Stochastic Simulation: Algorithms and Analysis

Søren Asmussen|Peter W. Glynn

ISBN 10: 038730679X / ISBN 13: 9780387306797

Published by Springer New York, 2007

About this Item

First rigorous and comprehensive advanced book on stochastic simulationLarge amount of exercises and illustrations includedTop world wide experts in areaSampling-based computational methods have become a fundamental part of the n.

Seller Inventory # 5909889

Bibliographic Details

• Title: Stochastic Simulation: Algorithms and Analysis
• Publisher: Springer New York
• Publication Date: 2007
• Language: English
• ISBN 10: 038730679X
• ISBN 13: 9780387306797
• Binding: Hardcover
• Condition: New

About this title

Synopsis

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.

From the Back Cover

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.

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.

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.