Optimal scaling of MCMC beyond Metropolis
From MaRDI portal
Publication:6159395
DOI10.1017/apr.2022.37zbMath1514.65004arXiv2104.02020OpenAlexW3143257014MaRDI QIDQ6159395
Gareth O. Roberts, Unnamed Author, Krzysztof Łatuszyński, Dootika Vats
Publication date: 5 May 2023
Published in: Advances in Applied Probability (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2104.02020
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Conditional sequential Monte Carlo in high dimensions, Collective proposal distributions for nonlinear MCMC samplers: mean-field theory and fast implementation
Cites Work
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- Optimal scaling for the transient phase of Metropolis Hastings algorithms: the longtime behavior
- Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets
- Markov chains and stochastic stability
- Optimal scaling for partially updating MCMC algorithms
- Exponential convergence of Langevin distributions and their discrete approximations
- Weak convergence and optimal scaling of random walk Metropolis algorithms
- A geometric interpretation of the Metropolis-Hastings algorithm.
- Optimal scaling for various Metropolis-Hastings algorithms.
- On Metropolis-Hastings algorithms with delayed rejection
- A Dirichlet form approach to MCMC optimal scaling
- Barker's algorithm for Bayesian inference with intractable likelihoods
- CLTs and asymptotic variance of time-sampled Markov chains
- Efficiency of delayed-acceptance random walk metropolis algorithms
- From the Bernoulli factory to a dice enterprise via perfect sampling of Markov chains
- Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics
- Optimal scaling of random-walk Metropolis algorithms on general target distributions
- Diffusion limit for the random walk Metropolis algorithm out of stationarity
- On the efficiency of pseudo-marginal random walk Metropolis algorithms
- Optimal search efficiency of Barker's algorithm with an exponential fitness function
- Optimal acceptance rates for Metropolis algorithms: Moving beyond 0.234
- Optimum Monte-Carlo sampling using Markov chains
- Does Waste Recycling Really Improve the Multi-Proposal Metropolis–Hastings algorithm? an Analysis Based on Control Variates
- Handbook of Markov Chain Monte Carlo
- Optimal Scaling of Discrete Approximations to Langevin Diffusions
- Multivariate output analysis for Markov chain Monte Carlo
- Efficient Bernoulli factory Markov chain Monte Carlo for intractable posteriors
- Equation of State Calculations by Fast Computing Machines
- Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator
- Scaling Limits for the Transient Phase of Local Metropolis–Hastings Algorithms
- Monte Carlo sampling methods using Markov chains and their applications
- Large-sample asymptotics of the pseudo-marginal method
