DocumentCode :
3270514
Title :
Fitting mixture importance sampling distributions via improved cross-entropy
Author :
Brereton, Tim J. ; Chan, Joshua C C ; Kroese, Dirk P.
Author_Institution :
Dept. of Math., Univ. of Queensland, Brisbane, QLD, Australia
fYear :
2011
fDate :
11-14 Dec. 2011
Firstpage :
422
Lastpage :
428
Abstract :
In some rare-event settings, exponentially twisted distributions perform very badly. One solution to this problem is to use mixture distributions. However, it is difficult to select a good mixture distribution for importance sampling. We here introduce a simple adaptive method for choosing good mixture importance sampling distributions.
Keywords :
entropy; importance sampling; statistical distributions; adaptive method; cross-entropy; mixture importance sampling distribution fitting; rare-event probability; Algorithm design and analysis; Australia; Educational institutions; Estimation; Monte Carlo methods; Numerical models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2011 Winter
Conference_Location :
Phoenix, AZ
ISSN :
0891-7736
Print_ISBN :
978-1-4577-2108-3
Electronic_ISBN :
0891-7736
Type :
conf
DOI :
10.1109/WSC.2011.6147769
Filename :
6147769
Link To Document :
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