Monte Carlo Methods in Bayesian Computation
Dealing with methods for sampling from posterior distributions and how to compute posterior quantities of interest using Markov chain Monte Carlo (MCMC) samples, this book addresses such topics as improving simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, highest posterior density interval calculations, computation of posterior modes, and posterior computations for proportional hazards models and Dirichlet process models. The authors also discuss model comparisons, including both nested and non-nested models, marginal likelihood methods, ratios of normalizing cons…
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Produktdetails
Weitere Autoren: Ibrahim, Joseph G. / Shao, Qi-Man
- ISBN: 978-1-4612-7074-4
- EAN: 9781461270744
- Produktnummer: 14642560
- Verlag: Springer New York
- Sprache: Englisch
- Erscheinungsjahr: 2012
- Seitenangabe: 404 S.
- Masse: H23.5 cm x B15.5 cm x D2.1 cm 610 g
- Auflage: Softcover reprint of the original 1st ed. 2000
- Abbildungen: Paperback
- Gewicht: 610
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