 300.936260
224 -86.667797 73.523555
225 84.729443 -86.667797
226 -27.593365 84.729443
227 -75.011941 -27.593365
228 117.877351 -75.011941
229 343.408111 117.877351
230 59.429946 343.408111
231 188.334867 59.429946
232 124.164265 188.334867
233 22.589706 124.164265
234 -82.996533 22.589706
235 -23.026928 -82.996533
236 60.061293 -23.026928
237 31.213485 60.061293
238 -2.521478 31.213485
239 -54.849838 -2.521478
240 113.843544 -54.849838
241 232.157000 113.843544
242 -8.800747 232.157000
243 -57.677113 -8.800747
244 -42.382535 -57.677113
245 20.093070 -42.382535
246 248.406203 20.093070
247 -71.756169 248.406203
248 -74.587157 -71.756169
249 -95.952925 -74.587157
250 9.630227 -95.952925
251 12.280751 9.630227
252 -85.065648 12.280751
253 -3.285809 -85.065648
254 -59.283361 -3.285809
255 -80.785224 -59.283361
256 -15.129688 -80.785224
257 -67.226986 -15.129688
258 -14.488883 -67.226986
259 -2.662823 -14.488883
260 -21.439254 -2.662823
261 40.977753 -21.439254
262 52.696911 40.977753
263 56.504726 52.696911
264 -49.610692 56.504726
265 20.680125 -49.610692
266 -33.824178 20.680125
267 -160.504388 -33.824178
268 -96.483729 -160.504388
269 -84.175637 -96.483729
270 161.280173 -84.175637
271 -60.454152 161.280173
272 -20.727912 -60.454152
273 21.652739 -20.727912
274 54.535856 21.652739
275 105.488411 54.535856
276 79.714578 105.488411
277 -46.546755 79.714578
278 124.344937 -46.546755
279 -28.308199 124.344937
280 9.026223 -28.308199
281 -24.593025 9.026223
282 33.925050 -24.593025
283 -33.931149 33.925050
284 -66.272984 -33.931149
285 384.503980 -66.272984
286 131.557181 384.503980
287 83.247213 131.557181
288 40.989463 83.247213
289 NA 40.989463
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -207.241781 55.840307
[2,] -69.122740 -207.241781
[3,] -392.325496 -69.122740
[4,] -17.400532 -392.325496
[5,] -72.433300 -17.400532
[6,] -418.355672 -72.433300
[7,] -65.390173 -418.355672
[8,] 20.465817 -65.390173
[9,] -87.102977 20.465817
[10,] 47.431208 -87.102977
[11,] -123.869728 47.431208
[12,] -66.885281 -123.869728
[13,] -91.435799 -66.885281
[14,] -120.555659 -91.435799
[15,] -5.559519 -120.555659
[16,] 323.660621 -5.559519
[17,] -21.442222 323.660621
[18,] -232.380114 -21.442222
[19,] -133.517689 -232.380114
[20,] 174.256706 -133.517689
[21,] 105.911585 174.256706
[22,] -227.760734 105.911585
[23,] 35.808926 -227.760734
[24,] 3.698886 35.808926
[25,] -86.685854 3.698886
[26,] 8.917283 -86.685854
[27,] -80.171941 8.917283
[28,] 25.429861 -80.171941
[29,] -40.780498 25.429861
[30,] -97.593446 -40.780498
[31,] -92.536268 -97.593446
[32,] 40.499363 -92.536268
[33,] -119.000869 40.499363
[34,] -43.755811 -119.000869
[35,] -66.802883 -43.755811
[36,] 37.656124 -66.802883
[37,] -75.488542 37.656124
[38,] 198.756867 -75.488542
[39,] -94.961211 198.756867
[40,] 7.450642 -94.961211
[41,] 47.894314 7.450642
[42,] 246.836494 47.894314
[43,] -37.425838 246.836494
[44,] -213.908233 -37.425838
[45,] -208.824803 -213.908233
[46,] 315.048810 -208.824803
[47,] -160.692354 315.048810
[48,] 131.622115 -160.692354
[49,] -45.733094 131.622115
[50,] -448.783835 -45.733094
[51,] -71.588472 -448.783835
[52,] 185.695695 -71.588472
[53,] 373.329069 185.695695
[54,] -151.717976 373.329069
[55,] 64.397086 -151.717976
[56,] -118.116276 64.397086
[57,] -486.473608 -118.116276
[58,] 10.104148 -486.473608
[59,] -167.979801 10.104148
[60,] 187.336637 -167.979801
[61,] 384.442509 187.336637
[62,] 1190.204992 384.442509
[63,] 4.664242 1190.204992
[64,] 161.366561 4.664242
[65,] -295.084000 161.366561
[66,] -122.065327 -295.084000
[67,] 305.388000 -122.065327
[68,] -85.140185 305.388000
[69,] -113.794543 -85.140185
[70,] 75.691509 -113.794543
[71,] -195.992252 75.691509
[72,] 154.800070 -195.992252
[73,] -37.483613 154.800070
[74,] 128.265114 -37.483613
[75,] -85.836858 128.265114
[76,] -188.159686 -85.836858
[77,] 141.074300 -188.159686
[78,] -157.161877 141.074300
[79,] 116.280619 -157.161877
[80,] -260.633157 116.280619
[81,] -11.444297 -260.633157
[82,] -352.803584 -11.444297
[83,] -162.859289 -352.803584
[84,] 44.411963 -162.859289
[85,] 73.517452 44.411963
[86,] -74.829728 73.517452
[87,] 75.539626 -74.829728
[88,] 289.869320 75.539626
[89,] -321.769061 289.869320
[90,] 116.404917 -321.769061
[91,] -247.280901 116.404917
[92,] -184.422712 -247.280901
[93,] -23.253475 -184.422712
[94,] 76.738583 -23.253475
[95,] -241.115185 76.738583
[96,] 19.716804 -241.115185
[97,] 148.411356 19.716804
[98,] 108.987454 148.411356
[99,] 3.039718 108.987454
[100,] 88.275031 3.039718
[101,] 152.681350 88.275031
[102,] -126.999826 152.681350
[103,] 22.499025 -126.999826
[104,] -33.920353 22.499025
[105,] -135.615731 -33.920353
[106,] 228.777501 -135.615731
[107,] 248.099847 228.777501
[108,] -82.462131 248.099847
[109,] 2.172147 -82.462131
[110,] -45.587191 2.172147
[111,] -214.099124 -45.587191
[112,] -54.006621 -214.099124
[113,] 61.570440 -54.006621
[114,] -204.587662 61.570440
[115,] -203.228249 -204.587662
[116,] -82.223882 -203.228249
[117,] 182.533819 -82.223882
[118,] -15.095522 182.533819
[119,] 77.370837 -15.095522
[120,] 140.992554 77.370837
[121,] -84.587062 140.992554
[122,] 39.238314 -84.587062
[123,] -69.788202 39.238314
[124,] 23.396330 -69.788202
[125,] 37.860334 23.396330
[126,] -32.063432 37.860334
[127,] 209.554464 -32.063432
[128,] 98.901950 209.554464
[129,] -54.907108 98.901950
[130,] 32.526279 -54.907108
[131,] -51.199139 32.526279
[132,] -120.755556 -51.199139
[133,] 290.297567 -120.755556
[134,] 89.602082 290.297567
[135,] -134.672372 89.602082
[136,] -38.189082 -134.672372
[137,] -47.165897 -38.189082
[138,] 35.761080 -47.165897
[139,] -143.015777 35.761080
[140,] -26.912885 -143.015777
[141,] 210.591399 -26.912885
[142,] -45.590347 210.591399
[143,] 78.728846 -45.590347
[144,] 65.588950 78.728846
[145,] 212.926308 65.588950
[146,] -59.181466 212.926308
[147,] 15.724283 -59.181466
[148,] -250.941593 15.724283
[149,] 32.534266 -250.941593
[150,] -54.271613 32.534266
[151,] -88.569516 -54.271613
[152,] 122.365726 -88.569516
[153,] -269.397612 122.365726
[154,] -147.464734 -269.397612
[155,] 145.386664 -147.464734
[156,] -137.025746 145.386664
[157,] -97.569294 -137.025746
[158,] -30.564608 -97.569294
[159,] -421.734867 -30.564608
[160,] 240.260224 -421.734867
[161,] -29.864553 240.260224
[162,] -98.870231 -29.864553
[163,] -199.050219 -98.870231
[164,] -47.172713 -199.050219
[165,] -29.789095 -47.172713
[166,] -91.007204 -29.789095
[167,] -120.987137 -91.007204
[168,] 19.112940 -120.987137
[169,] 146.173694 19.112940
[170,] 47.044084 146.173694
[171,] -41.578293 47.044084
[172,] 248.890078 -41.578293
[173,] 157.671059 248.890078
[174,] -186.223906 157.671059
[175,] -8.747637 -186.223906
[176,] 33.200036 -8.747637
[177,] 22.327454 33.200036
[178,] 26.873733 22.327454
[179,] -10.294528 26.873733
[180,] 54.455755 -10.294528
[181,] 122.746477 54.455755
[182,] -86.345883 122.746477
[183,] 72.894617 -86.345883
[184,] 80.333460 72.894617
[185,] -108.870823 80.333460
[186,] -196.278288 -108.870823
[187,] -106.981732 -196.278288
[188,] 269.519885 -106.981732
[189,] 19.447190 269.519885
[190,] 72.355446 19.447190
[191,] -144.085599 72.355446
[192,] 78.955645 -144.085599
[193,] 150.688827 78.955645
[194,] -6.786257 150.688827
[195,] 84.832667 -6.786257
[196,] -77.927547 84.832667
[197,] -44.844661 -77.927547
[198,] -23.301262 -44.844661
[199,] -32.802695 -23.301262
[200,] -19.354283 -32.802695
[201,] -31.539402 -19.354283
[202,] -44.488898 -31.539402
[203,] 21.426032 -44.488898
[204,] 30.725843 21.426032
[205,] -0.817536 30.725843
[206,] 157.363281 -0.817536
[207,] -42.976619 157.363281
[208,] 20.703692 -42.976619
[209,] 2.589295 20.703692
[210,] 91.320628 2.589295
[211,] 241.977638 91.320628
[212,] 5.351047 241.977638
[213,] -89.699616 5.351047
[214,] 89.605462 -89.699616
[215,] 49.307782 89.605462
[216,] 7.299845 49.307782
[217,] -71.511835 7.299845
[218,] -31.660909 -71.511835
[219,] -22.847146 -31.660909
[220,] 82.346567 -22.847146
[221,] 427.230630 82.346567
[222,] 300.936260 427.230630
[223,] 73.523555 300.936260
[224,] -86.667797 73.523555
[225,] 84.729443 -86.667797
[226,] -27.593365 84.729443
[227,] -75.011941 -27.593365
[228,] 117.877351 -75.011941
[229,] 343.408111 117.877351
[230,] 59.429946 343.408111
[231,] 188.334867 59.429946
[232,] 124.164265 188.334867
[233,] 22.589706 124.164265
[234,] -82.996533 22.589706
[235,] -23.026928 -82.996533
[236,] 60.061293 -23.026928
[237,] 31.213485 60.061293
[238,] -2.521478 31.213485
[239,] -54.849838 -2.521478
[240,] 113.843544 -54.849838
[241,] 232.157000 113.843544
[242,] -8.800747 232.157000
[243,] -57.677113 -8.800747
[244,] -42.382535 -57.677113
[245,] 20.093070 -42.382535
[246,] 248.406203 20.093070
[247,] -71.756169 248.406203
[248,] -74.587157 -71.756169
[249,] -95.952925 -74.587157
[250,] 9.630227 -95.952925
[251,] 12.280751 9.630227
[252,] -85.065648 12.280751
[253,] -3.285809 -85.065648
[254,] -59.283361 -3.285809
[255,] -80.785224 -59.283361
[256,] -15.129688 -80.785224
[257,] -67.226986 -15.129688
[258,] -14.488883 -67.226986
[259,] -2.662823 -14.488883
[260,] -21.439254 -2.662823
[261,] 40.977753 -21.439254
[262,] 52.696911 40.977753
[263,] 56.504726 52.696911
[264,] -49.610692 56.504726
[265,] 20.680125 -49.610692
[266,] -33.824178 20.680125
[267,] -160.504388 -33.824178
[268,] -96.483729 -160.504388
[269,] -84.175637 -96.483729
[270,] 161.280173 -84.175637
[271,] -60.454152 161.280173
[272,] -20.727912 -60.454152
[273,] 21.652739 -20.727912
[274,] 54.535856 21.652739
[275,] 105.488411 54.535856
[276,] 79.714578 105.488411
[277,] -46.546755 79.714578
[278,] 124.344937 -46.546755
[279,] -28.308199 124.344937
[280,] 9.026223 -28.308199
[281,] -24.593025 9.026223
[282,] 33.925050 -24.593025
[283,] -33.931149 33.925050
[284,] -66.272984 -33.931149
[285,] 384.503980 -66.272984
[286,] 131.557181 384.503980
[287,] 83.247213 131.557181
[288,] 40.989463 83.247213
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -207.241781 55.840307
2 -69.122740 -207.241781
3 -392.325496 -69.122740
4 -17.400532 -392.325496
5 -72.433300 -17.400532
6 -418.355672 -72.433300
7 -65.390173 -418.355672
8 20.465817 -65.390173
9 -87.102977 20.465817
10 47.431208 -87.102977
11 -123.869728 47.431208
12 -66.885281 -123.869728
13 -91.435799 -66.885281
14 -120.555659 -91.435799
15 -5.559519 -120.555659
16 323.660621 -5.559519
17 -21.442222 323.660621
18 -232.380114 -21.442222
19 -133.517689 -232.380114
20 174.256706 -133.517689
21 105.911585 174.256706
22 -227.760734 105.911585
23 35.808926 -227.760734
24 3.698886 35.808926
25 -86.685854 3.698886
26 8.917283 -86.685854
27 -80.171941 8.917283
28 25.429861 -80.171941
29 -40.780498 25.429861
30 -97.593446 -40.780498
31 -92.536268 -97.593446
32 40.499363 -92.536268
33 -119.000869 40.499363
34 -43.755811 -119.000869
35 -66.802883 -43.755811
36 37.656124 -66.802883
37 -75.488542 37.656124
38 198.756867 -75.488542
39 -94.961211 198.756867
40 7.450642 -94.961211
41 47.894314 7.450642
42 246.836494 47.894314
43 -37.425838 246.836494
44 -213.908233 -37.425838
45 -208.824803 -213.908233
46 315.048810 -208.824803
47 -160.692354 315.048810
48 131.622115 -160.692354
49 -45.733094 131.622115
50 -448.783835 -45.733094
51 -71.588472 -448.783835
52 185.695695 -71.588472
53 373.329069 185.695695
54 -151.717976 373.329069
55 64.397086 -151.717976
56 -118.116276 64.397086
57 -486.473608 -118.116276
58 10.104148 -486.473608
59 -167.979801 10.104148
60 187.336637 -167.979801
61 384.442509 187.336637
62 1190.204992 384.442509
63 4.664242 1190.204992
64 161.366561 4.664242
65 -295.084000 161.366561
66 -122.065327 -295.084000
67 305.388000 -122.065327
68 -85.140185 305.388000
69 -113.794543 -85.140185
70 75.691509 -113.794543
71 -195.992252 75.691509
72 154.800070 -195.992252
73 -37.483613 154.800070
74 128.265114 -37.483613
75 -85.836858 128.265114
76 -188.159686 -85.836858
77 141.074300 -188.159686
78 -157.161877 141.074300
79 116.280619 -157.161877
80 -260.633157 116.280619
81 -11.444297 -260.633157
82 -352.803584 -11.444297
83 -162.859289 -352.803584
84 44.411963 -162.859289
85 73.517452 44.411963
86 -74.829728 73.517452
87 75.539626 -74.829728
88 289.869320 75.539626
89 -321.769061 289.869320
90 116.404917 -321.769061
91 -247.280901 116.404917
92 -184.422712 -247.280901
93 -23.253475 -184.422712
94 76.738583 -23.253475
95 -241.115185 76.738583
96 19.716804 -241.115185
97 148.411356 19.716804
98 108.987454 148.411356
99 3.039718 108.987454
100 88.275031 3.039718
101 152.681350 88.275031
102 -126.999826 152.681350
103 22.499025 -126.999826
104 -33.920353 22.499025
105 -135.615731 -33.920353
106 228.777501 -135.615731
107 248.099847 228.777501
108 -82.462131 248.099847
109 2.172147 -82.462131
110 -45.587191 2.172147
111 -214.099124 -45.587191
112 -54.006621 -214.099124
113 61.570440 -54.006621
114 -204.587662 61.570440
115 -203.228249 -204.587662
116 -82.223882 -203.228249
117 182.533819 -82.223882
118 -15.095522 182.533819
119 77.370837 -15.095522
120 140.992554 77.370837
121 -84.587062 140.992554
122 39.238314 -84.587062
123 -69.788202 39.238314
124 23.396330 -69.788202
125 37.860334 23.396330
126 -32.063432 37.860334
127 209.554464 -32.063432
128 98.901950 209.554464
129 -54.907108 98.901950
130 32.526279 -54.907108
131 -51.199139 32.526279
132 -120.755556 -51.199139
133 290.297567 -120.755556
134 89.602082 290.297567
135 -134.672372 89.602082
136 -38.189082 -134.672372
137 -47.165897 -38.189082
138 35.761080 -47.165897
139 -143.015777 35.761080
140 -26.912885 -143.015777
141 210.591399 -26.912885
142 -45.590347 210.591399
143 78.728846 -45.590347
144 65.588950 78.728846
145 212.926308 65.588950
146 -59.181466 212.926308
147 15.724283 -59.181466
148 -250.941593 15.724283
149 32.534266 -250.941593
150 -54.271613 32.534266
151 -88.569516 -54.271613
152 122.365726 -88.569516
153 -269.397612 122.365726
154 -147.464734 -269.397612
155 145.386664 -147.464734
156 -137.025746 145.386664
157 -97.569294 -137.025746
158 -30.564608 -97.569294
159 -421.734867 -30.564608
160 240.260224 -421.734867
161 -29.864553 240.260224
162 -98.870231 -29.864553
163 -199.050219 -98.870231
164 -47.172713 -199.050219
165 -29.789095 -47.172713
166 -91.007204 -29.789095
167 -120.987137 -91.007204
168 19.112940 -120.987137
169 146.173694 19.112940
170 47.044084 146.173694
171 -41.578293 47.044084
172 248.890078 -41.578293
173 157.671059 248.890078
174 -186.223906 157.671059
175 -8.747637 -186.223906
176 33.200036 -8.747637
177 22.327454 33.200036
178 26.873733 22.327454
179 -10.294528 26.873733
180 54.455755 -10.294528
181 122.746477 54.455755
182 -86.345883 122.746477
183 72.894617 -86.345883
184 80.333460 72.894617
185 -108.870823 80.333460
186 -196.278288 -108.870823
187 -106.981732 -196.278288
188 269.519885 -106.981732
189 19.447190 269.519885
190 72.355446 19.447190
191 -144.085599 72.355446
192 78.955645 -144.085599
193 150.688827 78.955645
194 -6.786257 150.688827
195 84.832667 -6.786257
196 -77.927547 84.832667
197 -44.844661 -77.927547
198 -23.301262 -44.844661
199 -32.802695 -23.301262
200 -19.354283 -32.802695
201 -31.539402 -19.354283
202 -44.488898 -31.539402
203 21.426032 -44.488898
204 30.725843 21.426032
205 -0.817536 30.725843
206 157.363281 -0.817536
207 -42.976619 157.363281
208 20.703692 -42.976619
209 2.589295 20.703692
210 91.320628 2.589295
211 241.977638 91.320628
212 5.351047 241.977638
213 -89.699616 5.351047
214 89.605462 -89.699616
215 49.307782 89.605462
216 7.299845 49.307782
217 -71.511835 7.299845
218 -31.660909 -71.511835
219 -22.847146 -31.660909
220 82.346567 -22.847146
221 427.230630 82.346567
222 300.936260 427.230630
223 73.523555 300.936260
224 -86.667797 73.523555
225 84.729443 -86.667797
226 -27.593365 84.729443
227 -75.011941 -27.593365
228 117.877351 -75.011941
229 343.408111 117.877351
230 59.429946 343.408111
231 188.334867 59.429946
232 124.164265 188.334867
233 22.589706 124.164265
234 -82.996533 22.589706
235 -23.026928 -82.996533
236 60.061293 -23.026928
237 31.213485 60.061293
238 -2.521478 31.213485
239 -54.849838 -2.521478
240 113.843544 -54.849838
241 232.157000 113.843544
242 -8.800747 232.157000
243 -57.677113 -8.800747
244 -42.382535 -57.677113
245 20.093070 -42.382535
246 248.406203 20.093070
247 -71.756169 248.406203
248 -74.587157 -71.756169
249 -95.952925 -74.587157
250 9.630227 -95.952925
251 12.280751 9.630227
252 -85.065648 12.280751
253 -3.285809 -85.065648
254 -59.283361 -3.285809
255 -80.785224 -59.283361
256 -15.129688 -80.785224
257 -67.226986 -15.129688
258 -14.488883 -67.226986
259 -2.662823 -14.488883
260 -21.439254 -2.662823
261 40.977753 -21.439254
262 52.696911 40.977753
263 56.504726 52.696911
264 -49.610692 56.504726
265 20.680125 -49.610692
266 -33.824178 20.680125
267 -160.504388 -33.824178
268 -96.483729 -160.504388
269 -84.175637 -96.483729
270 161.280173 -84.175637
271 -60.454152 161.280173
272 -20.727912 -60.454152
273 21.652739 -20.727912
274 54.535856 21.652739
275 105.488411 54.535856
276 79.714578 105.488411
277 -46.546755 79.714578
278 124.344937 -46.546755
279 -28.308199 124.344937
280 9.026223 -28.308199
281 -24.593025 9.026223
282 33.925050 -24.593025
283 -33.931149 33.925050
284 -66.272984 -33.931149
285 384.503980 -66.272984
286 131.557181 384.503980
287 83.247213 131.557181
288 40.989463 83.247213
> 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/7v20u1323901908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/84b6y1323901908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9cky31323901908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10u78t1323901908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11gkx11323901908.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/125es61323901908.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/131qc41323901909.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/1499r51323901909.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/15brzf1323901909.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/1626ef1323901909.tab")
+ }
>
> try(system("convert tmp/1u1ez1323901908.ps tmp/1u1ez1323901908.png",intern=TRUE))
character(0)
> try(system("convert tmp/2r9841323901908.ps tmp/2r9841323901908.png",intern=TRUE))
character(0)
> try(system("convert tmp/3z8c31323901908.ps tmp/3z8c31323901908.png",intern=TRUE))
character(0)
> try(system("convert tmp/4lkgq1323901908.ps tmp/4lkgq1323901908.png",intern=TRUE))
character(0)
> try(system("convert tmp/51ny51323901908.ps tmp/51ny51323901908.png",intern=TRUE))
character(0)
> try(system("convert tmp/63jwm1323901908.ps tmp/63jwm1323901908.png",intern=TRUE))
character(0)
> try(system("convert tmp/7v20u1323901908.ps tmp/7v20u1323901908.png",intern=TRUE))
character(0)
> try(system("convert tmp/84b6y1323901908.ps tmp/84b6y1323901908.png",intern=TRUE))
character(0)
> try(system("convert tmp/9cky31323901908.ps tmp/9cky31323901908.png",intern=TRUE))
character(0)
> try(system("convert tmp/10u78t1323901908.ps tmp/10u78t1323901908.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
8.681 0.602 9.369