Splitting algorithms for rare event simulation over long time intervals

DOI10.1214/20-AAP1578zbMath1477.60054OpenAlexW3111766688MaRDI QIDQ2240483

Michael Snarski, Anne Buijsrogge, Paul Dupuis

Publication date: 4 November 2021

Published in: The Annals of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/journals/annals-of-applied-probability/volume-30/issue-6/Splitting-algorithms-for-rare-event-simulation-over-long-time-intervals/10.1214/20-AAP1578.full

zbMATH Keywords

Monte Carlo methodslarge deviationsrestartsplitting algorithmsmetastable points

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Large deviations (60F10) Stochastic processes (60G99)

Uses Software

• RESTART

Cites Work

• The design and analysis of a generalized RESTART/DPR algorithm for rare event simulation
• A nonasymptotic theorem for unnormalized Feynman-Kac particle models
• Escaping from an attractor: Importance sampling and rest points. I.
• Splitting for rare event simulation: A large deviation approach to design and analysis
• Large deviations for Markov processes with discontinuous statistics. I: General upper bounds
• Large deviations for small noise diffusions in a fast Markovian environment
• Dynamic importance sampling for queueing networks
• The Asymptotic Efficiency of Simulation Estimators
• Analysis and Approximation of Rare Events
• Subsolutions of an Isaacs Equation and Efficient Schemes for Importance Sampling
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