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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| Datum: | 2006 |
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| Format: | Artikel |
| Sprache: | English |
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Інститут математики НАН України
2006
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| Online Zugang: | 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 |
| Zitieren: | 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. |
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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 |
| institution |
Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| collection |
DSpace DC |
| title |
Matrix parameter estimation in an autoregression model |
| spellingShingle |
Matrix parameter estimation in an autoregression model Yurachkivsky, A.P. Ivanenko, D.O. |
| 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 |
| author |
Yurachkivsky, A.P. Ivanenko, D.O. |
| author_facet |
Yurachkivsky, A.P. Ivanenko, D.O. |
| publishDate |
2006 |
| language |
English |
| publisher |
Інститут математики НАН України |
| format |
Article |
| 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.
|
| issn |
0321-3900 |
| url |
https://nasplib.isofts.kiev.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 |
| first_indexed |
2025-12-01T15:40:45Z |
| last_indexed |
2025-12-01T15:40:45Z |
| _version_ |
1850860562439733248 |