mlsanityData to 14 Oct 2026

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

arXiv 2406.06851 ↗First posted 10 Jun 2024stat.MEcited by 3

Not on the map. Why?

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.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 0; 2026: 2.

3 papers.