Improved cross-entropy method for estimation
نویسندگان
چکیده
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.
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ورودعنوان ژورنال:
- Statistics and Computing
دوره 22 شماره
صفحات -
تاریخ انتشار 2012