Prior Processes and Their Applications

Idioma: inglés

Editorial: Springer, Springer Apr 2018, 2018

3319813706 / 9783319813707

Serie: Libro 142 de 160 - Springer Series in Statistics

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This item is printed on demand - Print on Demand Titel. Neuware -This book presents a systematic and comprehensive treatment of various prior processes that have been developed over the past four decades for dealing with Bayesian approach to solving selected nonparametric inference problems. This revised edition has been substantially expanded to reflect the current interest in this area. After an overview of different prior processes, it examines the now pre-eminent Dirichlet process and its variants including hierarchical processes, then addresses new processes such as dependent Dirichlet, local Dirichlet, time-varying and spatial processes, all of which exploit the countable mixture representation of the Dirichlet process. It subsequently discusses various neutral to right type processes, including gamma and extended gamma, beta and beta-Stacy processes, and then describes the Chinese Restaurant, Indian Buffet and infinite gamma-Poisson processes, which prove to be very useful in areas such as machine learning, information retrieval and featural modeling. Tailfree and Polya tree and their extensions form a separate chapter, while the last two chapters present the Bayesian solutions to certain estimation problems pertaining to the distribution function and its functional based on complete data as well as right censored data. Because of the conjugacy property of some of these processes, most solutions are presented in closed form.However, the current interest in modeling and treating large-scale and complex data also poses a problem ¿ the posterior distribution, which is essential to Bayesian analysis, is invariably not in a closed form, making it necessary to resort to simulation. Accordingly, the book also introduces several computational procedures, such as the Gibbs sampler, Blocked Gibbs sampler and slice sampling, highlighting essential steps of algorithms while discussing specific models. In addition, it features crucial steps of proofs and derivations, explains the relationships between different processes and provides further clarifications to promote a deeper understanding. Lastly, it includes a comprehensive list of references, equipping readers to explore further on their own.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 348 pp. Englisch.

N° de ref. del artículo 9783319813707

Título
Prior Processes and Their Applications
Autor
Eswar G. Phadia
Editorial
Springer, Springer Apr 2018
Año de publicación
2018
Estado
Neu
Encuadernación
Taschenbuch
Idioma
inglés
ISBN 10
3319813706
ISBN 13
9783319813707
Peso del artículo
528 gramos
Dimensiones
235x155x19 mm
Serie
Libro 142 de 160: Springer Series in Statistics

buchversandmimpf2000

Emtmannsberg, BAYE, Alemania

Vendedor de 5 estrellas

Vendedor de AbeBooks desde 23 de enero de 2017

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