Simulation and the Monte Carlo Method
This accessible new edition explores the major topics in MonteCarlo simulation
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:
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.
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Random Number Random Variable
Simulation of DiscreteEvent Systems
Counting viaMonte Carlo
Markov ChainMonte Carlo
Statistical Analysisof DiscreteEvent Systems 4 1 Introduction 4 2 Static Simulation Models
Sensitivity Analysisand MonteCarlo Optimization
The CrossEntropy Method
and Decision Making 9 7 Numerical Results
Abbreviations and Acronyms