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Generalized Cross-entropy Methods with Applications to Rare-event Simulation and Optimization.
- Source :
- Simulation; Nov2007, Vol. 83 Issue 11, p785-806, 22p
- Publication Year :
- 2007
-
Abstract
- The cross-entropy and minimum cross-entropy methods are well-known Monte Carlo simulation techniques for rare-event probability estimation and optimization. In this paper, we investigate how these methods can be eXtended to provide a general non-parametric cross-entropy framework based on -divergence distance measures. We show how the χ 2distance, in particular, yields a viable alternative to the Kullback—Leibler distance. The theory is illustrated with various eXamples from density estimation, rare-event simulation and continuous multi-eXtremal optimization. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00375497
- Volume :
- 83
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- Simulation
- Publication Type :
- Academic Journal
- Accession number :
- 30076542
- Full Text :
- https://doi.org/10.1177/0037549707087067