Bayesian Approaches to the Design of Markov Chain Monte Carlo Samplers

DOI10.1007/978-3-642-41095-6_22zbMath1302.65009OpenAlexW2103560517MaRDI QIDQ2926232

Christian M. Davey, Jonathan M. Keith

Publication date: 31 October 2014

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-41095-6_22

zbMATH Keywords

numerical examplesMarkov processstatistical inferencerandom walkMarkov chain Monte Carlo methodsBayesian approachMetropolis-Hasting sampling

Mathematics Subject Classification ID

Bayesian inference (62F15) Sampling theory, sample surveys (62D05) Monte Carlo methods (65C05) Sums of independent random variables; random walks (60G50) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Numerical analysis or methods applied to Markov chains (65C40)

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