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Based on the author's more than 25 years of teaching experience, Modeling and Analysis of Stochastic Systems, Second Edition covers the most important classes of stochastic processes used in the modeling of diverse systems, from supply chains and inventory systems to genetics and biological systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. Along with reorganizing the material, this edition revises and adds new exercises and examples. New to the second edition: a new chapter on diffusion processes that gives an accessible and non-measure-theoretic treatment with applications to finance; a more streamlined, application-oriented approach to renewal, regenerative, and Markov regenerative processes; and, two appendices that collect relevant results from analysis and differential and difference equations. Rather than offer special tricks that work in specific problems, this book provides thorough coverage of general tools that enable the solution and analysis of stochastic models. After mastering the material in the text, students will be well-equipped to build and analyze useful stochastic models for various situations. A collection of MATLAB[registered]-based programs can be downloaded from the author's website and a solutions manual is available for qualifying instructors.
- Sales Rank: #208704 in Books
- Brand: Brand: Chapman and Hall/CRC
- Published on: 2009-12-18
- Original language: English
- Number of items: 1
- Dimensions: 10.00" h x 1.25" w x 7.01" l, 1.97 pounds
- Binding: Hardcover
- 544 pages
- Used Book in Good Condition
Review
This book is written by a well-experienced scientist and teacher. The material is carefully chosen and presented in a systematic way, starting with the basics and reaching more advanced topics. ? It is very useful to see a large number of examples worked out in detail. Thus, besides university courses, the book can be successfully used for self-education. ? This book is a good example of how to write on sophisticated topics about stochastic processes without involving the heavy measure theoretic machinery. Another advantage of the book is the application-oriented approach that is followed by the author. ? This book can be strongly recommended for introductory, intermediate or advanced university courses on stochastic processes. Both students and their teachers may benefit considerably from it.
?Journal of the Royal Statistical Society: Series A, July 2011
? an accessible, well paced, and very nicely presented book. The publishers are also to be commended on its nice production:
About the Author
Kulkarni, University of North Carolina, Chapel Hill.
Most helpful customer reviews
7 of 7 people found the following review helpful.
precise, modern treatment of stochastic analysis
By A Customer
The book arises from lectures at UNC-CH in a two-semester course on stochastic models. The author has exceptional precision and
organization in the classroom, and this comes through in the book. Great book for teaching
from, as well as learning from.
This book also takes a step which more venerable texts, such as the Trivedi book or the Ross series
could not -- it has computational excercises suitable for math packages like Mathematica. Thus,
the student can be introduced to scientific computer literacy as well as stochastic processes.
I recommend this book to anyone interested in teaching today's student, or for preparing themselves
for challenges in Operations Research. The book would make an above-average reference as well.
Mike Bailey
Associate Professor, Naval Postgraduate School
6 of 7 people found the following review helpful.
An average book
By AR PSU
I used this book in a graduate course on Stochastic processes. The book would rate as average or just above that as I found it to be insufficient for a start in the subject unless you were in a classroom course. It does assume some background in probabilty. Also, the explanations, while complete, are not as easy to understand as the Roos book. I also found that the examples were extremely easy as compared to the excersice problems. THis makes it tougher to 'extrapolate' and understand. It has one nice feature though- solutions to half the problems are there at the end of the book making it better for students while giving faculty leeway too. The excercises are quite comprehensive too. I'd say this is an excellent book for someone with some prior knowlede of Stochastic Processes. For a beginner, this may not be the best start.
1 of 1 people found the following review helpful.
Strictly fair text
By C. Price
This text book isn't great but it isn't awful either. There are numerous typos and mistakes in the book. The author has a list of errata on his webpage that is 7 pages long and that is only a partial list. The explaination in the book is okay and the exercises are pretty good. If you have a choice I recommend using the text by Ross for learning the material or Karlin and Taylor for reference.
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