December 23, 2017

Nils Lid Hjort,Chris Holmes,Peter Müller,Stephen G. Walker's Bayesian Nonparametrics (Cambridge Series in Statistical and PDF

By Nils Lid Hjort,Chris Holmes,Peter Müller,Stephen G. Walker

Bayesian nonparametrics works - theoretically, computationally. the idea presents hugely versatile types whose complexity grows thoroughly with the quantity of knowledge. Computational matters, although difficult, aren't any longer intractable. All that's wanted is an access aspect: this clever e-book is the best consultant to what can look a forbidding panorama. instructional chapters via Ghosal, Lijoi and Prünster, Teh and Jordan, and Dunson increase from idea, to easy versions and hierarchical modeling, to functions and implementation, rather in computing device technological know-how and biostatistics. those are complemented via spouse chapters by way of the editors and Griffin and Quintana, offering extra types, interpreting computational concerns, selecting destiny development parts, and giving hyperlinks to comparable subject matters. This coherent textual content provides prepared entry either to underlying rules and to cutting-edge perform. particular examples are drawn from details retrieval, NLP, desktop imaginative and prescient, computational biology, biostatistics, and bioinformatics.

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Bayesian Nonparametrics (Cambridge Series in Statistical and Probabilistic Mathematics) by Nils Lid Hjort,Chris Holmes,Peter Müller,Stephen G. Walker


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