Foundations and methods of stochastic simulation : a first course / Barry L. Nelson, Linda Pei.
Nelson, Barry L., author.; Pei, Linda, author.
2021
QA274.2
Available Online

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Title Foundations and methods of stochastic simulation : a first course / Barry L. Nelson, Linda Pei.
Author Nelson, Barry L., author.
Edition Second edition.
ISBN 9783030861940 (electronic bk.)
3030861945 (electronic bk.)
9783030861933
DOI https://doi.org/10.1007/978-3-030-86194-0
Published Cham, Switzerland : Springer, 2021.
Language English
Description 1 online resource (xvi, 313 pages) : illustrations (some color)
Item Number 10.1007/978-3-030-86194-0 doi
Call Number QA274.2
Dewey Decimal Classification 519.2/2
Summary This graduate-level textbook covers modelling, programming and analysis of stochastic computer simulation experiments, including the mathematical and statistical foundations of simulation and why it works. The book is rigorous and complete, but concise and accessible, providing all necessary background material. Object-oriented programming of simulations is illustrated in Python, while the majority of the book is programming language independent. In addition to covering the foundations of simulation and simulation programming for applications, the text prepares readers to use simulation in their research. A solutions manual for end-of-chapter exercises is available for instructors.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Digital File Characteristics text file
PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed November 15, 2021).
Added Author Pei, Linda, author.
Series International series in operations research & management science ; v. 316. 2214-7934
Available in Other Form Print version: 9783030861933
Print version: 9783030861957
Print version: 9783030861964
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
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Chapter 1: Why Do We Simulate
Chapter 2: Simulation Programming: Quick Start
Chapter 3: Examples
Chapter 4: Simulation Programming with PythonSim
Chapter 5: Three Views of Simulation
Chapter 6: Simulation Input
Chapter 7: Simulation Output
Chapter 8: Experiment Design and Analysis
Chapter 9: Simulation Optimization and Sensitivity
Chapter 10: Simulation for Research
References
Index.

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