Interacting multiple try algorithms with different proposal distributions

DOI10.1007/s11222-011-9301-9zbMath1322.65003arXiv1011.1170OpenAlexW3105437351WikidataQ60362008 ScholiaQ60362008MaRDI QIDQ746262

Roberto Casarin, Fabrizio Leisen, Radu V. Craiu

Publication date: 16 October 2015

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

Full work available at URL: https://arxiv.org/abs/1011.1170

zbMATH Keywords

Markov chain Monte Carlosimulated annealingpopulation Monte Carlointeracting Monte Carlomultiple-try Metropolis

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Software, source code, etc. for problems pertaining to statistics (62-04) Bayesian inference (62F15) Monte Carlo methods (65C05)

Related Items

Issues in the multiple try Metropolis mixing ⋮ A generalized multiple-try version of the reversible jump algorithm ⋮ An adaptive multiple-try Metropolis algorithm ⋮ Adaptive Metropolis-Hastings sampling using reversible dependent mixture proposals ⋮ Improving the acceptance in Monte Carlo simulations: sampling through intermediate states ⋮ Efficient Gibbs sampling for Markov switching GARCH models ⋮ Computing the halfspace depth with multiple try algorithm and simulated annealing algorithm ⋮ Convergence rate of multiple-try Metropolis independent sampler ⋮ A multi-point Metropolis scheme with generic weight functions ⋮ Multiple-try simulated annealing algorithm for global optimization ⋮ On the flexibility of the design of multiple try Metropolis schemes ⋮ A parallel evolutionary multiple-try Metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions ⋮ Generalized multiple-point Metropolis algorithms for approximate Bayesian computation ⋮ Adaptive Component-Wise Multiple-Try Metropolis Sampling ⋮ A multiple-try Metropolis-Hastings algorithm with tailored proposals ⋮ Plateau proposal distributions for adaptive component-wise multiple-try metropolis ⋮ On the empirical efficiency of local MCMC algorithms with pools of proposals

Uses Software

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Cites Work

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• Towards optimal scaling of Metropolis-coupled Markov chain Monte Carlo
• Parallel and interacting Markov chain Monte Carlo algorithm
• Scaling analysis of multiple-try MCMC methods
• Iterated importance sampling in missing data problems
• A generalized multiple-try version of the reversible jump algorithm
• Inference from iterative simulation using multiple sequences
• Online data processing: comparison of Bayesian regularized particle filters
• Multiprocess parallel antithetic coupling for backward and forward Markov chain Monte Carlo
• Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
• Finite mixture and Markov switching models.
• Learn From Thy Neighbor: Parallel-Chain and Regional Adaptive MCMC
• Sequential Monte Carlo Samplers
• Likelihood analysis of non-Gaussian measurement time series
• MODELING STOCHASTIC VOLATILITY: A REVIEW AND COMPARATIVE STUDY
• Improving Convergence of the Hastings–Metropolis Algorithm with an Adaptive Proposal
• Real-Parameter Evolutionary Monte Carlo With Applications to Bayesian Mixture Models
• The Multiple-Try Method and Local Optimization in Metropolis Sampling
• Annealing Markov Chain Monte Carlo with Applications to Ancestral Inference
• Monte Carlo sampling methods using Markov chains and their applications
• A Quantitative Study of Gene Regulation Involved in the Immune Response of Anopheline Mosquitoes