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Zhurnal Vychislitel'noi Matematiki i Matematicheskoi Fiziki, 2021, Volume 61, Number 9, Pages 1431–1446
DOI: https://doi.org/10.31857/S0044466921090076 (Mi zvmmf11286) 		 
This article is cited in 2 scientific papers (total in 2 papers)

Optimal control

Conditional optimization of the functional computational kernel algorithm for approximating the probability density on the basis of a given sample

T. Bulgakovaa, A. V. Voitishekab

a Novosibirsk State University, 630090, Novosibirsk, Russia
b Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences, 630090, Novosibirsk, Russia
Citations (2)
DOI: https://doi.org/10.31857/S0044466921090076
Abstract: The problem of obtaining a numerical functional approximation of probability density on the basis of a given or simulated sample values with a prescribed error level at the minimum cost is considered. A computational algorithm for solving this problem that is a functional version of the kernel estimate of the probability density is proposed. This algorithm is similar to the functional computational kernel statistical algorithm for the approximate solution of the Fredholm integral equation of second kind, for which the theory of conditional optimization was earlier built. In this paper, this theory is built for the constructed functional computational kernel algorithm of approximating the probability density.
Key words: numerical functional approximation of probability density, numerical approximation of functions, functional computational kernel algorithm, functional computational statistical algorithm, conditionally optimal parameters.
Funding agency Grant number
Ministry of Education and Science of the Russian Federation 0315-2019-0002
This work was performed within the state program of the Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences, project no. 0315-2019-0002.
Received: 18.08.2020
Revised: 29.12.2020
Accepted: 07.04.2021
English version:
Computational Mathematics and Mathematical Physics, 2021, Volume 61, Issue 9, Pages 1401–1415
DOI: https://doi.org/10.1134/S0965542521090062
Bibliographic databases:
Document Type: Article
UDC: 519.87
Language: Russian
Citation: T. Bulgakova, A. V. Voitishek, “Conditional optimization of the functional computational kernel algorithm for approximating the probability density on the basis of a given sample”, Zh. Vychisl. Mat. Mat. Fiz., 61:9 (2021), 1431–1446; Comput. Math. Math. Phys., 61:9 (2021), 1401–1415
Citation in format AMSBIB
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\paper Conditional optimization of the functional computational kernel algorithm for approximating the probability density on the basis of a given sample
\jour Zh. Vychisl. Mat. Mat. Fiz.
\yr 2021
\vol 61
\issue 9
\pages 1431--1446
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\crossref{https://doi.org/10.31857/S0044466921090076}
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\transl
\jour Comput. Math. Math. Phys.
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    • This publication is cited in the following 2 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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