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

摘要

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.