Unbiased Markov Chain Monte Carlo: what, why, and how
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Jun 2024.
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Citing papers per year: 2024: 1; 2025: 0; 2026: 2.
3 papers.