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- 000 02974cam a2200325 a 4500
- 008 090911s2010 enka b 001 0 eng
- 020 __ |a 9780521513463 (hardback)
- 020 __ |a 0521513464 (hardback)
- 040 __ |a DLC |c DLC |d YDX |d YDXCP |d BWX |d CDX |d UtOrBLW
- 050 00 |a QA278.8 |b .B39 2010
- 245 00 |a Bayesian nonparametrics / |c edited by Nils Lid Hjort ... [et al.]
- 260 __ |a Cambridge, UK ; |a New York : |b Cambridge University Press, |c 2010.
- 300 __ |a viii, 299 p. : |b ill. ; |c 27 cm.
- 490 1_ |a Cambridge series in statistical and probabilistic mathematics ; |v 28.
- 504 __ |a Includes bibliographical references and indexes.
- 520 __ |a "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 Prunster, 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.
- 505 8_ |a Machine generated contents note: An invitation to Bayesian nonparametrics Nils Lid Hjort, Chris Holmes, Peter Muller 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 Prunster; 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 Muller and Fernando Quintana; Author index; Subject index.
- 650 _0 |a Nonparametric statistics.
- 650 _0 |a Bayesian statistical decision theory.
- 700 1_ |a Hjort, Nils Lid.
- 830 _0 |a Cambridge series on statistical and probabilistic mathematics ; |v 28.