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

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

Bayesian nonparametrics works - theoretically, computationally. the speculation presents hugely versatile versions whose complexity grows adequately with the volume of knowledge. Computational matters, even though hard, are not any longer intractable. All that's wanted is an access aspect: this clever publication is the best consultant to what can look a forbidding panorama. educational chapters through Ghosal, Lijoi and Prünster, Teh and Jordan, and Dunson strengthen from concept, to easy versions and hierarchical modeling, to functions and implementation, really in computing device technological know-how and biostatistics. those are complemented by means of significant other chapters by way of the editors and Griffin and Quintana, delivering extra types, reading computational concerns, making a choice on destiny progress parts, and giving hyperlinks to similar issues. This coherent textual content supplies prepared entry either to underlying rules and to state of the art perform. particular examples are drawn from info retrieval, NLP, desktop imaginative and prescient, computational biology, biostatistics, and bioinformatics.

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