电邮这篇文章 Variance Reduction in Monte Carlo Estimators via Empirical Variance Minimization
- 作者: Belomestny D.1,2, Iosipoi L.1,3, Zhivotovskiy N.1,2,4
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隶属关系:
- National Research University Higher School of Economics
- University of Duisburg-Essen
- Faculty of Mechanics and Mathematics
- Institute for Information Transmission Problems
- 期: 卷 98, 编号 2 (2018)
- 页面: 494-497
- 栏目: Mathematics
- URL: https://journals.rcsi.science/1064-5624/article/view/225565
- DOI: https://doi.org/10.1134/S1064562418060261
- ID: 225565
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详细
For Monte Carlo estimators, a variance reduction method based on empirical variance minimization in the class of functions with zero mean (control functions) is described. An upper bound for the efficiency of the method is obtained in terms of the properties of the functional class.
作者简介
D. Belomestny
National Research University Higher School of Economics; University of Duisburg-Essen
Email: iosipoileonid@gmail.com
俄罗斯联邦, Moscow; Duisburg and Essen
L. Iosipoi
National Research University Higher School of Economics; Faculty of Mechanics and Mathematics
编辑信件的主要联系方式.
Email: iosipoileonid@gmail.com
俄罗斯联邦, Moscow; Moscow
N. Zhivotovskiy
National Research University Higher School of Economics; University of Duisburg-Essen; Institute for Information Transmission Problems
Email: iosipoileonid@gmail.com
俄罗斯联邦, Moscow; Duisburg and Essen; Moscow
