- Contains 175 exercises including research-oriented problems about special stochastic processes not covered in traditional textbooks
- Includes detailed simulation programs of the main models
- Covers topics not typically included in traditional textbooks, allowing for readers to learn quickly on many topics, including research-oriented topics
- Includes a timeline with the main contributors since the origin of probability theory until today
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- About this Textbook
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Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes.
- About the authors
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Nicolas Lanchier is Associate Professor at Arizona State University, School of Mathematical and Statistical Sciences. His research interests include mathematical models introduced in the life and social sciences literature that describe inherently spatial phenomena of interacting populations consist of systems of ordinary differential equations.
- Reviews
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“Stochastic Modeling by Nicolas Lanchier is an introduction to stochastic processes accessible to advanced students and interdisciplinary scientists with a background in graduate-level real analysis. The work offers a rigorous approach to stochastic models used in social, biological and physical sciences ... . Stochastic modeling provides a link between applied research in stochastic models and the literature covering their mathematical foundations.” (Ben Dyhr, Mathematical Reviews, May, 2018)
“There is a wide spectrum of topics discussed in this book. … It is also interesting to find several classical examples with all details. … The text is so carefully written and checked, that I was unable to find a single typo. The book can be strongly recommended to those students and teachers who want to be in line with modern probability theory and its diverse applications.” (Jordan M. Stoyanov, zbMATH 1360.60002, 2017)
- Table of contents (17 chapters)
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Basics of measure and probability theory
Pages 3-24
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Distribution and conditional expectation
Pages 25-40
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Limit theorems
Pages 41-56
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Stochastic processes: general definition
Pages 59-63
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Martingales
Pages 65-91
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Table of contents (17 chapters)
- Download Preface 1 PDF (88.4 KB)
- Download Sample pages 1 PDF (247.6 KB)
- Download Table of contents PDF (57.4 KB)
- Solution's Manual
- Solution's Manual
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Stochastic Modeling
- Authors
-
- Nicolas Lanchier
- Series Title
- Universitext
- Copyright
- 2017
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG
- eBook ISBN
- 978-3-319-50038-6
- DOI
- 10.1007/978-3-319-50038-6
- Softcover ISBN
- 978-3-319-50037-9
- Series ISSN
- 0172-5939
- Edition Number
- 1
- Number of Pages
- XIII, 303
- Number of Illustrations
- 57 b/w illustrations, 6 illustrations in colour
- Topics