Overview
- First rigorous and comprehensive advanced book on stochastic simulation
- Large amount of exercises and illustrations included
- Top world wide experts in area
Part of the book series: Stochastic Modelling and Applied Probability (SMAP, volume 57)
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Table of contents (14 chapters)
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Front Matter
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What This Book Is About
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Front Matter
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General Methods and Algorithms
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Front Matter
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Algorithms for Special Models
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Front Matter
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Back Matter
Keywords
About this book
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.
Reviews
From the reviews:
"The adequate statistical simulation of random quantities is one of the challenges of this century. Therefore, sampling-based computational methods have become a fundamental part of the numerical toolset of both practitioners and researchers … . This book provides a descriptive treatment of a variety of such sampling-based methods. Some steps to the mathematical analysis of their convergence properties and diverse applications are sketched as well. … this book is of potential interest to many researchers, students and instructors." (Henri Schurz, Zentralblatt MATH, Vol. 1126 (3), 2008)
"This is a very interesting book for all who are interested in stochastic simulations. … the book is designed as a potential teaching and learning tool for use in a wide variety of courses. … it is a book that should be on the bookshelf of everybody who is seriously interested in stochastic simulations." (EMS Newsletter, September, 2008)
"The present book provides a broad treatment of sampling-based computational methods, as well as accompanying mathematical analysis of the convergence properties of these methods for a wide range of stochastic application problems. … A set of exercises … is also given at the end of each chapter. This book will be a reference of great value for researchers in probability, statistics, operations research, economics, finance, and engineering … . It would also be perfect as a textbook for graduate seminars or courses in stochastic simulation." (Mou-Hsiung Chang, Siam Review, Vol. 51 (1), 2009)
"This book is intended to provide a broad treatment of the basic ideas and algorithms associated with sampling-based methods, often referred to as Monte Carlo algorithms or stochastic simulation. … the book will be very useful to students and researchers from a wide range of disciplines." (John P. Lehoczky, Mathematical Reviews, Issue 2009 c)
"Stochastic Simulation, written by twoprominent researchers in applied probability, is an outgrowth of that maturation. The authors’ goal is not to tell the reader everything known about simulation, nor is it to give a collection of recipes, but rather to provide insight into analyzing problems via simulation. … The book would make an excellent text for a graduate course in simulation, especially in a mathematical sciences department." (Peter C. Kiessler, Journal of the American Statistical Association, Vol. 104 (486), June, 2009)
Authors and Affiliations
Bibliographic Information
Book Title: Stochastic Simulation: Algorithms and Analysis
Authors: Søren Asmussen, Peter W. Glynn
Series Title: Stochastic Modelling and Applied Probability
DOI: https://doi.org/10.1007/978-0-387-69033-9
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag New York 2007
Hardcover ISBN: 978-0-387-30679-7Published: 27 July 2007
Softcover ISBN: 978-1-4419-2146-8Published: 19 November 2010
eBook ISBN: 978-0-387-69033-9Published: 14 July 2007
Series ISSN: 0172-4568
Series E-ISSN: 2197-439X
Edition Number: 1
Number of Pages: XIV, 476
Topics: Probability Theory and Stochastic Processes, Statistical Theory and Methods, Operations Research/Decision Theory, Industrial and Production Engineering, Operations Research, Management Science, Quantitative Finance