01808cam a2200229 a 4500 090911s2010 enka b 001 0 eng 9780521513463 0521513464 SDU QA278.8 B357 2010 Bayesian nonparametrics / edited by Nils Lid Hjort ... [et al.]. Cambridge, UK ; New York : Cambridge University Press, 2010. 299 p. : ill. Cambridge series in statistical and probabilistic mathematics ; 28 HKBU Library "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 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. Nonparametric statistics. 114573 Bayesian statistical decision theory. Hjort, Nils Lid. 193290 = C.1 SDU GBE lcc 104017 104017 0 0 lcc 0 QA02788 B357 02010 0 CGB 284069 SDU SDU GEN3 2025-10-07 2 0 QA278.8 B357 2010 1000385016 2025-10-07 00:00:00 C.1 2025-10-07 GBE