Description: Bayesian Nonparametrics, Hardcover by Hjort, Nils Lid (EDT); Holmes, Chris (EDT); Muller, Peter (EDT); Walker, Stephen G. (EDT), ISBN 0521513464, ISBN-13 9780521513463, Brand New, Free P&P in the UK "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 Prèunster, 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"--Provided by publisher.
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Book Title: Bayesian Nonparametrics
Number of Pages: 308 Pages
Language: English
Publication Name: Bayesian Nonparametrics
Publisher: Cambridge University Press
Publication Year: 2010
Subject: Mathematics
Item Height: 254 mm
Item Weight: 730 g
Type: Textbook
Author: Stephen G. Walker, Nils Lid Hjort, Peter Muller, Chris Holmes
Series: Cambridge Series in Statistical and Probabilistic Mathematics
Item Width: 178 mm
Format: Hardcover
