ABSTRACT

Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments, where processes evolve over time. The text begins with a review of relevant fundamental probability. It then covers gambling problems, random walks, and Markov chains. The authors go on to discuss random processes continuous in time, including Poisson, birth and death processes, and general population models, and present an extended discussion on the analysis of associated stationary processes in queues.

The book also explores reliability and other random processes, such as branching, martingales, and simple epidemics. A new chapter describing Brownian motion, where the outcomes are continuously observed over continuous time, is included. Further applications, worked examples and problems, and biographical details have been added to this edition. Much of the text has been reworked. The appendix contains key results in probability for reference.

This concise, updated book makes the material accessible, highlighting simple applications and examples. A solutions manual with fully worked answers of all end-of-chapter problems, and Mathematica® and R programs illustrating many processes discussed in the book, can be downloaded from crcpress.com.

chapter 1|31 pages

Some Background on Probability

chapter 2|16 pages

Some Gambling Problems

chapter 3|15 pages

Random Walks

chapter 4|39 pages

Markov Chains

chapter 5|13 pages

Poisson Processes

chapter 6|25 pages

Birth and Death Processes

chapter 7|23 pages

Queues

chapter 8|14 pages

Reliability and Renewal

chapter 9|30 pages

Branching and Other Random Processes

chapter 10|14 pages

Brownian Motion: Wiener Process

chapter 11|10 pages

Computer Simulations and Projects