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.
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.
Table of Contents
- Title Page
Part One: Basic Concepts and Tools
- 1: Stochastic processes
- 2: Bayesian analysis
Part Two: Models
- 3: Discrete time Markov chains and extensions
- 4: Continuous time Markov chains and extensions
- 5: Poisson processes and extensions
- 6: Continuous time continuous space processes
Part Three: Applications
7: Queueing analysis
- 7.1 Introduction
- 7.2 Basic queueing concepts
- 7.3 The main queueing models
- 7.4 Bayesian inference for queueing systems
- 7.5 Bayesian inference for the system
- 7.6 Inference for non-Markovian systems
- 7.7 Decision problems in queueing systems
- 7.8 Case study: Optimal number of beds in a hospital
- 7.9 Discussion
- 8: Reliability
- 9: Discrete event simulation
- 10: Risk analysis
- 7: Queueing analysis
- Appendix A: Main distributions
- Appendix B: Generating functions and the Laplace–Stieltjes transform
- Series List
- Title: Bayesian Analysis of Stochastic Process Models
- Release date: May 2012
- Publisher(s): Wiley
- ISBN: 9781118304037