Login

Insua, David

Bayesian Analysis of Stochastic Process Models

Insua, David - Bayesian Analysis of Stochastic Process Models, ebook

DRM Restrictions

Printing96 pages with an additional page accrued every 8 hours, capped at 96 pages
Copy to clipboard5 excerpts

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.

Keywords: Engineering Statistics, Experimental Design, Engineering Statistics, Experimental Design

Author(s)
 
 
Publisher
John Wiley and Sons, Inc.
Publication year
2012
Language
en
Edition
1
Series
Wiley Series in Probability and Statistics
Page amount
320 pages
Category
Natural Sciences
Format
Ebook
eISBN (ePUB)
9781118304037
Printed ISBN
9780470744536

Similar titles