Stochastic Simulation: Algorithms and Analysis

Peter W. Glynn

ISBN 10: 144192146X / ISBN 13: 9781441921468

Editore: Springer New York, Springer US, 2010

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value.

Codice articolo 9781441921468

Dati bibliografici

• Titolo: Stochastic Simulation: Algorithms and Analysis
• Editore: Springer New York, Springer US
• Data di pubblicazione: 2010
• Lingua: Inglese
• ISBN 10: 144192146X
• ISBN 13: 9781441921468
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 27 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 27 millimetri di profondità
• Peso: 739 grammi

Descrizione articolo

Riassunto

Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. It is the first rigorous and comprehensive advanced book on stochastic simulation. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focuses on general methods; the second half discusses model-specific algorithms. A large amount of exercises and illustrations are included, making the book of value to students, practitioners and researchers in a broad range of fields.

Dalla quarta di copertina

<p>Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focuses on general methods, whereas the second half discusses model-specific algorithms.</p><p>Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value. </p><p>Søren Asmussen is a professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is the Thomas Ford professor of Engineering at Stanford University. </p>