Modeling and analysis of stochastic systems
著者
書誌事項
Modeling and analysis of stochastic systems
（Texts in statistical science）
Chapman & Hall, 1995
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
This practical and accessible text enables readers from engineering, business, operations research, public policy and computer science to analyze stochastic systems. Emphasizing the modeling of real-life situations with stochastic elements and analyzing the resulting stochastic model, it presents the major cases of useful stochastic processes-discrete and continuous time Markov chains, renewal processes, regenerative processes, and Markov regenerative processes.The author provides reader-friendly yet rigorous coverage. He follows a set pattern of development for each class of stochastic processes and introduces Markov chains before renewal processes, so that readers can begin modeling systems early. He demonstrates both numerical and analytical solution methods in detail and dedicates a separate chapter to queueing applications.Modeling and Analysis of Stochastic Systems includes numerous worked examples and exercises, conveniently categorized as modeling, computational, or conceptual and making difficult concepts easy to grasp.
Taking a practical approach to working with stochastic models, this book helps readers to model and analyze the increasingly complex and interdependent systems made possible by recent advances.
目次
IntroductionDiscrete-Time Markov Chains: Transient BehaviorDiscrete-Time Markov Chains: Limiting BehavorDiscrete-Time Markov Chains: First Passage TimesPoisson ProcessesContinuous-Time Markov ChainsApplications of Markov Chains to Queueing TheoryRenewal ProcessesMarkov Renewal ProcessesEpilogueAppendicesAnswers to Selected ProblemsBibliography
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