This accessible new edition explores the major topics in Monte
Carlo simulation
Simulation and the Monte Carlo Method, Second Edition reflects
the latest developments in the field and 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.
The book begins with a modernized introduction that addresses
the basic concepts of probability, Markov processes, and convex
optimization. Subsequent chapters discuss the dramatic changes that
have occurred in the field of the Monte Carlo method, with coverage
of many modern topics including:
Markov Chain Monte Carlo
Variance reduction techniques such as the transform likelihood
ratio method and the screening method
The score function method for sensitivity analysis
The stochastic approximation method and the stochastic
counter-part method for Monte Carlo optimization
The cross-entropy method to rare events estimation and
combinatorial optimization
Application of Monte Carlo techniques for counting problems,
with an emphasis on the parametric minimum cross-entropy method
An extensive range of exercises is provided at the end of each
chapter, with more difficult sections and exercises marked
accordingly for advanced readers. A generous sampling of applied
examples is positioned throughout the book, emphasizing various
areas of application, and a detailed appendix presents an
introduction to exponential families, a discussion of the
computational complexity of stochastic programming problems, and
sample MATLAB® programs.
Requiring only a basic, introductory knowledge of probability
and statistics, Simulation and the Monte Carlo Method, Second
Edition is an excellent text for upper-undergraduate and beginning
graduate courses in simulation and Monte Carlo techniques. The book
also serves as a valuable reference for professionals who would
like to achieve a more formal understanding of the Monte Carlo
method.
विषयसूची
Preface.
Acknolwedgments.
I: Problems.
1. Preliminaries.
2. Random Number, random Variable, and Stochastic Process
Generation.
3. Simulatin of Discrete-Event Systems.
4. Stastical Analysis of Discrete-Event Systems.
5. Controlling the Variance.
6. Markov Chain Monte Carlo.
7. Sensitivity Analysis and Monte Carlo Optimization.
8. The Cross-Entropy Method.
9. Counting via Monte Carlo.
10. Appendix.
II: Solutions.
11. Prelimiaries.
12. Random Number, Random Variable, and Stochastic Process
Generation.
13. Simulatin of Discrete-Event Systems.
14. Stastical Analysis of Discrete-Event Systems.
15. Controlling the Variance.
16. Markov Chain Monte Carlo.
17. Sensitivity Analysis and Monte Carlo Optimization.
18. The Cross-Entropy Method.
19. Counting via Monte Carlo.
20. Appendix.
लेखक के बारे में
Dirk P. Kroese, Ph D, is Australian Professorial Fellow in Statistics at The University of Queensland. Dr. Kroese has more than seventy publications in such areas as stochastic modeling, randomized algorithms, computational statistics, and reliability. He is a pioneer of the cross-entropy method and the coauthor of Simulation and the Monte Carlo Method, Second Edition.
Thomas Taimre, Ph D, is a Postdoctoral Research Fellow at The University of Queensland. He currently focuses his research on Monte Carlo methods and simulation, from the theoretical foundations to performing computer implementations.
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