An Introduction to Stochastic Modeling,
Edition 4
By Mark Pinsky and Samuel Karlin

Publication Date: 10 Dec 2010

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, Fourth Edition, 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

Key Features

  • 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
About the author
By Mark Pinsky and Samuel Karlin, Stanford University and The Weizmann Institute of Science
Table of Contents
IntroductionConditional Probability and Conditional ExpectationMarkov Chains: IntroductionThe Long Run Behavior of Markov ChainsPoisson ProcessesContinuous Time Markov ChainsRenewal PhenomenaBrownian Motion and Related ProcessesQueueing Systems Random EvolutionsCharacteristic Functions and Their Applications
Book details
ISBN: 9780123814166
Page Count: 584
Retail Price : £78.99
Instructor Resources
Upper division undergraduate and graduate-level courses in stochastic processes and stochastic modeling, offered in statistics and mathematics departments at all major universities