Articles liés à Monte Carlo Methods in Bayesian Computation
Synopsis
Bayesian statistics is one of the active research areas in statistics. This book provides the theoretical background behind the most important recent development, Markov chain Monte Carlos methods.
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Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
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Etat : New. N° de réf. du vendeur ABLIING23Mar2716030028518
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Monte Carlo Methods in Bayesian Computation (Paperback)
Edité par
Springer-Verlag New York Inc., New York, NY, 2012
ISBN 10 : 146127074X
ISBN 13 : 9781461270744
Neuf
Paperback
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
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Paperback. Etat : new. Paperback. Sampling from the posterior distribution and computing posterior quanti ties of interest using Markov chain Monte Carlo (MCMC) samples are two major challenges involved in advanced Bayesian computation. This book examines each of these issues in detail and focuses heavily on comput ing various posterior quantities of interest from a given MCMC sample. Several topics are addressed, including techniques for MCMC sampling, Monte Carlo (MC) methods for estimation of posterior summaries, improv ing simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, Highest Poste rior Density (HPD) interval calculations, computation of posterior modes, and posterior computations for proportional hazards models and Dirichlet process models. Also extensive discussion is given for computations in volving model comparisons, including both nested and nonnested models. Marginal likelihood methods, ratios of normalizing constants, Bayes fac tors, the Savage-Dickey density ratio, Stochastic Search Variable Selection (SSVS), Bayesian Model Averaging (BMA), the reverse jump algorithm, and model adequacy using predictive and latent residual approaches are also discussed. The book presents an equal mixture of theory and real applications. 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 constants, Bayes factors, the Savage-Dickey density ratio, Stochastic Search Variable Selection, Bayesian Model Averaging, the reverse jump algorithm, and model adequacy using predictive and latent residual approaches. The book presents an equal mixture of theory and applications involving real data, and is intended as a graduate textbook or a reference book for a one-semester course at the advanced masters or Ph.D. level. It will also serve as a useful reference for applied or theoretical researchers as well as practitioners. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781461270744
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Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Monte Carlo Methods in Bayesian Computation
Edité par
Springer New York Okt 2012, 2012
ISBN 10 : 146127074X
ISBN 13 : 9781461270744
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 constants, Bayes factors, the Savage-Dickey density ratio, Stochastic Search Variable Selection, Bayesian Model Averaging, the reverse jump algorithm, and model adequacy using predictive and latent residual approaches. The book presents an equal mixture of theory and applications involving real data, and is intended as a graduate textbook or a reference book for a one-semester course at the advanced masters or Ph.D. level. It will also serve as a useful reference for applied or theoretical researchers as well as practitioners. 404 pp. Englisch. N° de réf. du vendeur 9781461270744
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Monte Carlo Methods in Bayesian Computation
Edité par
Springer New York, 2012
ISBN 10 : 146127074X
ISBN 13 : 9781461270744
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 es. N° de réf. du vendeur 4189705
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Monte Carlo Methods in Bayesian Computation
Vendeur : Books Puddle, New York, NY, Etats-Unis
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Etat : New. pp. 406. N° de réf. du vendeur 2658570361
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Monte Carlo Methods in Bayesian Computation
Edité par
Springer-Verlag New York Inc., 2012
ISBN 10 : 146127074X
ISBN 13 : 9781461270744
Neuf
Paperback / softback
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 598. N° de réf. du vendeur C9781461270744
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Monte Carlo Methods in Bayesian Computation
impression à la demandeVendeur : Majestic Books, Hounslow, Royaume-Uni
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Etat : New. Print on Demand pp. 406 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam. N° de réf. du vendeur 50989478
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Monte Carlo Methods in Bayesian Computation
impression à la demandeVendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Etat : New. PRINT ON DEMAND pp. 406. N° de réf. du vendeur 1858570355
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Monte Carlo Methods in Bayesian Computation
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Taschenbuch. Etat : Neu. Monte Carlo Methods in Bayesian Computation | Ming-Hui Chen (u. a.) | Taschenbuch | xiii | Englisch | 2012 | Springer | EAN 9781461270744 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 106014054
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