A modified conditional Metropolis-Hastings sampler

DOI10.1016/j.csda.2014.04.009zbMath1506.62088OpenAlexW2029818761MaRDI QIDQ1623632

James M. Flegal, Alicia A. Johnson

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2014.04.009

zbMATH Keywords

Markov chain Monte CarloGibbs samplergeometric ergodicityMetropolis-Hastings

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Related Items (1)

Geometric ergodicity of a more efficient conditional Metropolis-Hastings algorithm

Cites Work

• Markov chains and stochastic stability
• On the Markov chain central limit theorem
• Honest exploration of intractable probability distributions via Markov chain Monte Carlo.
• Miscellanea. Peskun's theorem and a modified discrete-state Gibbs sampler
• Improved Bounds for Mixing Rates of Markov Chains and Multicommodity Flow

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