Bayesian nonparametrics / / edited by Nils Lid Hjort [and others] [[electronic resource]]

• Record Nr.: UNINA9910791805303321
• Pubbl/distr/stampa: Cambridge : , : Cambridge University Press, , 2010
• ISBN: 1-107-20607-3; 1-283-06796-X; 9786613067968; 0-511-67417-1; 0-511-67536-4; 0-511-67211-X; 0-511-80247-1; 0-511-67083-4; 0-511-67338-8
• Descrizione fisica: 1 online resource (viii, 299 pages) : digital, PDF file(s)
• Collana: Cambridge series on statistical and probabilistic mathematics ; ; 28
• Disciplina: 519.5/42
• Soggetti: Nonparametric statistics; Bayesian statistical decision theory
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Title from publisher's bibliographic system (viewed on 05 Oct 2015).
• Nota di bibliografia: Includes bibliographical references and indexes.
• Nota di contenuto: 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.
• Sommario/riassunto: 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.

The Devil Doctor

• Record Nr.: UNINA9910163396603321
• Autore: Rohmer Sax
• Pubbl/distr/stampa: Munchen : , : Liese, Andreas. OUTSIDE THE BOX, , 1994; ©1994
• ISBN: 3-95676-706-3
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (230 p.)
• Collana: Classics to Go Series
• Disciplina: FIC
• Soggetti: Detective and mystery stories; Criminals in literature
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Sommario/riassunto: This is the second volume in Sax Rohmer's Fu Manchu series, and the first full novel; it may also be found alternatively titled as "The Return of Dr. Fu Manchu." (The first volume, if you wish to start at the beginning, is a collection of short stories, and can be found either titled ; "The Mystery of Dr. Fu Manchu" or "The Insidious Dr. Fu Manchu"). "The Devil Doctor" was written by Arthur Henry Sarsfield Ward, known better under his pseudonym, Sax Rohmer. Sax Rohmer was a prolific eng novelist. He is best remembered for his series of novels featuring the master criminal Dr. Fu Manchu. (Excerpt from Wikipedia)