This article is cited in 11 papers

Randomized algorithms of Monte Carlo method for problems with random parameters (“double randomization” method)

G. A. Mikhailov<sup>ab

a</sup> Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences, pr. Akad. Lavrent'eva 6, Novosibirsk, 630090 Russia
^b Novosibirsk State University, ul. Pirogova 2, Novosibirsk, 630090 Russia

Abstract: Randomized algorithms of Monte Carlo method are constructed by the combined realization of the base probabilistic model and its random parameters for investigation of the parametric distribution of linear functionals. The optimization of algorithms with the use of the statistical kernel estimator for the probability density is presented. The randomized projection algorithm for estimating a nonlinear functional distribution as applied to the investigation of criticality fluctuations for the particles multiplication process in a random medium is formulated.

Key words: probabilistic model, statistic modeling, random parameter, randomized algorithm, double randomization method, random medium, splitting method, statistic kernel estimator.

UDC: 519.676

Received: 21.06.2018
Accepted: 21.01.2019

DOI: 10.15372/SJNM20190205

 English version: Numerical Analysis and Applications, 2019, 12:2, 155–165

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