Bayesian Analysis of Stochastic Process Models - Wiley Series in Probability and Statistics

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.

ISBN:	9780470744536
Publisher:	Wiley
Imprint:	John Wiley & Sons, Inc.
Published date:	30 Mar 2012
DEWEY:	519.542
DEWEY edition:	23
Language:	English
Number of pages:	290
Weight:	588g
Height:	159mm
Width:	235mm
Spine width:	22mm

Write a review

Your Name:

Your Review: Note: HTML is not translated!

Rating: Bad           Good

Enter the code in the box below: