Book description
This book provides a pedagogical examination of the way in which stochastic models are encountered in applied sciences and techniques such as physics, engineering, biology and genetics, economics and social sciences. It covers Markov and semi-Markov models, as well as their particular cases: Poisson, renewal processes, branching processes, Ehrenfest models, genetic models, optimal stopping, reliability, reservoir theory, storage models, and queuing systems. Given this comprehensive treatment of the subject, students and researchers in applied sciences, as well as anyone looking for an introduction to stochastic models, will find this title of invaluable use.
Table of contents
- Cover
- Dedication
- Title Page
- Copyright
- Preface
- Chapter 1: Introduction to Stochastic Processes
- Chapter 2: Simple Stochastic Models
- Chapter 3: Elements of Markov Modeling
-
Chapter 4: Renewal Models
- 4.1. Fundamental concepts and examples
- 4.2. Waiting times
- 4.3. Modified renewal processes
- 4.4. Replacement models
- 4.5. Renewal reward processes
- 4.6. The risk problem of an insurance company
- 4.7. Counter models
- 4.8. Alternating renewal processes
- 4.9. Superposition of renewal processes
- 4.10. Regenerative processes
- Chapter 5: Semi-Markov Models
- Chapter 6: Branching Models
- Chapter 7: Optimal Stopping Models
- Bibliography
- Notation
- Index
Product information
- Title: Introduction to Stochastic Models
- Author(s):
- Release date: April 2010
- Publisher(s): Wiley
- ISBN: 9781848210578
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