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 − A) as n→∞is proved wit...
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| Дата: | 2006 |
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| Автори: | , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Інститут математики НАН України
2006
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| Онлайн доступ: | http://dspace.nbuv.gov.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| id |
irk-123456789-4450 |
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| record_format |
dspace |
| spelling |
irk-123456789-44502009-11-11T12:00:27Z Matrix parameter estimation in an autoregression model Yurachkivsky, A.P. Ivanenko, D.O. 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. 2006 Article 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 http://dspace.nbuv.gov.ua/handle/123456789/4450 519.21 en Інститут математики НАН України |
| institution |
Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| collection |
DSpace DC |
| language |
English |
| 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. |
| format |
Article |
| author |
Yurachkivsky, A.P. Ivanenko, D.O. |
| spellingShingle |
Yurachkivsky, A.P. Ivanenko, D.O. Matrix parameter estimation in an autoregression model |
| author_facet |
Yurachkivsky, A.P. Ivanenko, D.O. |
| author_sort |
Yurachkivsky, A.P. |
| title |
Matrix parameter estimation in an autoregression model |
| title_short |
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_sort |
matrix parameter estimation in an autoregression model |
| publisher |
Інститут математики НАН України |
| publishDate |
2006 |
| url |
http://dspace.nbuv.gov.ua/handle/123456789/4450 |
| 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. |
| work_keys_str_mv |
AT yurachkivskyap matrixparameterestimationinanautoregressionmodel AT ivanenkodo matrixparameterestimationinanautoregressionmodel |
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2023-03-24T08:30:13Z |
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2023-03-24T08:30:13Z |
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