Matrix parameter estimation in an autoregression model
The vector difference equation ξk = Af(ξk−1)+εk, where (εk) is a square integrable
 difference martingale, is considered. A family of estimators ˇAn depending, besides
 the sample size n, on a bounded Lipschitz function is constructed. Convergence in
 distribution of √n (ˇAn...
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| Дата: | 2006 |
|---|---|
| Автори: | , |
| Формат: | Стаття |
| Мова: | Англійська |
| Опубліковано: |
Інститут математики НАН України
2006
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| Онлайн доступ: | https://nasplib.isofts.kiev.ua/handle/123456789/4450 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Цитувати: | Matrix parameter estimation in an autoregression model / A.P. Yurachkivsky, D.O. Ivanenko // Theory of Stochastic Processes. — 2006. — Т. 12 (28), № 1-2. — С. 154–161. — Бібліогр.: 4 назв.— англ. |
Репозитарії
Digital Library of Periodicals of National Academy of Sciences of Ukraine| _version_ | 1862649306255720448 |
|---|---|
| author | Yurachkivsky, A.P. Ivanenko, D.O. |
| author_facet | Yurachkivsky, A.P. Ivanenko, D.O. |
| citation_txt | Matrix parameter estimation in an autoregression model / A.P. Yurachkivsky, D.O. Ivanenko // Theory of Stochastic Processes. — 2006. — Т. 12 (28), № 1-2. — С. 154–161. — Бібліогр.: 4 назв.— англ. |
| collection | DSpace DC |
| description | The vector difference equation ξk = Af(ξk−1)+εk, where (εk) is a square integrable
difference martingale, is considered. A family of estimators ˇAn depending, besides
the sample size n, on a bounded Lipschitz function is constructed. Convergence in
distribution of √n (ˇAn − A) as n→∞is proved with the use of stochastic calculus.
Ergodicity and even stationarity of (εk) is not assumed, so the limiting distribution
may be, as the example shows, other than normal.
|
| first_indexed | 2025-12-01T15:40:45Z |
| format | Article |
| fulltext | |
| id | nasplib_isofts_kiev_ua-123456789-4450 |
| institution | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| issn | 0321-3900 |
| language | English |
| last_indexed | 2025-12-01T15:40:45Z |
| publishDate | 2006 |
| publisher | Інститут математики НАН України |
| record_format | dspace |
| spelling | Yurachkivsky, A.P. Ivanenko, D.O. 2009-11-10T14:54:04Z 2009-11-10T14:54:04Z 2006 Matrix parameter estimation in an autoregression model / A.P. Yurachkivsky, D.O. Ivanenko // Theory of Stochastic Processes. — 2006. — Т. 12 (28), № 1-2. — С. 154–161. — Бібліогр.: 4 назв.— англ. 0321-3900 https://nasplib.isofts.kiev.ua/handle/123456789/4450 519.21 The vector difference equation ξk = Af(ξk−1)+εk, where (εk) is a square integrable
 difference martingale, is considered. A family of estimators ˇAn depending, besides
 the sample size n, on a bounded Lipschitz function is constructed. Convergence in
 distribution of √n (ˇAn − A) as n→∞is proved with the use of stochastic calculus.
 Ergodicity and even stationarity of (εk) is not assumed, so the limiting distribution
 may be, as the example shows, other than normal. en Інститут математики НАН України Matrix parameter estimation in an autoregression model Article published earlier |
| spellingShingle | Matrix parameter estimation in an autoregression model Yurachkivsky, A.P. Ivanenko, D.O. |
| title | Matrix parameter estimation in an autoregression model |
| title_full | Matrix parameter estimation in an autoregression model |
| title_fullStr | Matrix parameter estimation in an autoregression model |
| title_full_unstemmed | Matrix parameter estimation in an autoregression model |
| title_short | Matrix parameter estimation in an autoregression model |
| title_sort | matrix parameter estimation in an autoregression model |
| url | https://nasplib.isofts.kiev.ua/handle/123456789/4450 |
| work_keys_str_mv | AT yurachkivskyap matrixparameterestimationinanautoregressionmodel AT ivanenkodo matrixparameterestimationinanautoregressionmodel |