Introduction to Stochastic Models
Publication Date: March 2010 Hardback 384 pp.
This book provides a pedagogical examination of the way in which stochastic models are encountered in applied sciences and techniques such as physics, engineering, biology and genetics, economics and social sciences. It covers Markov and semi-Markov models, as well as their particular cases: Poisson, renewal processes, branching processes, Ehrenfest models, genetic models, optimal stopping, reliability, reservoir theory, storage models and queuing systems.
Given this comprehensive treatment of the subject, students and researchers in applied sciences, as well as anyone looking for an introduction to stochastic models, will find this title of invaluable use.
1. Introduction to Stochastic Processes.
2. Simple Stochastic Models.
3. Elements of Markov Modeling.
4. Renewal Models.
5. Semi-Markov Models.
6. Branching Models.
7. Optimal Stopping Models.
About the Authors
Marius Iosifescu is a member and vice-president of the Romanian Academy of Sciences and director of the Bucharest Institute of Mathematical Statistics and Applied Mathematics. His research concerns stochastic processes, the probabilistic theory of numbers and their applications.
Nikolaos Limnios is a professor of applied mathematics at the University of Technology of Compiègne, France. His research and teaching activities concern stochastic processes, statistical inference and their applications.
Gheorghe Opri\s,an is a professor of applied mathematics at the ‘Politehnica’ University of Bucharest and the head of the Mathematical section II there. His research concerns stochastic processes and their applications.