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Foundations and methods of stochasti...
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Nelson, Barry L.
Foundations and methods of stochastic simulationa first course /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Foundations and methods of stochastic simulationby Barry L. Nelson, Linda Pei.
Reminder of title:
a first course /
Author:
Nelson, Barry L.
other author:
Pei, Linda.
Published:
Cham :Springer International Publishing :2021.
Description:
xvi, 313 p. :ill. (some col.), digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
Stochastic analysis.
Online resource:
https://doi.org/10.1007/978-3-030-86194-0
ISBN:
9783030861940$q(electronic bk.)
Foundations and methods of stochastic simulationa first course /
Nelson, Barry L.
Foundations and methods of stochastic simulation
a first course /[electronic resource] :by Barry L. Nelson, Linda Pei. - Second edition. - Cham :Springer International Publishing :2021. - xvi, 313 p. :ill. (some col.), digital ;24 cm. - International series in operations research & management science,3162214-7934 ;. - International series in operations research & management science ;v. 140..
Chapter 1: Why Do We Simulate -- Chapter 2: Simulation Programming: Quick Start -- Chapter 3: Examples -- Chapter 4: Simulation Programming with PythonSim -- Chapter 5: Three Views of Simulation -- Chapter 6: Simulation Input -- Chapter 7: Simulation Output -- Chapter 8: Experiment Design and Analysis -- Chapter 9: Simulation Optimization and Sensitivity -- Chapter 10: Simulation for Research -- References -- Index.
This graduate-level textbook covers modelling, programming and analysis of stochastic computer simulation experiments, including the mathematical and statistical foundations of simulation and why it works. The book is rigorous and complete, but concise and accessible, providing all necessary background material. Object-oriented programming of simulations is illustrated in Python, while the majority of the book is programming language independent. In addition to covering the foundations of simulation and simulation programming for applications, the text prepares readers to use simulation in their research. A solutions manual for end-of-chapter exercises is available for instructors.
ISBN: 9783030861940$q(electronic bk.)
Standard No.: 10.1007/978-3-030-86194-0doiSubjects--Topical Terms:
183332
Stochastic analysis.
LC Class. No.: QA274.2 / .N45 2021
Dewey Class. No.: 519.22
Foundations and methods of stochastic simulationa first course /
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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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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.
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EB QA274.2 .N424 2021 2021
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https://doi.org/10.1007/978-3-030-86194-0
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