Standard

Randomized Monte Carlo Algorithms for Problems with Random Parameters (“Double Randomization” Method). / Mikhailov, G. A.

в: Numerical Analysis and Applications, Том 12, № 2, 01.04.2019, стр. 155-165.

Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование

Harvard

Mikhailov, GA 2019, 'Randomized Monte Carlo Algorithms for Problems with Random Parameters (“Double Randomization” Method)', Numerical Analysis and Applications, Том. 12, № 2, стр. 155-165. https://doi.org/10.1134/S1995423919020058

APA

Mikhailov, G. A. (2019). Randomized Monte Carlo Algorithms for Problems with Random Parameters (“Double Randomization” Method). Numerical Analysis and Applications, 12(2), 155-165. https://doi.org/10.1134/S1995423919020058

Vancouver

Mikhailov GA. Randomized Monte Carlo Algorithms for Problems with Random Parameters (“Double Randomization” Method). Numerical Analysis and Applications. 2019 апр. 1;12(2):155-165. doi: 10.1134/S1995423919020058

Author

Mikhailov, G. A. / Randomized Monte Carlo Algorithms for Problems with Random Parameters (“Double Randomization” Method). в: Numerical Analysis and Applications. 2019 ; Том 12, № 2. стр. 155-165.

BibTeX

@article{6fee07e34f944fb6a796a16c2bc75a6e,
title = "Randomized Monte Carlo Algorithms for Problems with Random Parameters (“Double Randomization” Method)",
abstract = "Randomized Monte Carlo algorithms are constructed by a combination of a basic probabilistic model and its random parameters to investigate parametric distributions of linear functionals. An optimization of the algorithms with a statistical kernel estimator for the probability density is presented. A randomized projection algorithm for estimating a nonlinear functional distribution is formulated and applied to the investigation of the criticality fluctuations of a particle multiplication process in a random medium.",
keywords = "double randomization method, probabilistic model, random medium, random parameter, randomized algorithm, splitting method, statistical kernel estimator, statistical modeling",
author = "Mikhailov, {G. A.}",
year = "2019",
month = apr,
day = "1",
doi = "10.1134/S1995423919020058",
language = "English",
volume = "12",
pages = "155--165",
journal = "Numerical Analysis and Applications",
issn = "1995-4239",
publisher = "Maik Nauka-Interperiodica Publishing",
number = "2",

}

RIS

TY - JOUR

T1 - Randomized Monte Carlo Algorithms for Problems with Random Parameters (“Double Randomization” Method)

AU - Mikhailov, G. A.

PY - 2019/4/1

Y1 - 2019/4/1

N2 - Randomized Monte Carlo algorithms are constructed by a combination of a basic probabilistic model and its random parameters to investigate parametric distributions of linear functionals. An optimization of the algorithms with a statistical kernel estimator for the probability density is presented. A randomized projection algorithm for estimating a nonlinear functional distribution is formulated and applied to the investigation of the criticality fluctuations of a particle multiplication process in a random medium.

AB - Randomized Monte Carlo algorithms are constructed by a combination of a basic probabilistic model and its random parameters to investigate parametric distributions of linear functionals. An optimization of the algorithms with a statistical kernel estimator for the probability density is presented. A randomized projection algorithm for estimating a nonlinear functional distribution is formulated and applied to the investigation of the criticality fluctuations of a particle multiplication process in a random medium.

KW - double randomization method

KW - probabilistic model

KW - random medium

KW - random parameter

KW - randomized algorithm

KW - splitting method

KW - statistical kernel estimator

KW - statistical modeling

UR - http://www.scopus.com/inward/record.url?scp=85066811828&partnerID=8YFLogxK

U2 - 10.1134/S1995423919020058

DO - 10.1134/S1995423919020058

M3 - Article

AN - SCOPUS:85066811828

VL - 12

SP - 155

EP - 165

JO - Numerical Analysis and Applications

JF - Numerical Analysis and Applications

SN - 1995-4239

IS - 2

ER -

ID: 20537639