RAS PhysicsРадиотехника и электроника Journal of Communications Technology and Electronics

  • ISSN (Print) 0033-8494
  • ISSN (Online) 3034-5901

New methods for statistical decision making in conditions of a limited volume of observations and with a prioriy parametric uncertainty

PII
10.31857/S0033849424010064-1
DOI
10.31857/S0033849424010064
Publication type
Article
Status
Published
Authors
Volume/ Edition
Volume 69 / Issue number 1
Pages
76-87
Abstract
A new generalized adaptive algorithm for learning to make statistical decisions for exponential families of distributions with a priori parametric uncertainty in conditions of small samples has been developed. A generalized decision rule is presented, obtained by estimating unknown parameters of distributions, as well as a decision rule that satisfies the necessary optimality conditions: constancy of the average probability of a type I error and unbiasedness. Specific decision procedures for partial distributions obtained from a generalized algorithm are considered. Numerical examples are given. The effectiveness of the developed optimal procedure for small samples is shown.
Keywords
априорная параметрическая неопределённость обобщенный адаптивный алгоритм экспоненциальное семейство распределений выборки малого объема
Date of publication
16.09.2025
Year of publication
2025
Number of purchasers
0
Views
12

References

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At the Ministry of Education and Science of the Russian Federation

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