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A First Course in Stochastic Models, by Henk C. Tijms
PDF Ebook A First Course in Stochastic Models, by Henk C. Tijms
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The field of applied probability has changed profoundly in the past twenty years. The development of computational methods has greatly contributed to a better understanding of the theory. A First Course in Stochastic Models provides a self-contained introduction to the theory and applications of stochastic models. Emphasis is placed on establishing the theoretical foundations of the subject, thereby providing a framework in which the applications can be understood. Without this solid basis in theory no applications can be solved.
- Provides an introduction to the use of stochastic models through an integrated presentation of theory, algorithms and applications.
- Incorporates recent developments in computational probability.
- Includes a wide range of examples that illustrate the models and make the methods of solution clear.
- Features an abundance of motivating exercises that help the student learn how to apply the theory.
- Accessible to anyone with a basic knowledge of probability.
A First Course in Stochastic Models is suitable for senior undergraduate and graduate students from computer science, engineering, statistics, operations resear ch, and any other discipline where stochastic modelling takes place. It stands out amongst other textbooks on the subject because of its integrated presentation of theory, algorithms and applications.
- Sales Rank: #2385669 in Books
- Published on: 2003-04-18
- Original language: English
- Number of items: 1
- Dimensions: 9.35" h x 1.25" w x 6.10" l, 1.78 pounds
- Binding: Hardcover
- 492 pages
Review
"…successfully combined theory and real world examples into a systematic introduction...an excellent reference for the applied statistician who deals in various queuing models." (Technometrics, August 2005)
“…clear and straightforward…plenty of worked (or orientated) examples as well as a substantial set of exercises…” (Short Book Reviews, August 2004)
From the Back Cover
The field of applied probability has changed profoundly in the past twenty years. The development of computational methods has greatly contributed to a better understanding of the theory. A First Course in Stochastic Models provides a self-contained introduction to the theory and applications of stochastic models. Emphasis is placed on establishing the theoretical foundations of the subject, thereby providing a framework in which the applications can be understood. Without this solid basis in theory no applications can be solved.
- Provides an introduction to the use of stochastic models through an integrated presentation of theory, algorithms and applications.
- Incorporates recent developments in computational probability.
- Includes a wide range of examples that illustrate the models and make the methods of solution clear.
- Features an abundance of motivating exercises that help the student learn how to apply the theory.
- Accessible to anyone with a basic knowledge of probability.
Most helpful customer reviews
4 of 6 people found the following review helpful.
Nice book
By Abhijit Gosavi
This is a really nice book that covers a lot of ground on stochastic operations research. It is one of those rare books that present difficult matter as if it were very easy to understand. A nice effort has been made to simplify ideas that really are not simple. You will find in-depth discussions on Markov chains, renewal theory (both elementary and advanced), queueing theory, and Markov Decision Processes. What I liked is (i) the thoroughness with which topics have been treated and (ii) that the book does present many important topics that other introductory books just fail to cover (e.g., semi-Markov decision process with an LP formulation, GI/G/1 queues). And the book is at the beginner graduate level!
0 of 8 people found the following review helpful.
Worst...math...text...EVER!
By Bluto
This was the assigned text for an upper-level graduate course I took in Advanced Operations Research. My classmates and I despised it. It's disjointed, inconsistent, with unilluminating, half-worked examples (when there are any examples at all). Even the PhD candidates denounced it as unreadable. All of us wound up buying alternative texts to get through the course, and so will you if you waste your money on this book. Grade = NO STARS!
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