Conditional Monte Carlo
Gradient Estimation and Optimization Applications
Authors: Fu, Michael C., Jian-Qiang Hu
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- About this book
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Conditional Monte Carlo: Gradient Estimation and Optimization Applications deals with various gradient estimation techniques of perturbation analysis based on the use of conditional expectation. The primary setting is discrete-event stochastic simulation. This book presents applications to queueing and inventory, and to other diverse areas such as financial derivatives, pricing and statistical quality control. To researchers already in the area, this book offers a unified perspective and adequately summarizes the state of the art. To researchers new to the area, this book offers a more systematic and accessible means of understanding the techniques without having to scour through the immense literature and learn a new set of notation with each paper. To practitioners, this book provides a number of diverse application areas that makes the intuition accessible without having to fully commit to understanding all the theoretical niceties. In sum, the objectives of this monograph are two-fold: to bring together many of the interesting developments in perturbation analysis based on conditioning under a more unified framework, and to illustrate the diversity of applications to which these techniques can be applied.
Conditional Monte Carlo: Gradient Estimation and Optimization Applications is suitable as a secondary text for graduate level courses on stochastic simulations, and as a reference for researchers and practitioners in industry.
- Table of contents (8 chapters)
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Introduction
Pages 1-32
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Three Extended Examples
Pages 33-72
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Conditional Monte Carlo Gradient Estimation
Pages 73-131
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Links to Other Settings
Pages 133-180
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Synopsis and Preview
Pages 181-204
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Table of contents (8 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Conditional Monte Carlo
- Book Subtitle
- Gradient Estimation and Optimization Applications
- Authors
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- Michael C. Fu
- Jian-Qiang Hu
- Series Title
- The Springer International Series in Engineering and Computer Science
- Series Volume
- 392
- Copyright
- 1997
- Publisher
- Springer US
- Copyright Holder
- Springer Science+Business Media New York
- eBook ISBN
- 978-1-4615-6293-1
- DOI
- 10.1007/978-1-4615-6293-1
- Hardcover ISBN
- 978-0-7923-9873-8
- Softcover ISBN
- 978-1-4613-7889-1
- Series ISSN
- 0893-3405
- Edition Number
- 1
- Number of Pages
- XV, 399
- Topics
