Markov chain Monte Carlo: can we trust the third significant figure?
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Publication:900463
DOI10.1214/08-STS257zbMath1327.62017arXivmath/0703746WikidataQ121691093 ScholiaQ121691093MaRDI QIDQ900463
James M. Flegal, Galin L. Jones, Murali Haran
Publication date: 22 December 2015
Published in: Statistical Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/math/0703746
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Cites Work
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- Markov chains and stochastic stability
- General state space Markov chains and MCMC algorithms
- On the Markov chain central limit theorem
- Estimating the asymptotic variance with batch means
- The asymptotic validity of sequential stopping rules for stochastic simulations
- Geometric ergodicity of Gibbs and block Gibbs samplers for a hierarchical random effects model
- Computable bounds for geometric convergence rates of Markov chains
- Honest exploration of intractable probability distributions via Markov chain Monte Carlo.
- \(V\)-subgeometric ergodicity for a Hastings-Metropolis algorithm
- Convergence control methods for Markov chain Monte Carlo algorithms
- Geometric ergodicity of Metropolis algorithms
- Inference from iterative simulation using multiple sequences
- Polynomial convergence rates of Markov chains
- Practical drift conditions for subgeometric rates of convergence.
- Sufficient burn-in for Gibbs samplers for a hierarchical random effects model.
- Markov chains for exploring posterior distributions. (With discussion)
- Rates of convergence of the Hastings and Metropolis algorithms
- Monte Carlo methods in Bayesian computation
- Estimating the risk of a crop epidemic from coincident spatio-temporal processes
- Polynomial ergodicity of Markov transition kernels.
- Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review
- Fixed-Width Output Analysis for Markov Chain Monte Carlo
- Simulation Output Analysis Using Standardized Time Series
- The Reporting of Computation-Based Results in Statistics
- Convergence of Slice Sampler Markov Chains
- Efficiency and Convergence Properties of Slice Samplers
- Possible biases induced by mcmc convergence diagnostics
- Regeneration in Markov Chain Samplers
- Minorization Conditions and Convergence Rates for Markov Chain Monte Carlo
- Annealing Markov Chain Monte Carlo with Applications to Ancestral Inference
- Geometric Ergodicity of van Dyk and Meng's Algorithm for the Multivariate Student'stModel
- Monte Carlo strategies in scientific computing
- Geometric ergodicity of Metropolis-Hastings algorithms for conditional simulation in generalized linear mixed models