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An Introduction to Stochastic Modeling
- 5th Edition - January 1, 2026
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 1 5 5 2 - 7
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 1 5 5 3 - 4
Introduction to Stochastic Modeling, Fifth Edition bridges the gap between basic probability and an intermediate level course in stochastic processes, serving as the foundation… Read more
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Request a sales quoteIntroduction to Stochastic Modeling, Fifth Edition bridges the gap between basic probability and an intermediate level course in stochastic processes, serving as the foundation for either a one-semester or two-semester course in stochastic processes for students familiar with elementary probability theory and calculus. The objectives are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide an integrated treatment of theory, applications and practical implementation. A well-regarded resource for many years, the text is an ideal foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus.
• Explores realistic applications from a variety of disciplines, including biological, chemical, and financial examples • Provides extensive end-of-chapter exercises sets with answers, as well as numerical illustrations and pseudo code/links to downloadable resources. • Presents new coverage on stochastic differential equations, Brownian motion, Martingale and Poisson processes • Includes computational examples, codes, and exercises that will empower students to explore concepts in a practical way • Offers online support, sample code and solutions to coding problems and access to code such as Python for students
Upper-level undergraduate and graduate students in one-semester stochastic processes and stochastic modeling courses; assumes some background with advanced mathematics, probability theory, and calculus
1 Introduction
2 Conditional Probability and Conditional Expectation
3 Markov Chains: Introduction
4 The Long Run Behavior of Markov Chains
5 Poisson Processes
6 Continuous Time Markov Chains
7 Renewal Phenomena
8 Queueing Systems
9 Brownian Motion and Related Processes
10 Modeling Using Stochastic Differential Equations
2 Conditional Probability and Conditional Expectation
3 Markov Chains: Introduction
4 The Long Run Behavior of Markov Chains
5 Poisson Processes
6 Continuous Time Markov Chains
7 Renewal Phenomena
8 Queueing Systems
9 Brownian Motion and Related Processes
10 Modeling Using Stochastic Differential Equations
- No. of pages: 600
- Language: English
- Edition: 5
- Published: January 1, 2026
- Imprint: Academic Press
- Paperback ISBN: 9780443315527
- eBook ISBN: 9780443315534