„The book is clearly written and easy to read for people withmathematical background.... The material of the book is useful inmost areas of the nowadays research work.“ (InternationalStatistical Review, April 2009)
„I enjoyed reading the book, and found the individual examplesquite interesting.“ (Biometrics, December 2008)
„I enjoyed reading the book, and found the individual examplesquite interesting.“ (Biometrics, December 2008)
„.. if you need to learn how to use Monte Carlo in yoursimulations, this is probably the best single document I have everread. “(Computing Reviews, September 2008)
„Rubinstein and Kroese did an exemplary job of addressing majorissues and providing much needed updated information in this area.“(CHOICE, June 2008)
„the book is nicely written and the additional to the book fromthe 1st edition certainly make it more attractive to a wideraudience. I would recommend it to students and practioners withappropriate background.“ (MAA Review March 2008)
Simulation and the Monte Carlo Method, Second Editionreflects the latest developments in the field and presents a fullyupdated and comprehensive account of the major topics that haveemerged in Monte Carlo simulation since the publication of theclassic First Edition over twenty-five years ago. Whilemaintaining its accessible and intuitive approach, this revisededition features a wealth of up-to-date information thatfacilitates a deeper understanding of problem solving across a widearray of subject areas, such as engineering, statistics, computerscience, mathematics, and the physical and life sciences.
The book begins with a modernized introduction that addressesthe basic concepts of probability, Markov processes, and convexoptimization. Subsequent chapters discuss the dramatic changes thathave occurred in the field of the Monte Carlo method, with coverageof many modern topics including:
* Markov Chain Monte Carlo
* Variance reduction techniques such as the transform likelihoodratio method and the screening method
* The score function method for sensitivity analysis
* The stochastic approximation method and the stochasticcounter-part method for Monte Carlo optimization
* The cross-entropy method to rare events estimation andcombinatorial optimization
* Application of Monte Carlo techniques for counting problems, with an emphasis on the parametric minimum cross-entropymethod
An extensive range of exercises is provided at the end of eachchapter, with more difficult sections and exercises markedaccordingly for advanced readers. A generous sampling of appliedexamples is positioned throughout the book, emphasizing variousareas of application, and a detailed appendix presents anintroduction to exponential families, a discussion of thecomputational complexity of stochastic programming problems, andsample MATLAB programs.
Requiring only a basic, introductory knowledge of probabilityand statistics, Simulation and the Monte Carlo Method, Second Edition is an excellent text for upper-undergraduate andbeginning graduate courses in simulation and Monte Carlotechniques. The book also serves as a valuable reference forprofessionals who would like to achieve a more formal understandingof the Monte Carlo method.
