Variance reduction in Monte Carlo estimators via empirical variance minimization

DOI10.1134/S1064562418060261zbMath1409.62146OpenAlexW2899681820WikidataQ128954521 ScholiaQ128954521MaRDI QIDQ1709870

L. S. Iosipoi, Nikita Zhivotovskiy, D. V. Belomestnyij

Publication date: 15 January 2019

Published in: Doklady Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s1064562418060261

zbMATH Keywords

variance minimizationMonte Carlo estimatorscontrol functions

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Monte Carlo methods (65C05) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (6)

Empirical variance minimization with applications in variance reduction and optimal control ⋮ Unbiased Deep Solvers for Linear Parametric PDEs ⋮ A Riemann-Stein kernel method ⋮ Variance reduction for Markov chains with application to MCMC ⋮ Scalable Control Variates for Monte Carlo Methods Via Stochastic Optimization ⋮ Variance Reduction for Dependent Sequences with Applications to Stochastic Gradient MCMC

Cites Work

• Unnamed Item
• Unnamed Item
• Variance reduction for discretised diffusions via regression
• Ranking and empirical minimization of \(U\)-statistics
• Bracketing metric entropy rates and empirical central limit theorems for function classes of Besov- and Sobolev-type
• Simulation and the Monte Carlo Method
• Probability Inequalities for Sums of Bounded Random Variables
• Monte Carlo Methods for Applied Scientists
• Control Functionals for Monte Carlo Integration

This page was built for publication: Variance reduction in Monte Carlo estimators via empirical variance minimization