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Stochastic Simulation: Algorithms and Analysis

  • Søren Asmussen
  • Peter W. Glynn

Part of the Stochastic Modelling and Applied Probability book series (SMAP, volume 57)

Table of contents

  1. Front Matter
    Pages I-XIV
  2. What This Book Is About

    1. Front Matter
      Pages 1-1
    2. Søren Asmussen, Peter W. Glynn
      Pages 1-27
  3. General Methods and Algorithms

    1. Front Matter
      Pages 29-29
    2. Søren Asmussen, Peter W. Glynn
      Pages 30-67
    3. Søren Asmussen, Peter W. Glynn
      Pages 68-95
    4. Søren Asmussen, Peter W. Glynn
      Pages 96-125
    5. Søren Asmussen, Peter W. Glynn
      Pages 126-157
    6. Søren Asmussen, Peter W. Glynn
      Pages 158-205
    7. Søren Asmussen, Peter W. Glynn
      Pages 206-241
    8. Søren Asmussen, Peter W. Glynn
      Pages 242-258
  4. Algorithms for Special Models

    1. Front Matter
      Pages 259-259
    2. Søren Asmussen, Peter W. Glynn
      Pages 260-273
    3. Søren Asmussen, Peter W. Glynn
      Pages 274-305
    4. Søren Asmussen, Peter W. Glynn
      Pages 306-324
    5. Søren Asmussen, Peter W. Glynn
      Pages 325-349
    6. Søren Asmussen, Peter W. Glynn
      Pages 350-380
    7. Søren Asmussen, Peter W. Glynn
      Pages 381-441
  5. Back Matter
    Pages 442-476

About this book

Introduction

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.

Keywords

Analysis Gaussian process Lévy process Markov chain Monte Carlo method Sage Stochastic Differential Equations Stochastic Optimization algorithms operations research optimization

Authors and affiliations

  • Søren Asmussen
    • 1
  • Peter W. Glynn
    • 2
  1. 1.Department of Mathematical SciencesAarhus UniversityNy MunkegadeDenmark
  2. 2.Department of Management Science and EngineeringStanford UniversityStanfordUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-69033-9
  • Copyright Information Springer Science+Business Media, LLC 2007
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-387-30679-7
  • Online ISBN 978-0-387-69033-9
  • Series Print ISSN 0172-4568
  • Buy this book on publisher's site
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