Description

Book Synopsis


Trade Review
"This textbook contains and describes all the tools one needs to plan and to carry out a simulation study as well as to analyze its results." --J.Wolters, zbMATH Open "It presents the statistics needed to analyze simulated data and to validate the simulation model. In this edition, several new topics are included as well as a number of new exercises." --Vigirdas Mackevicius, zbMATH Open

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

Simulation

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    £69.26

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    RRP £76.95 – you save £7.69 (9%)

    Order before 4pm tomorrow for delivery by Tue 4 Aug 2026.

    A Hardback by Sheldon M. Ross

    10 in stock

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      Publisher: Elsevier Science & Technology
      Publication Date: Publication Date: 14/12/2022
      ISBN13: 9780323857390, 978-0323857390
      ISBN10: 0323857396
      Also in:
      Mathematics Probability and statistics Stochastics

      Description

      Book Synopsis


      Trade Review
      "This textbook contains and describes all the tools one needs to plan and to carry out a simulation study as well as to analyze its results." --J.Wolters, zbMATH Open "It presents the statistics needed to analyze simulated data and to validate the simulation model. In this edition, several new topics are included as well as a number of new exercises." --Vigirdas Mackevicius, zbMATH Open

      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

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