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Bayesian Nonparametrics (Cambridge Series in Statistical and Probabilistic
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Bayesian Nonparametrics (Cambridge Series in Statistical and Probabilistic Mathematics) Hardcover - 2010

by Hjort, Nils Lid [Editor]; Holmes, Chris [Editor]; Müller, Peter [Editor]; Walker, Stephen G. [Editor];


From the publisher

Bayesian nonparametrics works - theoretically, computationally. The theory provides highly flexible models whose complexity grows appropriately with the amount of data. Computational issues, though challenging, are no longer intractable. All that is needed is an entry point: this intelligent book is the perfect guide to what can seem a forbidding landscape. Tutorial chapters by Ghosal, Lijoi and Prnster, Teh and Jordan, and Dunson advance from theory, to basic models and hierarchical modeling, to applications and implementation, particularly in computer science and biostatistics. These are complemented by companion chapters by the editors and Griffin and Quintana, providing additional models, examining computational issues, identifying future growth areas, and giving links to related topics. This coherent text gives ready access both to underlying principles and to state-of-the-art practice. Specific examples are drawn from information retrieval, NLP, machine vision, computational biology, biostatistics, and bioinformatics.

Details

  • Title Bayesian Nonparametrics (Cambridge Series in Statistical and Probabilistic Mathematics)
  • Author Hjort, Nils Lid [Editor]; Holmes, Chris [Editor]; Müller, Peter [Editor]; Walker, Stephen G. [Editor];
  • Binding Hardcover
  • Edition Hardback
  • Pages 308
  • Language ENG
  • Publisher Cambridge University Press
  • Date 2010-04
  • ISBN 9780521513463

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Bayesian Nonparametrics (Cambridge Series in Statistical and Probabilistic Mathematics)
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Bayesian Nonparametrics (Cambridge Series in Statistical and Probabilistic Mathematics)

by Editor-Nils Lid Hjort; Editor-Chris Holmes; Editor-Peter Müller; Editor-Stephen G. Walker

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Cambridge, New York, Melbourne: Cambridge University Press, 2009. First Edition. Hardcover. Larger Octavo; G; blue spine with white and pink text; first edition; no jacket; cloth front and rear shows modest wear; noticeable wear to corners, as is; sturdy boards; text block exterior edges have slight wear; mild defect to gutter to title page; partially loosened title page; interior clean; illustrated; minor crease to rear endpaper to tail fore corner; pp 299. 1346796. FP New Rockville Stock.
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Hardback. New. Bayesian nonparametrics works. Applications are appearing in such disciplines as information retrieval, NLP, machine vision, computational biology, cognitive science, signal processing. In this coherent introduction, the editors weave together tutorial chapters by Ghosal, Lijoi and Prunster, Dunson, and Teh and Jordan, giving direct access to these exciting ideas and methods.
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by Hjort, Nils Lid [Editor]; Holmes, Chris [Editor]; Müller, Peter [Editor]; Walker, Stephen G. [Editor];

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