Simulation / Edition 3

Simulation / Edition 3

by Sheldon M. Ross
     
 

ISBN-10: 0125980531

ISBN-13: 9780125980531

Pub. Date: 01/28/2002

Publisher: Elsevier Science & Technology Books

Ross's Simulation, Fourth Edition introduces 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…  See more details below

Overview

Ross's Simulation, Fourth Edition introduces 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 text explains how a computer can be used to generate random numbers, and how to use these random numbers to generate the behavior of a stochastic model over time. It presents the statistics needed to analyze simulated data as well as that needed for validating the simulation model.

New to this Edition:
-More focus on variance reduction, including control variables and their use in estimating the expected return at blackjack and their relation to regression analysis
-A chapter on Markov chain monte carlo methods with many examples
-Unique material on the alias method for generating discrete random variables

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Product Details

ISBN-13:
9780125980531
Publisher:
Elsevier Science & Technology Books
Publication date:
01/28/2002
Edition description:
Older Edition
Pages:
274
Product dimensions:
6.16(w) x 9.30(h) x 0.74(d)

Table of Contents

1Introduction1
2Elements of probability5
3Random numbers41
4Generating discrete random variables49
5Generating continuous random variables67
6The discrete event simulation approach93
7Statistical analysis of simulated data117
8Variance reduction techniques137
9Statistical validation techniques219
10Markov chain Monte Carlo methods245
11Some additional topics273

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