Détails de l’annonce
Titre: Bayesian Nonparametrics Condition: Neuf Auteur: Stephen G. Walker Contributeur: Nils Lid Hjort (Edited by), Chris Holmes (Edited by), Peter Müller (Edited by), Stephen G. Walker (Edited by) Format: Relié EAN: 9780521513463 ISBN: 9780521513463 Publisher: Cambridge University Press Genre: Science Nature & Math Date de publication: 2010-04-12 Description: 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 Prünster, 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. Sujet: Anglais Pays/Région de fabrication: GB Item Height: 254 Item Length: 178.00 Item Width: 23.00 Poids: 730g Série: Cambridge Series in Statistical and Probabilistic Mathematics Année de publication: 2010
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