Fundamentals of Nonparametric Bayesian Inference
Language: English
Published by Cambridge University Press, 2017
Series: Book 49 of 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 154.67
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - Explosive growth in computing power has made Bayesian methods for infinite-dimensional models - Bayesian nonparametrics - a nearly universal framework for inference, finding practical use in numerous subject areas. Written by leading researchers, this authoritative text draws on theoretical advances of the past twenty years to synthesize all aspects of Bayesian nonparametrics, from prior construction to computation and large sample behavior of posteriors. Because understanding the behavior of posteriors is critical to selecting priors that work, the large sample theory is developed systematically, illustrated by various examples of model and prior combinations. Precise sufficient conditions are given, with complete proofs, that ensure desirable posterior properties and behavior. Each chapter ends with historical notes and numerous exercises to deepen and consolidate the reader's understanding, making the book valuable for both graduate students and researchers in statistics and machine learning, as well as in application areas such as econometrics and biostatistics.…
Seller Inventory # 9780521878265
- Title
- Fundamentals of Nonparametric Bayesian Inference
- Author
- Aad van der Vaart
- Publisher
- Cambridge University Press
- Publication year
- 2017
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 0521878268
- ISBN 13
- 9780521878265
- Item weight
- 1,438 grams
- Dimensions
- 260x183x40 mm
- Series
- Book 49 of 64: Cambridge Series in Statistical and Probabilistic Mathematics
"Synopsis" may belong to another edition of this title.
About the Author
Aad van der Vaart is Professor of Stochastics at Universiteit Leiden. He is the author of several books and lecture notes in topics ranging from asymptotic statistics to genetics and finance, and many research papers in statistics and its applications. He is a member of the Royal Netherlands Academy of Arts and Sciences, former president of Netherlands Statistical Society, and a recipient of the Spinoza Prize of the Netherlands Organisation of Scientific Research.
"About the title" may belong to another edition of this title.
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