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
Edité par
Springer New York, 2000
ISBN 10 : 0387989358
ISBN 13 : 9780387989358
Ancien ou d'occasion
Couverture rigide
Vendeur : Better World Books, Mishawaka, IN, Etats-Unis
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Etat : Good. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages. N° de réf. du vendeur 10847492-6
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Monte Carlo Methods in Bayesian Computation
Edité par
Springer New York, 2000
ISBN 10 : 0387989358
ISBN 13 : 9780387989358
Ancien ou d'occasion
Couverture rigide
Vendeur : Better World Books: West, Reno, NV, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : Good. Used book that is in clean, average condition without any missing pages. N° de réf. du vendeur 2306751-6
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Monte Carlo Methods in Bayesian Computation
Edité par
Springer New York, 2000
ISBN 10 : 0387989358
ISBN 13 : 9780387989358
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
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Gebunden. 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 5913580
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Monte Carlo Methods in Bayesian Computation
Edité par
Springer New York Jan 2000, 2000
ISBN 10 : 0387989358
ISBN 13 : 9780387989358
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book examines advanced Bayesian computational methods. It presents methods for sampling from posterior distributions and discusses how to compute posterior quantities of interest using Markov chain Monte Carlo (MCMC) samples. This book examines each of these issues in detail and heavily focuses on computing various posterior quantities of interest from a given MCMC sample. Several topics are addressed, including techniques for MCMC sampling, Monte Carlo methods for estimation of posterior quantities, 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 computions involving 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 predictiveand latent residual approaches. The book presents an equal mixture of theory and applications involving real data. The book is intended as a graduate textbook or a reference book for a one semester course at the advanced masters or Ph.D. level. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners. Ming-Hui Chen is Associate Professor of Mathematical Sciences at Worcester Polytechnic Institute, Qu-Man Shao is Assistant Professor of Mathematics at the University of Oregon. Joseph G. Ibrahim is Associate Professor of Biostatistics at the Harvard School of Public Health and Dana-Farber Cancer Institute. 406 pp. Englisch. N° de réf. du vendeur 9780387989358
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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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Etat : New. In. N° de réf. du vendeur ria9780387989358_new
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Monte Carlo Methods in Bayesian Computation
Edité par
Springer New York, Springer US Jan 2000, 2000
ISBN 10 : 0387989358
ISBN 13 : 9780387989358
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 406 pp. Englisch. N° de réf. du vendeur 9780387989358
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Monte Carlo Methods in Bayesian Computation
Edité par
Springer New York, Springer US, 2000
ISBN 10 : 0387989358
ISBN 13 : 9780387989358
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9780387989358
Quantité disponible : 1 disponible(s)
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Monte Carlo Methods in Bayesian Computation
Edité par
Springer-Verlag New York Inc., 2000
ISBN 10 : 0387989358
ISBN 13 : 9780387989358
Neuf
Couverture rigide
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Hardback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 777. N° de réf. du vendeur C9780387989358
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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. 408. N° de réf. du vendeur 26295839
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Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics)
Edité par
Springer, 2001
ISBN 10 : 0387989358
ISBN 13 : 9780387989358
Ancien ou d'occasion
Couverture rigide
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Hardcover. Etat : Like New. Like New. book. N° de réf. du vendeur ERICA78703879893586
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