Markov Chains

Cambridge Series in Statistical and Probabilistic Mathematics #2

by J.R. Norris

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.

Genres: Mathematics, Nonfiction, Reference

253 pages, Hardcover

First published February 28, 1997

Reviews

[Bhuvanesh · Rating 4 out of 5]

Not bad for an introduction to the topic.

[Goo · Rating 2 out of 5]

Read as supplement to a course on Markov Chains from November 2019 to January 2020