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: Yurachkivsky, A.P., Ivanenko, D.O.
Формат: Стаття
Мова:Англійська
Опубліковано: Інститут математики НАН України 2006
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
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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.
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last_indexed 2025-12-01T15:40:45Z
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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