A framework for adaptive MCMC targeting multimodal distributions

DOI10.1214/19-AOS1916zbMath1486.62009arXiv1812.02609OpenAlexW3087616194MaRDI QIDQ2215766

Krzysztof Łatuszyński, Emilia Pompe, Christopher C. Holmes

Publication date: 14 December 2020

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

Full work available at URL: https://arxiv.org/abs/1812.02609

zbMATH Keywords

ergodicityadaptive MCMCmultimodal distribution

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items

Cauchy Markov random field priors for Bayesian inversion ⋮ Adaptive schemes for piecewise deterministic Monte Carlo algorithms ⋮ Latent uniform samplers on multivariate binary spaces ⋮ Polya tree Monte Carlo method ⋮ Global Likelihood Sampler for Multimodal Distributions ⋮ A Metropolis-class sampler for targets with non-convex support ⋮ Hopping between distant basins ⋮ Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable selection

Uses Software

• MultiNest

Cites Work

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