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Simulation.

Author: Sheldon M Ross
Publisher: Burlington : Elsevier Science, 2012.
Edition/Format:   eBook : Document : English : 5th edView all editions and formats
Database:WorldCat
Summary:
The 5th edition of Ross's Simulation continues to introduce aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions about future  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Ross, Sheldon M.
Simulation.
Burlington : Elsevier Science, ©2012
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Sheldon M Ross
ISBN: 9780124159716 0124159710
OCLC Number: 880902813
Description: 1 online resource (325 pages)
Contents: Half Title; Title; Copyright; Contents; Preface; Introduction; Elements of Probability; 2.1 Sample Space and Events; 2.2 Axioms of Probability; 2.3 Conditional Probability and Independence; 2.4 Random Variables; 2.5 Expectation; 2.6 Variance; 2.7 Chebyshev's Inequality and the Laws of Large Numbers; 2.8 Some Discrete Random Variables; 2.9 Continuous Random Variables; 2.10 Conditional Expectation and Conditional Variance; Bibliography; Random Numbers; 3.1 Pseudorandom Number Generation; 3.2 Using Random Numbers to Evaluate Integrals; Bibliography; Generating Discrete Random Variables. 4.1 The Inverse Transform Method4.2 Generating a Poisson Random Variable; 4.3 Generating Binomial Random Variables; 4.4 The Acceptance4pt'0137Rejection Technique; 4.5 The Composition Approach; 4.6 The Alias Method for Generating Discrete Random Variables; 4.7 Generating Random Vectors; Generating Continuous Random Variables; 5.1 The Inverse Transform Algorithm; 5.2 The Rejection Method; 5.3 The Polar Method for Generating Normal Random Variables; 5.4 Generating a Poisson Process; 5.5 Generating a Nonhomogeneous Poisson Process; 5.6 Simulating a Two-Dimensional Poisson Process; Bibliography. The Multivariate Normal Distribution and Copulas6.1 The Multivariate Normal; 6.2 Generating a Multivariate Normal Random Vector; 6.3 Copulas; 6.4 Generating Variables from Copula Models; The Discrete Event Simulation Approach; 7.1 Simulation via Discrete Events; 7.2 A Single-Server Queueing System; 7.3 A Queueing System with Two Servers in Series; 7.4 A Queueing System with Two Parallel Servers; 7.5 An Inventory Model; 7.6 An Insurance Risk Model; 7.7 A Repair Problem; 7.8 Exercising a Stock Option; 7.9 Verification of the Simulation Model; Bibliography; Statistical Analysis of Simulated Data. 8.1 The Sample Mean and Sample Variance8.2 Interval Estimates of a Population Mean; 8.3 The Bootstrapping Technique for Estimating MSE; Bibliography; Variance Reduction Techniques; 9.1 The Use of Antithetic Variables; 9.2 The Use of Control Variates; 9.3 Variance Reduction by Conditioning; 9.4 Stratified Sampling; 9.5 Applications of Stratified Sampling; 9.5.1 Analyzing Systems Having Poisson Arrivals; 9.5.2 Computing Multidimensional Integrals of Monotone Functions; 9.5.3 Compound Random Vectors; 9.5.4 The Use of Post-Stratification; 9.6 Importance Sampling; 9.7 Using Common Random Numbers. 9.8 Evaluating an Exotic Option9.9 Appendix: Verification of Antithetic Variable Approach; Bibliography; Additional Variance Reduction Techniques; 10.1 The Conditional Bernoulli Sampling Method; 10.2 Normalized Importance Sampling; 10.3 Latin Hypercube Sampling; Statistical Validation Techniques; 11.1 Goodness of Fit Tests; 11.2 Goodness of Fit Tests When Some Parameters Are Unspecified; 11.3 The Two-Sample Problem; 11.4 Validating the Assumption of a Nonhomogeneous Poisson; Bibliography; Markov Chain Monte Carlo Methods; 12.1 Markov Chains; 12.2 The Hastings4pt'0137Metropolis Algorithm. 12.3 The Gibbs Sampler.

Abstract:

The 5th edition of Ross's Simulation continues to introduce aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions about future outcomes. This latest edition features all-new material on variance reduction, including control variables and their use in estimating the expected return at blackjack and their relati.

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