Variance Reduction in Monte Carlo Estimators via Empirical Variance Minimization

被引：6

作者：

Belomestny, D. V. ^{[1
,2
,3
]}

Iosipoi, L. S. ^{[1
,4
]}

Zhivotovskiy, N. K. ^{[1
,2
,3
,5
]}

机构：

[1] Natl Res Univ, Higher Sch Econ, Moscow, Russia

[2] Univ Duisburg Essen, Duisburg, Germany

[3] Univ Duisburg Essen, Essen, Germany

[4] Moscow MV Lomonosov State Univ, Fac Mech & Math, Moscow, Russia

[5] Russian Acad Sci, Inst Informat Transmiss Problems, Moscow, Russia

来源：

DOKLADY MATHEMATICS | 2018年 / 98卷 / 02期

基金：

俄罗斯科学基金会;

关键词：

D O I：

10.1134/S1064562418060261

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

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.

引用

页码：494 / 497

页数：4

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