On the convergence complexity of Gibbs samplers for a family of simple Bayesian random effects models

DOI10.1007/s11009-020-09808-8zbMath1478.60207arXiv2004.14330OpenAlexW3082305398MaRDI QIDQ2065471

James P. Hobert, Bryant Davis

Publication date: 7 January 2022

Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2004.14330

zbMATH Keywords

Monte Carlotrace-class operatorspectral gapconvergence rategeometric ergodicityWasserstein distancehigh-dimensional inferencetotal variation distancequantitative bound

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Numerical analysis or methods applied to Markov chains (65C40)

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Complexity results for MCMC derived from quantitative bounds

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