Markov Processes
Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic processes. The text is designed to be understandable to students who have taken an undergraduate probability course without needing an instructor to fill in any gaps.

Clear, rigorous, and intuitive, the second edition builds on the successful first, used in courses and 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 second edition presents a new chapter illustrating the utility of using digraphs to describe whether a Markov process is reducible, absorbing, etc. There are additional exercises, and some material has been Applications to a number of fields, including economics, physics, and mathematical biology.

The book begins with a review of basic probability, then covers the case of finite state, discrete time Markov processes. Building on this, the text deals with the discrete time, infinite state case and provides background for continuous Markov processes with exponential random variables and Poisson processes. It presents continuous Markov processes which include the basic material of Kolmogorov’s equations, infinitesimal generators, and explosions. The book concludes with coverage of both discrete and continuous reversible Markov chains.

While Markov processes are touched on in probability courses, this book offers the opportunity to concentrate on the topic when additional study is required. It creates a more seamless transition to prepare the student for what comes next.

1120079095
Markov Processes
Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic processes. The text is designed to be understandable to students who have taken an undergraduate probability course without needing an instructor to fill in any gaps.

Clear, rigorous, and intuitive, the second edition builds on the successful first, used in courses and 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 second edition presents a new chapter illustrating the utility of using digraphs to describe whether a Markov process is reducible, absorbing, etc. There are additional exercises, and some material has been Applications to a number of fields, including economics, physics, and mathematical biology.

The book begins with a review of basic probability, then covers the case of finite state, discrete time Markov processes. Building on this, the text deals with the discrete time, infinite state case and provides background for continuous Markov processes with exponential random variables and Poisson processes. It presents continuous Markov processes which include the basic material of Kolmogorov’s equations, infinitesimal generators, and explosions. The book concludes with coverage of both discrete and continuous reversible Markov chains.

While Markov processes are touched on in probability courses, this book offers the opportunity to concentrate on the topic when additional study is required. It creates a more seamless transition to prepare the student for what comes next.

89.99 Pre Order
Markov Processes

Markov Processes

by James R. Kirkwood
Markov Processes

Markov Processes

by James R. Kirkwood

Paperback(2nd ed.)

$89.99 
  • SHIP THIS ITEM
    Available for Pre-Order. This item will be released on October 28, 2025

Related collections and offers


Overview

Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic processes. The text is designed to be understandable to students who have taken an undergraduate probability course without needing an instructor to fill in any gaps.

Clear, rigorous, and intuitive, the second edition builds on the successful first, used in courses and 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 second edition presents a new chapter illustrating the utility of using digraphs to describe whether a Markov process is reducible, absorbing, etc. There are additional exercises, and some material has been Applications to a number of fields, including economics, physics, and mathematical biology.

The book begins with a review of basic probability, then covers the case of finite state, discrete time Markov processes. Building on this, the text deals with the discrete time, infinite state case and provides background for continuous Markov processes with exponential random variables and Poisson processes. It presents continuous Markov processes which include the basic material of Kolmogorov’s equations, infinitesimal generators, and explosions. The book concludes with coverage of both discrete and continuous reversible Markov chains.

While Markov processes are touched on in probability courses, this book offers the opportunity to concentrate on the topic when additional study is required. It creates a more seamless transition to prepare the student for what comes next.


Product Details

ISBN-13: 9781041046660
Publisher: CRC Press
Publication date: 10/28/2025
Series: Advances in Applied Mathematics
Edition description: 2nd ed.
Pages: 344
Product dimensions: 6.12(w) x 9.19(h) x (d)

About the Author

James R. Kirkwood holds a Ph.D. from the University of Virginia. He has had ten mathematics textbooks published on various topics including calculus, real analysis, mathematical biology and mathematical physics. His original research was in mathematical physics, and he co-authored the seminal paper in a topic now called Kirkwood-Thomas Theory in mathematical physics. During the summer, he teaches real analysis to graduate students at the University of Virginia. He has been awarded several National Science Foundation grants. Dr. Kirkwood’s books for CRC Press include, An Introduction to Analysis, third edition ©2024; A Transition to Advanced Mathematics (with Raina S. Robeva) ©2024; Linear Algebra (with Bessie H. Kirkwood) ©2024; Elementary Linear Algebra (with Bessie H. Kirkwood) ©2023.

 

Table of Contents

Preface to Second Edition  1. Review of Probability 2. Discrete-Time, Finite-State Markov Chains  3. Discrete-Time, Infinite-State Markov Chains  4. Exponential Distribution and Poisson Process  5. Continuous Time Markov Chains  6. Queuing Models and Detailed Balance Equations  7. Reversible Markov Chains  8.Digraphs

From the B&N Reads Blog

Customer Reviews