An Introduction to Stochastic Modeling

Häftad, Engelska, 2026

1 125 kr

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Beskrivning

An Introduction 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 broad range of students.

Explores realistic applications from a variety of disciplines, including biological, chemical, physical, engineering, and financial examples
Presents a completely new treatment of modeling with stochastic differential equations, and expanded coverage of Brownian motion and martingale processes
New applications of Markov chains to the simulation of chemical reactions via the Gillespie algorithm and to Bayesian inference via the Metropolis-Hastings algorithm
Provides extensive end-of-section exercises sets with answers, as well as numerical illustrations
Each chapter concludes with a section focusing on computational examples, code, and exercises that will empower students to explore concepts in a practical way
Offers online support, sample code and solutions to coding problems for instructors, and electronic access to sample Python code for students

Produktinformation

Utgivningsdatum:2026-03-02
Mått:152 x 229 x 25 mm
Vikt:810 g
Format:Häftad
Språk:Engelska
Antal sidor:600
Upplaga:5
Förlag:Elsevier Science
ISBN:9780443315527

Utforska kategorier

Tillämpad matematik inom Naturvetenskap och teknik

Mer om författaren

Gabriel J. Lord is Professor of Applied Analysis at Radboud University Nijmegen in the Netherlands since 2019. Prior to this, he was a Professorat the Maxwell Institute in Edinburgh, UK which he joined after a couple of years in industry at the National Physical Laboratory, UK. With over25 years teaching experience he has been giving lectures on elements of stochastic modeling for the last twenty years. He has co-authored Stochastic Methods in Neuroscience and An Introduction to Computational Stochastic PDEs. His research is in applied and computational mathematics and in particularfor stochastic systems and models.Cónall Kelly is Senior Lecturer (Associate Professor) of Financial Mathematics and Chair of the BSc Financial Mathematics and Actuarial Science degree at University College Cork in Ireland. He has taught courses in stochastic analysis and modeling for over 15 years and is the author of the textbook Computation and Simulation for Finance: An Introduction with Python. His research focuses on the qualitative dynamics of stochastic difference and differential equations, the analysis of numerical methods for stochastic systems, and applications in finance and biology.

Innehållsförteckning

1. Introduction2. Conditional Probability and Conditional Expectation3. Markov Chains: Introduction4. The Long Run Behavior of Markov Chains5. Poisson Processes6. Continuous Time Markov Chains7. Renewal Phenomena8. Queueing Systems9. Brownian Motion and Related Processes10. Modeling Using Stochastic Differential Equations