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Variance Reduction in Monte Carlo Estimators via Empirical Variance Minimization

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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.

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Correspondence to L. S. Iosipoi.

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Original Russian Text © D.V. Belomestny, L.S. Iosipoi, N.K. Zhivotovskiy, 2018, published in Doklady Akademii Nauk, 2018, Vol. 482, No. 6.

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Belomestny, D.V., Iosipoi, L.S. & Zhivotovskiy, N.K. Variance Reduction in Monte Carlo Estimators via Empirical Variance Minimization. Dokl. Math. 98, 494–497 (2018).

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