Introduction to ``On the use of Markov chain Monte Carlo methods for the sampling of mixture models by R. Douc, F. Maire, J. Olsson
DOI10.1007/S11222-014-9532-7zbMath1333.62045OpenAlexW1995728323MaRDI QIDQ5963555
Publication date: 22 February 2016
Published in: Statistics and Computing (Search for Journal in Brave)
Full work available at URL: http://doc.rero.ch/record/331150/files/11222_2014_Article_9532.pdf
Multivariate distribution of statistics (62H10) Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Sampling theory, sample surveys (62D05) Markov processes: estimation; hidden Markov models (62M05) Numerical analysis or methods applied to Markov chains (65C40)
Cites Work
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- Comparison of asymptotic variances of inhomogeneous Markov chains with application to Markov chain Monte Carlo methods
- Bayesian analysis of mixture models with an unknown number of components\,--\,an alternative to reversible jump methods.
- Analysis of a nonreversible Markov chain sampler.
- Marginal Likelihood from the Gibbs Output
- Marginal Likelihood From the Metropolis–Hastings Output
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