Introduction to Stochastic Models

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.Content: Chapter 1 Introduction to Stochastic Processes (pages 1–35): Chapter 2 Simple Stochastic Models (pages 37–60): Chapter 3 Elements of Markov Modeling (pages 61–147): Chapter 4 Renewal Models (pages 149–188): Chapter 5 Semi?Markov Models (pages 189–225): Chapter 6 Branching Models (pages 227–313): Chapter 7 Optimal Stopping Models (pages 315–341):