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Fundamentals of Nonparametric Bayesian Inference: 44 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44) - Hardcover
Synopsis
Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.
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About the Authors
Subhashis Ghosal is Professor of Statistics at North Carolina State University. His primary research interest is in the theory, methodology and various applications of Bayesian nonparametrics. He has edited one book, written nearly one hundred papers, and serves on the editorial boards of the Annals of Statistics, Bernoulli, and the Electronic Journal of Statistics. He is an elected fellow of the Institute of Mathematical Statistics, the American Statistical Association and the International Society for Bayesian Analysis.
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.
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
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Cambridge University Press, 2017
ISBN 10: 0521878268
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Fundamentals of Nonparametric Bayesian Inference
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Fundamentals of Nonparametric Bayesian Inference
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
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ISBN 13: 9780521878265
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics)
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Fundamentals of Nonparametric Bayesian Inference Cambridge Series in Statistical and Probabilistic Mathematics, Band 44
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Condition: Gut. 646 Seiten Zustand: Einband etwas berieben, Ecken etwas bestoßen, Schnitt etwas abgegriffen // Text in Englisch. Unser Produktfoto entspricht dem hier angebotenen Artikel. Alle Artikel befinden sich stets in gebrauchsfähigem Zustand. Gebrauchte Bücher sparen Ressourcen gegenüber Neuware und schonen die Umwelt. /// Versand gratis Innerhalb Deutschlands - Portofrei in Deutschland- ab 20 Euro mit Post ID - Gratisversand deutschlandweit innerhalb Deutschlands gratis Versand -Versandkostenfrei innerhalb Deutschlands /// Sprache: Englisch Gewicht in Gramm: 1440 26,0 x 18,5 cm, Pappband/Hardcover. Seller Inventory # 354201
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Fundamentals of Nonparametric Bayesian Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 44)
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ISBN 10: 0521878268
ISBN 13: 9780521878265
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Fundamentals of Nonparametric Bayesian Inference (Hardcover)
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ISBN 10: 0521878268
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Hardcover. Condition: new. Hardcover. 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. Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and biostatistics. Appendices with prerequisites and numerous exercises support its use for graduate courses. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780521878265
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Fundamentals of Nonparametric Bayesian Inference
Published by
Cambridge University Press, 2017
ISBN 10: 0521878268
ISBN 13: 9780521878265
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