Limit theorems for cloning algorithms
نویسندگان
چکیده
Large deviations for additive path functionals of stochastic processes have attracted significant research interest, in particular the context particle systems and statistical physics. Efficient numerical `cloning' algorithms been developed to estimate scaled cumulant generating function, based on importance sampling via cloning rare event trajectories. So far, attempts study convergence properties these continuous time only led partial results cases. Adapting previous from literature filters sequential Monte Carlo methods, we establish a first comprehensive fully rigorous approach bound systematic random errors time. To this end develop method compare different classes observables, martingale characterization processes. Our apply large class jump compact state space, do not involve any discretization contrast approaches. This provides robust framework that can also be used evaluate improve efficiency algorithms.
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ژورنال
عنوان ژورنال: Stochastic Processes and their Applications
سال: 2021
ISSN: ['1879-209X', '0304-4149']
DOI: https://doi.org/10.1016/j.spa.2021.04.007