KFU. Card publication. Consistency of the Empirical Bayesian Analogue of the Regression Estimation

KAZAN
FEDERAL UNIVERSITY

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CONSISTENCY OF THE EMPIRICAL BAYESIAN ANALOGUE OF THE REGRESSION ESTIMATION

Form of presentation

Articles in international journals and collections

Year of publication

2024

Язык

английский

Authors, employees of KFU

Simushkin Sergey Vladimirovich, author

Authors, postgraduates KFU

Zaarur Ezeddin -, postgraduate kfu

Bibliographic description in the original language

Simushkin S.V. Consistency of the Empirical Bayesian Analogue of the Regression Estimation / E. Zaarour, S. V. Simushkin // Lobachevskii Journal of Mathematics. - 2024. - Vol. 45, No. 1. - pp. 551–554.

Annotation

We study the possibility of constructing a Bayesian estimate based on a kernel estimate of the unconditional distribution density. We consider the situation when the observed random variable is the sum of an unknown parameter and a centered normal error with a known variance. In this case, the Bayesian estimate can be represented through the unconditional density of observations and its derivative, which makes it possible to construct empirical analogues of the Bayesian estimate only on the basis of density estimates. The consistency of these analogues is shown both for a fixed result of the current experiment, and in the mean.

Keywords

empirical Bayesian estimation, kernel density estimation, mean square consistency.

The name of the journal

Lobachevskii Journal of Mathematics

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=300078&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Simushkin Sergey Vladimirovich	ru_RU
dc.contributor.author	Zaarur Ezeddin -	ru_RU
dc.date.accessioned	2024-01-01T00:00:00Z	ru_RU
dc.date.available	2024-01-01T00:00:00Z	ru_RU
dc.date.issued	2024	ru_RU
dc.identifier.citation	Simushkin S.V. Consistency of the Empirical Bayesian Analogue of the Regression Estimation / E. Zaarour, S. V. Simushkin // Lobachevskii Journal of Mathematics. - 2024. - Vol. 45, No. 1. - pp. 551–554.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=300078&p_lang=2	ru_RU
dc.description.abstract	Lobachevskii Journal of Mathematics	ru_RU
dc.description.abstract	We study the possibility of constructing a Bayesian estimate based on a kernel estimate of the unconditional distribution density. We consider the situation when the observed random variable is the sum of an unknown parameter and a centered normal error with a known variance. In this case, the Bayesian estimate can be represented through the unconditional density of observations and its derivative, which makes it possible to construct empirical analogues of the Bayesian estimate only on the basis of density estimates. The consistency of these analogues is shown both for a fixed result of the current experiment, and in the mean.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	empirical Bayesian estimation	ru_RU
dc.subject	kernel density estimation	ru_RU
dc.subject	mean square consistency.	ru_RU
dc.title	Consistency of the Empirical Bayesian Analogue of the Regression Estimation	ru_RU
dc.type	Articles in international journals and collections	ru_RU