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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Type 'q()' to quit R.
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+ ,8
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+ ,0
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+ ,947
+ ,50857
+ ,21
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+ ,0
+ ,15
+ ,20
+ ,819
+ ,56613
+ ,19
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+ ,1
+ ,15
+ ,12
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+ ,62792
+ ,35
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+ ,46
+ ,0
+ ,28
+ ,15
+ ,894
+ ,72535
+ ,14
+ ,329
+ ,44
+ ,0
+ ,17
+ ,16)
+ ,dim=c(8
+ ,277)
+ ,dimnames=list(c('Pageviews'
+ ,'Time_in_rfc'
+ ,'Logins'
+ ,'Compendium_views_info'
+ ,'Compendium_views_pr'
+ ,'Shared_compendiums'
+ ,'Blogged_computations'
+ ,'Compendium_reviewed
')
+ ,1:277))
> y <- array(NA,dim=c(8,277),dimnames=list(c('Pageviews','Time_in_rfc','Logins','Compendium_views_info','Compendium_views_pr','Shared_compendiums','Blogged_computations','Compendium_reviewed
'),1:277))
> 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'
> 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
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
Pageviews Time_in_rfc Logins Compendium_views_info Compendium_views_pr
1 1495 173326 88 465 49
2 1373 133131 55 525 52
3 2187 258873 60 885 88
4 1491 180083 66 497 36
5 4041 324799 154 1436 108
6 1706 230964 53 612 43
7 2152 236785 119 865 75
8 1036 135473 41 385 32
9 1882 202925 61 567 44
10 1929 215147 58 639 85
11 2242 344297 75 963 86
12 1220 153935 33 398 56
13 1289 132943 40 410 50
14 2515 174724 92 966 135
15 2147 174415 100 801 63
16 2352 225548 112 892 81
17 1638 223632 73 513 52
18 1222 124817 40 469 44
19 1812 221698 45 683 113
20 1677 210767 60 643 39
21 1579 170266 62 535 73
22 1731 260561 75 625 48
23 807 84853 31 264 33
24 2452 294424 77 992 59
25 829 101011 34 238 41
26 1940 215641 46 818 69
27 2662 325107 99 937 64
28 186 7176 17 70 1
29 1499 167542 66 507 59
30 865 106408 30 260 32
31 1793 96560 76 503 129
32 2527 265769 146 927 37
33 2747 269651 67 1269 31
34 1324 149112 56 537 65
35 2702 175824 107 910 107
36 1383 152871 58 532 74
37 1179 111665 34 345 54
38 2099 116408 61 918 76
39 4308 362301 119 1635 715
40 918 78800 42 330 57
41 1831 183167 66 557 66
42 3373 277965 89 1178 106
43 1713 150629 44 740 54
44 1438 168809 66 452 32
45 496 24188 24 218 20
46 2253 329267 259 764 71
47 744 65029 17 255 21
48 1161 101097 64 454 70
49 2352 218946 41 866 112
50 2144 244052 68 574 66
51 4691 341570 168 1276 190
52 1112 103597 43 379 66
53 2694 233328 132 825 165
54 1973 256462 105 798 56
55 1769 206161 71 663 61
56 3148 311473 112 1069 53
57 2474 235800 94 921 127
58 2084 177939 82 858 63
59 1954 207176 70 711 38
60 1226 196553 57 503 50
61 1389 174184 53 382 52
62 1496 143246 103 464 42
63 2269 187559 121 717 76
64 1833 187681 62 690 67
65 1268 119016 52 462 50
66 1943 182192 52 657 53
67 893 73566 32 385 39
68 1762 194979 62 577 50
69 1403 167488 45 619 77
70 1425 143756 46 479 57
71 1857 275541 63 817 73
72 1840 243199 75 752 34
73 1502 182999 88 430 39
74 1441 135649 46 451 46
75 1420 152299 53 537 63
76 1416 120221 37 519 35
77 2970 346485 90 1000 106
78 1317 145790 63 637 43
79 1644 193339 78 465 47
80 870 80953 25 437 31
81 1654 122774 45 711 162
82 1054 130585 46 299 57
83 937 112611 41 248 36
84 3004 286468 144 1162 263
85 2008 241066 82 714 78
86 2547 148446 91 905 63
87 1885 204713 71 649 54
88 1626 182079 63 512 63
89 1468 140344 53 472 77
90 2445 220516 62 905 79
91 1964 243060 63 786 110
92 1381 162765 32 489 56
93 1369 182613 39 479 56
94 1659 232138 62 617 43
95 2888 265318 117 925 111
96 1290 85574 34 351 71
97 2845 310839 92 1144 62
98 1982 225060 93 669 56
99 1904 232317 54 707 74
100 1391 144966 144 458 60
101 602 43287 14 214 43
102 1743 155754 61 599 68
103 1559 164709 109 572 53
104 2014 201940 38 897 87
105 2143 235454 73 819 46
106 2146 220801 75 720 105
107 874 99466 50 273 32
108 1590 92661 61 508 133
109 1590 133328 55 506 79
110 1210 61361 77 451 51
111 2072 125930 75 699 207
112 1281 100750 72 407 67
113 1401 224549 50 465 47
114 834 82316 32 245 34
115 1105 102010 53 370 66
116 1272 101523 42 316 76
117 1944 243511 71 603 65
118 391 22938 10 154 9
119 761 41566 35 229 42
120 1605 152474 65 577 45
121 530 61857 25 192 25
122 1988 99923 66 617 115
123 1386 132487 41 411 97
124 2395 317394 86 975 53
125 387 21054 16 146 2
126 1742 209641 42 705 52
127 620 22648 19 184 44
128 449 31414 19 200 22
129 800 46698 45 274 35
130 1684 131698 65 502 74
131 1050 91735 35 382 103
132 2699 244749 95 964 144
133 1606 184510 49 537 60
134 1502 79863 37 438 134
135 1204 128423 64 369 89
136 1138 97839 38 417 42
137 568 38214 34 276 52
138 1459 151101 32 514 98
139 2158 272458 65 822 99
140 1111 172494 52 389 52
141 1421 108043 62 466 29
142 2833 328107 65 1255 125
143 1955 250579 83 694 106
144 2922 351067 95 1024 95
145 1002 158015 29 400 40
146 1060 98866 18 397 140
147 956 85439 33 350 43
148 2186 229242 247 719 128
149 3604 351619 139 1277 142
150 1035 84207 29 356 73
151 1417 120445 118 457 72
152 3261 324598 110 1402 128
153 1587 131069 67 600 61
154 1424 204271 42 480 73
155 1701 165543 65 595 148
156 1249 141722 94 436 64
157 946 116048 64 230 45
158 1926 250047 81 651 58
159 3352 299775 95 1367 97
160 1641 195838 67 564 50
161 2035 173260 63 716 37
162 2312 254488 83 747 50
163 1369 104389 45 467 105
164 1577 136084 30 671 69
165 2201 199476 70 861 46
166 961 92499 32 319 57
167 1900 224330 83 612 52
168 1254 135781 31 433 98
169 1335 74408 67 434 61
170 1597 81240 66 503 89
171 207 14688 10 85 0
172 1645 181633 70 564 48
173 2429 271856 103 824 91
174 151 7199 5 74 0
175 474 46660 20 259 7
176 141 17547 5 69 3
177 1639 133368 36 535 54
178 872 95227 34 239 70
179 1318 152601 48 438 36
180 1018 98146 40 459 37
181 1383 79619 43 426 123
182 1314 59194 31 288 247
183 1335 139942 42 498 46
184 1403 118612 46 454 72
185 910 72880 33 376 41
186 616 65475 18 225 24
187 1407 99643 55 555 45
188 771 71965 35 252 33
189 766 77272 59 208 27
190 473 49289 19 130 36
191 1376 135131 66 481 87
192 1232 108446 60 389 90
193 1521 89746 36 565 114
194 572 44296 25 173 31
195 1059 77648 47 278 45
196 1544 181528 54 609 69
197 1230 134019 53 422 51
198 1206 124064 40 445 34
199 1205 92630 40 387 60
200 1255 121848 39 339 45
201 613 52915 14 181 54
202 721 81872 45 245 25
203 1109 58981 36 384 38
204 740 53515 28 212 52
205 1126 60812 44 399 67
206 728 56375 30 229 74
207 689 65490 22 224 38
208 592 80949 17 203 30
209 995 76302 31 333 26
210 1613 104011 55 384 67
211 2048 98104 54 636 132
212 705 67989 21 185 42
213 301 30989 14 93 35
214 1803 135458 81 581 118
215 799 73504 35 248 68
216 861 63123 43 304 43
217 1186 61254 46 344 76
218 1451 74914 30 407 64
219 628 31774 23 170 48
220 1161 81437 38 312 64
221 1463 87186 54 507 56
222 742 50090 20 224 71
223 979 65745 53 340 75
224 675 56653 45 168 39
225 1241 158399 39 443 42
226 676 46455 20 204 39
227 1049 73624 24 367 93
228 620 38395 31 210 38
229 1081 91899 35 335 60
230 1688 139526 151 364 71
231 736 52164 52 178 52
232 617 51567 30 206 27
233 812 70551 31 279 59
234 1051 84856 29 387 40
235 1656 102538 57 490 79
236 705 86678 40 238 44
237 945 85709 44 343 65
238 554 34662 25 232 10
239 1597 150580 77 530 124
240 982 99611 35 291 81
241 222 19349 11 67 15
242 1212 99373 63 397 92
243 1143 86230 44 467 42
244 435 30837 19 178 10
245 532 31706 13 175 24
246 882 89806 42 299 64
247 608 62088 38 154 45
248 459 40151 29 106 22
249 578 27634 20 189 56
250 826 76990 27 194 94
251 509 37460 20 135 19
252 717 54157 19 201 35
253 637 49862 37 207 32
254 857 84337 26 280 35
255 830 64175 42 260 48
256 652 59382 49 227 49
257 707 119308 30 239 48
258 954 76702 49 333 62
259 1461 103425 67 428 96
260 672 70344 28 230 45
261 778 43410 19 292 63
262 1141 104838 49 350 71
263 680 62215 27 186 26
264 1090 69304 30 326 48
265 616 53117 22 155 29
266 285 19764 12 75 19
267 1145 86680 31 361 45
268 733 84105 20 261 45
269 888 77945 20 299 67
270 849 89113 39 300 30
271 1182 91005 29 450 36
272 528 40248 16 183 34
273 642 64187 27 238 36
274 947 50857 21 165 34
275 819 56613 19 234 37
276 757 62792 35 176 46
277 894 72535 14 329 44
Shared_compendiums Blogged_computations Compendium_reviewed\r
1 7 86 44
2 7 44 30
3 3 104 40
4 9 63 34
5 0 158 47
6 4 102 30
7 3 77 31
8 0 82 23
9 7 115 36
10 0 101 36
11 1 80 30
12 5 50 25
13 7 83 39
14 0 123 34
15 0 73 31
16 5 81 31
17 0 105 33
18 0 47 25
19 0 105 33
20 3 94 35
21 4 44 42
22 1 114 43
23 4 38 30
24 2 107 33
25 0 30 13
26 0 71 32
27 0 84 36
28 0 0 0
29 2 59 28
30 1 33 14
31 0 42 17
32 2 96 32
33 10 106 30
34 6 56 35
35 0 57 20
36 5 59 28
37 4 39 28
38 1 34 39
39 2 76 34
40 2 20 26
41 0 91 39
42 8 115 39
43 3 85 33
44 0 76 28
45 0 8 4
46 8 79 39
47 5 21 18
48 3 30 14
49 1 76 29
50 5 101 44
51 1 94 21
52 1 27 16
53 5 92 28
54 0 123 35
55 12 75 28
56 8 128 38
57 8 105 23
58 8 55 36
59 8 56 32
60 2 41 29
61 0 72 25
62 5 67 27
63 8 75 36
64 2 114 28
65 5 118 23
66 12 77 40
67 6 22 23
68 7 66 40
69 2 69 28
70 0 105 34
71 4 116 33
72 3 88 28
73 6 73 34
74 2 99 30
75 0 62 33
76 1 53 22
77 0 118 38
78 5 30 26
79 2 100 35
80 0 49 8
81 0 24 24
82 5 67 29
83 0 46 20
84 1 57 29
85 0 75 45
86 1 135 37
87 1 68 33
88 2 124 33
89 6 33 25
90 1 98 32
91 4 58 29
92 2 68 28
93 3 81 28
94 0 131 31
95 10 110 52
96 0 37 21
97 9 130 24
98 7 93 41
99 0 118 33
100 0 39 32
101 4 13 19
102 4 74 20
103 0 81 31
104 0 109 31
105 0 151 32
106 1 51 18
107 0 28 23
108 1 40 17
109 0 56 20
110 0 27 12
111 4 37 17
112 0 83 30
113 4 54 31
114 4 27 10
115 3 28 13
116 0 59 22
117 0 133 42
118 0 12 1
119 5 0 9
120 0 106 32
121 4 23 11
122 0 44 25
123 0 71 36
124 1 116 31
125 0 4 0
126 5 62 24
127 0 12 13
128 0 18 8
129 0 14 13
130 0 60 19
131 0 7 18
132 2 98 33
133 7 64 40
134 1 29 22
135 8 32 38
136 2 25 24
137 0 16 8
138 2 48 35
139 0 100 43
140 0 46 43
141 1 45 14
142 3 129 41
143 0 130 38
144 3 136 45
145 0 59 31
146 0 25 13
147 0 32 28
148 4 63 31
149 4 95 40
150 11 14 30
151 0 36 16
152 0 113 37
153 4 47 30
154 0 92 35
155 1 70 32
156 0 19 27
157 0 50 20
158 0 41 18
159 9 91 31
160 1 111 31
161 3 41 21
162 10 120 39
163 5 135 41
164 0 27 13
165 2 87 32
166 0 25 18
167 1 131 39
168 2 45 14
169 4 29 7
170 0 58 17
171 0 4 0
172 2 47 30
173 1 109 37
174 0 7 0
175 0 12 5
176 0 0 1
177 1 37 16
178 0 37 32
179 2 46 24
180 0 15 17
181 3 42 11
182 6 7 24
183 0 54 22
184 2 54 12
185 0 14 19
186 2 16 13
187 1 33 17
188 1 32 15
189 2 21 16
190 1 15 24
191 0 38 15
192 1 22 17
193 3 28 18
194 0 10 20
195 0 31 16
196 0 32 16
197 0 32 18
198 1 43 22
199 4 27 8
200 0 37 17
201 0 20 18
202 0 32 16
203 7 0 23
204 2 5 22
205 0 26 13
206 7 10 13
207 3 27 16
208 0 11 16
209 0 29 20
210 6 25 22
211 2 55 17
212 0 23 18
213 0 5 17
214 3 43 12
215 0 23 7
216 1 34 17
217 1 36 14
218 0 35 23
219 1 0 17
220 0 37 14
221 0 28 15
222 0 16 17
223 0 26 21
224 0 38 18
225 0 23 18
226 0 22 17
227 0 30 17
228 0 16 16
229 0 18 15
230 0 28 21
231 0 32 16
232 2 21 14
233 0 23 15
234 1 29 17
235 1 50 15
236 0 12 15
237 0 21 10
238 0 18 6
239 0 27 22
240 0 41 21
241 0 13 1
242 1 12 18
243 0 21 17
244 0 8 4
245 0 26 10
246 0 27 16
247 1 13 16
248 0 16 9
249 0 2 16
250 0 42 17
251 0 5 7
252 0 37 15
253 0 17 14
254 0 38 14
255 0 37 18
256 0 29 12
257 0 32 16
258 0 35 21
259 1 17 19
260 0 20 16
261 0 7 1
262 1 46 16
263 0 24 10
264 6 40 19
265 3 3 12
266 1 10 2
267 2 37 14
268 0 17 17
269 0 28 19
270 0 19 14
271 3 29 11
272 1 8 4
273 0 10 16
274 0 15 20
275 1 15 12
276 0 28 15
277 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
9.576e+01 3.793e-04 3.201e+00
Compendium_views_info Compendium_views_pr Shared_compendiums
1.812e+00 1.434e+00 5.518e+00
Blogged_computations `Compendium_reviewed\\r`
1.804e+00 7.986e-02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-472.95 -84.98 -11.17 73.34 1166.00
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.576e+01 2.497e+01 3.835 0.000156 ***
Time_in_rfc 3.793e-04 3.438e-04 1.103 0.270967
Logins 3.201e+00 4.114e-01 7.780 1.56e-13 ***
Compendium_views_info 1.812e+00 8.703e-02 20.826 < 2e-16 ***
Compendium_views_pr 1.434e+00 2.247e-01 6.383 7.58e-10 ***
Shared_compendiums 5.518e+00 3.926e+00 1.406 0.160996
Blogged_computations 1.804e+00 5.235e-01 3.447 0.000658 ***
`Compendium_reviewed\\r` 7.986e-02 1.595e+00 0.050 0.960116
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 159 on 269 degrees of freedom
Multiple R-squared: 0.9545, Adjusted R-squared: 0.9533
F-statistic: 806.3 on 7 and 269 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,] 0.57978061 8.404388e-01 4.202194e-01
[2,] 0.52718453 9.456309e-01 4.728155e-01
[3,] 0.40896394 8.179279e-01 5.910361e-01
[4,] 0.56497379 8.700524e-01 4.350262e-01
[5,] 0.47085586 9.417117e-01 5.291441e-01
[6,] 0.36330266 7.266053e-01 6.366973e-01
[7,] 0.27931932 5.586386e-01 7.206807e-01
[8,] 0.20758661 4.151732e-01 7.924134e-01
[9,] 0.14507632 2.901526e-01 8.549237e-01
[10,] 0.15229362 3.045872e-01 8.477064e-01
[11,] 0.13088290 2.617658e-01 8.691171e-01
[12,] 0.14630054 2.926011e-01 8.536995e-01
[13,] 0.10348060 2.069612e-01 8.965194e-01
[14,] 0.07501278 1.500256e-01 9.249872e-01
[15,] 0.10219643 2.043929e-01 8.978036e-01
[16,] 0.07301940 1.460388e-01 9.269806e-01
[17,] 0.14686070 2.937214e-01 8.531393e-01
[18,] 0.11036292 2.207258e-01 8.896371e-01
[19,] 0.08396777 1.679355e-01 9.160322e-01
[20,] 0.07736949 1.547390e-01 9.226305e-01
[21,] 0.13085761 2.617152e-01 8.691424e-01
[22,] 0.10569740 2.113948e-01 8.943026e-01
[23,] 0.08541445 1.708289e-01 9.145856e-01
[24,] 0.09623771 1.924754e-01 9.037623e-01
[25,] 0.16135075 3.227015e-01 8.386493e-01
[26,] 0.15794235 3.158847e-01 8.420577e-01
[27,] 0.17066245 3.413249e-01 8.293376e-01
[28,] 0.13777291 2.755458e-01 8.622271e-01
[29,] 0.23354429 4.670886e-01 7.664557e-01
[30,] 0.20086940 4.017388e-01 7.991306e-01
[31,] 0.19833801 3.966760e-01 8.016620e-01
[32,] 0.56180404 8.763919e-01 4.381960e-01
[33,] 0.55762933 8.847413e-01 4.423707e-01
[34,] 0.51000870 9.799826e-01 4.899913e-01
[35,] 0.47910571 9.582114e-01 5.208943e-01
[36,] 0.73500095 5.299981e-01 2.649990e-01
[37,] 0.69920568 6.015886e-01 3.007943e-01
[38,] 0.68007609 6.398478e-01 3.199239e-01
[39,] 0.69236839 6.152632e-01 3.076316e-01
[40,] 0.87086908 2.582618e-01 1.291309e-01
[41,] 1.00000000 7.064592e-10 3.532296e-10
[42,] 1.00000000 1.352527e-09 6.762636e-10
[43,] 1.00000000 1.670356e-09 8.351778e-10
[44,] 1.00000000 2.009625e-10 1.004812e-10
[45,] 1.00000000 2.915833e-10 1.457917e-10
[46,] 1.00000000 1.123888e-10 5.619442e-11
[47,] 1.00000000 1.494268e-10 7.471342e-11
[48,] 1.00000000 2.283510e-10 1.141755e-10
[49,] 1.00000000 3.507489e-10 1.753745e-10
[50,] 1.00000000 3.319316e-10 1.659658e-10
[51,] 1.00000000 3.763860e-10 1.881930e-10
[52,] 1.00000000 6.967851e-10 3.483925e-10
[53,] 1.00000000 7.880332e-10 3.940166e-10
[54,] 1.00000000 9.966840e-10 4.983420e-10
[55,] 1.00000000 7.733443e-10 3.866722e-10
[56,] 1.00000000 7.023815e-10 3.511908e-10
[57,] 1.00000000 8.207397e-10 4.103698e-10
[58,] 1.00000000 9.852352e-10 4.926176e-10
[59,] 1.00000000 3.864353e-10 1.932177e-10
[60,] 1.00000000 7.065887e-10 3.532944e-10
[61,] 1.00000000 5.464213e-11 2.732107e-11
[62,] 1.00000000 4.848842e-11 2.424421e-11
[63,] 1.00000000 8.185890e-11 4.092945e-11
[64,] 1.00000000 1.327144e-10 6.635721e-11
[65,] 1.00000000 2.178348e-10 1.089174e-10
[66,] 1.00000000 3.537226e-10 1.768613e-10
[67,] 1.00000000 1.332019e-10 6.660094e-11
[68,] 1.00000000 2.041075e-11 1.020538e-11
[69,] 1.00000000 2.685440e-11 1.342720e-11
[70,] 1.00000000 1.169952e-11 5.849759e-12
[71,] 1.00000000 8.344973e-12 4.172487e-12
[72,] 1.00000000 1.483737e-11 7.418686e-12
[73,] 1.00000000 2.147352e-11 1.073676e-11
[74,] 1.00000000 5.833478e-12 2.916739e-12
[75,] 1.00000000 1.096641e-11 5.483204e-12
[76,] 1.00000000 1.316001e-11 6.580007e-12
[77,] 1.00000000 1.816729e-11 9.083646e-12
[78,] 1.00000000 3.301507e-11 1.650754e-11
[79,] 1.00000000 4.365967e-11 2.182984e-11
[80,] 1.00000000 5.236546e-11 2.618273e-11
[81,] 1.00000000 5.064398e-11 2.532199e-11
[82,] 1.00000000 9.018689e-11 4.509345e-11
[83,] 1.00000000 1.576375e-10 7.881876e-11
[84,] 1.00000000 1.706554e-10 8.532771e-11
[85,] 1.00000000 1.108463e-10 5.542314e-11
[86,] 1.00000000 3.699391e-11 1.849695e-11
[87,] 1.00000000 4.884465e-11 2.442233e-11
[88,] 1.00000000 8.872346e-11 4.436173e-11
[89,] 1.00000000 1.471883e-10 7.359417e-11
[90,] 1.00000000 1.110815e-10 5.554075e-11
[91,] 1.00000000 1.747753e-10 8.738763e-11
[92,] 1.00000000 2.855440e-10 1.427720e-10
[93,] 1.00000000 2.155387e-10 1.077693e-10
[94,] 1.00000000 1.053925e-10 5.269623e-11
[95,] 1.00000000 1.499835e-10 7.499175e-11
[96,] 1.00000000 1.344050e-10 6.720249e-11
[97,] 1.00000000 2.387496e-10 1.193748e-10
[98,] 1.00000000 3.586976e-10 1.793488e-10
[99,] 1.00000000 3.906907e-10 1.953454e-10
[100,] 1.00000000 6.054745e-10 3.027373e-10
[101,] 1.00000000 9.042168e-10 4.521084e-10
[102,] 1.00000000 1.456352e-09 7.281759e-10
[103,] 1.00000000 2.461535e-09 1.230767e-09
[104,] 1.00000000 3.941237e-09 1.970619e-09
[105,] 1.00000000 6.435114e-09 3.217557e-09
[106,] 1.00000000 3.713395e-09 1.856697e-09
[107,] 1.00000000 4.606774e-09 2.303387e-09
[108,] 1.00000000 7.541191e-09 3.770595e-09
[109,] 0.99999999 1.191783e-08 5.958913e-09
[110,] 0.99999999 1.914363e-08 9.571815e-09
[111,] 0.99999999 2.342234e-08 1.171117e-08
[112,] 1.00000000 6.910781e-09 3.455391e-09
[113,] 1.00000000 9.395319e-09 4.697660e-09
[114,] 1.00000000 9.512883e-09 4.756441e-09
[115,] 0.99999999 1.562751e-08 7.813757e-09
[116,] 0.99999999 2.147781e-08 1.073891e-08
[117,] 0.99999998 3.386234e-08 1.693117e-08
[118,] 0.99999998 3.749031e-08 1.874516e-08
[119,] 0.99999997 6.142315e-08 3.071157e-08
[120,] 0.99999998 3.641098e-08 1.820549e-08
[121,] 0.99999997 5.417207e-08 2.708603e-08
[122,] 0.99999996 8.332318e-08 4.166159e-08
[123,] 0.99999994 1.269420e-07 6.347102e-08
[124,] 0.99999996 8.499408e-08 4.249704e-08
[125,] 0.99999995 1.073018e-07 5.365092e-08
[126,] 0.99999991 1.730285e-07 8.651425e-08
[127,] 0.99999996 7.431224e-08 3.715612e-08
[128,] 0.99999994 1.195373e-07 5.976864e-08
[129,] 0.99999991 1.778441e-07 8.892205e-08
[130,] 0.99999988 2.454749e-07 1.227375e-07
[131,] 0.99999986 2.749431e-07 1.374715e-07
[132,] 0.99999998 3.307410e-08 1.653705e-08
[133,] 0.99999998 3.037242e-08 1.518621e-08
[134,] 0.99999998 4.198366e-08 2.099183e-08
[135,] 0.99999998 3.855227e-08 1.927613e-08
[136,] 0.99999998 3.540253e-08 1.770127e-08
[137,] 0.99999997 5.728040e-08 2.864020e-08
[138,] 1.00000000 7.250500e-10 3.625250e-10
[139,] 1.00000000 7.230123e-10 3.615062e-10
[140,] 1.00000000 6.260958e-10 3.130479e-10
[141,] 1.00000000 6.528897e-10 3.264448e-10
[142,] 1.00000000 1.284302e-10 6.421510e-11
[143,] 1.00000000 1.513846e-10 7.569229e-11
[144,] 1.00000000 2.644763e-10 1.322382e-10
[145,] 1.00000000 2.011387e-10 1.005693e-10
[146,] 1.00000000 1.030469e-10 5.152343e-11
[147,] 1.00000000 1.873661e-10 9.368307e-11
[148,] 1.00000000 2.622679e-10 1.311340e-10
[149,] 1.00000000 1.892015e-10 9.460077e-11
[150,] 1.00000000 3.079460e-10 1.539730e-10
[151,] 1.00000000 2.150734e-10 1.075367e-10
[152,] 1.00000000 3.405895e-10 1.702948e-10
[153,] 1.00000000 2.659057e-11 1.329528e-11
[154,] 1.00000000 4.943101e-11 2.471551e-11
[155,] 1.00000000 6.733835e-11 3.366918e-11
[156,] 1.00000000 1.255100e-10 6.275500e-11
[157,] 1.00000000 1.238002e-10 6.190008e-11
[158,] 1.00000000 1.989365e-10 9.946823e-11
[159,] 1.00000000 3.538814e-10 1.769407e-10
[160,] 1.00000000 5.782908e-10 2.891454e-10
[161,] 1.00000000 1.039451e-09 5.197253e-10
[162,] 1.00000000 1.783303e-09 8.916514e-10
[163,] 1.00000000 1.531020e-09 7.655101e-10
[164,] 1.00000000 2.686550e-09 1.343275e-09
[165,] 1.00000000 2.349397e-09 1.174698e-09
[166,] 1.00000000 4.166740e-09 2.083370e-09
[167,] 1.00000000 1.193227e-09 5.966135e-10
[168,] 1.00000000 1.901604e-09 9.508022e-10
[169,] 1.00000000 3.362649e-09 1.681324e-09
[170,] 1.00000000 2.811507e-09 1.405754e-09
[171,] 1.00000000 4.781667e-09 2.390833e-09
[172,] 1.00000000 6.632203e-09 3.316101e-09
[173,] 1.00000000 9.588549e-09 4.794275e-09
[174,] 0.99999999 1.666687e-08 8.333437e-09
[175,] 0.99999999 2.201626e-08 1.100813e-08
[176,] 0.99999998 3.672839e-08 1.836419e-08
[177,] 0.99999998 4.628444e-08 2.314222e-08
[178,] 0.99999996 7.218517e-08 3.609258e-08
[179,] 0.99999994 1.152765e-07 5.763827e-08
[180,] 0.99999991 1.756860e-07 8.784301e-08
[181,] 0.99999989 2.292439e-07 1.146219e-07
[182,] 0.99999981 3.838621e-07 1.919311e-07
[183,] 0.99999975 5.098991e-07 2.549495e-07
[184,] 0.99999956 8.735511e-07 4.367756e-07
[185,] 0.99999957 8.637269e-07 4.318634e-07
[186,] 0.99999948 1.038590e-06 5.192949e-07
[187,] 0.99999916 1.686885e-06 8.434423e-07
[188,] 0.99999900 1.990060e-06 9.950301e-07
[189,] 0.99999840 3.200419e-06 1.600209e-06
[190,] 0.99999924 1.527093e-06 7.635464e-07
[191,] 0.99999869 2.620392e-06 1.310196e-06
[192,] 0.99999846 3.077944e-06 1.538972e-06
[193,] 0.99999794 4.120326e-06 2.060163e-06
[194,] 0.99999658 6.839034e-06 3.419517e-06
[195,] 0.99999452 1.095435e-05 5.477177e-06
[196,] 0.99999717 5.663414e-06 2.831707e-06
[197,] 0.99999692 6.166315e-06 3.083157e-06
[198,] 0.99999475 1.049399e-05 5.246993e-06
[199,] 0.99999162 1.676893e-05 8.384465e-06
[200,] 0.99999793 4.131580e-06 2.065790e-06
[201,] 0.99999860 2.791551e-06 1.395775e-06
[202,] 0.99999786 4.270885e-06 2.135442e-06
[203,] 0.99999692 6.156426e-06 3.078213e-06
[204,] 0.99999475 1.049411e-05 5.247055e-06
[205,] 0.99999091 1.817142e-05 9.085711e-06
[206,] 0.99999111 1.777208e-05 8.886040e-06
[207,] 0.99998709 2.582811e-05 1.291405e-05
[208,] 0.99999878 2.448182e-06 1.224091e-06
[209,] 0.99999795 4.095562e-06 2.047781e-06
[210,] 0.99999897 2.065142e-06 1.032571e-06
[211,] 0.99999881 2.377835e-06 1.188917e-06
[212,] 0.99999784 4.327338e-06 2.163669e-06
[213,] 0.99999758 4.833171e-06 2.416586e-06
[214,] 0.99999589 8.212737e-06 4.106368e-06
[215,] 0.99999294 1.411600e-05 7.058000e-06
[216,] 0.99998741 2.517588e-05 1.258794e-05
[217,] 0.99997726 4.548524e-05 2.274262e-05
[218,] 0.99996557 6.886926e-05 3.443463e-05
[219,] 0.99996300 7.400327e-05 3.700163e-05
[220,] 0.99998862 2.276916e-05 1.138458e-05
[221,] 0.99997868 4.263793e-05 2.131896e-05
[222,] 0.99997235 5.529870e-05 2.764935e-05
[223,] 0.99995506 8.987812e-05 4.493906e-05
[224,] 0.99991997 1.600614e-04 8.003068e-05
[225,] 0.99999146 1.708372e-05 8.541861e-06
[226,] 0.99998613 2.774976e-05 1.387488e-05
[227,] 0.99997328 5.343659e-05 2.671829e-05
[228,] 0.99995131 9.737015e-05 4.868507e-05
[229,] 0.99991159 1.768102e-04 8.840508e-05
[230,] 0.99983623 3.275373e-04 1.637686e-04
[231,] 0.99971269 5.746228e-04 2.873114e-04
[232,] 0.99947630 1.047406e-03 5.237030e-04
[233,] 0.99913967 1.720650e-03 8.603252e-04
[234,] 0.99858514 2.829729e-03 1.414865e-03
[235,] 0.99759222 4.815554e-03 2.407777e-03
[236,] 0.99632291 7.354175e-03 3.677088e-03
[237,] 0.99438154 1.123692e-02 5.618462e-03
[238,] 0.99074858 1.850285e-02 9.251423e-03
[239,] 0.99025838 1.948324e-02 9.741620e-03
[240,] 0.98412904 3.174192e-02 1.587096e-02
[241,] 0.97675078 4.649844e-02 2.324922e-02
[242,] 0.96511676 6.976648e-02 3.488324e-02
[243,] 0.95122969 9.754063e-02 4.877031e-02
[244,] 0.93219398 1.356120e-01 6.780602e-02
[245,] 0.90331753 1.933649e-01 9.668247e-02
[246,] 0.91254549 1.749090e-01 8.745451e-02
[247,] 0.87465401 2.506920e-01 1.253460e-01
[248,] 0.95088690 9.822620e-02 4.911310e-02
[249,] 0.92864615 1.427077e-01 7.135385e-02
[250,] 0.92394705 1.521059e-01 7.605295e-02
[251,] 0.90284515 1.943097e-01 9.715485e-02
[252,] 0.87242346 2.551531e-01 1.275765e-01
[253,] 0.79545178 4.090964e-01 2.045482e-01
[254,] 0.89541108 2.091778e-01 1.045889e-01
[255,] 0.80941904 3.811619e-01 1.905810e-01
[256,] 0.92235214 1.552957e-01 7.764786e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1i5nu1355474619.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2mpo61355474619.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3bgya1355474619.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4rav31355474619.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/511uc1355474619.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 = 277
Frequency = 1
1 2 3 4 5 6
-58.5362659 -95.8125253 -136.6129152 -2.7729405 282.7405726 -26.3996905
7 8 9 10 11 12
-247.7390609 -135.8543896 174.2655540 100.8209741 -245.3840349 38.7603618
13 14 15 16 17 18
8.4733853 -110.5817191 -11.2930106 -96.8666382 27.3099617 -49.0699660
19 20 21 22 23 24
-103.9385370 -101.0377649 41.0501438 -119.9108736 -39.0107701 -91.1836043
25 26 27 28 29 30
40.7724849 -96.9839700 181.5760563 -95.1962201 5.1941150 49.5511006
31 32 33 34 35 36
243.5576105 -56.8682037 -258.7652705 -211.0037096 289.8583517 -163.0130193
37 38 39 40 41 42
134.6475472 -78.9480215 -445.7226488 -71.1276703 183.0204523 345.1109597
43 44 45 46 47 48
-171.9363026 62.4800583 -124.2983233 -472.9487553 9.9560268 -172.9890954
49 50 51 52 53 54
166.7979404 389.6814369 1166.0007024 2.2341427 159.5211687 -307.4830236
55 56 57 58 59 60
-125.1139582 283.9762196 -98.8990302 -133.3877162 64.7276207 -197.4461829
61 62 63 64 65 66
158.6933458 -35.6064805 123.9583550 -98.0368786 -190.7413586 136.5703128
67 68 69 70 71 72
-161.4447531 115.4489227 -270.4250611 -14.6040860 -364.3909530 -177.3471569
73 74 75 76 77 78
52.3462285 71.1060141 -81.3031264 62.4562818 274.3418278 -335.6865254
79 80 81 82 83 84
120.7920654 -262.0318433 -198.5592748 -12.9896689 81.5843331 -255.2361630
85 86 87 88 89 90
13.4791663 120.9956851 99.7755110 3.7933487 88.8231199 128.6949257
91 92 93 94 95 96
-136.9718886 18.5133924 -34.2708447 -142.0513794 223.6140973 246.5268401
97 98 99 100 101 102
-111.6197529 0.6702190 -55.7949323 -209.7109026 -51.5641617 52.5532200
103 104 105 106 107 108
-209.4636043 -229.6698554 -101.0994227 171.9179797 -12.5685370 73.3381432
109 110 111 112 113 114
134.5947001 -95.7119819 34.4655299 -69.3369362 27.8610375 40.1992536
115 116 117 118 119 120
-32.4585478 213.3583924 99.1636516 -59.2218944 33.8621842 -60.7756241
121 122 123 124 125 126
-117.5314819 278.5017095 93.7433857 -156.8480641 -42.6565946 -61.4288419
127 128 129 130 131 132
35.5544341 -146.6447511 -30.6042329 204.4894172 -46.7166566 62.1290030
133 134 135 136 137 138
66.7922984 211.8934505 -46.6608088 9.4218076 -255.3951754 30.9210017
139 140 141 142 143 144
-64.8302285 -82.6732887 111.7986167 -301.7338934 -148.9252888 131.2858878
145 146 147 148 149 150
-137.7932898 -97.3436828 -33.7881458 -412.2097828 215.1610978 -23.7928450
151 152 153 154 155 156
-99.9005737 -241.4172204 -57.1384182 -27.1364048 -90.6352722 -119.8238617
157 158 159 160 161 162
28.1645327 137.6485503 5.4207950 -45.6944930 228.9024683 153.6355716
163 164 165 166 167 168
-181.8451327 -31.2561129 8.4773833 21.2711947 24.6949955 -11.1699090
169 170 171 172 173 174
47.5344280 113.8709884 -87.6113717 67.0081801 71.3443318 -110.2442924
175 176 177 178 179 180
-204.9825326 -106.8583066 256.7722450 28.4137626 69.2943894 -156.4080205
181 182 183 184 185 186
77.6925074 172.6882726 -16.0288439 79.4804110 -86.0802110 -45.3685694
187 188 189 190 191 192
-39.4505131 -32.5977916 -13.8218725 -24.0151631 -48.5790115 22.3818251
193 194 195 196 197 198
19.9386830 1.7707616 157.7478815 -55.1991392 16.6026562 -5.0042729
199 200 201 202 203 204
87.1872451 241.1225441 9.3375141 -88.7633416 84.7121217 53.6963343
205 206 207 208 209 210
-0.8591144 -64.0455228 -29.0494631 -20.9507060 76.3237159 429.7145126
211 212 213 214 215 216
288.5358930 77.7627161 -80.4551603 79.2483486 -25.7317752 -77.2061147
217 218 219 220 221 222
115.7058451 336.3649905 62.7442075 187.5767940 110.3955506 25.1871071
223 224 225 226 227 228
-83.7146403 -16.7055365 54.2508205 31.8819166 -5.5347362 -54.8014915
229 230 231 232 233 234
111.4662436 242.2683779 -2.1895260 -56.4692395 -42.7257673 12.2521408
235 236 237 238 239 240
240.5795241 -68.9765568 -77.6760319 -102.7083101 8.7700391 17.1881545
241 242 243 244 245 246
-82.7890951 -3.1816517 -72.1879862 -84.9779146 -16.7047799 -65.9534730
247 248 249 250 251 252
-6.8400488 1.9328965 -20.0047643 51.0498706 53.5100828 57.4279030
253 254 255 256 257 258
-48.9569909 18.6693028 -32.8039552 -158.0993015 -91.0654274 -84.9768446
259 260 261 262 263 264
160.4545011 -58.8238776 -27.3325314 22.6643921 55.7181227 105.4379217
265 266 267 268 269 270
84.2360009 -43.5675328 119.3974667 -28.2903786 8.6125245 -27.5431460
271 272 273 274 275 276
21.9169794 -34.9461828 -66.8349276 388.2591916 130.2378136 88.7175911
277
34.5704547
> postscript(file="/var/wessaorg/rcomp/tmp/6ak811355474619.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 = 277
Frequency = 1
lag(myerror, k = 1) myerror
0 -58.5362659 NA
1 -95.8125253 -58.5362659
2 -136.6129152 -95.8125253
3 -2.7729405 -136.6129152
4 282.7405726 -2.7729405
5 -26.3996905 282.7405726
6 -247.7390609 -26.3996905
7 -135.8543896 -247.7390609
8 174.2655540 -135.8543896
9 100.8209741 174.2655540
10 -245.3840349 100.8209741
11 38.7603618 -245.3840349
12 8.4733853 38.7603618
13 -110.5817191 8.4733853
14 -11.2930106 -110.5817191
15 -96.8666382 -11.2930106
16 27.3099617 -96.8666382
17 -49.0699660 27.3099617
18 -103.9385370 -49.0699660
19 -101.0377649 -103.9385370
20 41.0501438 -101.0377649
21 -119.9108736 41.0501438
22 -39.0107701 -119.9108736
23 -91.1836043 -39.0107701
24 40.7724849 -91.1836043
25 -96.9839700 40.7724849
26 181.5760563 -96.9839700
27 -95.1962201 181.5760563
28 5.1941150 -95.1962201
29 49.5511006 5.1941150
30 243.5576105 49.5511006
31 -56.8682037 243.5576105
32 -258.7652705 -56.8682037
33 -211.0037096 -258.7652705
34 289.8583517 -211.0037096
35 -163.0130193 289.8583517
36 134.6475472 -163.0130193
37 -78.9480215 134.6475472
38 -445.7226488 -78.9480215
39 -71.1276703 -445.7226488
40 183.0204523 -71.1276703
41 345.1109597 183.0204523
42 -171.9363026 345.1109597
43 62.4800583 -171.9363026
44 -124.2983233 62.4800583
45 -472.9487553 -124.2983233
46 9.9560268 -472.9487553
47 -172.9890954 9.9560268
48 166.7979404 -172.9890954
49 389.6814369 166.7979404
50 1166.0007024 389.6814369
51 2.2341427 1166.0007024
52 159.5211687 2.2341427
53 -307.4830236 159.5211687
54 -125.1139582 -307.4830236
55 283.9762196 -125.1139582
56 -98.8990302 283.9762196
57 -133.3877162 -98.8990302
58 64.7276207 -133.3877162
59 -197.4461829 64.7276207
60 158.6933458 -197.4461829
61 -35.6064805 158.6933458
62 123.9583550 -35.6064805
63 -98.0368786 123.9583550
64 -190.7413586 -98.0368786
65 136.5703128 -190.7413586
66 -161.4447531 136.5703128
67 115.4489227 -161.4447531
68 -270.4250611 115.4489227
69 -14.6040860 -270.4250611
70 -364.3909530 -14.6040860
71 -177.3471569 -364.3909530
72 52.3462285 -177.3471569
73 71.1060141 52.3462285
74 -81.3031264 71.1060141
75 62.4562818 -81.3031264
76 274.3418278 62.4562818
77 -335.6865254 274.3418278
78 120.7920654 -335.6865254
79 -262.0318433 120.7920654
80 -198.5592748 -262.0318433
81 -12.9896689 -198.5592748
82 81.5843331 -12.9896689
83 -255.2361630 81.5843331
84 13.4791663 -255.2361630
85 120.9956851 13.4791663
86 99.7755110 120.9956851
87 3.7933487 99.7755110
88 88.8231199 3.7933487
89 128.6949257 88.8231199
90 -136.9718886 128.6949257
91 18.5133924 -136.9718886
92 -34.2708447 18.5133924
93 -142.0513794 -34.2708447
94 223.6140973 -142.0513794
95 246.5268401 223.6140973
96 -111.6197529 246.5268401
97 0.6702190 -111.6197529
98 -55.7949323 0.6702190
99 -209.7109026 -55.7949323
100 -51.5641617 -209.7109026
101 52.5532200 -51.5641617
102 -209.4636043 52.5532200
103 -229.6698554 -209.4636043
104 -101.0994227 -229.6698554
105 171.9179797 -101.0994227
106 -12.5685370 171.9179797
107 73.3381432 -12.5685370
108 134.5947001 73.3381432
109 -95.7119819 134.5947001
110 34.4655299 -95.7119819
111 -69.3369362 34.4655299
112 27.8610375 -69.3369362
113 40.1992536 27.8610375
114 -32.4585478 40.1992536
115 213.3583924 -32.4585478
116 99.1636516 213.3583924
117 -59.2218944 99.1636516
118 33.8621842 -59.2218944
119 -60.7756241 33.8621842
120 -117.5314819 -60.7756241
121 278.5017095 -117.5314819
122 93.7433857 278.5017095
123 -156.8480641 93.7433857
124 -42.6565946 -156.8480641
125 -61.4288419 -42.6565946
126 35.5544341 -61.4288419
127 -146.6447511 35.5544341
128 -30.6042329 -146.6447511
129 204.4894172 -30.6042329
130 -46.7166566 204.4894172
131 62.1290030 -46.7166566
132 66.7922984 62.1290030
133 211.8934505 66.7922984
134 -46.6608088 211.8934505
135 9.4218076 -46.6608088
136 -255.3951754 9.4218076
137 30.9210017 -255.3951754
138 -64.8302285 30.9210017
139 -82.6732887 -64.8302285
140 111.7986167 -82.6732887
141 -301.7338934 111.7986167
142 -148.9252888 -301.7338934
143 131.2858878 -148.9252888
144 -137.7932898 131.2858878
145 -97.3436828 -137.7932898
146 -33.7881458 -97.3436828
147 -412.2097828 -33.7881458
148 215.1610978 -412.2097828
149 -23.7928450 215.1610978
150 -99.9005737 -23.7928450
151 -241.4172204 -99.9005737
152 -57.1384182 -241.4172204
153 -27.1364048 -57.1384182
154 -90.6352722 -27.1364048
155 -119.8238617 -90.6352722
156 28.1645327 -119.8238617
157 137.6485503 28.1645327
158 5.4207950 137.6485503
159 -45.6944930 5.4207950
160 228.9024683 -45.6944930
161 153.6355716 228.9024683
162 -181.8451327 153.6355716
163 -31.2561129 -181.8451327
164 8.4773833 -31.2561129
165 21.2711947 8.4773833
166 24.6949955 21.2711947
167 -11.1699090 24.6949955
168 47.5344280 -11.1699090
169 113.8709884 47.5344280
170 -87.6113717 113.8709884
171 67.0081801 -87.6113717
172 71.3443318 67.0081801
173 -110.2442924 71.3443318
174 -204.9825326 -110.2442924
175 -106.8583066 -204.9825326
176 256.7722450 -106.8583066
177 28.4137626 256.7722450
178 69.2943894 28.4137626
179 -156.4080205 69.2943894
180 77.6925074 -156.4080205
181 172.6882726 77.6925074
182 -16.0288439 172.6882726
183 79.4804110 -16.0288439
184 -86.0802110 79.4804110
185 -45.3685694 -86.0802110
186 -39.4505131 -45.3685694
187 -32.5977916 -39.4505131
188 -13.8218725 -32.5977916
189 -24.0151631 -13.8218725
190 -48.5790115 -24.0151631
191 22.3818251 -48.5790115
192 19.9386830 22.3818251
193 1.7707616 19.9386830
194 157.7478815 1.7707616
195 -55.1991392 157.7478815
196 16.6026562 -55.1991392
197 -5.0042729 16.6026562
198 87.1872451 -5.0042729
199 241.1225441 87.1872451
200 9.3375141 241.1225441
201 -88.7633416 9.3375141
202 84.7121217 -88.7633416
203 53.6963343 84.7121217
204 -0.8591144 53.6963343
205 -64.0455228 -0.8591144
206 -29.0494631 -64.0455228
207 -20.9507060 -29.0494631
208 76.3237159 -20.9507060
209 429.7145126 76.3237159
210 288.5358930 429.7145126
211 77.7627161 288.5358930
212 -80.4551603 77.7627161
213 79.2483486 -80.4551603
214 -25.7317752 79.2483486
215 -77.2061147 -25.7317752
216 115.7058451 -77.2061147
217 336.3649905 115.7058451
218 62.7442075 336.3649905
219 187.5767940 62.7442075
220 110.3955506 187.5767940
221 25.1871071 110.3955506
222 -83.7146403 25.1871071
223 -16.7055365 -83.7146403
224 54.2508205 -16.7055365
225 31.8819166 54.2508205
226 -5.5347362 31.8819166
227 -54.8014915 -5.5347362
228 111.4662436 -54.8014915
229 242.2683779 111.4662436
230 -2.1895260 242.2683779
231 -56.4692395 -2.1895260
232 -42.7257673 -56.4692395
233 12.2521408 -42.7257673
234 240.5795241 12.2521408
235 -68.9765568 240.5795241
236 -77.6760319 -68.9765568
237 -102.7083101 -77.6760319
238 8.7700391 -102.7083101
239 17.1881545 8.7700391
240 -82.7890951 17.1881545
241 -3.1816517 -82.7890951
242 -72.1879862 -3.1816517
243 -84.9779146 -72.1879862
244 -16.7047799 -84.9779146
245 -65.9534730 -16.7047799
246 -6.8400488 -65.9534730
247 1.9328965 -6.8400488
248 -20.0047643 1.9328965
249 51.0498706 -20.0047643
250 53.5100828 51.0498706
251 57.4279030 53.5100828
252 -48.9569909 57.4279030
253 18.6693028 -48.9569909
254 -32.8039552 18.6693028
255 -158.0993015 -32.8039552
256 -91.0654274 -158.0993015
257 -84.9768446 -91.0654274
258 160.4545011 -84.9768446
259 -58.8238776 160.4545011
260 -27.3325314 -58.8238776
261 22.6643921 -27.3325314
262 55.7181227 22.6643921
263 105.4379217 55.7181227
264 84.2360009 105.4379217
265 -43.5675328 84.2360009
266 119.3974667 -43.5675328
267 -28.2903786 119.3974667
268 8.6125245 -28.2903786
269 -27.5431460 8.6125245
270 21.9169794 -27.5431460
271 -34.9461828 21.9169794
272 -66.8349276 -34.9461828
273 388.2591916 -66.8349276
274 130.2378136 388.2591916
275 88.7175911 130.2378136
276 34.5704547 88.7175911
277 NA 34.5704547
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -95.8125253 -58.5362659
[2,] -136.6129152 -95.8125253
[3,] -2.7729405 -136.6129152
[4,] 282.7405726 -2.7729405
[5,] -26.3996905 282.7405726
[6,] -247.7390609 -26.3996905
[7,] -135.8543896 -247.7390609
[8,] 174.2655540 -135.8543896
[9,] 100.8209741 174.2655540
[10,] -245.3840349 100.8209741
[11,] 38.7603618 -245.3840349
[12,] 8.4733853 38.7603618
[13,] -110.5817191 8.4733853
[14,] -11.2930106 -110.5817191
[15,] -96.8666382 -11.2930106
[16,] 27.3099617 -96.8666382
[17,] -49.0699660 27.3099617
[18,] -103.9385370 -49.0699660
[19,] -101.0377649 -103.9385370
[20,] 41.0501438 -101.0377649
[21,] -119.9108736 41.0501438
[22,] -39.0107701 -119.9108736
[23,] -91.1836043 -39.0107701
[24,] 40.7724849 -91.1836043
[25,] -96.9839700 40.7724849
[26,] 181.5760563 -96.9839700
[27,] -95.1962201 181.5760563
[28,] 5.1941150 -95.1962201
[29,] 49.5511006 5.1941150
[30,] 243.5576105 49.5511006
[31,] -56.8682037 243.5576105
[32,] -258.7652705 -56.8682037
[33,] -211.0037096 -258.7652705
[34,] 289.8583517 -211.0037096
[35,] -163.0130193 289.8583517
[36,] 134.6475472 -163.0130193
[37,] -78.9480215 134.6475472
[38,] -445.7226488 -78.9480215
[39,] -71.1276703 -445.7226488
[40,] 183.0204523 -71.1276703
[41,] 345.1109597 183.0204523
[42,] -171.9363026 345.1109597
[43,] 62.4800583 -171.9363026
[44,] -124.2983233 62.4800583
[45,] -472.9487553 -124.2983233
[46,] 9.9560268 -472.9487553
[47,] -172.9890954 9.9560268
[48,] 166.7979404 -172.9890954
[49,] 389.6814369 166.7979404
[50,] 1166.0007024 389.6814369
[51,] 2.2341427 1166.0007024
[52,] 159.5211687 2.2341427
[53,] -307.4830236 159.5211687
[54,] -125.1139582 -307.4830236
[55,] 283.9762196 -125.1139582
[56,] -98.8990302 283.9762196
[57,] -133.3877162 -98.8990302
[58,] 64.7276207 -133.3877162
[59,] -197.4461829 64.7276207
[60,] 158.6933458 -197.4461829
[61,] -35.6064805 158.6933458
[62,] 123.9583550 -35.6064805
[63,] -98.0368786 123.9583550
[64,] -190.7413586 -98.0368786
[65,] 136.5703128 -190.7413586
[66,] -161.4447531 136.5703128
[67,] 115.4489227 -161.4447531
[68,] -270.4250611 115.4489227
[69,] -14.6040860 -270.4250611
[70,] -364.3909530 -14.6040860
[71,] -177.3471569 -364.3909530
[72,] 52.3462285 -177.3471569
[73,] 71.1060141 52.3462285
[74,] -81.3031264 71.1060141
[75,] 62.4562818 -81.3031264
[76,] 274.3418278 62.4562818
[77,] -335.6865254 274.3418278
[78,] 120.7920654 -335.6865254
[79,] -262.0318433 120.7920654
[80,] -198.5592748 -262.0318433
[81,] -12.9896689 -198.5592748
[82,] 81.5843331 -12.9896689
[83,] -255.2361630 81.5843331
[84,] 13.4791663 -255.2361630
[85,] 120.9956851 13.4791663
[86,] 99.7755110 120.9956851
[87,] 3.7933487 99.7755110
[88,] 88.8231199 3.7933487
[89,] 128.6949257 88.8231199
[90,] -136.9718886 128.6949257
[91,] 18.5133924 -136.9718886
[92,] -34.2708447 18.5133924
[93,] -142.0513794 -34.2708447
[94,] 223.6140973 -142.0513794
[95,] 246.5268401 223.6140973
[96,] -111.6197529 246.5268401
[97,] 0.6702190 -111.6197529
[98,] -55.7949323 0.6702190
[99,] -209.7109026 -55.7949323
[100,] -51.5641617 -209.7109026
[101,] 52.5532200 -51.5641617
[102,] -209.4636043 52.5532200
[103,] -229.6698554 -209.4636043
[104,] -101.0994227 -229.6698554
[105,] 171.9179797 -101.0994227
[106,] -12.5685370 171.9179797
[107,] 73.3381432 -12.5685370
[108,] 134.5947001 73.3381432
[109,] -95.7119819 134.5947001
[110,] 34.4655299 -95.7119819
[111,] -69.3369362 34.4655299
[112,] 27.8610375 -69.3369362
[113,] 40.1992536 27.8610375
[114,] -32.4585478 40.1992536
[115,] 213.3583924 -32.4585478
[116,] 99.1636516 213.3583924
[117,] -59.2218944 99.1636516
[118,] 33.8621842 -59.2218944
[119,] -60.7756241 33.8621842
[120,] -117.5314819 -60.7756241
[121,] 278.5017095 -117.5314819
[122,] 93.7433857 278.5017095
[123,] -156.8480641 93.7433857
[124,] -42.6565946 -156.8480641
[125,] -61.4288419 -42.6565946
[126,] 35.5544341 -61.4288419
[127,] -146.6447511 35.5544341
[128,] -30.6042329 -146.6447511
[129,] 204.4894172 -30.6042329
[130,] -46.7166566 204.4894172
[131,] 62.1290030 -46.7166566
[132,] 66.7922984 62.1290030
[133,] 211.8934505 66.7922984
[134,] -46.6608088 211.8934505
[135,] 9.4218076 -46.6608088
[136,] -255.3951754 9.4218076
[137,] 30.9210017 -255.3951754
[138,] -64.8302285 30.9210017
[139,] -82.6732887 -64.8302285
[140,] 111.7986167 -82.6732887
[141,] -301.7338934 111.7986167
[142,] -148.9252888 -301.7338934
[143,] 131.2858878 -148.9252888
[144,] -137.7932898 131.2858878
[145,] -97.3436828 -137.7932898
[146,] -33.7881458 -97.3436828
[147,] -412.2097828 -33.7881458
[148,] 215.1610978 -412.2097828
[149,] -23.7928450 215.1610978
[150,] -99.9005737 -23.7928450
[151,] -241.4172204 -99.9005737
[152,] -57.1384182 -241.4172204
[153,] -27.1364048 -57.1384182
[154,] -90.6352722 -27.1364048
[155,] -119.8238617 -90.6352722
[156,] 28.1645327 -119.8238617
[157,] 137.6485503 28.1645327
[158,] 5.4207950 137.6485503
[159,] -45.6944930 5.4207950
[160,] 228.9024683 -45.6944930
[161,] 153.6355716 228.9024683
[162,] -181.8451327 153.6355716
[163,] -31.2561129 -181.8451327
[164,] 8.4773833 -31.2561129
[165,] 21.2711947 8.4773833
[166,] 24.6949955 21.2711947
[167,] -11.1699090 24.6949955
[168,] 47.5344280 -11.1699090
[169,] 113.8709884 47.5344280
[170,] -87.6113717 113.8709884
[171,] 67.0081801 -87.6113717
[172,] 71.3443318 67.0081801
[173,] -110.2442924 71.3443318
[174,] -204.9825326 -110.2442924
[175,] -106.8583066 -204.9825326
[176,] 256.7722450 -106.8583066
[177,] 28.4137626 256.7722450
[178,] 69.2943894 28.4137626
[179,] -156.4080205 69.2943894
[180,] 77.6925074 -156.4080205
[181,] 172.6882726 77.6925074
[182,] -16.0288439 172.6882726
[183,] 79.4804110 -16.0288439
[184,] -86.0802110 79.4804110
[185,] -45.3685694 -86.0802110
[186,] -39.4505131 -45.3685694
[187,] -32.5977916 -39.4505131
[188,] -13.8218725 -32.5977916
[189,] -24.0151631 -13.8218725
[190,] -48.5790115 -24.0151631
[191,] 22.3818251 -48.5790115
[192,] 19.9386830 22.3818251
[193,] 1.7707616 19.9386830
[194,] 157.7478815 1.7707616
[195,] -55.1991392 157.7478815
[196,] 16.6026562 -55.1991392
[197,] -5.0042729 16.6026562
[198,] 87.1872451 -5.0042729
[199,] 241.1225441 87.1872451
[200,] 9.3375141 241.1225441
[201,] -88.7633416 9.3375141
[202,] 84.7121217 -88.7633416
[203,] 53.6963343 84.7121217
[204,] -0.8591144 53.6963343
[205,] -64.0455228 -0.8591144
[206,] -29.0494631 -64.0455228
[207,] -20.9507060 -29.0494631
[208,] 76.3237159 -20.9507060
[209,] 429.7145126 76.3237159
[210,] 288.5358930 429.7145126
[211,] 77.7627161 288.5358930
[212,] -80.4551603 77.7627161
[213,] 79.2483486 -80.4551603
[214,] -25.7317752 79.2483486
[215,] -77.2061147 -25.7317752
[216,] 115.7058451 -77.2061147
[217,] 336.3649905 115.7058451
[218,] 62.7442075 336.3649905
[219,] 187.5767940 62.7442075
[220,] 110.3955506 187.5767940
[221,] 25.1871071 110.3955506
[222,] -83.7146403 25.1871071
[223,] -16.7055365 -83.7146403
[224,] 54.2508205 -16.7055365
[225,] 31.8819166 54.2508205
[226,] -5.5347362 31.8819166
[227,] -54.8014915 -5.5347362
[228,] 111.4662436 -54.8014915
[229,] 242.2683779 111.4662436
[230,] -2.1895260 242.2683779
[231,] -56.4692395 -2.1895260
[232,] -42.7257673 -56.4692395
[233,] 12.2521408 -42.7257673
[234,] 240.5795241 12.2521408
[235,] -68.9765568 240.5795241
[236,] -77.6760319 -68.9765568
[237,] -102.7083101 -77.6760319
[238,] 8.7700391 -102.7083101
[239,] 17.1881545 8.7700391
[240,] -82.7890951 17.1881545
[241,] -3.1816517 -82.7890951
[242,] -72.1879862 -3.1816517
[243,] -84.9779146 -72.1879862
[244,] -16.7047799 -84.9779146
[245,] -65.9534730 -16.7047799
[246,] -6.8400488 -65.9534730
[247,] 1.9328965 -6.8400488
[248,] -20.0047643 1.9328965
[249,] 51.0498706 -20.0047643
[250,] 53.5100828 51.0498706
[251,] 57.4279030 53.5100828
[252,] -48.9569909 57.4279030
[253,] 18.6693028 -48.9569909
[254,] -32.8039552 18.6693028
[255,] -158.0993015 -32.8039552
[256,] -91.0654274 -158.0993015
[257,] -84.9768446 -91.0654274
[258,] 160.4545011 -84.9768446
[259,] -58.8238776 160.4545011
[260,] -27.3325314 -58.8238776
[261,] 22.6643921 -27.3325314
[262,] 55.7181227 22.6643921
[263,] 105.4379217 55.7181227
[264,] 84.2360009 105.4379217
[265,] -43.5675328 84.2360009
[266,] 119.3974667 -43.5675328
[267,] -28.2903786 119.3974667
[268,] 8.6125245 -28.2903786
[269,] -27.5431460 8.6125245
[270,] 21.9169794 -27.5431460
[271,] -34.9461828 21.9169794
[272,] -66.8349276 -34.9461828
[273,] 388.2591916 -66.8349276
[274,] 130.2378136 388.2591916
[275,] 88.7175911 130.2378136
[276,] 34.5704547 88.7175911
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -95.8125253 -58.5362659
2 -136.6129152 -95.8125253
3 -2.7729405 -136.6129152
4 282.7405726 -2.7729405
5 -26.3996905 282.7405726
6 -247.7390609 -26.3996905
7 -135.8543896 -247.7390609
8 174.2655540 -135.8543896
9 100.8209741 174.2655540
10 -245.3840349 100.8209741
11 38.7603618 -245.3840349
12 8.4733853 38.7603618
13 -110.5817191 8.4733853
14 -11.2930106 -110.5817191
15 -96.8666382 -11.2930106
16 27.3099617 -96.8666382
17 -49.0699660 27.3099617
18 -103.9385370 -49.0699660
19 -101.0377649 -103.9385370
20 41.0501438 -101.0377649
21 -119.9108736 41.0501438
22 -39.0107701 -119.9108736
23 -91.1836043 -39.0107701
24 40.7724849 -91.1836043
25 -96.9839700 40.7724849
26 181.5760563 -96.9839700
27 -95.1962201 181.5760563
28 5.1941150 -95.1962201
29 49.5511006 5.1941150
30 243.5576105 49.5511006
31 -56.8682037 243.5576105
32 -258.7652705 -56.8682037
33 -211.0037096 -258.7652705
34 289.8583517 -211.0037096
35 -163.0130193 289.8583517
36 134.6475472 -163.0130193
37 -78.9480215 134.6475472
38 -445.7226488 -78.9480215
39 -71.1276703 -445.7226488
40 183.0204523 -71.1276703
41 345.1109597 183.0204523
42 -171.9363026 345.1109597
43 62.4800583 -171.9363026
44 -124.2983233 62.4800583
45 -472.9487553 -124.2983233
46 9.9560268 -472.9487553
47 -172.9890954 9.9560268
48 166.7979404 -172.9890954
49 389.6814369 166.7979404
50 1166.0007024 389.6814369
51 2.2341427 1166.0007024
52 159.5211687 2.2341427
53 -307.4830236 159.5211687
54 -125.1139582 -307.4830236
55 283.9762196 -125.1139582
56 -98.8990302 283.9762196
57 -133.3877162 -98.8990302
58 64.7276207 -133.3877162
59 -197.4461829 64.7276207
60 158.6933458 -197.4461829
61 -35.6064805 158.6933458
62 123.9583550 -35.6064805
63 -98.0368786 123.9583550
64 -190.7413586 -98.0368786
65 136.5703128 -190.7413586
66 -161.4447531 136.5703128
67 115.4489227 -161.4447531
68 -270.4250611 115.4489227
69 -14.6040860 -270.4250611
70 -364.3909530 -14.6040860
71 -177.3471569 -364.3909530
72 52.3462285 -177.3471569
73 71.1060141 52.3462285
74 -81.3031264 71.1060141
75 62.4562818 -81.3031264
76 274.3418278 62.4562818
77 -335.6865254 274.3418278
78 120.7920654 -335.6865254
79 -262.0318433 120.7920654
80 -198.5592748 -262.0318433
81 -12.9896689 -198.5592748
82 81.5843331 -12.9896689
83 -255.2361630 81.5843331
84 13.4791663 -255.2361630
85 120.9956851 13.4791663
86 99.7755110 120.9956851
87 3.7933487 99.7755110
88 88.8231199 3.7933487
89 128.6949257 88.8231199
90 -136.9718886 128.6949257
91 18.5133924 -136.9718886
92 -34.2708447 18.5133924
93 -142.0513794 -34.2708447
94 223.6140973 -142.0513794
95 246.5268401 223.6140973
96 -111.6197529 246.5268401
97 0.6702190 -111.6197529
98 -55.7949323 0.6702190
99 -209.7109026 -55.7949323
100 -51.5641617 -209.7109026
101 52.5532200 -51.5641617
102 -209.4636043 52.5532200
103 -229.6698554 -209.4636043
104 -101.0994227 -229.6698554
105 171.9179797 -101.0994227
106 -12.5685370 171.9179797
107 73.3381432 -12.5685370
108 134.5947001 73.3381432
109 -95.7119819 134.5947001
110 34.4655299 -95.7119819
111 -69.3369362 34.4655299
112 27.8610375 -69.3369362
113 40.1992536 27.8610375
114 -32.4585478 40.1992536
115 213.3583924 -32.4585478
116 99.1636516 213.3583924
117 -59.2218944 99.1636516
118 33.8621842 -59.2218944
119 -60.7756241 33.8621842
120 -117.5314819 -60.7756241
121 278.5017095 -117.5314819
122 93.7433857 278.5017095
123 -156.8480641 93.7433857
124 -42.6565946 -156.8480641
125 -61.4288419 -42.6565946
126 35.5544341 -61.4288419
127 -146.6447511 35.5544341
128 -30.6042329 -146.6447511
129 204.4894172 -30.6042329
130 -46.7166566 204.4894172
131 62.1290030 -46.7166566
132 66.7922984 62.1290030
133 211.8934505 66.7922984
134 -46.6608088 211.8934505
135 9.4218076 -46.6608088
136 -255.3951754 9.4218076
137 30.9210017 -255.3951754
138 -64.8302285 30.9210017
139 -82.6732887 -64.8302285
140 111.7986167 -82.6732887
141 -301.7338934 111.7986167
142 -148.9252888 -301.7338934
143 131.2858878 -148.9252888
144 -137.7932898 131.2858878
145 -97.3436828 -137.7932898
146 -33.7881458 -97.3436828
147 -412.2097828 -33.7881458
148 215.1610978 -412.2097828
149 -23.7928450 215.1610978
150 -99.9005737 -23.7928450
151 -241.4172204 -99.9005737
152 -57.1384182 -241.4172204
153 -27.1364048 -57.1384182
154 -90.6352722 -27.1364048
155 -119.8238617 -90.6352722
156 28.1645327 -119.8238617
157 137.6485503 28.1645327
158 5.4207950 137.6485503
159 -45.6944930 5.4207950
160 228.9024683 -45.6944930
161 153.6355716 228.9024683
162 -181.8451327 153.6355716
163 -31.2561129 -181.8451327
164 8.4773833 -31.2561129
165 21.2711947 8.4773833
166 24.6949955 21.2711947
167 -11.1699090 24.6949955
168 47.5344280 -11.1699090
169 113.8709884 47.5344280
170 -87.6113717 113.8709884
171 67.0081801 -87.6113717
172 71.3443318 67.0081801
173 -110.2442924 71.3443318
174 -204.9825326 -110.2442924
175 -106.8583066 -204.9825326
176 256.7722450 -106.8583066
177 28.4137626 256.7722450
178 69.2943894 28.4137626
179 -156.4080205 69.2943894
180 77.6925074 -156.4080205
181 172.6882726 77.6925074
182 -16.0288439 172.6882726
183 79.4804110 -16.0288439
184 -86.0802110 79.4804110
185 -45.3685694 -86.0802110
186 -39.4505131 -45.3685694
187 -32.5977916 -39.4505131
188 -13.8218725 -32.5977916
189 -24.0151631 -13.8218725
190 -48.5790115 -24.0151631
191 22.3818251 -48.5790115
192 19.9386830 22.3818251
193 1.7707616 19.9386830
194 157.7478815 1.7707616
195 -55.1991392 157.7478815
196 16.6026562 -55.1991392
197 -5.0042729 16.6026562
198 87.1872451 -5.0042729
199 241.1225441 87.1872451
200 9.3375141 241.1225441
201 -88.7633416 9.3375141
202 84.7121217 -88.7633416
203 53.6963343 84.7121217
204 -0.8591144 53.6963343
205 -64.0455228 -0.8591144
206 -29.0494631 -64.0455228
207 -20.9507060 -29.0494631
208 76.3237159 -20.9507060
209 429.7145126 76.3237159
210 288.5358930 429.7145126
211 77.7627161 288.5358930
212 -80.4551603 77.7627161
213 79.2483486 -80.4551603
214 -25.7317752 79.2483486
215 -77.2061147 -25.7317752
216 115.7058451 -77.2061147
217 336.3649905 115.7058451
218 62.7442075 336.3649905
219 187.5767940 62.7442075
220 110.3955506 187.5767940
221 25.1871071 110.3955506
222 -83.7146403 25.1871071
223 -16.7055365 -83.7146403
224 54.2508205 -16.7055365
225 31.8819166 54.2508205
226 -5.5347362 31.8819166
227 -54.8014915 -5.5347362
228 111.4662436 -54.8014915
229 242.2683779 111.4662436
230 -2.1895260 242.2683779
231 -56.4692395 -2.1895260
232 -42.7257673 -56.4692395
233 12.2521408 -42.7257673
234 240.5795241 12.2521408
235 -68.9765568 240.5795241
236 -77.6760319 -68.9765568
237 -102.7083101 -77.6760319
238 8.7700391 -102.7083101
239 17.1881545 8.7700391
240 -82.7890951 17.1881545
241 -3.1816517 -82.7890951
242 -72.1879862 -3.1816517
243 -84.9779146 -72.1879862
244 -16.7047799 -84.9779146
245 -65.9534730 -16.7047799
246 -6.8400488 -65.9534730
247 1.9328965 -6.8400488
248 -20.0047643 1.9328965
249 51.0498706 -20.0047643
250 53.5100828 51.0498706
251 57.4279030 53.5100828
252 -48.9569909 57.4279030
253 18.6693028 -48.9569909
254 -32.8039552 18.6693028
255 -158.0993015 -32.8039552
256 -91.0654274 -158.0993015
257 -84.9768446 -91.0654274
258 160.4545011 -84.9768446
259 -58.8238776 160.4545011
260 -27.3325314 -58.8238776
261 22.6643921 -27.3325314
262 55.7181227 22.6643921
263 105.4379217 55.7181227
264 84.2360009 105.4379217
265 -43.5675328 84.2360009
266 119.3974667 -43.5675328
267 -28.2903786 119.3974667
268 8.6125245 -28.2903786
269 -27.5431460 8.6125245
270 21.9169794 -27.5431460
271 -34.9461828 21.9169794
272 -66.8349276 -34.9461828
273 388.2591916 -66.8349276
274 130.2378136 388.2591916
275 88.7175911 130.2378136
276 34.5704547 88.7175911
> 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/7nmyp1355474619.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8llnx1355474619.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/97i0a1355474619.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10dl3a1355474619.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11kqjg1355474619.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/12prj71355474619.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/13uh0v1355474619.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/14oykc1355474619.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/1592be1355474619.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/16gydr1355474619.tab")
+ }
>
> try(system("convert tmp/1i5nu1355474619.ps tmp/1i5nu1355474619.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mpo61355474619.ps tmp/2mpo61355474619.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bgya1355474619.ps tmp/3bgya1355474619.png",intern=TRUE))
character(0)
> try(system("convert tmp/4rav31355474619.ps tmp/4rav31355474619.png",intern=TRUE))
character(0)
> try(system("convert tmp/511uc1355474619.ps tmp/511uc1355474619.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ak811355474619.ps tmp/6ak811355474619.png",intern=TRUE))
character(0)
> try(system("convert tmp/7nmyp1355474619.ps tmp/7nmyp1355474619.png",intern=TRUE))
character(0)
> try(system("convert tmp/8llnx1355474619.ps tmp/8llnx1355474619.png",intern=TRUE))
character(0)
> try(system("convert tmp/97i0a1355474619.ps tmp/97i0a1355474619.png",intern=TRUE))
character(0)
> try(system("convert tmp/10dl3a1355474619.ps tmp/10dl3a1355474619.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
11.775 1.018 12.811