Modeling and Analysis of Stochastic Systems - 9781439808757

Kulkarni (statistics and operations research, U. of North Carolina at Chapel Hill) presents a text designed for use in a two-course sequence in stochastic models, with an emphasis on modeling and analysis. The text reverses the standard treatment by introducing Markov chains before renewal theory, which allows the students to begin producing stochastic model immediately. The discussion is organized into chapters dealing with introductory matters, transient behavior and discrete-time Markov chains, first passage times and discrete-time Markov chains, limiting behavior and discrete-time Markov chains, Poisson processes, continuous-time Markov chains, queuing models, renewal processes, Markov regenerative processes, and diffusion processes. Each chapter includes modeling, computational, and conceptual exercises. The chapter on diffusion processes is new to this second edition and some material on numerical methods, stochastic ordering, and Markov renewal theory has been deleted in order to maintain a reasonable length to the book. The material assumes a background in probability theory, advanced calculus, and matrix algebra. Annotation ©2010 Book News, Inc., Portland, OR (booknews.com)