| Bayesian Theory and Applications Contributor(s): Damien, Paul (Editor), Dellaportas, Petros (Editor), Polson, Nicholas G. (Editor) |
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ISBN: 0198739079 ISBN-13: 9780198739074 Publisher: Oxford University Press, USA OUR PRICE: $85.50 Product Type: Paperback - Other Formats Published: April 2015 |
| Additional Information |
| BISAC Categories: - Mathematics | Probability & Statistics - Bayesian Analysis |
| Dewey: 519.542 |
| Physical Information: 1.44" H x 6.14" W x 9.21" (2.18 lbs) 718 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and developments, and who may be looking for ideas that could spawn new research. Hence, the audience for this unique book would likely include academicians/practitioners, and could likely be required reading for undergraduate and graduate students in statistics, medicine, engineering, scientific computation, business, psychology, bio-informatics, computational physics, graphical models, neural networks, geosciences, and public policy. The book honours the contributions of Sir Adrian F. M. Smith, one of the seminal Bayesian researchers, with his papers on hierarchical models, sequential Monte Carlo, and Markov chain Monte Carlo and his mentoring of numerous graduate students -- the chapters are authored by prominent statisticians influenced by him. Bayesian Theory and Applications should serve the dual purpose of a reference book, and a textbook in Bayesian Statistics. |