Unbiased Markov Chain Monte Carlo: what, why, and how

Fuente: arXiv
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Main Authors: Atchadé, Yves F., Jacob, Pierre E.
Format: Preprint
Published: 2024
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author Atchadé, Yves F.
Jacob, Pierre E.
author_facet Atchadé, Yves F.
Jacob, Pierre E.
contents This document presents methods to remove the initialization or burn-in bias from Markov chain Monte Carlo (MCMC) estimates, with consequences on parallel computing, convergence diagnostics and performance assessment. The document is written as an introduction to these methods for MCMC users. Some theoretical results are mentioned, but the focus is on the methodology.
format Preprint
id arxiv_https___arxiv_org_abs_2406_06851
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Unbiased Markov Chain Monte Carlo: what, why, and how
Atchadé, Yves F.
Jacob, Pierre E.
Methodology
This document presents methods to remove the initialization or burn-in bias from Markov chain Monte Carlo (MCMC) estimates, with consequences on parallel computing, convergence diagnostics and performance assessment. The document is written as an introduction to these methods for MCMC users. Some theoretical results are mentioned, but the focus is on the methodology.
title Unbiased Markov Chain Monte Carlo: what, why, and how
topic Methodology
url https://arxiv.org/abs/2406.06851