Geodesic
Randomized algorithms of Monte Carlo method for problems with random parameters (“double randomization” method)
Sibirskij žurnal vyčislitelʹnoj matematiki, Tome 22 (2019) no. 2, pp. 187-200.

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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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     author = {G. A. Mikhailov},
     title = {Randomized algorithms of {Monte} {Carlo} method for problems with random parameters ({\textquotedblleft}double randomization{\textquotedblright} method)},
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G. A. Mikhailov. Randomized algorithms of Monte Carlo method for problems with random parameters (“double randomization” method). Sibirskij žurnal vyčislitelʹnoj matematiki, Tome 22 (2019) no. 2, pp. 187-200. http://geodesic.mathdoc.fr/item/SJVM_2019_22_2_a5/

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