Аннотация
Randomized Monte Carlo algorithms intended for statistical kernel estimation of the averaged solution to a problem with random baseline parameters are optimized. For this purpose, a criterion for the complexity of a functional Monte Carlo estimate is formulated. The algorithms involve a splitting method in which, for each realization of the parameters, a certain number of trajectories of the corresponding baseline process are constructed.
Язык оригинала | английский |
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Страницы (с-по) | 448-451 |
Число страниц | 4 |
Журнал | Doklady Mathematics |
Том | 98 |
Номер выпуска | 2 |
DOI | |
Состояние | Опубликовано - 1 сен 2018 |