Dimension-independent single-loop Monte Carlo simulation method for estimate of Sobol’ indices in variance-based sensitivity analysis

Zhiqiang Wan, Silong Wang, Ziyan Wu and Xiuli Wang

Reliability Engineering and System Safety, 2025, vol. 263, issue C

Abstract: This contribution presents a novel approach for estimating the Sobol’ index, which has been commonly employed in variance-based sensitivity analysis of computational models that may often involve multiple uncertain parameters. Specifically, a single-loop Monte Carlo simulation (MCS) method, which is independent of the dimensionality of inputs, is proposed to reduce the computational cost of complicated models. The proposed method is realized by developing a new estimator of the Sobol’ index computed via the two-dimensional kernel density estimation, which can be easy programming while ensuring high accuracy. Numerical examples are studied to demonstrate the advantages of the proposed method.

Keywords: Uncertainty quantification; Monte Carlo simulation; Variance-based sensitivity analysis; Kernel density estimation (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:263:y:2025:i:c:s0951832025004375

DOI: 10.1016/j.ress.2025.111236

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