Markov Chains
In this rigorous account the author studies both discrete-time and continuous-time chains. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials, in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and a careful selection of exercises and examples drawn both from theory and practice. This is an ideal text for seminars on random processes or for those that are more oriented towards applications, for advanced undergraduates or graduate students with some background in basic probability theory.
- Self-contained and systematic introduction to Markov chains
- Large selection of student-tested exercises and examples
- Special chapter on applications and links with other topics
Reviews & endorsements
"...impressive ....I heartily recommend this book....this is the best book available summarizing the theory of Markov Chains....Norris achieves for Markov Chains what Kingman has so elegantly achieved for Poisson processes....Such creative tinkering will be a pleasure to many teachers." Bulletin of Mathematical Biology
Product details
July 1998Paperback
9780521633963
254 pages
254 × 178 × 18 mm
0.47kg
20 b/w illus.
Available
Table of Contents
- Introduction
- 1. Discrete-time Markov chains
- 2. Continuous-time Markov chains I
- 3. Continuous-time Markov chains II
- 4. Further theory
- 5. Applications
- Appendix
- Probability and measure
- Index.