Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics) | 
 enlarge | Authors: Reuven Y. Rubinstein, Dirk P. Kroese
Publisher: Wiley-Interscience
Category: Book
List Price: $99.95
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Rating:  5 reviews
Sales Rank: 103455
Media: Hardcover
Edition: 2
Pages: 345
Number Of Items: 1
Shipping Weight (lbs): 1.6
Dimensions (in): 9.2 x 6.4 x 1
ISBN: 0470177942
Dewey Decimal Number: 518.282
EAN: 9780470177945
Publication Date: December 19, 2007
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Product Description
This new edition presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences.
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| Customer Reviews:
 excellent February 12, 2008
O.B. Bommel
2 out of 2 found this review helpful
This is an excellent textbook for a course on stochastic simulation
for senior and master students in science. It gives a comprehensive
treatment of all important aspects of dynamic discrete event
simulations with examples and applications in queueing and reliability
models. And each chapter concludes with many problems. In this respect
it is self-contained as it has a chapter on (basic principles of)
probability as well. Just a minor criticism is that the book handles
traditional simulation topics such as building simulation models
and verification/validation rather sketchy (in chapter 3). However,
there are many other topics that you quite often do not see in books on
simulation, like MCMC, optimization, rare-event simulation,
cross-entropy algorithms for combinatorial optimization. The authors
treat the mathematical background and details before giving the
simulation algorithms, which makes the book easy to use as a reference
and suitable for instruction and case studies.
Specifically, I enjoyed reading the last chapter on counting problems
and how to solve them (approximately) by Monte Carlo simulation. There
seems to be many open problems in that area and this chapter is a good
starting point for initiating interesting research.
Computer Simulation in the Next Decade May 7, 2008
Don L. Mcleish (Waterloo)
2 out of 2 found this review helpful
Difficult computational problems often require solutions which adapt to the problem being solved. Such sequential methods are the focus of Simulation and the Monte Carlo Method, providing an algorithmic approach to hard counting and optimization problems, the simulation of rare-event probabilities through minimum cross-entropy, sensitivity analysis, and Markov Chain Monte Carlo.
This book, by two leading experts in the field, travels well-beyond the usual introduction to stochastic simulation and variance reduction to the heart of the adaptive tools required by the complex simulation and optimization problems of the next decade. I recommend the book for researchers and practitioners alike, interested in the extraordinary power and potential of modern Monte Carlo Methods for solving problems in modeling, statistics and optimization.
Enthusiastic reader January 16, 2008
Alexander Shapiro
1 out of 1 found this review helpful
This book is supposed to be a revision of the classical book by Rubinstein 1981. As is pointed out in the Preface: "Dramatic changes have taken place in the entire field of Monte Carlo simulation [since 1981]". This edition includes a considerable amount of new, and important, material for which the authors were among principal developers. This alone makes this book a valuable addition to the recent literature on theory and applications of Monte Carlo methods. The book is written in a clear style and is a pleasure to read.
Up to date December 29, 2007
The Casual Observer
1 out of 2 found this review helpful
This book is a revision of the classic first edition and is authoritative and up to date, including most of the interesting new advances in Monte Carlo methods including modern techniques like perfect sampling and Hit-and-Run algorithms.
 Boring!!! December 7, 2004
Wagner F. Sacco (Atlanta, GA)
1 out of 12 found this review helpful
This book is regarded as a classic, but the writing style is as soporific as can be. Some scientists should read Gamow or Feynman to learn that one can write a piece of work that's both authoritative and entertaining.
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