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Conditional Monte Carlo
Michael C. Fu
Jian-Qiang Hu
其他書名
Gradient Estimation and Optimization Applications
出版
Springer Science & Business Media
, 2012-12-06
主題
Computers / Data Science / General
Mathematics / Probability & Statistics / General
Science / System Theory
Mathematics / Calculus
Mathematics / Discrete Mathematics
Computers / Information Technology
Language Arts & Disciplines / Library & Information Science / General
Mathematics / Functional Analysis
ISBN
1461562937
9781461562931
URL
http://books.google.com.hk/books?id=1n3gBwAAQBAJ&hl=&source=gbs_api
EBook
SAMPLE
註釋
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.