Simulation 5/e
售價
$
1,250
- 一般書籍
- ISBN：9780124158252
- 作者：Sheldon M. Ross
- 版次：5
- 年份：2013
- 出版商：Elsevier B.V.
- 頁數/規格：310頁/精裝單色
書籍介紹
本書特色
目錄
Description
The fifth edition of Sheldon Ross’ best-selling Simulation provides a practical introduction to utilizing computerized simulation to analyze stochastic models. These simulations are applied to problems in a wide variety of fields, including the physical and social sciences, engineering, and mathematics, to obtain effective, accurate solutions.
Simulation Fifth Edition includes the new Chapter 6, dealing with copulas, useful for modeling the joint distribution of random variables, as well as with the multivariate normal distribution. Another new chapter is Chapter 10, which introduces additional variance reduction methods. Whereas such standard variance reduction techniques as the use of antithetic variables, control variables, conditional expectation estimators, importance sampling, and stratified sampling are studied in Chapter 9, the new chapter introduces the conditional Bernoulli sampling method, normalized importance sampling, and Latin Hypercube sampling.
The fifth edition of Sheldon Ross’ best-selling Simulation provides a practical introduction to utilizing computerized simulation to analyze stochastic models. These simulations are applied to problems in a wide variety of fields, including the physical and social sciences, engineering, and mathematics, to obtain effective, accurate solutions.
Simulation Fifth Edition includes the new Chapter 6, dealing with copulas, useful for modeling the joint distribution of random variables, as well as with the multivariate normal distribution. Another new chapter is Chapter 10, which introduces additional variance reduction methods. Whereas such standard variance reduction techniques as the use of antithetic variables, control variables, conditional expectation estimators, importance sampling, and stratified sampling are studied in Chapter 9, the new chapter introduces the conditional Bernoulli sampling method, normalized importance sampling, and Latin Hypercube sampling.
Features
- Presents the statistics methods needed to analyze simulated data, and to validate the simulation model
- Provides applied examples throughout the text – such as multiple server queuing models, inventory control, and exercising stock options – to illustrate and motivate the theory
- Stresses variance reduction
- Includes a chapter on Markov chain Monte Carlo methods
Table of Contents
1.Introduction
2.Elements of Probability
3.Random Numbers
4.Generating Discrete Random Variables
5.Generating Continuous Random Variables
6.The Multivariate Normal Distribution and Copulas
7.The Discrete Event Simulation Approach
8.Statistical Analysis of Simulated Data
9.Variance Reduction Techniques
10.Additional Variance Reduction Techniques
11.Statistical Validation Techniques
12.Markov Chain Monte Carlo Methods
1.Introduction
2.Elements of Probability
3.Random Numbers
4.Generating Discrete Random Variables
5.Generating Continuous Random Variables
6.The Multivariate Normal Distribution and Copulas
7.The Discrete Event Simulation Approach
8.Statistical Analysis of Simulated Data
9.Variance Reduction Techniques
10.Additional Variance Reduction Techniques
11.Statistical Validation Techniques
12.Markov Chain Monte Carlo Methods
