Bayesian Analysis of Stochastic Process Models by David Insua
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Author: David Insua
Number of Pages: 332 pages
Published Date: 29 May 2012
Publisher: John Wiley and Sons Ltd
Publication Country: Hoboken, United States
Language: English
Type: PDF
ISBN: 9780470744536
File size: 27 Mb
Download Link: 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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