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Introduction to Rare Event Simulation

Author: James Antonio Bucklew
Publisher: New York, NY : Springer New York, 2004.
Series: Springer series in statistics.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book presents a unified theory of rare event simulation and the variance reduction technique known as importance sampling from the point of view of the probabilistic theory of large deviations. This perspective allows us to view a vast assortment of simulation problems from a unified single perspective. It gives a great deal of insight into the fundamental nature of rare event simulation. Until now, this area  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: James Antonio Bucklew
ISBN: 9781475740783 1475740786 0387200789 9780387200781
OCLC Number: 851702826
Description: 1 online resource (xi, 262 pages).
Contents: Random Number Generation --
Stochastic Models --
Large Deviation Theory --
Importance Sampling --
The Large Deviation Theory of Importance Sampling Estimators --
The Large Deviation Theory of Conditional Importance Sampling Estimators --
The Large Deviations of Bias Point Selection --
Chernoff's Bound and Asymptotic Expansions --
Gaussian Systems --
Universal Simulation Distributions --
Rare Event Simulation for Level Crossing and Queueing Models --
Blind Simulation --
The (Over- Under) Biasing Problem in Importance Sampling --
Tools and Techniques for Importance Sampling.
Series Title: Springer series in statistics.
Responsibility: by James Antonio Bucklew.

Abstract:

This book presents a unified theory of rare event simulation and the variance reduction technique known as importance sampling from the point of view of the probabilistic theory of large deviations.  Read more...

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From the reviews:"On the whole, Introduction to Rare Event Simulation succeeds at its stated goal, providing a good overview of importance sampling from the perspective of large deviations." Journal Read more...

 
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