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Foundations and methods of stochasti...

Nelson, Barry L.

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Foundations and methods of stochastic simulation = a first course /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Foundations and methods of stochastic simulation/ by 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.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Stochastic analysis. -
Online resource:	https://doi.org/10.1007/978-3-030-86194-0
ISBN:	9783030861940

Foundations and methods of stochastic simulation = a first course /
Nelson, Barry L.

Foundations and methods of stochastic simulationa 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 ;316..

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

Standard No.: 10.1007/978-3-030-86194-0doiSubjects--Topical Terms:

533923
Stochastic analysis.

LC Class. No.: QA274.2 / .N45 2021

Dewey Class. No.: 519.22

Foundations and methods of stochastic simulation = a first course /
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245 1 0 $a Foundations and methods of stochastic simulation $h [electronic resource] : $b a first course / $c by Barry L. Nelson, Linda Pei.
250 $a Second edition.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xvi, 313 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a International series in operations research & management science, $x 2214-7934 ; $v 316
505 0 $a 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.
520 $a 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.
650 0 $a Stochastic analysis. $3 533923
650 0 $a Simulation methods. $3 581321
650 0 $a Stochastic processes $x Mathematical models. $3 587808
650 1 4 $a Operations Research/Decision Theory. $3 890895
650 2 4 $a Operations Research, Management Science. $3 1532996
650 2 4 $a Simulation and Modeling. $3 890873
650 2 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 3382132
700 1 $a Pei, Linda. $3 3531360
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a International series in operations research & management science ; $v 316. $3 3531361
856 4 0 $u https://doi.org/10.1007/978-3-030-86194-0
950 $a Business and Management (SpringerNature-41169)