On the Geometric Ergodicity of Two-Variable Gibbs Samplers

DOI10.1214/12-IMSCOLL1002zbMath1329.60257arXiv1206.4770OpenAlexW1558800859MaRDI QIDQ5499665

Galin L. Jones, Aixin Tan, James P. Hobert

Publication date: 30 July 2015

Published in: Advances in Modern Statistical Theory and Applications: A Festschrift in honor of Morris L. Eaton (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1206.4770

zbMATH Keywords

Markov chainsGibbs samplergeometric ergodicity

Mathematics Subject Classification ID

Bayesian inference (62F15) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10)

Related Items (7)

Convergence rates of two-component MCMC samplers ⋮ Assessing and Visualizing Simultaneous Simulation Error ⋮ Neuronized Priors for Bayesian Sparse Linear Regression ⋮ Geometric ergodicity for Bayesian shrinkage models ⋮ Geometric ergodicity of random scan Gibbs samplers for hierarchical one-way random effects models ⋮ Component-wise Markov chain Monte Carlo: uniform and geometric ergodicity under mixing and composition ⋮ Convergence rate bounds for iterative random functions using one-shot coupling

This page was built for publication: On the Geometric Ergodicity of Two-Variable Gibbs Samplers