This book is a contemporary introduction to theory, methods and computation in Bayesian Analysis. It focuses on topics that have stood the test of time and emerging areas such as reference priors, objective Bayes testing, Bayesian model selection and wavelets. No other such book is available in the market.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are developed to a level where real-life data can be analyzed using the current techniques of statistical computing. Advances in both low-dimensional and high-dimensional problems are covered, as well as important topics such as empirical Bayes and hierarchical Bayes methods and Markov chain Monte Carlo (MCMC) techniques. Many topics are at the cutting edge of statistical research. Solutions to common inference problems appear throughout the text along with discussion of what prior to choose. There is a discussion of elicitation of a subjective prior as well as the motivation, applicability, and limitations of objective priors. By way of important applications the book presents microarrays, nonparametric regression via wavelets as well as DMA mixtures of normals, and spatial analysis with illustrations using simulated and real data. Theoretical topics at the cutting edge include high-dimensional model selection and Intrinsic Bayes Factors, which the authors have successfully applied to geological mapping. The style is informal but clear. Asymptotics is used to supplement simulation or understand some aspects of the posterior.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Three Hegemons Books, Brooklyn, NY, Etats-Unis
hardcover. Etat : Very Good. Previous owner's name inside. Sticker on back. No marks in text. N° de réf. du vendeur B2-0924202504
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Vendeur : ThriftBooks-Atlanta, AUSTELL, GA, Etats-Unis
Hardcover. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. N° de réf. du vendeur G0387400842I4N00
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Vendeur : Book Alley, Pasadena, CA, Etats-Unis
hardcover. Etat : Good. Former library book, still has stickers. Used with wear, stamp to textblock and first page. Edgewear and some soiling to textblock, bumping/wear to corners but is still in solid reading condition. N° de réf. du vendeur mon0000722202
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Vendeur : BennettBooksLtd, Los Angeles, CA, Etats-Unis
hardcover. Etat : New. In shrink wrap. Looks like an interesting title! N° de réf. du vendeur Q-0387400842
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 4389081-n
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Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
Hardback. Etat : New. This book is a contemporary introduction to theory, methods and computation in Bayesian Analysis. It focuses on topics that have stood the test of time and emerging areas such as reference priors, objective Bayes testing, Bayesian model selection and wavelets. No other such book is available in the market. N° de réf. du vendeur LU-9780387400846
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 4389081-n
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are dev. N° de réf. du vendeur 5910276
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Though there are many recent additions to graduate-level introductory books on Bayesian analysis, none has quite our blend of theory, methods, and ap plications. We believe a beginning graduate student taking a Bayesian course or just trying to find out what it means to be a Bayesian ought to have some familiarity with all three aspects. More specialization can come later. Each of us has taught a course like this at Indian Statistical Institute or Purdue. In fact, at least partly, the book grew out of those courses. We would also like to refer to the review (Ghosh and Samanta (2002b)) that first made us think of writing a book. The book contains somewhat more material than can be covered in a single semester. We have done this intentionally, so that an instructor has some choice as to what to cover as well as which of the three aspects to emphasize. Such a choice is essential for the instructor. The topics include several results or methods that have not appeared in a graduate text before. In fact, the book can be used also as a second course in Bayesian analysis if the instructor supplies more details. Chapter 1 provides a quick review of classical statistical inference. Some knowledge of this is assumed when we compare different paradigms. Following this, an introduction to Bayesian inference is given in Chapter 2 emphasizing the need for the Bayesian approach to statistics. 372 pp. Englisch. N° de réf. du vendeur 9780387400846
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Vendeur : preigu, Osnabrück, Allemagne
Buch. Etat : Neu. An Introduction to Bayesian Analysis | Theory and Methods | Jayanta K. Ghosh (u. a.) | Buch | Springer Texts in Statistics | xiii | Englisch | 2006 | Humana | EAN 9780387400846 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 102211975
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