A Fresh Look at the Running Time Analysis for the Gibbs Sampler

DOI10.1080/03610918.2012.677922zbMath1268.65010OpenAlexW2005285138MaRDI QIDQ5299924

Yuchung J. Wang, Kun-Lin Kuo

Publication date: 24 June 2013

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2012.677922

zbMATH Keywords

burn-instationarityoddsconvergence of marginal distributionsmultiple chainsample trajectorysingle chain

Mathematics Subject Classification ID

Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Numerical analysis or methods applied to Markov chains (65C40)

Cites Work

• Unnamed Item
• Gibbs sampling, exponential families and orthogonal polynomials
• Markov chain Monte Carlo: can we trust the third significant figure?
• Methods for approximating integrals in statistics with special emphasis on Bayesian integration problems
• Practical Markov Chain Monte Carlo
• Bayesian Computation with R

This page was built for publication: A Fresh Look at the Running Time Analysis for the Gibbs Sampler