Overview
- Provides a good balance between a rigorous mathematical approach and easy access to methods in applied research
- Revised and expanded edition includes new exercises, updated methodologies, and a new chapter on ergodic theory
- Minimal background knowledge of stochastic processes required
- Includes models of real world problems
Part of the book series: Modeling and Simulation in Science, Engineering and Technology (MSSET)
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Table of contents (7 chapters)
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Theory of Stochastic Processes
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Applications of Stochastic Processes
Keywords
About this book
Reviews
“This is indeed a very well written book on stochastic processes and their numerous applications. … The reader will definitely benefit from the exercises given at the end of each of the chapters. … The book is strongly recommended to students following any graduate program in mathematics and mathematical modeling. University teachers can easily use this book as a possible reference book for special intermediate and advanced courses in stochastics and its applications.” (Jordan M. Stoyanov, zbMATH 1333.60002, 2016)
Authors and Affiliations
About the authors
Bibliographic Information
Book Title: An Introduction to Continuous-Time Stochastic Processes
Book Subtitle: Theory, Models, and Applications to Finance, Biology, and Medicine
Authors: Vincenzo Capasso, David Bakstein
Series Title: Modeling and Simulation in Science, Engineering and Technology
DOI: https://doi.org/10.1007/978-1-4939-2757-9
Publisher: Birkhäuser New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media New York 2015
Softcover ISBN: 978-1-4939-3836-0Published: 09 October 2016
eBook ISBN: 978-1-4939-2757-9Published: 29 May 2015
Series ISSN: 2164-3679
Series E-ISSN: 2164-3725
Edition Number: 3
Number of Pages: XVI, 482
Number of Illustrations: 14 b/w illustrations
Topics: Probability Theory and Stochastic Processes, Mathematical Modeling and Industrial Mathematics, Quantitative Finance, Mathematical and Computational Biology, Mathematical and Computational Engineering