Student Solutions Manual to Accompany

This long awaited Second Edition gives a fully updated and comprehensive account of the major topics in Monte Carlo Method simulation since the early 1980s. The book is geared to a broad audience of readers in engineering, the physical and life sciences, statistics, computer science, and mathematics. The authors aim to provide an accessible introduction to modern MCM, focusing on the main concepts, while providing a sound foundation for problem solving.

Dirk P. Kroese University of Queensland Department of Mathematics Brisbane, Australia Thomas Taimre University of Queensland Department of Mathematics Brisbane, Australia Zdravko I. Botev University of Queensland Department of Mathematics Brisbane, Australia Reuven Y. Rubinstein Technion-Israel Institute of Technology Faculty of Industrial Engineering and Management Haifa, Israel

Preface	p. vii
Acknowledgments	p. ix
Problems	p. 1
Preliminaries	p. 1
Random Number, Random Variable, and Stochastic Process Generation	p. 9
Simulation of Discrete-Event Systems	p. 15
Statistical Analysis of Discrete-Event Systems	p. 19
Controlling the Variance	p. 25
Markov Chain Monte Carlo	p. 31
Sensitivity Analysis and Monte Carlo Optimization	p. 37
The Cross-Entropy Method	p. 41
Counting via Monte Carlo	p. 47
Appendix	p. 51
Solutions	p. 53
Preliminaries	p. 55
Random Number, Random Variable, and Stochastic Process Generation	p. 69
Simulation of Discrete-Event Systems	p. 85
Statistical Analysis of Discrete-Event Systems	p. 95
Controlling the Variance	p. 105
Markov Chain Monte Carlo	p. 123
Sensitivity Analysis and Monte Carlo Optimization	p. 145
The Cross-Entropy Method	p. 151
Counting via Monte Carlo	p. 177
Appendix	p. 187
Table of Contents provided by Ingram. All Rights Reserved.

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Student Solutions Manual to Accompany Simulation and the Monte Carlo Method

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