The Apogee to Apogee Path Sampler

DOI10.1080/10618600.2023.2190784arXiv2112.08187MaRDI QIDQ6181416

Unnamed Author, Matthew Ludkin, Chris Sherlock

Publication date: 22 January 2024

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2112.08187

zbMATH Keywords

Markov chain Monte CarloHamiltonian Monte Carloleapfrog steprobustness to tuning

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
• Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets
• An improved acceptance procedure for the hybrid Monte Carlo algorithm
• Optimal scaling for various Metropolis-Hastings algorithms.
• Randomized Hamiltonian Monte Carlo
• Optimal tuning of the hybrid Monte Carlo algorithm
• Handbook of Markov Chain Monte Carlo
• Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods
• Unbiased Hamiltonian Monte Carlo with couplings
• Kinetic energy choice in Hamiltonian/hybrid Monte Carlo
• An n‐dimensional Rosenbrock distribution for Markov chain Monte Carlo testing
• The Expected Number of Zeros of a Stationary Gaussian Process

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