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Foundations and Methods of Stochastic Simulation [electronic resource] : A First Course / by Barry L. Nelson.

Por: Tipo de material: TextoTextoSeries International Series in Operations Research & Management Science ; 187 | International Series in Operations Research & Management Science ; 187Editor: Boston, MA : Springer US : Imprint: Springer, 2013Descripción: XIV, 276 p. 53 illus., 11 illus. in color. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9781461461609
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 658.40301 23
Clasificación LoC:
  • HD30.23
Recursos en línea:
Contenidos:
Springer eBooksResumen: This graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous treatment of the foundations of simulation and why it works. It introduces object-oriented programming for simulation, covers both the probabilistic and statistical basis for simulation in a rigorous but accessible manner (providing all necessary background material), and provides a modern treatment of experiment design and analysis that goes beyond classical statistics. The book emphasizes essential foundations throughout, rather than providing a compendium of algorithms and theorems, and prepares the reader to use simulation in research as well as practice. The book is a rigorous but concise treatment, emphasizing lasting principles, but also providing specific training in modeling, programming and analysis. In addition to teaching readers how to do simulation, it also prepares them to use simulation in their research; no other book does this.
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Why Do We Simulate? -- Simulation Programming: Quick Start -- Examples -- Simulation Programming with VBASim -- Two Views of Simulation -- Simulation Input -- Simulation Output -- Experiment Design and Analysis -- Simulation for Research -- VBASim.

This graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous treatment of the foundations of simulation and why it works. It introduces object-oriented programming for simulation, covers both the probabilistic and statistical basis for simulation in a rigorous but accessible manner (providing all necessary background material), and provides a modern treatment of experiment design and analysis that goes beyond classical statistics. The book emphasizes essential foundations throughout, rather than providing a compendium of algorithms and theorems, and prepares the reader to use simulation in research as well as practice. The book is a rigorous but concise treatment, emphasizing lasting principles, but also providing specific training in modeling, programming and analysis. In addition to teaching readers how to do simulation, it also prepares them to use simulation in their research; no other book does this.

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