Markov chain Monte Carlo algorithms with sequential proposals

DOI10.1007/s11222-020-09948-4zbMath1452.62108arXiv1907.06544OpenAlexW3037866298MaRDI QIDQ2209708

Yanyan Li

Publication date: 4 November 2020

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1907.06544

zbMATH Keywords

Markov chain Monte CarloPeskun orderingHamiltonian Monte Carlono-U-turn sampler

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (1)

A Metropolis-class sampler for targets with non-convex support

Uses Software

• R
• UCI-ml
• CODA
• mcmcse
• Stan
• NUTS

Cites Work

• The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
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• Slice sampling. (With discussions and rejoinder)
• On Metropolis-Hastings algorithms with delayed rejection
• Optimal tuning of the hybrid Monte Carlo algorithm
• On the efficiency of adaptive MCMC algorithms
• Perfect Slice Samplers
• Delayed rejection in reversible jump Metropolis-Hastings
• Simulating Hamiltonian Dynamics
• Optimum Monte-Carlo sampling using Markov chains
• Optimal Scaling of Discrete Approximations to Langevin Diffusions
• Convergence of Slice Sampler Markov Chains
• The Multiple-Try Method and Local Optimization in Metropolis Sampling
• Equation of State Calculations by Fast Computing Machines
• Coupling and Ergodicity of Adaptive Markov Chain Monte Carlo Algorithms
• Monte Carlo sampling methods using Markov chains and their applications
• An adaptive Metropolis algorithm
• Unnamed Item

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