Generalized Cross-Entropy Methods With Applications To Rare-Event Simulation And Optimization  

Oleh:

Botev, Z. I. ; Kroese, D. P. ; Taimre, T.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Simulation vol. 83 no. 11 (Nov. 2007), page 785-806.
Topik: generalized cross-entropy; maximum entropy method; cross-entropy method; rare-event simulation; stochastic optimization; Csisár’s -divergence
Fulltext: 785.pdf (916.01KB)

Isi artikel

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 distance, 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.

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