Bayesian Analysis of Stochastic Process Models by David Insua

Bayesian Analysis of Stochastic Process Models by David Insua

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.

Fabrizio Ruggeri, Research Director, CNR IMATI, Milano, Italy.

Michael P. Wiper, Associate Professor in Statistics, Department of Statistics, Universidad Carlos III de Madrid, Spain.

David Rios Insua, Professor of Statistics and Operations Research, Department of Statistics and Operations Research, Universidad Rey Juan Carlos, Spain.

SKU	Unavailable
ISBN 13	9780470744536
ISBN 10	0470744537
Title	Bayesian Analysis of Stochastic Process Models
Author	David Insua
Series	Wiley Series In Probability And Statistics
Condition	Unavailable
Publisher	John Wiley & Sons Inc
Year published	2012-03-30
Number of pages	316
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.