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An Introduction to Stochastic Modeling

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Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, "Introduction to Stochastic Modeling, 4e, " bridges the gap between basic probability and an intermediate level course in stochastic processes. The objectives of the text 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 exercises in the application of simple stochastic analysis to realistic problems.

New to this edition: Realistic applications from a variety of disciplines integrated throughout the text, including more biological applicationsPlentiful, completely updated problemsCompletely updated and reorganized end-of-chapter exercise sets, 250 exercises with answersNew chapters of stochastic differential equations and Brownian motion and related processesAdditional sections on Martingale and Poisson process
Realistic applications from a variety of disciplines integrated throughout the text.

Extensive end of chapter exercises sets, 250 with answers

Chapter 1-9 of the new edition are identical to the previous edition

New! Chapter 10 - Random Evolutions

New! Chapter 11- Characteristic functions and Their Applications

584 pages, Kindle Edition

First published August 1, 1984

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Profile Image for Kevin K. Gillette.
107 reviews41 followers
December 17, 2014
This textbook was in draft status when I encountered it as a part of the reading for a course I took in stochastic processes at Stanford from Ian Johnstone. Although the typesetting was rather crude in draft form (remember, this was well before the wonderful WYSIWYG editors like MS-Word), it was an effective and accessible text. It served as my first introduction to the Chapman-Kolmogorov equations, which were very much a foundational concept for this subject.
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