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Efficiency of delayed-acceptance random walk metropolis algorithms - MaRDI portal

Efficiency of delayed-acceptance random walk metropolis algorithms (Q2054541)

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Language	Label	Description	Also known as
English	Efficiency of delayed-acceptance random walk metropolis algorithms	scientific article

Statements

scholarly article

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Efficiency of delayed-acceptance random walk metropolis algorithms (English)

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Andrew Golightly

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Alexandre H. Thiery

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The Annals of Statistics

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publication date

3 December 2021

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full work available at URL

https://arxiv.org/abs/1506.08155

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https://projecteuclid.org/journals/annals-of-statistics/volume-49/issue-5/Efficiency-of-delayed-acceptance-random-walk-Metropolis-algorithms/10.1214/21-AOS2068.full

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zbMATH Keywords

delayed-acceptance

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diffusion limit

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Markov chain Monte Carlo

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pseudo-marginal MCMC

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random-walk metropolis

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MaRDI profile type

MaRDI publication profile

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Particle Markov Chain Monte Carlo Methods

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The pseudo-marginal approach for efficient Monte Carlo computations

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Weak convergence of Metropolis algorithms for non-I.I.D. target distributions

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Scaling analysis of multiple-try MCMC methods

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Optimal scaling of Metropolis algorithms: Heading toward general target distributions

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A lognormal central limit theorem for particle approximations of normalizing constants

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Optimal scalings for local Metropolis-Hastings chains on nonproduct targets in high dimensions

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Optimal scaling of MaLa for nonlinear regression.

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Handbook of Markov Chain Monte Carlo

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Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator

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Preconditioning Markov Chain Monte Carlo Simulations Using Coarse-Scale Models

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An Exact Gibbs Sampler for the Markov-Modulated Poisson Process

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BAYESIAN INFERENCE BASED ONLY ON SIMULATED LIKELIHOOD: PARTICLE FILTER ANALYSIS OF DYNAMIC ECONOMIC MODELS

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Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance

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Delayed acceptance particle MCMC for exact inference in stochastic kinetic models

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Statistical and computational inverse problems.

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Monte Carlo strategies in scientific computing

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Diffusion limits of the random walk Metropolis algorithm in high dimensions

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On some properties of Markov chain Monte Carlo simulation methods based on the particle filter

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Speeding up MCMC by Delayed Acceptance and Data Subsampling

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Weak convergence and optimal scaling of random walk Metropolis algorithms

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Optimal Scaling of Discrete Approximations to Langevin Diffusions

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Optimal scaling for various Metropolis-Hastings algorithms.

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Complexity bounds for Markov chain Monte Carlo algorithms via diffusion limits

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Minimising MCMC variance via diffusion limits, with an application to simulated tempering

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Large-sample asymptotics of the pseudo-marginal method

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Optimal Scaling of the Random Walk Metropolis: General Criteria for the 0.234 Acceptance Rule

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Optimal scaling for the pseudo-marginal random walk Metropolis: insensitivity to the noise generating mechanism

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The random walk Metropolis: linking theory and practice through a case study

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Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets

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Pseudo-marginal Metropolis–Hastings sampling using averages of unbiased estimators

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On the efficiency of pseudo-marginal random walk Metropolis algorithms

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Inverse problems: A Bayesian perspective

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Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo

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Optimal scaling of random-walk Metropolis algorithms on general target distributions

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A Dirichlet form approach to MCMC optimal scaling

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Identifiers

zbMATH Open document ID

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10.1214/21-AOS2068

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:2054541

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