A First Course in Stochastic Models | 
 enlarge | Author: Henk C. Tijms
Publisher: Wiley
Category: Book
List Price: $80.00
Buy New: $64.60
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Rating:  1 reviews
Sales Rank: 971792
Media: Hardcover
Edition: 2nd
Pages: 488
Number Of Items: 1
Shipping Weight (lbs): 1.8
Dimensions (in): 9 x 6.1 x 1.3
ISBN: 0471498807
Dewey Decimal Number: 519.23
EAN: 9780471498803
Publication Date: May 6, 2003
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Product Description
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.
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| Customer Reviews:
Nice book October 15, 2008
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!
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