Randomized algorithms of Monte Carlo method for problems with random parameters (“double randomization” method)
G.A. Mikhailov1,2
1Institute of Computational Mathematics and Mathematical Geophysics SB RAS, Novosibirsk, 630090 Russia
2Novosibirsk State University, Novosibirsk, 630090 Russia
Keywords: вероятностная модель, статистическое моделирование, случайный параметр, рандомизированный алгоритм, метод двойной рандомизации, случайная среда, метод расщепления, статистическая ядерная оценка, probabilistic model, statistic modeling, random parameter, randomized algorithm, double randomization method, random medium, splitting method, statistic kernel estimator
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.
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