Central Limit Theorem for Adaptive Multilevel Splitting Estimators in an Idealized Setting

DOI10.1007/978-3-319-33507-0_10zbMath1356.65029arXiv1501.01399OpenAlexW3106029663MaRDI QIDQ2957034

Loïc Tudela, Ludovic Goudenège, Charles-Edouard Bréhier

Publication date: 20 January 2017

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1501.01399

zbMATH Keywords

numerical examplesrare eventsMonte Carlo simulationcentral limit theoremmultilevel splittingGaussian confidence intervals

Mathematics Subject Classification ID

Central limit and other weak theorems (60F05) Nonparametric tolerance and confidence regions (62G15) Statistics of extreme values; tail inference (62G32) Monte Carlo methods (65C05)

Related Items (5)

Coupling rare event algorithms with data-based learned committor functions using the analogue Markov chain ⋮ On the Asymptotic Normality of Adaptive Multilevel Splitting ⋮ On a new class of score functions to estimate tail probabilities of some stochastic processes with adaptive multilevel splitting ⋮ Bayesian Subset Simulation ⋮ Recent advances in various fields of numerical probability

Cites Work

• Simulation and estimation of extreme quantiles and extreme probabilities
• Sequential Monte Carlo for rare event estimation
• Combinatorial analysis of the adaptive last particle method
• Stochastic simulation: Algorithms and analysis
• Multilevel Splitting for Estimating Rare Event Probabilities
• Analysis of adaptive multilevel splitting algorithms in an idealized case
• Adaptive Multilevel Splitting for Rare Event Analysis
• Rare Event Simulation using Monte Carlo Methods
• Asymptotic Statistics
• Adaptive particle techniques and rare event estimation
• Nested sampling for general Bayesian computation

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