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Simulation And The Monte Carlo Method

This accessible new edition explores the major topics in Monte Carlo simulation that have arisen over the past 30 years and presents a sound foundation for problem solving Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the state-of-the-art theory, methods and applications that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago

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A second new chapter introduces the stochastic enumeration method, which is a new fast sequential Monte Carlo method for tree search

An extensive range of exercises is provided at the end of each chapter, as well as a generous sampling of applied examples

Dirk P

He has published over 100 articles and four books in a wide range of areas in applied probability and statistics, including Monte Carlo methods, cross-entropy, randomized algorithms, tele-traffic c theory, reliability, computational statistics, applied probability, and stochastic modeling.

He served as a consultant at numerous large-scale organizations, such as IBM, Motorola, and NEC

In addition, the Third Edition features new material on Random number generation, including multiple-recursive generators and the Mersenne Twister Simulation of Gaussian processes, Brownian motion, and diffusion processes Multilevel Monte Carlo method New enhancements of the cross-entropy CE method, including the improved CE method, which uses sampling from the zero-variance distribution to find the optimal importance sampling parameters Over 100 algorithms in modern pseudo code with flow control Over 25 new exercises Simulation and the Monte Carlo Method, Third Edition is an excellent

Kroese, PhD, is a Professor of Mathematics and Statistics in the School of Mathematics and Physics of The University of Queensland, Australia

Reuven Y

Rubinstein was also the inventor of the popular score-function method in simulation analysis and generic cross-entropy methods for combinatorial optimization and counting

Rubinstein, DSc, was Professor Emeritus in the Faculty of Industrial Engineering and Management at Technion-Israel Institute of Technology

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 importance re- sampling, and the transform likelihood ratio 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 for rare events estimation and combinatorial optimization, and application of Monte Carlo techniques for counting problems

The Third Edition features a new chapter on the highly versatile splitting method, with applications to rare-event estimation, counting, sampling, and optimization

The author of over 100 articles and six books, Dr

The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method

The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization

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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