Stochastic Simulation: Algorithms and Analysis 2007 Edition Contributor(s): Asmussen, Søren (Author), Glynn, Peter W. (Author) |
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ISBN: 038730679X ISBN-13: 9780387306797 Publisher: Springer OUR PRICE: $61.74 Product Type: Hardcover - Other Formats Published: July 2007 Annotation: 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. S?ren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of Engineering at Stanford University. |
Additional Information |
BISAC Categories: - Mathematics | Probability & Statistics - General - Business & Economics | Finance - General - Business & Economics | Operations Research |
Dewey: 519.23 |
LCCN: 2007926471 |
Series: Stochastic Modelling and Applied Probability |
Physical Information: 1.1" H x 6.49" W x 9.38" (1.82 lbs) 476 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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. S ren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of Engineering at Stanford University. |