An Introduction to Stochastic ModelingServing as the foundation for a onesemester 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:

What people are saying  Write a review
Book is sometimes overdone, other times not comprehensive enough, error and typoridden, and fairly annoying to read. Would not recommend using unless absolutely required for a class.
Contents
Chapter 1 Introduction  1 
Chapter 2 Conditional Probability and Conditional Expectation  47 
Introduction  79 
Chapter 4 The Long Run Behavior of Markov Chains  165 
Chapter 5 Poisson Processes  223 
Chapter 6 Continuous Time Markov Chains  277 
Chapter 7 Renewal Phenomena  347 
Chapter 8 Brownian Motion and Related Processes  391 
Chapter 9 Queueing Systems  447 
Chapter 10 Random Evolutions  495 
Chapter 11 Characteristic Functions and Their Applications  525 
541  
Answers to Exercises  543 
557  