Improved Cross-Entropy Method for Estimation

Joshua C. C. Chan and Dirk P. Kroese (2010). Improved Cross-Entropy Method for Estimation. , School of Economics, University of Queensland.

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Author Joshua C. C. Chan
Dirk P. Kroese
Title Improved Cross-Entropy Method for Estimation
School, Department or Centre School of Economics
Institution University of Queensland
Open Access Status Other
Publication date 2010-05-24
Subject 010405 Statistical Theory
140207 Financial Economics
Abstract/Summary The cross-entropy (CE) method is an adaptive importance sampling procedure that has been successfully applied to a diverse range of complicated simulation problems. However, recent research has shown that in some high-dimensional settings, the likelihood ratio degeneracy problem becomes severe and the importance sampling estimator obtained from the CE algorithm becomes unreliable. We consider a variation of the CE method whose performance does not deteriorate as the dimension of the problem increases. We then illustrate the algorithm via a high-dimensional estimation problem in risk management.

Document type: Working Paper
Collection: Working Papers (School of Economics)
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Created: Mon, 24 May 2010, 10:01:43 EST by Joshua Chan on behalf of School of Economics