Variance-based sensitivity analysis in the presence of correlated input variables

In this paper we propose an extension of the classical Sobol' estimator for the estimation of variance based sensitivity indices. The approach assumes a linear correlation model between the input variables which is used to decompose the contribution of an input variable into a correlated and an uncorrelated part. This method provides sampling matrices following the original joint probability distribution which are used directly to compute the model output without any assumptions or approximations of the model response function.

• Publication year

  2024

• Venue

  arXiv.org

• Publication date

  2024-08-09

• Fields of study

  Mathematics, Computer Science, Engineering

• Identifiers
  DOI 10.48550/arXiv.2408.04933arXiv 2408.04933
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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