Handbook of Markov chain Monte Carlo, second edition

2026-05-06 · Source: Statistical Modeling, Causal Inference, and Social Science · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics · Depth: Expert, quick

Summary

The second edition of the "Handbook of Markov chain Monte Carlo" has been released, co-edited by Radu Craiu, Dootika Vats, Galin Jones, Steve Brooks, Xiao-Li Meng, and the author. A GitHub page for the book, maintained by Dootika Vats, lists all chapters and provides links to most of them in arXiv format. Notable chapters include Chapter 4, "For how many iterations should we run Markov chain Monte Carlo?" by Charles Margossian and the author, and Chapter 24, "Running Markov chain Monte Carlo on modern hardware and software," by Pavel Sountsov, Colin Carroll, and Matthew Hoffman. The editors expressed regret over not including chapters on probabilistic programming (e.g., Stan), sequential Monte Carlo (particle filtering), and divide-and-conquer algorithms (e.g., expectation propagation).

Key takeaway

For researchers and practitioners utilizing Markov chain Monte Carlo methods, exploring the second edition of the "Handbook of Markov chain Monte Carlo" is highly recommended. Your understanding of MCMC applications on contemporary hardware and software will benefit from Chapter 24, while Chapter 4 offers guidance on iteration counts. Consider the book's GitHub page as a central resource for accessing chapter content.

Key insights

The second edition of the MCMC Handbook is available, covering advanced computational methods.

In practice

• Consult Chapter 24 for MCMC on modern hardware.
• Explore the GitHub page for chapter links.

Topics

• Markov chain Monte Carlo
• Probabilistic Programming
• Sequential Monte Carlo
• Particle Filtering
• Divide-and-Conquer Algorithms

Code references

• dvats/HandbookOfMCMC

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Editorial summary, takeaway, and curation by AIssential. Original article published by Statistical Modeling, Causal Inference, and Social Science.