Computing the variance of a conditional expectation via non-nested Monte Carlo

DOI10.1016/j.orl.2016.12.002zbMath1409.65005arXiv1605.05454OpenAlexW2405639504MaRDI QIDQ1727950

Takashi Goda

Publication date: 21 February 2019

Published in: Operations Research Letters (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1605.05454

zbMATH Keywords

bias correctionMonte Carlo estimationvariance of a conditional expectation

Mathematics Subject Classification ID

Monte Carlo methods (65C05)

Related Items (6)

Test Comparison for Sobol Indices over Nested Sets of Variables ⋮ Kernel quantile estimators for nested simulation with application to portfolio value-at-risk measurement ⋮ Unnamed Item ⋮ Non-nested estimators for the central moments of a conditional expectation and their convergence properties ⋮ Constructing unbiased gradient estimators with finite variance for conditional stochastic optimization ⋮ Global Sensitivity Analysis and Wasserstein Spaces

Cites Work

• Unnamed Item
• Making best use of model evaluations to compute sensitivity indices
• Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation
• Asymptotic normality and efficiency of two Sobol index estimators
• Higher order Sobol' indices
• Variance Components and Generalized Sobol' Indices
• Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

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