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Volume 14 - 2018

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Detailed review of: 

Stochastic Processes in Science, Engineering and Finance




Chapman & Hall/CRC , Boca Raton, U.S.A




Frank Beichelt




Stochastic Processes in Science, Engineering and Finance


Year of Publication














Yuanshun  Dai, University of Tennessee




Review published in IJPE, Vol.6, No. 1, January 2010, p. 34. 

The book consists of 7 chapters as follows:


Chapter 1

Probability Theory

 90  Pages

Chapter 2

Basics of Stochastic Processes

 16  Pages

Chapter 3

Random Point Processes

100 Pages

Chapter 4

Markov Chains in Discrete Time

 32  Pages

Chapter 5

Markov Chains in Continuous Time

 92  Pages

Chapter 6


 20  Pages

Chapter 7

Brownian Motion

 45  Pages

Answers to Selected Exercises

 8    Pages



 6   Pages



 7   Pages


The author of this book has 7 books to his credit. Five of these have been in German and is currently Professor of Operations Research at University of Witswatersrand, South Africa and has published

Stochastic Processes in Science, Engineering and Finance

widely in reputed journals on reliability, and maintenance policies.

The book fulfills the author's aim in providing a comprehensive treatment of introducing stochastic process, with special emphasis on their applications in science, engineering, finance, computer science and operations research. The book provides theoretical foundations for modeling time-dependent random phenomena in these areas and illustrates their applications through the analysis of numerous, practically relevant examples. The book is encyclopedic in scope and will be useful to both practitioners and researchers in stochastic processes as well as other disciplines. The book is written at a relatively advanced level, which means that readers should have some basic knowledge in probability and statistics before reading it. Important features of this book are that it contains comprehensive sections of exercises at the end of each chapter and provides up-to-date information on what has been written on the subject to date. Therefore, this book can also serve as a good textbook for senior undergraduate and graduate level courses for students of applied fields. The book begins with discussion of various concepts of probability theory, stochastic processes, and random point processes. Then, two complete chapters are devoted to the Markov Chains in both discrete time and continuous time. Following that, the Martingales and Brownian motion are discussed.

The chapters are organized in such a way that reading a chapter only requires knowledge of some of the previous ones. Overall, I recommend this book to all serious-minded researchers, practitioners, teachers, graduate and undergraduate students who would like to have the most up-to-date information available on the subject of stochastic processes and their applications in a variety of fields. It also serves as reference book on probability and stochastic processes, and is a good addition to one's mathematical or statistical library

 -   Yuanshun Dai
University of Tennessee

Review published in the International Journal of Performability Engineering, Vo. 6, No. 1, January 2010, p. 34.


This review was published in the International Journal of Performability Engineering, Vol. 6, No. 1, January 2010 issue on page 34.

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