Bayesian analysis of stochastic process models

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Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified treatment of Bayesian analysis of models based on stochastic processes, covering the main classes of stochastic processing including modeling, computational, inference, forecasting, decision making and important applied models.

Key features:Explores Bayesian analysis of models based on stochastic processes, providing a unified treatment. Provides a thorough introduction for research students. Computational tools to deal with complex problems are illustrated along with real life case studies Looks at inference, prediction and decision making.

Researchers, graduate and advanced undergraduate students interested in stochastic processes in fields such as statistics, operations research (OR), engineering, finance, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practitioners of OR, stochastic modelling and applied statistics will also find this book useful.

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Taal: en

Bindwijze: E-book

Oorspronkelijke releasedatum: 02 april 2012

Aantal pagina's: 320

Ebook Formaat: Adobe ePub

Illustraties: Nee

Hoofdauteur: David Insua

Tweede Auteur: Fabrizio Ruggeri

Co Auteur: Mike Wiper

Hoofduitgeverij: John Wiley & Sons

Lees dit ebook op: Android (smartphone en tablet)

Lees dit ebook op: Kobo e-reader

Lees dit ebook op: Desktop (Mac en Windows)

Lees dit ebook op: iOS (smartphone en tablet)

Lees dit ebook op: Windows (smartphone en tablet)

Editie: 1

Extra groot lettertype: Nee

Studieboek: Nee

EAN: 9781118304037

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