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Introduction to Matrix Analytic Methods in Stochastic Modeling
Introduction to Matrix Analytic Methods in Stochastic Modeling
Date: 21 April 2011, 10:11

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Matrix analytic methods are popular as modeling tools because they give one the ability to construct and analyze a wide class of queuing models in a unified and algorithmically tractable way. The authors present the basic mathematical ideas and algorithms of the matrix analytic theory in a readable, up-to-date, and comprehensive manner. In the current literature, a mixed bag of techniques is used-some probabilistic, some from linear algebra, and some from transform methods. Here, many new proofs that emphasize the unity of the matrix analytic approach are included.
Summary: A Great Book
Rating: 5
Matrix Analytic Methods (MAM) are great modeling tools that can analyze a variety of stochastic systems in a unified way and in an algorithmically tractable manner. This book is one of the greatest that have been published on queueing theory and stochastic modeling.
This book covers
1. Examples of quasi-birth-and-death (QBD) processes.
2. Phase-type distributions
3. Stationary and non-stationary QBDs
4. Algorithms (from probabilistic reasoning)
5. And many others.
I used this book as a text for my graduate students and it was a real pleasure. Throughout the books, readers will see MAM as an art of modeling and analysis of stochastic systems, not the pile of techniques.
This book is aiming at readers in queueing theory, computer science, OR/MS, statistics, mathematics, and many other related disciplines. This book also serves as the source of bibliography not otherwise easily available.

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