On parallelizable Markov chain Monte Carlo algorithms with waste-recycling

DOI10.1007/s11222-017-9780-4zbMath1406.65008OpenAlexW2761112412MaRDI QIDQ1616782

R. Smith

Publication date: 7 November 2018

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

Full work available at URL: https://doi.org/10.1007/s11222-017-9780-4

zbMATH Keywords

Markov chain Monte Carloparallel computationestimation efficiencyeffective sample sizeRao-Blackwellizationweighted samples

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (4)

Conditional sequential Monte Carlo in high dimensions ⋮ Convergence rate of multiple-try Metropolis independent sampler ⋮ A Quantum Parallel Markov Chain Monte Carlo ⋮ Generating MCMC proposals by randomly rotating the regular simplex

Uses Software

• BayesDA

Cites Work

• Unnamed Item
• Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
• An improved acceptance procedure for the hybrid Monte Carlo algorithm
• Exponential convergence of Langevin distributions and their discrete approximations
• A vanilla Rao-Blackwellization of Metropolis-Hastings algorithms
• Does Waste Recycling Really Improve the Multi-Proposal Metropolis–Hastings algorithm? an Analysis Based on Control Variates
• The Multiple-Try Method and Local Optimization in Metropolis Sampling
• Equation of State Calculations by Fast Computing Machines
• Monte Carlo sampling methods using Markov chains and their applications
• Monte Carlo strategies in scientific computing
• Multipoint Metropolis method with application to hybrid Monte Carlo

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