An Introduction to Stochastic Modeling

Other | November 1, 2010

byPinsky, Mark, Mark Pinsky

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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 applications
  • Plentiful, completely updated problems
  • Completely updated and reorganized end-of-chapter exercise sets, 250 exercises with answers
  • New chapters of stochastic differential equations and Brownian motion and related processes
  • Additional 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

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From the Publisher

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 student...

Format:OtherDimensions:584 pages, 1 × 1 × 1 inPublished:November 1, 2010Publisher:Academic PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0123814170

ISBN - 13:9780123814173

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Extra Content

Table of Contents

Introduction
Conditional Probability and Conditional Expectation
Markov Chains: Introduction
The Long Run Behavior of Markov Chains
Poisson Processes
Continuous Time Markov Chains
Renewal Phenomena
Brownian Motion and Related Processes
Queueing Systems
Random Evolutions
Characteristic Functions and Their Applications