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Bayesian nonparametrics

Author: Nils Lid Hjort
Publisher: Cambridge, UK ; New York : Cambridge University Press, 2010.
Series: Cambridge series on statistical and probabilistic mathematics, 28.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
"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  Read more...
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Genre/Form: Electronic books
Electronic book
Additional Physical Format: Print version:
Bayesian nonparametrics.
Cambridge, UK ; New York : Cambridge University Press, 2010
(DLC) 2009037744
(OCoLC)441945339
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Nils Lid Hjort
ISBN: 9780511675362 0511675364 9780511802478 0511802471 9780511673382 0511673388
OCLC Number: 719370012
Description: 1 online resource (viii, 299 pages) : illustrations.
Contents: An invitation to Bayesian nonparametrics / Nils Lid Hjort, Chris Holmes, Peter Müller and Stephen G. Walker --
1. Bayesian nonparametric methods: motivation and ideas / Stephen G. Walker --
2. The Dirichlet process, related priors, and posterior asymptotics / Subhashis Ghosal --
3. Models beyond the Dirichlet process / Antonio Lijoi and Igor Prünster --
4. Further models and applications / Nils Lid Hjort --
5. Hierarchical Bayesian nonparametric models with applications / Yee Whye Teh and Michael I. Jordan --
6. Computational issues arising in Bayesian nonparametric hierarchical models / Jim Griffin and Chris Holmes --
7. Nonparametric Bayes applications to biostatistics / David B. Dunson --
8. More nonparametric Bayesian models for biostatistics / Peter Müller and Fernando Quintana --
Author index --
Subject index.
Series Title: Cambridge series on statistical and probabilistic mathematics, 28.
Responsibility: edited by Nils Lid Hjort [and others].

Abstract:

Bayesian nonparametrics works. Applications are appearing in such disciplines as information retrieval, NLP, machine vision, computational biology, cognitive science, signal processing. In this  Read more...

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"The book looks like it will be useful to a wide range of researchers. I like that there is a lot of discussion of the models themselves as well as the computation. The book, especially in the early Read more...

 
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