Unbiased Markov chain Monte Carlo for intractable target distributions

DOI10.1214/20-EJS1727zbMath1450.62027arXiv1807.08691OpenAlexW3047714077MaRDI QIDQ2192323

Pierre E. Jacob, Lawrence Middleton, George Deligiannidis, Arnaud Doucet

Publication date: 17 August 2020

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1807.08691

zbMATH Keywords

numerical integrationBayesian inferenceMarkov chain Monte Carlo (MCMC) algorithm

Mathematics Subject Classification ID

Bayesian inference (62F15) Markov processes: estimation; hidden Markov models (62M05) Monte Carlo methods (65C05)

Related Items (3)

Laplace based Bayesian inference for ordinary differential equation models using regularized artificial neural networks ⋮ Lagged couplings diagnose Markov chain Monte Carlo phylogenetic inference ⋮ Unbiased optimal stopping via the MUSE

Uses Software

• CODA

Cites Work

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• The pseudo-marginal approach for efficient Monte Carlo computations
• The Correlated Pseudo-Marginal Method
• Weak convergence and optimal scaling of random walk Metropolis algorithms
• Geometric ergodicity of Metropolis algorithms
• Polynomial convergence rates of Markov chains
• Practical drift conditions for subgeometric rates of convergence.
• Controlled sequential Monte Carlo
• Coupled conditional backward sampling particle filter
• Convergence properties of pseudo-marginal Markov chain Monte Carlo algorithms
• A lognormal central limit theorem for particle approximations of normalizing constants
• Quantitative Convergence Rates for Subgeometric Markov Chains
• Studying Convergence of Markov Chain Monte Carlo Algorithms Using Coupled Sample Paths
• Discrete Choice Methods with Simulation
• Markov Chains and Stochastic Stability
• Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms
• A Coupling-Regeneration Scheme for Diagnosing Convergence in Markov Chain Monte Carlo Algorithms
• Bias Properties of Budget Constrained Simulations
• The Asymptotic Efficiency of Simulation Estimators
• Bayesian Inference in the Presence of Intractable Normalizing Functions
• Markov Chains
• Particle Markov Chain Monte Carlo Methods
• Regeneration in Markov Chain Samplers
• Exact sampling with coupled Markov chains and applications to statistical mechanics
• Unbiased Hamiltonian Monte Carlo with couplings
• Unbiased Markov Chain Monte Carlo Methods with Couplings
• Smoothing With Couplings of Conditional Particle Filters
• Exact estimation for Markov chain equilibrium expectations
• Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator
• Sequential Quasi Monte Carlo
• Exact Sampling for the Ising Model at all Temperatures
• An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants
• Crystal Statistics. I. A Two-Dimensional Model with an Order-Disorder Transition

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