An Introduction to Stochastic Modeling
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.
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Book is sometimes overdone, other times not comprehensive enough, error and typo-ridden, and fairly annoying to read. Would not recommend using unless absolutely required for a class.
Chapter 1 Introduction
Chapter 2 Conditional Probability and Conditional Expectation
Chapter 4 The Long Run Behavior of Markov Chains
Chapter 5 Poisson Processes
Chapter 6 Continuous Time Markov Chains
Chapter 7 Renewal Phenomena
Chapter 8 Brownian Motion and Related Processes