Two convergence properties of hybrid samplers

DOI10.1214/aoap/1028903533zbMath0938.60055OpenAlexW2136521556MaRDI QIDQ1296738

Jeffrey S. Rosenthal, Gareth O. Roberts

Publication date: 21 June 2000

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

Full work available at URL: https://doi.org/10.1214/aoap/1028903533

zbMATH Keywords

Monte CarloMarkov chainconvergence rategeometric convergencehybrid sampler

Mathematics Subject Classification ID

Parametric inference (62F99) Markov processes: estimation; hidden Markov models (62M05) Discrete-time Markov processes on general state spaces (60J05)

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Cites Work

• Markov chains and stochastic stability
• Strong uniform times and finite random walks
• Computable bounds for geometric convergence rates of Markov chains
• Geometric ergodicity and hybrid Markov chains
• Markov chains for exploring posterior distributions. (With discussion)
• General Irreducible Markov Chains and Non-Negative Operators
• Sampling-Based Approaches to Calculating Marginal Densities
• Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms
• Minorization Conditions and Convergence Rates for Markov Chain Monte Carlo
• Monte Carlo sampling methods using Markov chains and their applications
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