Efficient rare event simulation for heavy-tailed systems via cross entropy
| Autor: | Yixi Shi, Jose Blanchet |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Mathematical optimization
Applied Mathematics Cross-entropy method Estimator Management Science and Operations Research Industrial and Manufacturing Engineering Binary entropy function Cross entropy Maximum entropy probability distribution Applied mathematics Parametric family Software Importance sampling Parametric statistics Mathematics |
| Zdroj: | Operations Research Letters. 41:271-276 |
| ISSN: | 0167-6377 |
| DOI: | 10.1016/j.orl.2013.02.004 |
| Popis: | The cross entropy method is an iterative technique that is used to obtain a low-variance importance sampling (IS) distribution from a given parametric family, which must satisfy two properties. First, subsequent iterations of the parameters must be easily computable and, second, the family should approximate the zero-variance IS distribution. We obtain parametric families for which these two properties are satisfied for a large class of heavy-tailed systems. Our estimators are shown to be strongly efficient in these settings. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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