On the convergence rate of random permutation sampler and ECR algorithm in missing data models

DOI10.1007/s11009-011-9238-7zbMath1277.65007OpenAlexW1994336023MaRDI QIDQ352882

Panagiotis Papastamoulis, George Iliopoulos

Publication date: 5 July 2013

Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11009-011-9238-7

zbMATH Keywords

Markov chain Monte Carlo methodlatent variableequivalence classes representatives algorithmlabel switchingrandom permutation sampler

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Discrete-time Markov processes on general state spaces (60J05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (4)

An alternative class of models to position social network groups in latent spaces ⋮ Handling the Label Switching Problem in Latent Class Models Via the ECR Algorithm ⋮ Clustering multivariate data using factor analytic Bayesian mixtures with an unknown number of components ⋮ Overfitting Bayesian mixtures of factor analyzers with an unknown number of components

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• Computational and Inferential Difficulties with Mixture Posterior Distributions
• Markov chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models
• Bayesian Inference in Hidden Markov Models Through the Reversible Jump Markov Chain Monte Carlo Method

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