Markov chain importance sampling with applications to rare event probability estimation

DOI10.1007/S11222-011-9308-2zbMath1322.62010OpenAlexW2001848173MaRDI QIDQ746273

Zdravko I. Botev, Bruno Tuffin, Pierre L'Ecuyer

Publication date: 16 October 2015

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-011-9308-2

zbMATH Keywords

importance samplingvariance reductionnonparametricminimum variance densityrare-event probability

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Nonparametric regression and quantile regression (62G08) Applications of statistics to actuarial sciences and financial mathematics (62P05) Monte Carlo methods (65C05)

Related Items (10)

Layered adaptive importance sampling ⋮ On the use of marginal posteriors in marginal likelihood estimation via importance sampling ⋮ Markov Chain Importance Sampling—A Highly Efficient Estimator for MCMC ⋮ Computing marginal likelihoods via the Fourier integral theorem and pointwise estimation of posterior densities ⋮ On a Metropolis-Hastings importance sampling estimator ⋮ The importance Markov chain ⋮ Multicanonical MCMC for sampling rare events: an illustrative review ⋮ An adaptive metamodel-based subset importance sampling approach for the assessment of the functional failure probability of a thermal-hydraulic passive system ⋮ Regenerative Markov Chain Importance Sampling ⋮ Scalable Bayesian Regression in High Dimensions With Multiple Data Sources

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Efficient simulation of tail probabilities of sums of correlated lognormals
• Improved cross-entropy method for estimation
• Efficient Monte Carlo simulation via the generalized splitting method
• Efficient rare-event simulation for the maximum of heavy-tailed random walks
• Counterexamples in importance sampling for large deviations probabilities
• Introduction to rare event simulation.
• Stochastic simulation: Algorithms and analysis
• Handbook of Monte Carlo Methods
• A comparison of cross-entropy and variance minimization strategies
• Marginal Likelihood from the Gibbs Output
• Portfolio Credit Risk with Extremal Dependence: Asymptotic Analysis and Efficient Simulation
• Rare Event Simulation using Monte Carlo Methods
• Nonparametric Importance Sampling
• Importance sampling for sums of random variables with regularly varying tails
• Asymptotic robustness of estimators in rare-event simulation
• Simulation and the Monte Carlo Method
• Monte Carlo strategies in scientific computing

This page was built for publication: Markov chain importance sampling with applications to rare event probability estimation