A note on acceptance rate criteria for CLTS for Metropolis–Hastings algorithms

DOI10.1239/jap/1032374766zbMath0966.65006OpenAlexW1979606171MaRDI QIDQ4954249

Gareth O. Roberts

Publication date: 18 May 2000

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

Full work available at URL: https://doi.org/10.1239/jap/1032374766

zbMATH Keywords

Markov chain Monte Carlo methodcentral limit theoremsMetropolis algorithmsHastings algorithms

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Central limit and other weak theorems (60F05) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items

Bayesian semiparametric model for pathway-based analysis with zero-inflated clinical outcomes ⋮ Multiplicative random walk Metropolis-Hastings on the real line ⋮ Applicability of Subsampling Bootstrap Methods in Markov Chain Monte Carlo ⋮ Variance bounding Markov chains ⋮ Quantitative non-geometric convergence bounds for independence samplers ⋮ Markov-chain monte carlo: Some practical implications of theoretical results

This page was built for publication: A note on acceptance rate criteria for CLTS for Metropolis–Hastings algorithms