Understanding Markov Chains: Examples and Applications / Edition 2

by Nicolas Privault

Overview

This book provides an undergraduate-level introduction to discrete and continuous-time Markov chains and their applications, with a particular focus on the first step analysis technique and its applications to average hitting times and ruin probabilities. It also discusses classical topics such as recurrence and transience, stationary and limiting distributions, as well as branching processes. It first examines in detail two important examples (gambling processes and random walks) before presenting the general theory itself in the subsequent chapters. It also provides an introduction to discrete-time martingales and their relation to ruin probabilities and mean exit times, together with a chapter on spatial Poisson processes. The concepts presented are illustrated by examples, 138 exercises and 9 problems with their solutions.

Product Details

ISBN-13:	9789811306587
Publisher:	Springer Nature Singapore
Publication date:	08/04/2018
Series:	Springer Undergraduate Mathematics Series
Edition description:	Second Edition 2018
Pages:	372
Product dimensions:	6.10(w) x 9.25(h) x (d)

About the Author

The author is an associate professor from the Nanyang Technological University (NTU) and is well-established in the field of shastic processes and a highly respected probabilist. He has authored the book, Shastic Analysis in Discrete and Continuous Settings: With Normal Martingales, Lecture Notes in Mathematics, Springer, 2009 and was a co-editor for the book, Shastic Analysis with Financial Applications, Progress in Probability, Vol. 65, Springer Basel, 2011. Aside from these two Springer titles, he has authored several others. He is currently teaching the course M27004-Probability Theory and Shastic Processes at NTU. The manuscript has been developed over the years from his courses on Shastic Processes.

Table of Contents

Probability Background.- Gambling Problems.- Random Walks.- Discrete-Time Markov Chains.- First Step Analysis.- Classification of States.- Long-Run Behavior of Markov Chains.- Branching Processes.- Continuous-Time Markov Chains.- Discrete-Time Martingales.- Spatial Poisson Processes.- Reliability Theory.

Editorial Reviews

“This textbook provides an elementary introduction to the classical theory of discrete and continuous time Markov chains motivated by gambling problems and covers a variety of primers on different topics … . this text may serve very well for a first undergraduate course on Markov chains for applied mathematicians, but also for students of financial engineering. It is completed by almost a hundred pages of solutions of exercises.” (Michael Högele, zbMATH 1305.60003, 2015)

“The book provides an introduction to discrete and continuous-time Markov chains and their applications. … The explanation is detailed and clear. Often the reader is guided through the less trivial concepts by means of appropriate examples and additional comments, including diagrams and graphs. Also, a big plus is the presence of numerous well-chosen exercises at the end of each chapter, which are discussed in a separate ‘Solutions to the Exercises’ part at the end of the book.” (Michele Zito, Mathematical Reviews, December, 2014)

From the Publisher