Author: Carlos Polanco

Markov Chain Process (Theory and Cases)

eBook: US $59 Special Offer (PDF + Printed Copy): US $94
Printed Copy: US $65
Library License: US $236
ISBN: 978-981-5080-48-3 (Print)
ISBN: 978-981-5080-47-6 (Online)
Year of Publication: 2023
DOI: 10.2174/9789815080476123010001


Markov Chain Process: Theory and Cases is designed for students of natural and formal sciences. It explains the fundamentals related to a stochastic process that satisfies the Markov property. It presents 10 structured chapters that provide a comprehensive insight into the complexity of this subject by presenting many examples and case studies that will help readers to deepen their acquired knowledge and relate learned theory to practice.

This book is divided into four parts. The first part thoroughly examines the definitions of probability, independent events, mutually (and not mutually) exclusive events, conditional probability, and Bayes’ theorem, which are essential elements in Markov’s theory. The second part examines the elements of probability vectors, stochastic matrices, regular stochastic matrices, and fixed points. The third part presents multiple cases in various disciplines: Predictive computational science, Urban complex systems, Computational finance, Computational biology, Complex systems theory, and Computational Science in Engineering. The last part introduces learners to Fortran 90 programs and Linux scripts.

To make the comprehension of Markov Chain concepts easier, all the examples, exercises, and case studies presented in this book are completely solved and given in a separate section.

This book serves as a textbook (either primary or auxiliary) for students required to understand Markov Chains in their courses, and as a reference book for researchers who want to learn about methods that involve Markov Processes.

Audience: Students of mathematics, advanced life sciences and formal science, researchers.


In his book, Dr. Carlos Polanco elegantly describes fundamentals of Markov Chain Process and its applications. The author was able to overcome the usual gap between mathematicians and users, describing the main topics related to Markov Chain Process Theory in an easily apprehendable way, utilizing multiple useful examples and providing exercises. This book can be used as auxiliary book for students interested in this field as well as a reference book for seasoned Researcher.

Vladimir N. Uversky
Russian Academy of Sciences
Pushchino, Moscow region, Russia

With Markov Chain Process, Carlos Polanco introduces an experienced view on first year in Sciences that presents a valuable reference for students as well as for their teachers. This book is very well structured, nicely written and provides a comprehensive insight into the complexity of this field. Especially, the presentation of many examples and case studies will help the readers to deepen their acquired knowledge and to relate the theory to practice. It will certainly also help researchers in related fields to refresh their knowledge and to serve as a solid and clear source on Markov Chain Process. Rounding up, Carlos Polanco’s book should become part of many bookshelves.

Thomas Buhse
Universidad Autónoma del Estado de Morelos
Cuernavaca Morelos, México