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Probability, Markov chains, queues, and simulation : the mathematical basis of performance modeling
Resource Information
The work ** Probability, Markov chains, queues, and simulation : the mathematical basis of performance modeling** represents a distinct intellectual or artistic creation found in **University of Liverpool**. This resource is a combination of several types including: Work, Language Material, Books.

The Resource
Probability, Markov chains, queues, and simulation : the mathematical basis of performance modeling
Resource Information

The work

**Probability, Markov chains, queues, and simulation : the mathematical basis of performance modeling**represents a distinct intellectual or artistic creation found in**University of Liverpool**. This resource is a combination of several types including: Work, Language Material, Books.- Label
- Probability, Markov chains, queues, and simulation : the mathematical basis of performance modeling

- Title remainder
- the mathematical basis of performance modeling

- Statement of responsibility
- William J. Stewart

- Language
- eng

- Summary
- Probability, Markov Chains, Queues, and Simulation provides a modern and authoritative treatment of the mathematical processes that underlie performance modeling. The detailed explanations of mathematical derivations and numerous illustrative examples make this textbook readily accessible to graduate and advanced undergraduate students taking courses in which stochastic processes play a fundamental role. The textbook is relevant to a wide variety of fields, including computer science, engineering, operations research, statistics, and mathematics. The textbook looks at the fundamentals of probability theory, from the basic concepts of set-based probability, through probability distributions, to bounds, limit theorems, and the laws of large numbers. Discrete and continuous-time Markov chains are analyzed from a theoretical and computational point of view. Topics include the Chapman-Kolmogorov equations; irreducibility; the potential, fundamental, and reachability matrices; random walk problems; reversibility; renewal processes; and the numerical computation of stationary and transient distributions. The M/M/1 queue and its extensions to more general birth-death processes are analyzed in detail, as are queues with phase-type arrival and service processes. The M/G/1 and G/M/1 queues are solved using embedded Markov chains; the busy period, residual service time, and priority scheduling are treated. Open and closed queueing networks are analyzed. The final part of the book addresses the mathematical basis of simulation. Each chapter of the textbook concludes with an extensive set of exercises. An instructor's solution manual, in which all exercises are completely worked out, is also available (to professors only). Numerous examples illuminate the mathematical theories; Carefully detailed explanations of mathematical derivations guarantee a valuable pedagogical approach; Each chapter concludes with an extensive set of exercises

- Cataloging source
- DLC

- Dewey number
- 519.201/13

- Illustrations
- illustrations

- Index
- index present

- LC call number
- QA273

- LC item number
- .S7532 2009

- Literary form
- non fiction

- Nature of contents
- bibliography

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`<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/resource/XCw05ZNXNeA/" typeof="CreativeWork http://bibfra.me/vocab/lite/Work"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/resource/XCw05ZNXNeA/">Probability, Markov chains, queues, and simulation : the mathematical basis of performance modeling</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>`