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Approximate Estimation Using the Accelerated Maximum Entropy Method. Part 2. Study of the Properties of Estimates
- Авторлар: Dubnov Y.A.1, Boulytchev A.V.1
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Мекемелер:
- Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
- Шығарылым: № 1 (2023)
- Беттер: 71-81
- Бөлім: Mathematical modeling
- URL: https://ogarev-online.ru/2071-8632/article/view/287844
- DOI: https://doi.org/10.14357/20718632230107
- ID: 287844
Дәйексөз келтіру
Ашық рұқсат
Рұқсат берілді
Тек жазылушылар үшін
Аннотация
In this paper, we investigate a method of approximate entropy estimation, designed to speed up the classical method of maximum entropy estimation due to the use of regularization in the optimization problem. This method is compared with the method of maximum likelihood and Bayesian estimation, both experimentally and in terms of theoretical calculations for some special cases. Estimation methods are tested on the example of a linear regression problem with errors of various types, including asymmetric distributions as well as a multimodal distribution in the form of a mixture of Gaussian components.
Авторлар туралы
Y. Dubnov
Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Хат алмасуға жауапты Автор.
Email: yury.dubnov@phystech.edu
Researcher, Senior Lecturer
Ресей, MoscowA. Boulytchev
Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Email: bulytchev.isa.ran@gmail.com
PhD, Leading Researcher, Assistant Professor
Ресей, MoscowӘдебиет тізімі
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