Markov Chains

For students in pure and applied probability; lots of applications, fairly self-contained.

J. R. Norris (Author)

9780521633963, Cambridge University Press

Paperback, published 28 July 1998

254 pages, 20 b/w illus.
25.4 x 17.8 x 1.8 cm, 0.47 kg

'We recently based a seminar on this book … it is well suited for an elementary, technically modest, but still rigorous introduction into the heart of a lively and relevant area of stochastic processes.' M. Scheutzow, Zentralblatt MATH

Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov chains and quickly develops a coherent and rigorous theory whilst showing also how actually to apply it. Both discrete-time and continuous-time chains are studied. 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 exercises and examples drawn both from theory and practice. It will therefore be an ideal text either for elementary courses on random processes or those that are more oriented towards applications.

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.

Subject Areas: Probability & statistics [PBT]