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Simulation

Ross Sheldon M.
Innbundet / 2022 / Engelsk

Product details

ISBN
9780323857390
Published
2022-12-14
Edition
6. edition
Publisher
Elsevier Science & Technology
Weight
680 gr
Height
229 mm
Width
152 mm
Age
U, 05
Language
Product language
Engelsk
Format
Product format
Innbundet
Number of pages
336

Author
Ross Sheldon M.

Biographical note

Dr. Sheldon M. Ross is a professor in the Department of Industrial and Systems Engineering at the University of Southern California. He received his PhD in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, a Fellow of INFORMS, and a recipient of the Humboldt US Senior Scientist Award.

Simulation

Ross Sheldon M.
Innbundet / 2022 / Engelsk
Ross Sheldon M.
Innbundet / 2022 / Engelsk
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"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 Mackevičius, zbMATH Open

Simulation, Sixth Edition 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 will learn to apply the results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions. By explaining 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, this book presents the statistics needed to analyze simulated data and validate simulation models.
Read more
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
Read more
Provides an introduction to simulation for computational statistics, including generating random numbers and gauging behavior of a stochastic model over time
Includes updated content throughout Offers a wealth of practice exercises as well as applied use of free software package R Features the author’s well-known, award-winning and accessible approach to complex information
Read more

Related products

"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 Mackevičius, zbMATH Open

Simulation, Sixth Edition 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 will learn to apply the results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions. By explaining 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, this book presents the statistics needed to analyze simulated data and validate simulation models.
Read more
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
Read more
Provides an introduction to simulation for computational statistics, including generating random numbers and gauging behavior of a stochastic model over time
Includes updated content throughout Offers a wealth of practice exercises as well as applied use of free software package R Features the author’s well-known, award-winning and accessible approach to complex information
Read more

Product details

ISBN
9780323857390
Published
2022-12-14
Edition
6. edition
Publisher
Elsevier Science & Technology
Weight
680 gr
Height
229 mm
Width
152 mm
Age
U, 05
Language
Product language
Engelsk
Format
Product format
Innbundet
Number of pages
336

Author
Ross Sheldon M.

Biographical note

Dr. Sheldon M. Ross is a professor in the Department of Industrial and Systems Engineering at the University of Southern California. He received his PhD in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, a Fellow of INFORMS, and a recipient of the Humboldt US Senior Scientist Award.

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