A comparison of cross-entropy and variance minimization strategies

Chan, Joshua. C., Glynn, Peter W. and Kroese, Dirk P. (2011) A comparison of cross-entropy and variance minimization strategies. Journal of Applied Probability, 48 A : 1-15.

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Author Chan, Joshua. C.
Glynn, Peter W.
Kroese, Dirk P.
Title A comparison of cross-entropy and variance minimization strategies
Journal name Journal of Applied Probability   Check publisher's open access policy
ISSN 0021-9002
Publication date 2011
Year available 2010
Sub-type Article (original research)
Volume 48 A
Start page 1
End page 15
Total pages 15
Place of publication United Kingdom
Publisher Applied Probability Trust
Collection year 2011
Language eng
Abstract The variance minimization (VM) and cross-entropy (CE) methods are two versatile adaptive importance sampling procedures that have been successfully applied to a wide variety of difficult rare-event estimation problems. We compare these two methods via various examples where the optimal VM and CE importance densities can be obtained analytically. We find that in the cases studied both VM and CE methods prescribe the same importance sampling parameters, suggesting that the criterion of minimizing the cross- entropy distance might be asymptotically identical to minimizing the variance of the associated importance sampling estimator.
Keyword Variance minimization
Cross-entropy
Importance sampling
Rare- event simulation
Likelihood ratio degeneracy
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
Official 2011 Collection
 
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Created: Tue, 15 Mar 2011, 10:14:08 EST by Prof Dirk P. Kroese on behalf of Mathematics