A two-stage adaptive Metropolis algorithm
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Publication:6074173
DOI10.1080/00949655.2022.2127720arXiv2101.00118OpenAlexW3120129458MaRDI QIDQ6074173
Kai Yin, Abhijit Mandal, Anirban Mondal
Publication date: 19 September 2023
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2101.00118
Markov chain Monte CarloergodicityMetropolis-Hastingsadaptive metropolistwo-stage Metropolis-Hastings
Cites Work
- Unnamed Item
- Adaptive proposal distribution for random walk Metropolis algorithm
- Two-stage Metropolis-Hastings for tall data
- Chaining via annealing
- Weak convergence and optimal scaling of random walk Metropolis algorithms
- Approximately Sufficient Statistics and Bayesian Computation
- General Irreducible Markov Chains and Non-Negative Operators
- Adaptive Rejection Metropolis Sampling within Gibbs Sampling
- Adaptive Markov Chain Monte Carlo through Regeneration
- Equation of State Calculations by Fast Computing Machines
- Speeding Up MCMC by Efficient Data Subsampling
- Preconditioning Markov Chain Monte Carlo Simulations Using Coarse-Scale Models
- Monte Carlo sampling methods using Markov chains and their applications
- An adaptive Metropolis algorithm
- Monte Carlo strategies in scientific computing
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