Reversible algorithm of simulating multivariate densities with multi-hump

DOI10.1007/BF02878717zbMath0997.60076OpenAlexW1567047693MaRDI QIDQ1609649

Gong Guanglu, Jun Xie, Min-ping Qian

Publication date: 15 August 2002

Published in: Science in China. Series A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02878717

zbMATH Keywords

simulationMarkov chain Monte CarloGibbs samplerreversible Markov chainmulti-hump

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10)

Cites Work

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• Geometric bounds for eigenvalues of Markov chains
• Convergence of some partially parallel Gibbs samplers with annealing
• Importance sampling for Gibbs random fields
• Simple conditions for the convergence of the Gibbs sampler and Metropolis-Hastings algorithms
• On the rate of convergence of the Metropolis algorithm and Gibbs sampler by geometric bounds
• Inference from iterative simulation using multiple sequences
• Markov chains for exploring posterior distributions. (With discussion)
• Rates of convergence for Gibbs sampling for variance component models
• Metastability of exponentially perturbed Markov chains
• Hierarchical Bayesian Analysis of Changepoint Problems

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