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Improvement of Multidimensional Randomized Monte Carlo Algorithms with “Splitting”. / Mikhailov, G. A.
в: Computational Mathematics and Mathematical Physics, Том 59, № 5, 01.05.2019, стр. 775-781.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Improvement of Multidimensional Randomized Monte Carlo Algorithms with “Splitting”
AU - Mikhailov, G. A.
PY - 2019/5/1
Y1 - 2019/5/1
N2 - Abstract: Randomized Monte Carlo algorithms are constructed by jointly realizing a baseline probabilistic model of the problem and its random parameters (random medium) in order to study a parametric distribution of linear functionals. This work relies on statistical kernel estimation of the multidimensional distribution density with a “homogeneous” kernel and on a splitting method, according to which a certain number n of baseline trajectories are modeled for each medium realization. The optimal value of n is estimated using a criterion for computational complexity formulated in this work. Analytical estimates of the corresponding computational efficiency are obtained with the help of rather complicated calculations.
AB - Abstract: Randomized Monte Carlo algorithms are constructed by jointly realizing a baseline probabilistic model of the problem and its random parameters (random medium) in order to study a parametric distribution of linear functionals. This work relies on statistical kernel estimation of the multidimensional distribution density with a “homogeneous” kernel and on a splitting method, according to which a certain number n of baseline trajectories are modeled for each medium realization. The optimal value of n is estimated using a criterion for computational complexity formulated in this work. Analytical estimates of the corresponding computational efficiency are obtained with the help of rather complicated calculations.
KW - complexity of functional estimate
KW - double randomization method
KW - Monte Carlo method
KW - probabilistic model
KW - random medium
KW - randomized algorithm
KW - splitting method
KW - statistical kernel estimate
KW - statistical modeling
KW - MODELS
UR - http://www.scopus.com/inward/record.url?scp=85067460114&partnerID=8YFLogxK
U2 - 10.1134/S0965542519050117
DO - 10.1134/S0965542519050117
M3 - Article
AN - SCOPUS:85067460114
VL - 59
SP - 775
EP - 781
JO - Computational Mathematics and Mathematical Physics
JF - Computational Mathematics and Mathematical Physics
SN - 0965-5425
IS - 5
ER -
ID: 20643071