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Introduction to Matrix Analytic Methods in Stochastic Modeling (ASA-SIAM Series on Statistics and Applied Probability) (English and Spanish Edition)

5 out of 5 stars 1 customer review
ISBN-13: 978-0898714258
ISBN-10: 0898714257
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Editorial Reviews

About the Author

Guy Latouche is a professor in the Department of Algorithmic Methods and Probability at the University of Brussels. V. Ramaswami works at AT&T Bell Laboratories in New Jersey.

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Product Details

  • Series: ASA-SIAM Series on Statistics and Applied Probability (Book 5)
  • Paperback: 348 pages
  • Publisher: Society for Industrial and Applied Mathematics (January 1, 1987)
  • Language: English, Spanish
  • ISBN-10: 0898714257
  • ISBN-13: 978-0898714258
  • Product Dimensions: 6 x 0.8 x 9 inches
  • Shipping Weight: 13.6 ounces
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #3,066,885 in Books (See Top 100 in Books)

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Top Customer Reviews

Format: Paperback
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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