A Multifidelity Monte Carlo Method for Realistic Computational Budgets
نویسندگان
چکیده
A method for the multifidelity Monte Carlo (MFMC) estimation of statistical quantities is proposed which applicable to computational budgets any size. Based on a sequence optimization problems each with globally minimizing closed-form solution, this extends usability well known MFMC algorithm, recovering it when budget large enough. Theoretical results verify that approach at least as optimal its namesake and retains benefits minimal assumptions or amount available data, providing notable reduction in variance over simple estimation.
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ژورنال
عنوان ژورنال: Journal of Scientific Computing
سال: 2022
ISSN: ['1573-7691', '0885-7474']
DOI: https://doi.org/10.1007/s10915-022-02051-y