R version 2.12.0 (2010-10-15)
Copyright (C) 2010 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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+ ,50857
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+ ,37
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+ ,24
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+ ,56613
+ ,19
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+ ,12
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+ ,16
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+ ,62792
+ ,35
+ ,28
+ ,15
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+ ,72
+ ,894
+ ,72535
+ ,14
+ ,17
+ ,16
+ ,64
+ ,39
+ ,19540
+ ,21)
+ ,dim=c(9
+ ,289)
+ ,dimnames=list(c('pageviews'
+ ,'time_in_rfc'
+ ,'logins'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'feedback_messages_p1'
+ ,'feedback_messages_p120'
+ ,'totsize'
+ ,'totblogs')
+ ,1:289))
> y <- array(NA,dim=c(9,289),dimnames=list(c('pageviews','time_in_rfc','logins','blogged_computations','compendiums_reviewed','feedback_messages_p1','feedback_messages_p120','totsize','totblogs'),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 = '2'
> #'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
time_in_rfc pageviews logins blogged_computations compendiums_reviewed
1 210907 1418 56 79 30
2 120982 869 56 58 28
3 176508 1530 54 60 38
4 179321 2172 89 108 30
5 123185 901 40 49 22
6 52746 463 25 0 26
7 385534 3201 92 121 25
8 33170 371 18 1 18
9 101645 1192 63 20 11
10 149061 1583 44 43 26
11 165446 1439 33 69 25
12 237213 1764 84 78 38
13 173326 1495 88 86 44
14 133131 1373 55 44 30
15 258873 2187 60 104 40
16 180083 1491 66 63 34
17 324799 4041 154 158 47
18 230964 1706 53 102 30
19 236785 2152 119 77 31
20 135473 1036 41 82 23
21 202925 1882 61 115 36
22 215147 1929 58 101 36
23 344297 2242 75 80 30
24 153935 1220 33 50 25
25 132943 1289 40 83 39
26 174724 2515 92 123 34
27 174415 2147 100 73 31
28 225548 2352 112 81 31
29 223632 1638 73 105 33
30 124817 1222 40 47 25
31 221698 1812 45 105 33
32 210767 1677 60 94 35
33 170266 1579 62 44 42
34 260561 1731 75 114 43
35 84853 807 31 38 30
36 294424 2452 77 107 33
37 101011 829 34 30 13
38 215641 1940 46 71 32
39 325107 2662 99 84 36
40 7176 186 17 0 0
41 167542 1499 66 59 28
42 106408 865 30 33 14
43 96560 1793 76 42 17
44 265769 2527 146 96 32
45 269651 2747 67 106 30
46 149112 1324 56 56 35
47 175824 2702 107 57 20
48 152871 1383 58 59 28
49 111665 1179 34 39 28
50 116408 2099 61 34 39
51 362301 4308 119 76 34
52 78800 918 42 20 26
53 183167 1831 66 91 39
54 277965 3373 89 115 39
55 150629 1713 44 85 33
56 168809 1438 66 76 28
57 24188 496 24 8 4
58 329267 2253 259 79 39
59 65029 744 17 21 18
60 101097 1161 64 30 14
61 218946 2352 41 76 29
62 244052 2144 68 101 44
63 341570 4691 168 94 21
64 103597 1112 43 27 16
65 233328 2694 132 92 28
66 256462 1973 105 123 35
67 206161 1769 71 75 28
68 311473 3148 112 128 38
69 235800 2474 94 105 23
70 177939 2084 82 55 36
71 207176 1954 70 56 32
72 196553 1226 57 41 29
73 174184 1389 53 72 25
74 143246 1496 103 67 27
75 187559 2269 121 75 36
76 187681 1833 62 114 28
77 119016 1268 52 118 23
78 182192 1943 52 77 40
79 73566 893 32 22 23
80 194979 1762 62 66 40
81 167488 1403 45 69 28
82 143756 1425 46 105 34
83 275541 1857 63 116 33
84 243199 1840 75 88 28
85 182999 1502 88 73 34
86 135649 1441 46 99 30
87 152299 1420 53 62 33
88 120221 1416 37 53 22
89 346485 2970 90 118 38
90 145790 1317 63 30 26
91 193339 1644 78 100 35
92 80953 870 25 49 8
93 122774 1654 45 24 24
94 130585 1054 46 67 29
95 112611 937 41 46 20
96 286468 3004 144 57 29
97 241066 2008 82 75 45
98 148446 2547 91 135 37
99 204713 1885 71 68 33
100 182079 1626 63 124 33
101 140344 1468 53 33 25
102 220516 2445 62 98 32
103 243060 1964 63 58 29
104 162765 1381 32 68 28
105 182613 1369 39 81 28
106 232138 1659 62 131 31
107 265318 2888 117 110 52
108 85574 1290 34 37 21
109 310839 2845 92 130 24
110 225060 1982 93 93 41
111 232317 1904 54 118 33
112 144966 1391 144 39 32
113 43287 602 14 13 19
114 155754 1743 61 74 20
115 164709 1559 109 81 31
116 201940 2014 38 109 31
117 235454 2143 73 151 32
118 220801 2146 75 51 18
119 99466 874 50 28 23
120 92661 1590 61 40 17
121 133328 1590 55 56 20
122 61361 1210 77 27 12
123 125930 2072 75 37 17
124 100750 1281 72 83 30
125 224549 1401 50 54 31
126 82316 834 32 27 10
127 102010 1105 53 28 13
128 101523 1272 42 59 22
129 243511 1944 71 133 42
130 22938 391 10 12 1
131 41566 761 35 0 9
132 152474 1605 65 106 32
133 61857 530 25 23 11
134 99923 1988 66 44 25
135 132487 1386 41 71 36
136 317394 2395 86 116 31
137 21054 387 16 4 0
138 209641 1742 42 62 24
139 22648 620 19 12 13
140 31414 449 19 18 8
141 46698 800 45 14 13
142 131698 1684 65 60 19
143 91735 1050 35 7 18
144 244749 2699 95 98 33
145 184510 1606 49 64 40
146 79863 1502 37 29 22
147 128423 1204 64 32 38
148 97839 1138 38 25 24
149 38214 568 34 16 8
150 151101 1459 32 48 35
151 272458 2158 65 100 43
152 172494 1111 52 46 43
153 108043 1421 62 45 14
154 328107 2833 65 129 41
155 250579 1955 83 130 38
156 351067 2922 95 136 45
157 158015 1002 29 59 31
158 98866 1060 18 25 13
159 85439 956 33 32 28
160 229242 2186 247 63 31
161 351619 3604 139 95 40
162 84207 1035 29 14 30
163 120445 1417 118 36 16
164 324598 3261 110 113 37
165 131069 1587 67 47 30
166 204271 1424 42 92 35
167 165543 1701 65 70 32
168 141722 1249 94 19 27
169 116048 946 64 50 20
170 250047 1926 81 41 18
171 299775 3352 95 91 31
172 195838 1641 67 111 31
173 173260 2035 63 41 21
174 254488 2312 83 120 39
175 104389 1369 45 135 41
176 136084 1577 30 27 13
177 199476 2201 70 87 32
178 92499 961 32 25 18
179 224330 1900 83 131 39
180 135781 1254 31 45 14
181 74408 1335 67 29 7
182 81240 1597 66 58 17
183 14688 207 10 4 0
184 181633 1645 70 47 30
185 271856 2429 103 109 37
186 7199 151 5 7 0
187 46660 474 20 12 5
188 17547 141 5 0 1
189 133368 1639 36 37 16
190 95227 872 34 37 32
191 152601 1318 48 46 24
192 98146 1018 40 15 17
193 79619 1383 43 42 11
194 59194 1314 31 7 24
195 139942 1335 42 54 22
196 118612 1403 46 54 12
197 72880 910 33 14 19
198 65475 616 18 16 13
199 99643 1407 55 33 17
200 71965 771 35 32 15
201 77272 766 59 21 16
202 49289 473 19 15 24
203 135131 1376 66 38 15
204 108446 1232 60 22 17
205 89746 1521 36 28 18
206 44296 572 25 10 20
207 77648 1059 47 31 16
208 181528 1544 54 32 16
209 134019 1230 53 32 18
210 124064 1206 40 43 22
211 92630 1205 40 27 8
212 121848 1255 39 37 17
213 52915 613 14 20 18
214 81872 721 45 32 16
215 58981 1109 36 0 23
216 53515 740 28 5 22
217 60812 1126 44 26 13
218 56375 728 30 10 13
219 65490 689 22 27 16
220 80949 592 17 11 16
221 76302 995 31 29 20
222 104011 1613 55 25 22
223 98104 2048 54 55 17
224 67989 705 21 23 18
225 30989 301 14 5 17
226 135458 1803 81 43 12
227 73504 799 35 23 7
228 63123 861 43 34 17
229 61254 1186 46 36 14
230 74914 1451 30 35 23
231 31774 628 23 0 17
232 81437 1161 38 37 14
233 87186 1463 54 28 15
234 50090 742 20 16 17
235 65745 979 53 26 21
236 56653 675 45 38 18
237 158399 1241 39 23 18
238 46455 676 20 22 17
239 73624 1049 24 30 17
240 38395 620 31 16 16
241 91899 1081 35 18 15
242 139526 1688 151 28 21
243 52164 736 52 32 16
244 51567 617 30 21 14
245 70551 812 31 23 15
246 84856 1051 29 29 17
247 102538 1656 57 50 15
248 86678 705 40 12 15
249 85709 945 44 21 10
250 34662 554 25 18 6
251 150580 1597 77 27 22
252 99611 982 35 41 21
253 19349 222 11 13 1
254 99373 1212 63 12 18
255 86230 1143 44 21 17
256 30837 435 19 8 4
257 31706 532 13 26 10
258 89806 882 42 27 16
259 62088 608 38 13 16
260 40151 459 29 16 9
261 27634 578 20 2 16
262 76990 826 27 42 17
263 37460 509 20 5 7
264 54157 717 19 37 15
265 49862 637 37 17 14
266 84337 857 26 38 14
267 64175 830 42 37 18
268 59382 652 49 29 12
269 119308 707 30 32 16
270 76702 954 49 35 21
271 103425 1461 67 17 19
272 70344 672 28 20 16
273 43410 778 19 7 1
274 104838 1141 49 46 16
275 62215 680 27 24 10
276 69304 1090 30 40 19
277 53117 616 22 3 12
278 19764 285 12 10 2
279 86680 1145 31 37 14
280 84105 733 20 17 17
281 77945 888 20 28 19
282 89113 849 39 19 14
283 91005 1182 29 29 11
284 40248 528 16 8 4
285 64187 642 27 10 16
286 50857 947 21 15 20
287 56613 819 19 15 12
288 62792 757 35 28 15
289 72535 894 14 17 16
feedback_messages_p1 feedback_messages_p120 totsize totblogs
1 115 94 112285 145
2 109 103 84786 101
3 146 93 83123 98
4 116 103 101193 132
5 68 51 38361 60
6 101 70 68504 38
7 96 91 119182 144
8 67 22 22807 5
9 44 38 17140 28
10 100 93 116174 84
11 93 60 57635 79
12 140 123 66198 127
13 166 148 71701 78
14 99 90 57793 60
15 139 124 80444 131
16 130 70 53855 84
17 181 168 97668 133
18 116 115 133824 150
19 116 71 101481 91
20 88 66 99645 132
21 139 134 114789 136
22 135 117 99052 124
23 108 108 67654 118
24 89 84 65553 70
25 156 156 97500 107
26 129 120 69112 119
27 118 114 82753 89
28 118 94 85323 112
29 125 120 72654 108
30 95 81 30727 52
31 126 110 77873 112
32 135 133 117478 116
33 154 122 74007 123
34 165 158 90183 125
35 113 109 61542 27
36 127 124 101494 162
37 52 39 27570 32
38 121 92 55813 64
39 136 126 79215 92
40 0 0 1423 0
41 108 70 55461 83
42 46 37 31081 41
43 54 38 22996 47
44 124 120 83122 120
45 115 93 70106 105
46 128 95 60578 79
47 80 77 39992 65
48 97 90 79892 70
49 104 80 49810 55
50 59 31 71570 39
51 125 110 100708 67
52 82 66 33032 21
53 149 138 82875 127
54 149 133 139077 152
55 122 113 71595 113
56 118 100 72260 99
57 12 7 5950 7
58 144 140 115762 141
59 67 61 32551 21
60 52 41 31701 35
61 108 96 80670 109
62 166 164 143558 133
63 80 78 117105 123
64 60 49 23789 26
65 107 102 120733 230
66 127 124 105195 166
67 107 99 73107 68
68 146 129 132068 147
69 84 62 149193 179
70 141 73 46821 61
71 123 114 87011 101
72 111 99 95260 108
73 98 70 55183 90
74 105 104 106671 114
75 135 116 73511 103
76 107 91 92945 142
77 85 74 78664 79
78 155 138 70054 88
79 88 67 22618 25
80 155 151 74011 83
81 104 72 83737 113
82 132 120 69094 118
83 127 115 93133 110
84 108 105 95536 129
85 129 104 225920 51
86 116 108 62133 93
87 122 98 61370 76
88 85 69 43836 49
89 147 111 106117 118
90 99 99 38692 38
91 87 71 84651 141
92 28 27 56622 58
93 90 69 15986 27
94 109 107 95364 91
95 78 73 26706 48
96 111 107 89691 63
97 158 93 67267 56
98 141 129 126846 144
99 122 69 41140 73
100 124 118 102860 168
101 93 73 51715 64
102 124 119 55801 97
103 112 104 111813 117
104 108 107 120293 100
105 99 99 138599 149
106 117 90 161647 187
107 199 197 115929 127
108 78 36 24266 37
109 91 85 162901 245
110 158 139 109825 87
111 126 106 129838 177
112 122 50 37510 49
113 71 64 43750 49
114 75 31 40652 73
115 115 63 87771 177
116 119 92 85872 94
117 124 106 89275 117
118 72 63 44418 60
119 91 69 192565 55
120 45 41 35232 39
121 78 56 40909 64
122 39 25 13294 26
123 68 65 32387 64
124 119 93 140867 58
125 117 114 120662 95
126 39 38 21233 25
127 50 44 44332 26
128 88 87 61056 76
129 155 110 101338 129
130 0 0 1168 11
131 36 27 13497 2
132 123 83 65567 101
133 32 30 25162 28
134 99 80 32334 36
135 136 98 40735 89
136 117 82 91413 193
137 0 0 855 4
138 88 60 97068 84
139 39 28 44339 23
140 25 9 14116 39
141 52 33 10288 14
142 75 59 65622 78
143 71 49 16563 14
144 124 115 76643 101
145 151 140 110681 82
146 71 49 29011 24
147 145 120 92696 36
148 87 66 94785 75
149 27 21 8773 16
150 131 124 83209 55
151 162 152 93815 131
152 165 139 86687 131
153 54 38 34553 39
154 159 144 105547 144
155 147 120 103487 139
156 170 160 213688 211
157 119 114 71220 78
158 49 39 23517 50
159 104 78 56926 39
160 120 119 91721 90
161 150 141 115168 166
162 112 101 111194 12
163 59 56 51009 57
164 136 133 135777 133
165 107 83 51513 69
166 130 116 74163 119
167 115 90 51633 119
168 107 36 75345 65
169 75 50 33416 61
170 71 61 83305 49
171 120 97 98952 101
172 116 98 102372 196
173 79 78 37238 15
174 150 117 103772 136
175 156 148 123969 89
176 51 41 27142 40
177 118 105 135400 123
178 71 55 21399 21
179 144 132 130115 163
180 47 44 24874 29
181 28 21 34988 35
182 68 50 45549 13
183 0 0 6023 5
184 110 73 64466 96
185 147 86 54990 151
186 0 0 1644 6
187 15 13 6179 13
188 4 4 3926 3
189 64 57 32755 56
190 111 48 34777 23
191 85 46 73224 57
192 68 48 27114 14
193 40 32 20760 43
194 80 68 37636 20
195 88 87 65461 72
196 48 43 30080 87
197 76 67 24094 21
198 51 46 69008 56
199 67 46 54968 59
200 59 56 46090 82
201 61 48 27507 43
202 76 44 10672 25
203 60 60 34029 38
204 68 65 46300 25
205 71 55 24760 38
206 76 38 18779 12
207 62 52 21280 29
208 61 60 40662 47
209 67 54 28987 45
210 88 86 22827 40
211 30 24 18513 30
212 64 52 30594 41
213 68 49 24006 25
214 64 61 27913 23
215 91 61 42744 14
216 88 81 12934 16
217 52 43 22574 26
218 49 40 41385 21
219 62 40 18653 27
220 61 56 18472 9
221 76 68 30976 33
222 88 79 63339 42
223 66 47 25568 68
224 71 57 33747 32
225 68 41 4154 6
226 48 29 19474 67
227 25 3 35130 33
228 68 60 39067 77
229 41 30 13310 46
230 90 79 65892 30
231 66 47 4143 0
232 54 40 28579 36
233 59 48 51776 46
234 60 36 21152 18
235 77 42 38084 48
236 68 49 27717 29
237 72 57 32928 28
238 67 12 11342 34
239 64 40 19499 33
240 63 43 16380 34
241 59 33 36874 33
242 84 77 48259 80
243 64 43 16734 32
244 56 45 28207 30
245 54 47 30143 41
246 67 43 41369 41
247 58 45 45833 51
248 59 50 29156 18
249 40 35 35944 34
250 22 7 36278 31
251 83 71 45588 39
252 81 67 45097 54
253 2 0 3895 14
254 72 62 28394 24
255 61 54 18632 24
256 15 4 2325 8
257 32 25 25139 26
258 62 40 27975 19
259 58 38 14483 11
260 36 19 13127 14
261 59 17 5839 1
262 68 67 24069 39
263 21 14 3738 5
264 55 30 18625 37
265 54 54 36341 32
266 55 35 24548 38
267 72 59 21792 47
268 41 24 26263 47
269 61 58 23686 37
270 67 42 49303 51
271 76 46 25659 45
272 64 61 28904 21
273 3 3 2781 1
274 63 52 29236 42
275 40 25 19546 26
276 69 40 22818 21
277 48 32 32689 4
278 8 4 5752 10
279 52 49 22197 43
280 66 63 20055 34
281 76 67 25272 31
282 43 32 82206 19
283 39 23 32073 34
284 14 7 5444 6
285 61 54 20154 11
286 71 37 36944 24
287 44 35 8019 16
288 60 51 30884 72
289 64 39 19540 21
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) pageviews logins
-1.457e+04 5.940e+01 1.102e+02
blogged_computations compendiums_reviewed feedback_messages_p1
1.160e+02 -4.623e+02 3.035e+02
feedback_messages_p120 totsize totblogs
1.374e+02 1.177e-01 3.555e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-123508 -15384 -219 14057 124480
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.457e+04 4.546e+03 -3.205 0.00150 **
pageviews 5.940e+01 4.508e+00 13.176 < 2e-16 ***
logins 1.102e+02 7.848e+01 1.404 0.16128
blogged_computations 1.160e+02 1.162e+02 0.998 0.31896
compendiums_reviewed -4.623e+02 9.097e+02 -0.508 0.61173
feedback_messages_p1 3.035e+02 2.758e+02 1.100 0.27216
feedback_messages_p120 1.374e+02 1.346e+02 1.021 0.30807
totsize 1.177e-01 7.681e-02 1.532 0.12653
totblogs 3.555e+02 8.269e+01 4.300 2.36e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 28610 on 280 degrees of freedom
Multiple R-squared: 0.8826, Adjusted R-squared: 0.8792
F-statistic: 263.1 on 8 and 280 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,] 0.7968168 4.063664e-01 2.031832e-01
[2,] 0.9038174 1.923652e-01 9.618258e-02
[3,] 0.8865236 2.269528e-01 1.134764e-01
[4,] 0.8540593 2.918814e-01 1.459407e-01
[5,] 0.7846549 4.306901e-01 2.153451e-01
[6,] 0.8530289 2.939422e-01 1.469711e-01
[7,] 0.7963087 4.073826e-01 2.036913e-01
[8,] 0.7697114 4.605773e-01 2.302886e-01
[9,] 0.7907272 4.185456e-01 2.092728e-01
[10,] 0.7268777 5.462446e-01 2.731223e-01
[11,] 0.6549803 6.900393e-01 3.450197e-01
[12,] 0.9361687 1.276626e-01 6.383131e-02
[13,] 0.9163415 1.673170e-01 8.365851e-02
[14,] 0.8921348 2.157303e-01 1.078652e-01
[15,] 0.9722473 5.550544e-02 2.775272e-02
[16,] 0.9755393 4.892132e-02 2.446066e-02
[17,] 0.9724581 5.508379e-02 2.754189e-02
[18,] 0.9905248 1.895049e-02 9.475246e-03
[19,] 0.9860601 2.787978e-02 1.393989e-02
[20,] 0.9844271 3.114587e-02 1.557293e-02
[21,] 0.9840030 3.199393e-02 1.599696e-02
[22,] 0.9902285 1.954298e-02 9.771489e-03
[23,] 0.9969618 6.076477e-03 3.038239e-03
[24,] 0.9957136 8.572826e-03 4.286413e-03
[25,] 0.9943164 1.136713e-02 5.683567e-03
[26,] 0.9928832 1.423361e-02 7.116804e-03
[27,] 0.9927826 1.443476e-02 7.217379e-03
[28,] 0.9986354 2.729101e-03 1.364551e-03
[29,] 0.9981139 3.772105e-03 1.886053e-03
[30,] 0.9972939 5.412213e-03 2.706107e-03
[31,] 0.9964213 7.157446e-03 3.578723e-03
[32,] 0.9992368 1.526489e-03 7.632444e-04
[33,] 0.9990431 1.913824e-03 9.569119e-04
[34,] 0.9986908 2.618498e-03 1.309249e-03
[35,] 0.9981040 3.792078e-03 1.896039e-03
[36,] 0.9988990 2.202060e-03 1.101030e-03
[37,] 0.9984183 3.163473e-03 1.581737e-03
[38,] 0.9979051 4.189816e-03 2.094908e-03
[39,] 0.9986678 2.664376e-03 1.332188e-03
[40,] 0.9984054 3.189282e-03 1.594641e-03
[41,] 0.9977472 4.505571e-03 2.252786e-03
[42,] 0.9981097 3.780570e-03 1.890285e-03
[43,] 0.9992583 1.483466e-03 7.417330e-04
[44,] 0.9995538 8.924472e-04 4.462236e-04
[45,] 0.9993558 1.288390e-03 6.441950e-04
[46,] 0.9991395 1.721062e-03 8.605309e-04
[47,] 0.9997054 5.892975e-04 2.946487e-04
[48,] 0.9995692 8.616105e-04 4.308053e-04
[49,] 0.9993896 1.220743e-03 6.103713e-04
[50,] 0.9991402 1.719667e-03 8.598334e-04
[51,] 0.9987871 2.425887e-03 1.212944e-03
[52,] 0.9991530 1.693971e-03 8.469857e-04
[53,] 0.9988650 2.270027e-03 1.135014e-03
[54,] 0.9998003 3.994390e-04 1.997195e-04
[55,] 0.9997327 5.346619e-04 2.673310e-04
[56,] 0.9997205 5.589532e-04 2.794766e-04
[57,] 0.9996004 7.992849e-04 3.996425e-04
[58,] 0.9995492 9.016457e-04 4.508228e-04
[59,] 0.9993985 1.202915e-03 6.014576e-04
[60,] 0.9991837 1.632691e-03 8.163453e-04
[61,] 0.9994444 1.111135e-03 5.555675e-04
[62,] 0.9993481 1.303848e-03 6.519240e-04
[63,] 0.9994916 1.016854e-03 5.084268e-04
[64,] 0.9996182 7.636597e-04 3.818299e-04
[65,] 0.9995650 8.700177e-04 4.350088e-04
[66,] 0.9995648 8.704765e-04 4.352382e-04
[67,] 0.9994851 1.029847e-03 5.149235e-04
[68,] 0.9993232 1.353565e-03 6.767823e-04
[69,] 0.9990700 1.860081e-03 9.300403e-04
[70,] 0.9987440 2.511945e-03 1.255973e-03
[71,] 0.9988891 2.221814e-03 1.110907e-03
[72,] 0.9997236 5.528372e-04 2.764186e-04
[73,] 0.9997754 4.492484e-04 2.246242e-04
[74,] 0.9996891 6.218437e-04 3.109219e-04
[75,] 0.9996944 6.112988e-04 3.056494e-04
[76,] 0.9995744 8.512275e-04 4.256138e-04
[77,] 0.9994313 1.137325e-03 5.686627e-04
[78,] 0.9998269 3.461881e-04 1.730941e-04
[79,] 0.9997946 4.107052e-04 2.053526e-04
[80,] 0.9997218 5.563128e-04 2.781564e-04
[81,] 0.9996170 7.659574e-04 3.829787e-04
[82,] 0.9994811 1.037802e-03 5.189010e-04
[83,] 0.9993118 1.376303e-03 6.881516e-04
[84,] 0.9991439 1.712248e-03 8.561239e-04
[85,] 0.9991777 1.644542e-03 8.222711e-04
[86,] 0.9995365 9.269285e-04 4.634642e-04
[87,] 0.9999990 1.948282e-06 9.741412e-07
[88,] 0.9999990 1.940307e-06 9.701536e-07
[89,] 0.9999991 1.879141e-06 9.395706e-07
[90,] 0.9999986 2.868582e-06 1.434291e-06
[91,] 0.9999979 4.255926e-06 2.127963e-06
[92,] 0.9999984 3.186799e-06 1.593399e-06
[93,] 0.9999976 4.859569e-06 2.429785e-06
[94,] 0.9999964 7.265872e-06 3.632936e-06
[95,] 0.9999947 1.063366e-05 5.316828e-06
[96,] 0.9999957 8.503014e-06 4.251507e-06
[97,] 0.9999951 9.773261e-06 4.886631e-06
[98,] 0.9999930 1.405002e-05 7.025010e-06
[99,] 0.9999901 1.975013e-05 9.875067e-06
[100,] 0.9999856 2.885169e-05 1.442584e-05
[101,] 0.9999826 3.485295e-05 1.742648e-05
[102,] 0.9999822 3.558823e-05 1.779411e-05
[103,] 0.9999747 5.067443e-05 2.533722e-05
[104,] 0.9999805 3.904625e-05 1.952313e-05
[105,] 0.9999717 5.655505e-05 2.827753e-05
[106,] 0.9999606 7.885684e-05 3.942842e-05
[107,] 0.9999757 4.852699e-05 2.426350e-05
[108,] 0.9999705 5.902266e-05 2.951133e-05
[109,] 0.9999705 5.906143e-05 2.953072e-05
[110,] 0.9999595 8.104545e-05 4.052273e-05
[111,] 0.9999601 7.972639e-05 3.986319e-05
[112,] 0.9999765 4.698527e-05 2.349263e-05
[113,] 0.9999895 2.104069e-05 1.052035e-05
[114,] 0.9999969 6.290083e-06 3.145042e-06
[115,] 0.9999958 8.391108e-06 4.195554e-06
[116,] 0.9999941 1.176165e-05 5.880827e-06
[117,] 0.9999953 9.392397e-06 4.696198e-06
[118,] 0.9999944 1.112553e-05 5.562765e-06
[119,] 0.9999919 1.626142e-05 8.130708e-06
[120,] 0.9999883 2.331669e-05 1.165835e-05
[121,] 0.9999870 2.591804e-05 1.295902e-05
[122,] 0.9999836 3.273965e-05 1.636983e-05
[123,] 0.9999963 7.375304e-06 3.687652e-06
[124,] 0.9999957 8.695414e-06 4.347707e-06
[125,] 0.9999986 2.765142e-06 1.382571e-06
[126,] 0.9999980 4.092584e-06 2.046292e-06
[127,] 0.9999990 2.050504e-06 1.025252e-06
[128,] 0.9999989 2.243308e-06 1.121654e-06
[129,] 0.9999983 3.373167e-06 1.686583e-06
[130,] 0.9999977 4.623381e-06 2.311691e-06
[131,] 0.9999975 4.927037e-06 2.463518e-06
[132,] 0.9999966 6.850755e-06 3.425377e-06
[133,] 0.9999949 1.011082e-05 5.055409e-06
[134,] 0.9999925 1.498299e-05 7.491496e-06
[135,] 0.9999931 1.372696e-05 6.863480e-06
[136,] 0.9999900 2.008636e-05 1.004318e-05
[137,] 0.9999887 2.260832e-05 1.130416e-05
[138,] 0.9999834 3.323695e-05 1.661848e-05
[139,] 0.9999757 4.853643e-05 2.426822e-05
[140,] 0.9999797 4.052554e-05 2.026277e-05
[141,] 0.9999719 5.613799e-05 2.806899e-05
[142,] 0.9999605 7.898735e-05 3.949367e-05
[143,] 0.9999768 4.649851e-05 2.324926e-05
[144,] 0.9999762 4.757728e-05 2.378864e-05
[145,] 0.9999724 5.519460e-05 2.759730e-05
[146,] 0.9999794 4.114781e-05 2.057390e-05
[147,] 0.9999719 5.627132e-05 2.813566e-05
[148,] 0.9999614 7.720932e-05 3.860466e-05
[149,] 0.9999448 1.104973e-04 5.524863e-05
[150,] 0.9999288 1.423436e-04 7.117180e-05
[151,] 0.9999106 1.787927e-04 8.939635e-05
[152,] 0.9998841 2.317922e-04 1.158961e-04
[153,] 0.9998721 2.557544e-04 1.278772e-04
[154,] 0.9998447 3.105156e-04 1.552578e-04
[155,] 0.9999077 1.845192e-04 9.225958e-05
[156,] 0.9998756 2.488480e-04 1.244240e-04
[157,] 0.9998374 3.251881e-04 1.625941e-04
[158,] 0.9998047 3.906376e-04 1.953188e-04
[159,] 0.9999967 6.581751e-06 3.290875e-06
[160,] 0.9999972 5.564540e-06 2.782270e-06
[161,] 0.9999961 7.820891e-06 3.910445e-06
[162,] 0.9999963 7.459133e-06 3.729567e-06
[163,] 0.9999968 6.319671e-06 3.159836e-06
[164,] 0.9999998 4.345273e-07 2.172637e-07
[165,] 0.9999998 3.710350e-07 1.855175e-07
[166,] 0.9999997 5.035994e-07 2.517997e-07
[167,] 0.9999996 7.191150e-07 3.595575e-07
[168,] 0.9999995 1.014691e-06 5.073454e-07
[169,] 0.9999998 4.831739e-07 2.415870e-07
[170,] 0.9999997 5.440167e-07 2.720083e-07
[171,] 0.9999999 1.210060e-07 6.050301e-08
[172,] 0.9999999 1.955812e-07 9.779062e-08
[173,] 0.9999999 1.125752e-07 5.628762e-08
[174,] 1.0000000 1.387609e-08 6.938046e-09
[175,] 1.0000000 2.286288e-08 1.143144e-08
[176,] 1.0000000 3.525904e-08 1.762952e-08
[177,] 1.0000000 5.713567e-08 2.856783e-08
[178,] 1.0000000 6.729250e-08 3.364625e-08
[179,] 1.0000000 8.061595e-08 4.030798e-08
[180,] 1.0000000 1.621825e-08 8.109126e-09
[181,] 1.0000000 1.999954e-08 9.999771e-09
[182,] 1.0000000 2.172972e-08 1.086486e-08
[183,] 1.0000000 1.280085e-08 6.400427e-09
[184,] 1.0000000 1.807416e-08 9.037080e-09
[185,] 1.0000000 2.698283e-08 1.349141e-08
[186,] 1.0000000 4.568798e-08 2.284399e-08
[187,] 1.0000000 7.704277e-08 3.852138e-08
[188,] 0.9999999 1.207049e-07 6.035246e-08
[189,] 0.9999999 1.986915e-07 9.934574e-08
[190,] 0.9999998 3.413979e-07 1.706989e-07
[191,] 0.9999997 5.080031e-07 2.540016e-07
[192,] 0.9999997 6.836000e-07 3.418000e-07
[193,] 0.9999994 1.162454e-06 5.812272e-07
[194,] 0.9999993 1.453024e-06 7.265119e-07
[195,] 0.9999988 2.420895e-06 1.210448e-06
[196,] 0.9999982 3.502120e-06 1.751060e-06
[197,] 0.9999999 1.122695e-07 5.613474e-08
[198,] 1.0000000 3.650906e-08 1.825453e-08
[199,] 1.0000000 4.692595e-08 2.346298e-08
[200,] 1.0000000 7.789233e-08 3.894617e-08
[201,] 1.0000000 5.236695e-08 2.618348e-08
[202,] 1.0000000 9.706518e-08 4.853259e-08
[203,] 0.9999999 1.757977e-07 8.789883e-08
[204,] 0.9999999 1.660284e-07 8.301421e-08
[205,] 0.9999999 2.072987e-07 1.036494e-07
[206,] 0.9999999 1.613776e-07 8.068879e-08
[207,] 0.9999999 2.724900e-07 1.362450e-07
[208,] 0.9999998 4.714292e-07 2.357146e-07
[209,] 0.9999998 4.538369e-07 2.269184e-07
[210,] 0.9999996 7.725898e-07 3.862949e-07
[211,] 0.9999997 6.709257e-07 3.354628e-07
[212,] 0.9999999 2.242569e-07 1.121285e-07
[213,] 0.9999998 4.233931e-07 2.116965e-07
[214,] 0.9999996 7.919064e-07 3.959532e-07
[215,] 0.9999994 1.141773e-06 5.708863e-07
[216,] 0.9999993 1.377736e-06 6.888681e-07
[217,] 0.9999991 1.736870e-06 8.684352e-07
[218,] 0.9999989 2.192328e-06 1.096164e-06
[219,] 1.0000000 8.441012e-08 4.220506e-08
[220,] 1.0000000 6.442241e-08 3.221120e-08
[221,] 0.9999999 1.173671e-07 5.868356e-08
[222,] 1.0000000 4.435235e-08 2.217617e-08
[223,] 1.0000000 8.690335e-08 4.345168e-08
[224,] 0.9999999 1.542479e-07 7.712396e-08
[225,] 0.9999999 2.649886e-07 1.324943e-07
[226,] 1.0000000 1.399788e-09 6.998939e-10
[227,] 1.0000000 2.080798e-09 1.040399e-09
[228,] 1.0000000 5.023717e-09 2.511858e-09
[229,] 1.0000000 6.833664e-09 3.416832e-09
[230,] 1.0000000 9.900261e-09 4.950130e-09
[231,] 1.0000000 1.794013e-08 8.970063e-09
[232,] 1.0000000 1.701217e-08 8.506085e-09
[233,] 1.0000000 2.682678e-08 1.341339e-08
[234,] 1.0000000 6.553447e-08 3.276724e-08
[235,] 0.9999999 1.475750e-07 7.378752e-08
[236,] 1.0000000 7.184816e-08 3.592408e-08
[237,] 0.9999999 1.074942e-07 5.374709e-08
[238,] 0.9999999 2.616255e-07 1.308128e-07
[239,] 0.9999997 5.161631e-07 2.580815e-07
[240,] 0.9999996 7.229068e-07 3.614534e-07
[241,] 0.9999992 1.659967e-06 8.299837e-07
[242,] 0.9999980 3.919175e-06 1.959588e-06
[243,] 0.9999957 8.676778e-06 4.338389e-06
[244,] 0.9999906 1.881611e-05 9.408053e-06
[245,] 0.9999789 4.219272e-05 2.109636e-05
[246,] 0.9999717 5.654660e-05 2.827330e-05
[247,] 0.9999555 8.900807e-05 4.450403e-05
[248,] 0.9999203 1.594647e-04 7.973236e-05
[249,] 0.9998253 3.494161e-04 1.747080e-04
[250,] 0.9996305 7.390741e-04 3.695370e-04
[251,] 0.9994412 1.117673e-03 5.588367e-04
[252,] 0.9988740 2.251947e-03 1.125973e-03
[253,] 0.9977592 4.481690e-03 2.240845e-03
[254,] 0.9984317 3.136616e-03 1.568308e-03
[255,] 0.9977327 4.534551e-03 2.267275e-03
[256,] 0.9978897 4.220588e-03 2.110294e-03
[257,] 0.9954180 9.163902e-03 4.581951e-03
[258,] 0.9999436 1.128927e-04 5.644634e-05
[259,] 0.9998511 2.978326e-04 1.489163e-04
[260,] 0.9995096 9.807223e-04 4.903611e-04
[261,] 0.9987899 2.420108e-03 1.210054e-03
[262,] 0.9982023 3.595425e-03 1.797712e-03
[263,] 0.9945280 1.094403e-02 5.472016e-03
[264,] 0.9894030 2.119396e-02 1.059698e-02
[265,] 0.9841456 3.170880e-02 1.585440e-02
[266,] 0.9944901 1.101977e-02 5.509886e-03
> postscript(file="/var/www/rcomp/tmp/1e3f11324656395.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2pusl1324656395.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3bddc1324656395.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4tlwz1324656395.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/51zkz1324656395.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 289
Frequency = 1
1 2 3 4 5
2.719363e+04 -9.144896e+03 3.135678e+03 -5.179479e+04 3.082177e+04
6 7 8 9 10
-1.276638e+04 9.047997e+04 4.106475e+03 1.068499e+04 -1.488509e+04
11 12 13 14 15
2.311572e+04 3.392638e+04 -7.130662e+03 -1.699970e+03 2.808086e+04
16 17 18 19 20
2.194676e+04 -5.104323e+04 2.030347e+04 2.654898e+04 -9.327815e+03
21 22 23 24 25
-2.017975e+04 8.739577e+02 1.244801e+05 2.700079e+04 -4.336120e+04
26 27 28 29 30
-7.487148e+04 -3.656673e+04 -5.592517e+03 3.455878e+04 6.430534e+03
31 32 33 34 35
2.440965e+04 1.006865e+04 -1.742217e+04 4.385257e+04 -8.584794e+03
36 37 38 39 40
3.257589e+04 2.935938e+04 3.777369e+04 7.691731e+04 8.659131e+03
41 42 43 44 45
1.346423e+04 3.165593e+04 -4.179032e+04 1.122886e+04 2.197274e+04
46 47 48 49 50
1.429680e+03 -4.194228e+04 8.901368e+03 -7.097935e+03 -3.079676e+04
51 52 53 54 55
2.603187e+04 -1.398167e+03 -2.991705e+04 -4.685068e+04 -3.716339e+04
56 57 58 59 60
1.559192e+03 -2.190400e+02 6.362888e+04 -5.958272e+02 5.052181e+03
61 62 63 64 65
-3.389223e+02 -4.702215e+03 -3.473253e+04 1.465369e+04 -6.687570e+04
66 67 68 69 70
1.719152e+04 3.321173e+04 -4.199936e+02 -2.370718e+04 -1.007871e+04
71 72 73 74 75
7.114588e+03 4.376515e+04 2.575745e+04 -3.693329e+04 -4.022864e+04
76 77 78 79 80
-2.014618e+04 -2.383070e+04 -2.036200e+04 -7.818339e+03 2.875552e+03
81 82 83 84 85
7.212483e+03 -3.448717e+04 7.024380e+04 3.862833e+04 7.733970e+03
86 87 88 89 90
-2.848521e+04 6.358593e+00 -7.233765e+03 6.428532e+04 2.201161e+04
91 92 93 94 95
9.985008e+03 -3.876767e+02 -5.829269e+03 -8.250148e+03 1.700241e+04
96 97 98 99 100
3.217470e+04 5.086621e+04 -1.235079e+05 2.955224e+04 -3.169169e+04
101 102 103 104 105
2.505618e+03 -8.596134e+03 3.766224e+04 -3.599732e+02 2.176744e+03
106 107 108 109 110
7.078523e+03 -3.954226e+04 -1.944246e+04 -3.286510e+03 8.902753e+03
111 112 113 114 115
-1.612258e+03 5.575634e+03 -2.508113e+04 2.968794e+03 -3.722234e+04
116 117 118 119 120
2.091738e+03 7.656584e+03 4.496875e+04 -1.532511e+04 -2.802259e+04
121 122 123 124 125
-8.796345e+03 -2.809327e+04 -4.341172e+04 -5.056338e+04 5.930350e+04
126 127 128 129 130
1.686641e+04 1.218142e+04 -3.363541e+04 1.882124e+04 8.205080e+03
131 132 133 134 135
-5.698528e+03 -2.532074e+04 1.785790e+04 -6.205966e+04 -2.256225e+04
136 137 138 139 140
5.494358e+04 8.888559e+03 4.376816e+04 -2.616462e+04 -5.519188e+03
141 142 143 144 145
-1.332926e+04 -2.542660e+04 1.237923e+04 -5.951724e+03 2.102778e+03
146 147 148 149 150
-3.228575e+04 -5.930457e+03 -2.447560e+04 -6.594166e+02 -5.436280e+01
151 152 153 154 155
3.228596e+04 3.926511e+03 -6.918039e+03 3.955808e+04 1.965754e+04
156 157 158 159 160
1.287525e+04 2.946185e+04 1.082445e+04 -1.402973e+04 -1.804426e+03
161 162 163 164 165
6.786830e+03 -1.887858e+04 -1.081005e+04 1.451676e+04 -2.207083e+04
166 167 168 169 170
2.870284e+04 -1.707169e+04 1.262076e+04 1.556541e+04 8.769331e+04
171 172 173 174 175
1.123466e+04 -2.340187e+04 2.054851e+04 4.517487e+03 -7.794247e+04
176 177 178 179 180
1.802423e+04 -2.961635e+04 1.279016e+04 -1.538375e+04 4.015122e+04
181 182 183 184 185
-2.577764e+04 -4.268639e+04 1.291221e+04 1.405725e+04 1.866259e+04
186 187 188 189 190
9.112709e+03 2.010381e+04 2.036323e+04 -1.302452e+03 1.220075e+04
191 192 193 194 195
2.834901e+04 1.855566e+04 -2.675446e+04 -4.258533e+04 2.524896e+03
196 197 198 199 200
-1.088956e+04 -5.655221e+03 -4.205438e+03 -2.549443e+04 -2.007593e+04
201 202 203 204 205
1.166204e+03 3.769078e+03 1.924916e+04 4.622015e+03 -3.045572e+04
206 207 208 209 210
-4.542911e+03 -1.084245e+04 5.386377e+04 2.713033e+04 1.233861e+04
211 212 213 214 215
6.534354e+03 1.639344e+04 -3.552253e+03 1.307203e+04 -3.166706e+04
216 217 218 219 220
-1.441484e+04 -2.694842e+04 -3.458673e+03 4.866854e+03 3.302014e+04
221 222 223 224 225
-1.355332e+04 -3.597364e+04 -6.712408e+04 -7.078585e+02 4.523645e+03
226 227 228 229 230
-1.010285e+04 1.345886e+04 -3.513010e+04 -3.188365e+04 -5.003104e+04
231 232 233 234 235
-1.261063e+04 -1.301158e+04 -3.436161e+04 -7.660473e+03 -2.767441e+04
236 237 238 239 240
-1.086086e+04 5.709427e+04 -1.143077e+04 -1.132934e+04 -2.078242e+04
241 242 243 244 245
4.734068e+03 -2.655136e+04 -1.770865e+04 -6.946984e+03 -3.232626e+03
246 247 248 249 250
-7.392506e+03 -3.371886e+04 2.589770e+04 8.216682e+03 -8.673306e+03
251 252 253 254 255
1.466179e+04 -1.350875e+03 1.243406e+04 -3.098547e+02 -3.179282e+03
256 257 258 259 260
1.017752e+04 -1.049858e+04 1.726093e+04 1.380475e+04 6.507640e+03
261 262 263 264 265
-8.452019e+03 -4.035186e+03 1.173442e+04 -9.474140e+03 -1.244595e+04
266 267 268 269 270
9.300055e+03 -2.038958e+04 -3.534444e+03 4.983597e+04 -1.518771e+04
271 272 273 274 275
-1.776643e+04 8.314812e+03 7.319525e+03 3.654503e+03 8.138392e+03
276 277 278 279 280
-1.662339e+04 9.638140e+03 8.639686e+03 -8.413934e+03 1.568236e+04
281 282 283 284 285
-3.168347e+03 1.934452e+04 3.030605e+03 1.463002e+04 1.166769e+04
286 287 288 289
-2.514592e+04 -5.462372e+02 -2.222455e+04 3.335599e+03
> postscript(file="/var/www/rcomp/tmp/6hzy71324656395.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 289
Frequency = 1
lag(myerror, k = 1) myerror
0 2.719363e+04 NA
1 -9.144896e+03 2.719363e+04
2 3.135678e+03 -9.144896e+03
3 -5.179479e+04 3.135678e+03
4 3.082177e+04 -5.179479e+04
5 -1.276638e+04 3.082177e+04
6 9.047997e+04 -1.276638e+04
7 4.106475e+03 9.047997e+04
8 1.068499e+04 4.106475e+03
9 -1.488509e+04 1.068499e+04
10 2.311572e+04 -1.488509e+04
11 3.392638e+04 2.311572e+04
12 -7.130662e+03 3.392638e+04
13 -1.699970e+03 -7.130662e+03
14 2.808086e+04 -1.699970e+03
15 2.194676e+04 2.808086e+04
16 -5.104323e+04 2.194676e+04
17 2.030347e+04 -5.104323e+04
18 2.654898e+04 2.030347e+04
19 -9.327815e+03 2.654898e+04
20 -2.017975e+04 -9.327815e+03
21 8.739577e+02 -2.017975e+04
22 1.244801e+05 8.739577e+02
23 2.700079e+04 1.244801e+05
24 -4.336120e+04 2.700079e+04
25 -7.487148e+04 -4.336120e+04
26 -3.656673e+04 -7.487148e+04
27 -5.592517e+03 -3.656673e+04
28 3.455878e+04 -5.592517e+03
29 6.430534e+03 3.455878e+04
30 2.440965e+04 6.430534e+03
31 1.006865e+04 2.440965e+04
32 -1.742217e+04 1.006865e+04
33 4.385257e+04 -1.742217e+04
34 -8.584794e+03 4.385257e+04
35 3.257589e+04 -8.584794e+03
36 2.935938e+04 3.257589e+04
37 3.777369e+04 2.935938e+04
38 7.691731e+04 3.777369e+04
39 8.659131e+03 7.691731e+04
40 1.346423e+04 8.659131e+03
41 3.165593e+04 1.346423e+04
42 -4.179032e+04 3.165593e+04
43 1.122886e+04 -4.179032e+04
44 2.197274e+04 1.122886e+04
45 1.429680e+03 2.197274e+04
46 -4.194228e+04 1.429680e+03
47 8.901368e+03 -4.194228e+04
48 -7.097935e+03 8.901368e+03
49 -3.079676e+04 -7.097935e+03
50 2.603187e+04 -3.079676e+04
51 -1.398167e+03 2.603187e+04
52 -2.991705e+04 -1.398167e+03
53 -4.685068e+04 -2.991705e+04
54 -3.716339e+04 -4.685068e+04
55 1.559192e+03 -3.716339e+04
56 -2.190400e+02 1.559192e+03
57 6.362888e+04 -2.190400e+02
58 -5.958272e+02 6.362888e+04
59 5.052181e+03 -5.958272e+02
60 -3.389223e+02 5.052181e+03
61 -4.702215e+03 -3.389223e+02
62 -3.473253e+04 -4.702215e+03
63 1.465369e+04 -3.473253e+04
64 -6.687570e+04 1.465369e+04
65 1.719152e+04 -6.687570e+04
66 3.321173e+04 1.719152e+04
67 -4.199936e+02 3.321173e+04
68 -2.370718e+04 -4.199936e+02
69 -1.007871e+04 -2.370718e+04
70 7.114588e+03 -1.007871e+04
71 4.376515e+04 7.114588e+03
72 2.575745e+04 4.376515e+04
73 -3.693329e+04 2.575745e+04
74 -4.022864e+04 -3.693329e+04
75 -2.014618e+04 -4.022864e+04
76 -2.383070e+04 -2.014618e+04
77 -2.036200e+04 -2.383070e+04
78 -7.818339e+03 -2.036200e+04
79 2.875552e+03 -7.818339e+03
80 7.212483e+03 2.875552e+03
81 -3.448717e+04 7.212483e+03
82 7.024380e+04 -3.448717e+04
83 3.862833e+04 7.024380e+04
84 7.733970e+03 3.862833e+04
85 -2.848521e+04 7.733970e+03
86 6.358593e+00 -2.848521e+04
87 -7.233765e+03 6.358593e+00
88 6.428532e+04 -7.233765e+03
89 2.201161e+04 6.428532e+04
90 9.985008e+03 2.201161e+04
91 -3.876767e+02 9.985008e+03
92 -5.829269e+03 -3.876767e+02
93 -8.250148e+03 -5.829269e+03
94 1.700241e+04 -8.250148e+03
95 3.217470e+04 1.700241e+04
96 5.086621e+04 3.217470e+04
97 -1.235079e+05 5.086621e+04
98 2.955224e+04 -1.235079e+05
99 -3.169169e+04 2.955224e+04
100 2.505618e+03 -3.169169e+04
101 -8.596134e+03 2.505618e+03
102 3.766224e+04 -8.596134e+03
103 -3.599732e+02 3.766224e+04
104 2.176744e+03 -3.599732e+02
105 7.078523e+03 2.176744e+03
106 -3.954226e+04 7.078523e+03
107 -1.944246e+04 -3.954226e+04
108 -3.286510e+03 -1.944246e+04
109 8.902753e+03 -3.286510e+03
110 -1.612258e+03 8.902753e+03
111 5.575634e+03 -1.612258e+03
112 -2.508113e+04 5.575634e+03
113 2.968794e+03 -2.508113e+04
114 -3.722234e+04 2.968794e+03
115 2.091738e+03 -3.722234e+04
116 7.656584e+03 2.091738e+03
117 4.496875e+04 7.656584e+03
118 -1.532511e+04 4.496875e+04
119 -2.802259e+04 -1.532511e+04
120 -8.796345e+03 -2.802259e+04
121 -2.809327e+04 -8.796345e+03
122 -4.341172e+04 -2.809327e+04
123 -5.056338e+04 -4.341172e+04
124 5.930350e+04 -5.056338e+04
125 1.686641e+04 5.930350e+04
126 1.218142e+04 1.686641e+04
127 -3.363541e+04 1.218142e+04
128 1.882124e+04 -3.363541e+04
129 8.205080e+03 1.882124e+04
130 -5.698528e+03 8.205080e+03
131 -2.532074e+04 -5.698528e+03
132 1.785790e+04 -2.532074e+04
133 -6.205966e+04 1.785790e+04
134 -2.256225e+04 -6.205966e+04
135 5.494358e+04 -2.256225e+04
136 8.888559e+03 5.494358e+04
137 4.376816e+04 8.888559e+03
138 -2.616462e+04 4.376816e+04
139 -5.519188e+03 -2.616462e+04
140 -1.332926e+04 -5.519188e+03
141 -2.542660e+04 -1.332926e+04
142 1.237923e+04 -2.542660e+04
143 -5.951724e+03 1.237923e+04
144 2.102778e+03 -5.951724e+03
145 -3.228575e+04 2.102778e+03
146 -5.930457e+03 -3.228575e+04
147 -2.447560e+04 -5.930457e+03
148 -6.594166e+02 -2.447560e+04
149 -5.436280e+01 -6.594166e+02
150 3.228596e+04 -5.436280e+01
151 3.926511e+03 3.228596e+04
152 -6.918039e+03 3.926511e+03
153 3.955808e+04 -6.918039e+03
154 1.965754e+04 3.955808e+04
155 1.287525e+04 1.965754e+04
156 2.946185e+04 1.287525e+04
157 1.082445e+04 2.946185e+04
158 -1.402973e+04 1.082445e+04
159 -1.804426e+03 -1.402973e+04
160 6.786830e+03 -1.804426e+03
161 -1.887858e+04 6.786830e+03
162 -1.081005e+04 -1.887858e+04
163 1.451676e+04 -1.081005e+04
164 -2.207083e+04 1.451676e+04
165 2.870284e+04 -2.207083e+04
166 -1.707169e+04 2.870284e+04
167 1.262076e+04 -1.707169e+04
168 1.556541e+04 1.262076e+04
169 8.769331e+04 1.556541e+04
170 1.123466e+04 8.769331e+04
171 -2.340187e+04 1.123466e+04
172 2.054851e+04 -2.340187e+04
173 4.517487e+03 2.054851e+04
174 -7.794247e+04 4.517487e+03
175 1.802423e+04 -7.794247e+04
176 -2.961635e+04 1.802423e+04
177 1.279016e+04 -2.961635e+04
178 -1.538375e+04 1.279016e+04
179 4.015122e+04 -1.538375e+04
180 -2.577764e+04 4.015122e+04
181 -4.268639e+04 -2.577764e+04
182 1.291221e+04 -4.268639e+04
183 1.405725e+04 1.291221e+04
184 1.866259e+04 1.405725e+04
185 9.112709e+03 1.866259e+04
186 2.010381e+04 9.112709e+03
187 2.036323e+04 2.010381e+04
188 -1.302452e+03 2.036323e+04
189 1.220075e+04 -1.302452e+03
190 2.834901e+04 1.220075e+04
191 1.855566e+04 2.834901e+04
192 -2.675446e+04 1.855566e+04
193 -4.258533e+04 -2.675446e+04
194 2.524896e+03 -4.258533e+04
195 -1.088956e+04 2.524896e+03
196 -5.655221e+03 -1.088956e+04
197 -4.205438e+03 -5.655221e+03
198 -2.549443e+04 -4.205438e+03
199 -2.007593e+04 -2.549443e+04
200 1.166204e+03 -2.007593e+04
201 3.769078e+03 1.166204e+03
202 1.924916e+04 3.769078e+03
203 4.622015e+03 1.924916e+04
204 -3.045572e+04 4.622015e+03
205 -4.542911e+03 -3.045572e+04
206 -1.084245e+04 -4.542911e+03
207 5.386377e+04 -1.084245e+04
208 2.713033e+04 5.386377e+04
209 1.233861e+04 2.713033e+04
210 6.534354e+03 1.233861e+04
211 1.639344e+04 6.534354e+03
212 -3.552253e+03 1.639344e+04
213 1.307203e+04 -3.552253e+03
214 -3.166706e+04 1.307203e+04
215 -1.441484e+04 -3.166706e+04
216 -2.694842e+04 -1.441484e+04
217 -3.458673e+03 -2.694842e+04
218 4.866854e+03 -3.458673e+03
219 3.302014e+04 4.866854e+03
220 -1.355332e+04 3.302014e+04
221 -3.597364e+04 -1.355332e+04
222 -6.712408e+04 -3.597364e+04
223 -7.078585e+02 -6.712408e+04
224 4.523645e+03 -7.078585e+02
225 -1.010285e+04 4.523645e+03
226 1.345886e+04 -1.010285e+04
227 -3.513010e+04 1.345886e+04
228 -3.188365e+04 -3.513010e+04
229 -5.003104e+04 -3.188365e+04
230 -1.261063e+04 -5.003104e+04
231 -1.301158e+04 -1.261063e+04
232 -3.436161e+04 -1.301158e+04
233 -7.660473e+03 -3.436161e+04
234 -2.767441e+04 -7.660473e+03
235 -1.086086e+04 -2.767441e+04
236 5.709427e+04 -1.086086e+04
237 -1.143077e+04 5.709427e+04
238 -1.132934e+04 -1.143077e+04
239 -2.078242e+04 -1.132934e+04
240 4.734068e+03 -2.078242e+04
241 -2.655136e+04 4.734068e+03
242 -1.770865e+04 -2.655136e+04
243 -6.946984e+03 -1.770865e+04
244 -3.232626e+03 -6.946984e+03
245 -7.392506e+03 -3.232626e+03
246 -3.371886e+04 -7.392506e+03
247 2.589770e+04 -3.371886e+04
248 8.216682e+03 2.589770e+04
249 -8.673306e+03 8.216682e+03
250 1.466179e+04 -8.673306e+03
251 -1.350875e+03 1.466179e+04
252 1.243406e+04 -1.350875e+03
253 -3.098547e+02 1.243406e+04
254 -3.179282e+03 -3.098547e+02
255 1.017752e+04 -3.179282e+03
256 -1.049858e+04 1.017752e+04
257 1.726093e+04 -1.049858e+04
258 1.380475e+04 1.726093e+04
259 6.507640e+03 1.380475e+04
260 -8.452019e+03 6.507640e+03
261 -4.035186e+03 -8.452019e+03
262 1.173442e+04 -4.035186e+03
263 -9.474140e+03 1.173442e+04
264 -1.244595e+04 -9.474140e+03
265 9.300055e+03 -1.244595e+04
266 -2.038958e+04 9.300055e+03
267 -3.534444e+03 -2.038958e+04
268 4.983597e+04 -3.534444e+03
269 -1.518771e+04 4.983597e+04
270 -1.776643e+04 -1.518771e+04
271 8.314812e+03 -1.776643e+04
272 7.319525e+03 8.314812e+03
273 3.654503e+03 7.319525e+03
274 8.138392e+03 3.654503e+03
275 -1.662339e+04 8.138392e+03
276 9.638140e+03 -1.662339e+04
277 8.639686e+03 9.638140e+03
278 -8.413934e+03 8.639686e+03
279 1.568236e+04 -8.413934e+03
280 -3.168347e+03 1.568236e+04
281 1.934452e+04 -3.168347e+03
282 3.030605e+03 1.934452e+04
283 1.463002e+04 3.030605e+03
284 1.166769e+04 1.463002e+04
285 -2.514592e+04 1.166769e+04
286 -5.462372e+02 -2.514592e+04
287 -2.222455e+04 -5.462372e+02
288 3.335599e+03 -2.222455e+04
289 NA 3.335599e+03
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -9.144896e+03 2.719363e+04
[2,] 3.135678e+03 -9.144896e+03
[3,] -5.179479e+04 3.135678e+03
[4,] 3.082177e+04 -5.179479e+04
[5,] -1.276638e+04 3.082177e+04
[6,] 9.047997e+04 -1.276638e+04
[7,] 4.106475e+03 9.047997e+04
[8,] 1.068499e+04 4.106475e+03
[9,] -1.488509e+04 1.068499e+04
[10,] 2.311572e+04 -1.488509e+04
[11,] 3.392638e+04 2.311572e+04
[12,] -7.130662e+03 3.392638e+04
[13,] -1.699970e+03 -7.130662e+03
[14,] 2.808086e+04 -1.699970e+03
[15,] 2.194676e+04 2.808086e+04
[16,] -5.104323e+04 2.194676e+04
[17,] 2.030347e+04 -5.104323e+04
[18,] 2.654898e+04 2.030347e+04
[19,] -9.327815e+03 2.654898e+04
[20,] -2.017975e+04 -9.327815e+03
[21,] 8.739577e+02 -2.017975e+04
[22,] 1.244801e+05 8.739577e+02
[23,] 2.700079e+04 1.244801e+05
[24,] -4.336120e+04 2.700079e+04
[25,] -7.487148e+04 -4.336120e+04
[26,] -3.656673e+04 -7.487148e+04
[27,] -5.592517e+03 -3.656673e+04
[28,] 3.455878e+04 -5.592517e+03
[29,] 6.430534e+03 3.455878e+04
[30,] 2.440965e+04 6.430534e+03
[31,] 1.006865e+04 2.440965e+04
[32,] -1.742217e+04 1.006865e+04
[33,] 4.385257e+04 -1.742217e+04
[34,] -8.584794e+03 4.385257e+04
[35,] 3.257589e+04 -8.584794e+03
[36,] 2.935938e+04 3.257589e+04
[37,] 3.777369e+04 2.935938e+04
[38,] 7.691731e+04 3.777369e+04
[39,] 8.659131e+03 7.691731e+04
[40,] 1.346423e+04 8.659131e+03
[41,] 3.165593e+04 1.346423e+04
[42,] -4.179032e+04 3.165593e+04
[43,] 1.122886e+04 -4.179032e+04
[44,] 2.197274e+04 1.122886e+04
[45,] 1.429680e+03 2.197274e+04
[46,] -4.194228e+04 1.429680e+03
[47,] 8.901368e+03 -4.194228e+04
[48,] -7.097935e+03 8.901368e+03
[49,] -3.079676e+04 -7.097935e+03
[50,] 2.603187e+04 -3.079676e+04
[51,] -1.398167e+03 2.603187e+04
[52,] -2.991705e+04 -1.398167e+03
[53,] -4.685068e+04 -2.991705e+04
[54,] -3.716339e+04 -4.685068e+04
[55,] 1.559192e+03 -3.716339e+04
[56,] -2.190400e+02 1.559192e+03
[57,] 6.362888e+04 -2.190400e+02
[58,] -5.958272e+02 6.362888e+04
[59,] 5.052181e+03 -5.958272e+02
[60,] -3.389223e+02 5.052181e+03
[61,] -4.702215e+03 -3.389223e+02
[62,] -3.473253e+04 -4.702215e+03
[63,] 1.465369e+04 -3.473253e+04
[64,] -6.687570e+04 1.465369e+04
[65,] 1.719152e+04 -6.687570e+04
[66,] 3.321173e+04 1.719152e+04
[67,] -4.199936e+02 3.321173e+04
[68,] -2.370718e+04 -4.199936e+02
[69,] -1.007871e+04 -2.370718e+04
[70,] 7.114588e+03 -1.007871e+04
[71,] 4.376515e+04 7.114588e+03
[72,] 2.575745e+04 4.376515e+04
[73,] -3.693329e+04 2.575745e+04
[74,] -4.022864e+04 -3.693329e+04
[75,] -2.014618e+04 -4.022864e+04
[76,] -2.383070e+04 -2.014618e+04
[77,] -2.036200e+04 -2.383070e+04
[78,] -7.818339e+03 -2.036200e+04
[79,] 2.875552e+03 -7.818339e+03
[80,] 7.212483e+03 2.875552e+03
[81,] -3.448717e+04 7.212483e+03
[82,] 7.024380e+04 -3.448717e+04
[83,] 3.862833e+04 7.024380e+04
[84,] 7.733970e+03 3.862833e+04
[85,] -2.848521e+04 7.733970e+03
[86,] 6.358593e+00 -2.848521e+04
[87,] -7.233765e+03 6.358593e+00
[88,] 6.428532e+04 -7.233765e+03
[89,] 2.201161e+04 6.428532e+04
[90,] 9.985008e+03 2.201161e+04
[91,] -3.876767e+02 9.985008e+03
[92,] -5.829269e+03 -3.876767e+02
[93,] -8.250148e+03 -5.829269e+03
[94,] 1.700241e+04 -8.250148e+03
[95,] 3.217470e+04 1.700241e+04
[96,] 5.086621e+04 3.217470e+04
[97,] -1.235079e+05 5.086621e+04
[98,] 2.955224e+04 -1.235079e+05
[99,] -3.169169e+04 2.955224e+04
[100,] 2.505618e+03 -3.169169e+04
[101,] -8.596134e+03 2.505618e+03
[102,] 3.766224e+04 -8.596134e+03
[103,] -3.599732e+02 3.766224e+04
[104,] 2.176744e+03 -3.599732e+02
[105,] 7.078523e+03 2.176744e+03
[106,] -3.954226e+04 7.078523e+03
[107,] -1.944246e+04 -3.954226e+04
[108,] -3.286510e+03 -1.944246e+04
[109,] 8.902753e+03 -3.286510e+03
[110,] -1.612258e+03 8.902753e+03
[111,] 5.575634e+03 -1.612258e+03
[112,] -2.508113e+04 5.575634e+03
[113,] 2.968794e+03 -2.508113e+04
[114,] -3.722234e+04 2.968794e+03
[115,] 2.091738e+03 -3.722234e+04
[116,] 7.656584e+03 2.091738e+03
[117,] 4.496875e+04 7.656584e+03
[118,] -1.532511e+04 4.496875e+04
[119,] -2.802259e+04 -1.532511e+04
[120,] -8.796345e+03 -2.802259e+04
[121,] -2.809327e+04 -8.796345e+03
[122,] -4.341172e+04 -2.809327e+04
[123,] -5.056338e+04 -4.341172e+04
[124,] 5.930350e+04 -5.056338e+04
[125,] 1.686641e+04 5.930350e+04
[126,] 1.218142e+04 1.686641e+04
[127,] -3.363541e+04 1.218142e+04
[128,] 1.882124e+04 -3.363541e+04
[129,] 8.205080e+03 1.882124e+04
[130,] -5.698528e+03 8.205080e+03
[131,] -2.532074e+04 -5.698528e+03
[132,] 1.785790e+04 -2.532074e+04
[133,] -6.205966e+04 1.785790e+04
[134,] -2.256225e+04 -6.205966e+04
[135,] 5.494358e+04 -2.256225e+04
[136,] 8.888559e+03 5.494358e+04
[137,] 4.376816e+04 8.888559e+03
[138,] -2.616462e+04 4.376816e+04
[139,] -5.519188e+03 -2.616462e+04
[140,] -1.332926e+04 -5.519188e+03
[141,] -2.542660e+04 -1.332926e+04
[142,] 1.237923e+04 -2.542660e+04
[143,] -5.951724e+03 1.237923e+04
[144,] 2.102778e+03 -5.951724e+03
[145,] -3.228575e+04 2.102778e+03
[146,] -5.930457e+03 -3.228575e+04
[147,] -2.447560e+04 -5.930457e+03
[148,] -6.594166e+02 -2.447560e+04
[149,] -5.436280e+01 -6.594166e+02
[150,] 3.228596e+04 -5.436280e+01
[151,] 3.926511e+03 3.228596e+04
[152,] -6.918039e+03 3.926511e+03
[153,] 3.955808e+04 -6.918039e+03
[154,] 1.965754e+04 3.955808e+04
[155,] 1.287525e+04 1.965754e+04
[156,] 2.946185e+04 1.287525e+04
[157,] 1.082445e+04 2.946185e+04
[158,] -1.402973e+04 1.082445e+04
[159,] -1.804426e+03 -1.402973e+04
[160,] 6.786830e+03 -1.804426e+03
[161,] -1.887858e+04 6.786830e+03
[162,] -1.081005e+04 -1.887858e+04
[163,] 1.451676e+04 -1.081005e+04
[164,] -2.207083e+04 1.451676e+04
[165,] 2.870284e+04 -2.207083e+04
[166,] -1.707169e+04 2.870284e+04
[167,] 1.262076e+04 -1.707169e+04
[168,] 1.556541e+04 1.262076e+04
[169,] 8.769331e+04 1.556541e+04
[170,] 1.123466e+04 8.769331e+04
[171,] -2.340187e+04 1.123466e+04
[172,] 2.054851e+04 -2.340187e+04
[173,] 4.517487e+03 2.054851e+04
[174,] -7.794247e+04 4.517487e+03
[175,] 1.802423e+04 -7.794247e+04
[176,] -2.961635e+04 1.802423e+04
[177,] 1.279016e+04 -2.961635e+04
[178,] -1.538375e+04 1.279016e+04
[179,] 4.015122e+04 -1.538375e+04
[180,] -2.577764e+04 4.015122e+04
[181,] -4.268639e+04 -2.577764e+04
[182,] 1.291221e+04 -4.268639e+04
[183,] 1.405725e+04 1.291221e+04
[184,] 1.866259e+04 1.405725e+04
[185,] 9.112709e+03 1.866259e+04
[186,] 2.010381e+04 9.112709e+03
[187,] 2.036323e+04 2.010381e+04
[188,] -1.302452e+03 2.036323e+04
[189,] 1.220075e+04 -1.302452e+03
[190,] 2.834901e+04 1.220075e+04
[191,] 1.855566e+04 2.834901e+04
[192,] -2.675446e+04 1.855566e+04
[193,] -4.258533e+04 -2.675446e+04
[194,] 2.524896e+03 -4.258533e+04
[195,] -1.088956e+04 2.524896e+03
[196,] -5.655221e+03 -1.088956e+04
[197,] -4.205438e+03 -5.655221e+03
[198,] -2.549443e+04 -4.205438e+03
[199,] -2.007593e+04 -2.549443e+04
[200,] 1.166204e+03 -2.007593e+04
[201,] 3.769078e+03 1.166204e+03
[202,] 1.924916e+04 3.769078e+03
[203,] 4.622015e+03 1.924916e+04
[204,] -3.045572e+04 4.622015e+03
[205,] -4.542911e+03 -3.045572e+04
[206,] -1.084245e+04 -4.542911e+03
[207,] 5.386377e+04 -1.084245e+04
[208,] 2.713033e+04 5.386377e+04
[209,] 1.233861e+04 2.713033e+04
[210,] 6.534354e+03 1.233861e+04
[211,] 1.639344e+04 6.534354e+03
[212,] -3.552253e+03 1.639344e+04
[213,] 1.307203e+04 -3.552253e+03
[214,] -3.166706e+04 1.307203e+04
[215,] -1.441484e+04 -3.166706e+04
[216,] -2.694842e+04 -1.441484e+04
[217,] -3.458673e+03 -2.694842e+04
[218,] 4.866854e+03 -3.458673e+03
[219,] 3.302014e+04 4.866854e+03
[220,] -1.355332e+04 3.302014e+04
[221,] -3.597364e+04 -1.355332e+04
[222,] -6.712408e+04 -3.597364e+04
[223,] -7.078585e+02 -6.712408e+04
[224,] 4.523645e+03 -7.078585e+02
[225,] -1.010285e+04 4.523645e+03
[226,] 1.345886e+04 -1.010285e+04
[227,] -3.513010e+04 1.345886e+04
[228,] -3.188365e+04 -3.513010e+04
[229,] -5.003104e+04 -3.188365e+04
[230,] -1.261063e+04 -5.003104e+04
[231,] -1.301158e+04 -1.261063e+04
[232,] -3.436161e+04 -1.301158e+04
[233,] -7.660473e+03 -3.436161e+04
[234,] -2.767441e+04 -7.660473e+03
[235,] -1.086086e+04 -2.767441e+04
[236,] 5.709427e+04 -1.086086e+04
[237,] -1.143077e+04 5.709427e+04
[238,] -1.132934e+04 -1.143077e+04
[239,] -2.078242e+04 -1.132934e+04
[240,] 4.734068e+03 -2.078242e+04
[241,] -2.655136e+04 4.734068e+03
[242,] -1.770865e+04 -2.655136e+04
[243,] -6.946984e+03 -1.770865e+04
[244,] -3.232626e+03 -6.946984e+03
[245,] -7.392506e+03 -3.232626e+03
[246,] -3.371886e+04 -7.392506e+03
[247,] 2.589770e+04 -3.371886e+04
[248,] 8.216682e+03 2.589770e+04
[249,] -8.673306e+03 8.216682e+03
[250,] 1.466179e+04 -8.673306e+03
[251,] -1.350875e+03 1.466179e+04
[252,] 1.243406e+04 -1.350875e+03
[253,] -3.098547e+02 1.243406e+04
[254,] -3.179282e+03 -3.098547e+02
[255,] 1.017752e+04 -3.179282e+03
[256,] -1.049858e+04 1.017752e+04
[257,] 1.726093e+04 -1.049858e+04
[258,] 1.380475e+04 1.726093e+04
[259,] 6.507640e+03 1.380475e+04
[260,] -8.452019e+03 6.507640e+03
[261,] -4.035186e+03 -8.452019e+03
[262,] 1.173442e+04 -4.035186e+03
[263,] -9.474140e+03 1.173442e+04
[264,] -1.244595e+04 -9.474140e+03
[265,] 9.300055e+03 -1.244595e+04
[266,] -2.038958e+04 9.300055e+03
[267,] -3.534444e+03 -2.038958e+04
[268,] 4.983597e+04 -3.534444e+03
[269,] -1.518771e+04 4.983597e+04
[270,] -1.776643e+04 -1.518771e+04
[271,] 8.314812e+03 -1.776643e+04
[272,] 7.319525e+03 8.314812e+03
[273,] 3.654503e+03 7.319525e+03
[274,] 8.138392e+03 3.654503e+03
[275,] -1.662339e+04 8.138392e+03
[276,] 9.638140e+03 -1.662339e+04
[277,] 8.639686e+03 9.638140e+03
[278,] -8.413934e+03 8.639686e+03
[279,] 1.568236e+04 -8.413934e+03
[280,] -3.168347e+03 1.568236e+04
[281,] 1.934452e+04 -3.168347e+03
[282,] 3.030605e+03 1.934452e+04
[283,] 1.463002e+04 3.030605e+03
[284,] 1.166769e+04 1.463002e+04
[285,] -2.514592e+04 1.166769e+04
[286,] -5.462372e+02 -2.514592e+04
[287,] -2.222455e+04 -5.462372e+02
[288,] 3.335599e+03 -2.222455e+04
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -9.144896e+03 2.719363e+04
2 3.135678e+03 -9.144896e+03
3 -5.179479e+04 3.135678e+03
4 3.082177e+04 -5.179479e+04
5 -1.276638e+04 3.082177e+04
6 9.047997e+04 -1.276638e+04
7 4.106475e+03 9.047997e+04
8 1.068499e+04 4.106475e+03
9 -1.488509e+04 1.068499e+04
10 2.311572e+04 -1.488509e+04
11 3.392638e+04 2.311572e+04
12 -7.130662e+03 3.392638e+04
13 -1.699970e+03 -7.130662e+03
14 2.808086e+04 -1.699970e+03
15 2.194676e+04 2.808086e+04
16 -5.104323e+04 2.194676e+04
17 2.030347e+04 -5.104323e+04
18 2.654898e+04 2.030347e+04
19 -9.327815e+03 2.654898e+04
20 -2.017975e+04 -9.327815e+03
21 8.739577e+02 -2.017975e+04
22 1.244801e+05 8.739577e+02
23 2.700079e+04 1.244801e+05
24 -4.336120e+04 2.700079e+04
25 -7.487148e+04 -4.336120e+04
26 -3.656673e+04 -7.487148e+04
27 -5.592517e+03 -3.656673e+04
28 3.455878e+04 -5.592517e+03
29 6.430534e+03 3.455878e+04
30 2.440965e+04 6.430534e+03
31 1.006865e+04 2.440965e+04
32 -1.742217e+04 1.006865e+04
33 4.385257e+04 -1.742217e+04
34 -8.584794e+03 4.385257e+04
35 3.257589e+04 -8.584794e+03
36 2.935938e+04 3.257589e+04
37 3.777369e+04 2.935938e+04
38 7.691731e+04 3.777369e+04
39 8.659131e+03 7.691731e+04
40 1.346423e+04 8.659131e+03
41 3.165593e+04 1.346423e+04
42 -4.179032e+04 3.165593e+04
43 1.122886e+04 -4.179032e+04
44 2.197274e+04 1.122886e+04
45 1.429680e+03 2.197274e+04
46 -4.194228e+04 1.429680e+03
47 8.901368e+03 -4.194228e+04
48 -7.097935e+03 8.901368e+03
49 -3.079676e+04 -7.097935e+03
50 2.603187e+04 -3.079676e+04
51 -1.398167e+03 2.603187e+04
52 -2.991705e+04 -1.398167e+03
53 -4.685068e+04 -2.991705e+04
54 -3.716339e+04 -4.685068e+04
55 1.559192e+03 -3.716339e+04
56 -2.190400e+02 1.559192e+03
57 6.362888e+04 -2.190400e+02
58 -5.958272e+02 6.362888e+04
59 5.052181e+03 -5.958272e+02
60 -3.389223e+02 5.052181e+03
61 -4.702215e+03 -3.389223e+02
62 -3.473253e+04 -4.702215e+03
63 1.465369e+04 -3.473253e+04
64 -6.687570e+04 1.465369e+04
65 1.719152e+04 -6.687570e+04
66 3.321173e+04 1.719152e+04
67 -4.199936e+02 3.321173e+04
68 -2.370718e+04 -4.199936e+02
69 -1.007871e+04 -2.370718e+04
70 7.114588e+03 -1.007871e+04
71 4.376515e+04 7.114588e+03
72 2.575745e+04 4.376515e+04
73 -3.693329e+04 2.575745e+04
74 -4.022864e+04 -3.693329e+04
75 -2.014618e+04 -4.022864e+04
76 -2.383070e+04 -2.014618e+04
77 -2.036200e+04 -2.383070e+04
78 -7.818339e+03 -2.036200e+04
79 2.875552e+03 -7.818339e+03
80 7.212483e+03 2.875552e+03
81 -3.448717e+04 7.212483e+03
82 7.024380e+04 -3.448717e+04
83 3.862833e+04 7.024380e+04
84 7.733970e+03 3.862833e+04
85 -2.848521e+04 7.733970e+03
86 6.358593e+00 -2.848521e+04
87 -7.233765e+03 6.358593e+00
88 6.428532e+04 -7.233765e+03
89 2.201161e+04 6.428532e+04
90 9.985008e+03 2.201161e+04
91 -3.876767e+02 9.985008e+03
92 -5.829269e+03 -3.876767e+02
93 -8.250148e+03 -5.829269e+03
94 1.700241e+04 -8.250148e+03
95 3.217470e+04 1.700241e+04
96 5.086621e+04 3.217470e+04
97 -1.235079e+05 5.086621e+04
98 2.955224e+04 -1.235079e+05
99 -3.169169e+04 2.955224e+04
100 2.505618e+03 -3.169169e+04
101 -8.596134e+03 2.505618e+03
102 3.766224e+04 -8.596134e+03
103 -3.599732e+02 3.766224e+04
104 2.176744e+03 -3.599732e+02
105 7.078523e+03 2.176744e+03
106 -3.954226e+04 7.078523e+03
107 -1.944246e+04 -3.954226e+04
108 -3.286510e+03 -1.944246e+04
109 8.902753e+03 -3.286510e+03
110 -1.612258e+03 8.902753e+03
111 5.575634e+03 -1.612258e+03
112 -2.508113e+04 5.575634e+03
113 2.968794e+03 -2.508113e+04
114 -3.722234e+04 2.968794e+03
115 2.091738e+03 -3.722234e+04
116 7.656584e+03 2.091738e+03
117 4.496875e+04 7.656584e+03
118 -1.532511e+04 4.496875e+04
119 -2.802259e+04 -1.532511e+04
120 -8.796345e+03 -2.802259e+04
121 -2.809327e+04 -8.796345e+03
122 -4.341172e+04 -2.809327e+04
123 -5.056338e+04 -4.341172e+04
124 5.930350e+04 -5.056338e+04
125 1.686641e+04 5.930350e+04
126 1.218142e+04 1.686641e+04
127 -3.363541e+04 1.218142e+04
128 1.882124e+04 -3.363541e+04
129 8.205080e+03 1.882124e+04
130 -5.698528e+03 8.205080e+03
131 -2.532074e+04 -5.698528e+03
132 1.785790e+04 -2.532074e+04
133 -6.205966e+04 1.785790e+04
134 -2.256225e+04 -6.205966e+04
135 5.494358e+04 -2.256225e+04
136 8.888559e+03 5.494358e+04
137 4.376816e+04 8.888559e+03
138 -2.616462e+04 4.376816e+04
139 -5.519188e+03 -2.616462e+04
140 -1.332926e+04 -5.519188e+03
141 -2.542660e+04 -1.332926e+04
142 1.237923e+04 -2.542660e+04
143 -5.951724e+03 1.237923e+04
144 2.102778e+03 -5.951724e+03
145 -3.228575e+04 2.102778e+03
146 -5.930457e+03 -3.228575e+04
147 -2.447560e+04 -5.930457e+03
148 -6.594166e+02 -2.447560e+04
149 -5.436280e+01 -6.594166e+02
150 3.228596e+04 -5.436280e+01
151 3.926511e+03 3.228596e+04
152 -6.918039e+03 3.926511e+03
153 3.955808e+04 -6.918039e+03
154 1.965754e+04 3.955808e+04
155 1.287525e+04 1.965754e+04
156 2.946185e+04 1.287525e+04
157 1.082445e+04 2.946185e+04
158 -1.402973e+04 1.082445e+04
159 -1.804426e+03 -1.402973e+04
160 6.786830e+03 -1.804426e+03
161 -1.887858e+04 6.786830e+03
162 -1.081005e+04 -1.887858e+04
163 1.451676e+04 -1.081005e+04
164 -2.207083e+04 1.451676e+04
165 2.870284e+04 -2.207083e+04
166 -1.707169e+04 2.870284e+04
167 1.262076e+04 -1.707169e+04
168 1.556541e+04 1.262076e+04
169 8.769331e+04 1.556541e+04
170 1.123466e+04 8.769331e+04
171 -2.340187e+04 1.123466e+04
172 2.054851e+04 -2.340187e+04
173 4.517487e+03 2.054851e+04
174 -7.794247e+04 4.517487e+03
175 1.802423e+04 -7.794247e+04
176 -2.961635e+04 1.802423e+04
177 1.279016e+04 -2.961635e+04
178 -1.538375e+04 1.279016e+04
179 4.015122e+04 -1.538375e+04
180 -2.577764e+04 4.015122e+04
181 -4.268639e+04 -2.577764e+04
182 1.291221e+04 -4.268639e+04
183 1.405725e+04 1.291221e+04
184 1.866259e+04 1.405725e+04
185 9.112709e+03 1.866259e+04
186 2.010381e+04 9.112709e+03
187 2.036323e+04 2.010381e+04
188 -1.302452e+03 2.036323e+04
189 1.220075e+04 -1.302452e+03
190 2.834901e+04 1.220075e+04
191 1.855566e+04 2.834901e+04
192 -2.675446e+04 1.855566e+04
193 -4.258533e+04 -2.675446e+04
194 2.524896e+03 -4.258533e+04
195 -1.088956e+04 2.524896e+03
196 -5.655221e+03 -1.088956e+04
197 -4.205438e+03 -5.655221e+03
198 -2.549443e+04 -4.205438e+03
199 -2.007593e+04 -2.549443e+04
200 1.166204e+03 -2.007593e+04
201 3.769078e+03 1.166204e+03
202 1.924916e+04 3.769078e+03
203 4.622015e+03 1.924916e+04
204 -3.045572e+04 4.622015e+03
205 -4.542911e+03 -3.045572e+04
206 -1.084245e+04 -4.542911e+03
207 5.386377e+04 -1.084245e+04
208 2.713033e+04 5.386377e+04
209 1.233861e+04 2.713033e+04
210 6.534354e+03 1.233861e+04
211 1.639344e+04 6.534354e+03
212 -3.552253e+03 1.639344e+04
213 1.307203e+04 -3.552253e+03
214 -3.166706e+04 1.307203e+04
215 -1.441484e+04 -3.166706e+04
216 -2.694842e+04 -1.441484e+04
217 -3.458673e+03 -2.694842e+04
218 4.866854e+03 -3.458673e+03
219 3.302014e+04 4.866854e+03
220 -1.355332e+04 3.302014e+04
221 -3.597364e+04 -1.355332e+04
222 -6.712408e+04 -3.597364e+04
223 -7.078585e+02 -6.712408e+04
224 4.523645e+03 -7.078585e+02
225 -1.010285e+04 4.523645e+03
226 1.345886e+04 -1.010285e+04
227 -3.513010e+04 1.345886e+04
228 -3.188365e+04 -3.513010e+04
229 -5.003104e+04 -3.188365e+04
230 -1.261063e+04 -5.003104e+04
231 -1.301158e+04 -1.261063e+04
232 -3.436161e+04 -1.301158e+04
233 -7.660473e+03 -3.436161e+04
234 -2.767441e+04 -7.660473e+03
235 -1.086086e+04 -2.767441e+04
236 5.709427e+04 -1.086086e+04
237 -1.143077e+04 5.709427e+04
238 -1.132934e+04 -1.143077e+04
239 -2.078242e+04 -1.132934e+04
240 4.734068e+03 -2.078242e+04
241 -2.655136e+04 4.734068e+03
242 -1.770865e+04 -2.655136e+04
243 -6.946984e+03 -1.770865e+04
244 -3.232626e+03 -6.946984e+03
245 -7.392506e+03 -3.232626e+03
246 -3.371886e+04 -7.392506e+03
247 2.589770e+04 -3.371886e+04
248 8.216682e+03 2.589770e+04
249 -8.673306e+03 8.216682e+03
250 1.466179e+04 -8.673306e+03
251 -1.350875e+03 1.466179e+04
252 1.243406e+04 -1.350875e+03
253 -3.098547e+02 1.243406e+04
254 -3.179282e+03 -3.098547e+02
255 1.017752e+04 -3.179282e+03
256 -1.049858e+04 1.017752e+04
257 1.726093e+04 -1.049858e+04
258 1.380475e+04 1.726093e+04
259 6.507640e+03 1.380475e+04
260 -8.452019e+03 6.507640e+03
261 -4.035186e+03 -8.452019e+03
262 1.173442e+04 -4.035186e+03
263 -9.474140e+03 1.173442e+04
264 -1.244595e+04 -9.474140e+03
265 9.300055e+03 -1.244595e+04
266 -2.038958e+04 9.300055e+03
267 -3.534444e+03 -2.038958e+04
268 4.983597e+04 -3.534444e+03
269 -1.518771e+04 4.983597e+04
270 -1.776643e+04 -1.518771e+04
271 8.314812e+03 -1.776643e+04
272 7.319525e+03 8.314812e+03
273 3.654503e+03 7.319525e+03
274 8.138392e+03 3.654503e+03
275 -1.662339e+04 8.138392e+03
276 9.638140e+03 -1.662339e+04
277 8.639686e+03 9.638140e+03
278 -8.413934e+03 8.639686e+03
279 1.568236e+04 -8.413934e+03
280 -3.168347e+03 1.568236e+04
281 1.934452e+04 -3.168347e+03
282 3.030605e+03 1.934452e+04
283 1.463002e+04 3.030605e+03
284 1.166769e+04 1.463002e+04
285 -2.514592e+04 1.166769e+04
286 -5.462372e+02 -2.514592e+04
287 -2.222455e+04 -5.462372e+02
288 3.335599e+03 -2.222455e+04
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/7lbjx1324656395.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8du7s1324656395.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9xmtn1324656395.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10gm9r1324656395.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/www/rcomp/tmp/110m4u1324656395.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/www/rcomp/tmp/1280ta1324656395.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/www/rcomp/tmp/130eai1324656395.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/www/rcomp/tmp/14e8p01324656395.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/www/rcomp/tmp/15k9xx1324656396.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/www/rcomp/tmp/1644q11324656396.tab")
+ }
>
> try(system("convert tmp/1e3f11324656395.ps tmp/1e3f11324656395.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pusl1324656395.ps tmp/2pusl1324656395.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bddc1324656395.ps tmp/3bddc1324656395.png",intern=TRUE))
character(0)
> try(system("convert tmp/4tlwz1324656395.ps tmp/4tlwz1324656395.png",intern=TRUE))
character(0)
> try(system("convert tmp/51zkz1324656395.ps tmp/51zkz1324656395.png",intern=TRUE))
character(0)
> try(system("convert tmp/6hzy71324656395.ps tmp/6hzy71324656395.png",intern=TRUE))
character(0)
> try(system("convert tmp/7lbjx1324656395.ps tmp/7lbjx1324656395.png",intern=TRUE))
character(0)
> try(system("convert tmp/8du7s1324656395.ps tmp/8du7s1324656395.png",intern=TRUE))
character(0)
> try(system("convert tmp/9xmtn1324656395.ps tmp/9xmtn1324656395.png",intern=TRUE))
character(0)
> try(system("convert tmp/10gm9r1324656395.ps tmp/10gm9r1324656395.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
9.290 0.400 9.699