On convergence rates of Gibbs samplers for uniform distributions

DOI10.1214/aoap/1028903381zbMath0935.60054OpenAlexW2089276831MaRDI QIDQ1296725

Gareth O. Roberts, Jeffrey S. Rosenthal

Publication date: 4 May 2000

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

Full work available at URL: https://doi.org/10.1214/aoap/1028903381

Mathematics Subject Classification ID

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

Related Items (10)

A computational procedure for estimation of the mixing time of the random-scan Metropolis algorithm ⋮ Partial identification in the statistical matching problem ⋮ Honest exploration of intractable probability distributions via Markov chain Monte Carlo. ⋮ Geometric ergodicity for Bayesian shrinkage models ⋮ Slow hit-and-run sampling ⋮ Convergence rates for a class of estimators based on Stein's method ⋮ Geometric Ergodicity and Scanning Strategies for Two-Component Gibbs Samplers ⋮ Sensitivity and convergence of uniformly ergodic Markov chains ⋮ Slow convergence of the Gibbs sampler ⋮ The polar slice sampler

Cites Work

• Unnamed Item
• Markov chains and stochastic stability
• Brownian motion and the fundamental frequency of a drum
• Markov chains for exploring posterior distributions. (With discussion)
• Bounds on the L 2 Spectrum for Markov Chains and Markov Processes: A Generalization of Cheeger's Inequality
• 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
• Gibbs Sampling for Bayesian Non-Conjugate and Hierarchical Models by Using Auxiliary Variables
• Slow convergence of the Gibbs sampler

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