ABSTRACT

Clear, rigorous, and intuitive, Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic processes and also as a reference for those that want to see detailed proofs of the theorems of Markov processes. It contains copious computational examples that motivate and illustrate the theorems. The text is desi

chapter 1|40 pages

Review of Probability

chapter 2|100 pages

Discrete-Time, Finite-State Markov Chains

chapter 5|72 pages

Continuous-Time Markov Chains

chapter 6|24 pages

Reversible Markov Chains