Derivative based global sensitivity measures

TL;DR

This paper surveys recent advances in derivative-based global sensitivity measures (DGSM), highlighting their advantages, bounds on Sobol' indices, and practical estimation methods, supported by illustrative examples.

Contribution

It provides a comprehensive overview of recent developments in DGSM, including bounds on Sobol' indices and practical estimation techniques.

Findings

DGSM are easy to implement and computationally efficient.

Bounds on Sobol' indices can be effectively used for estimation.

Examples demonstrate practical application of DGSM.

Abstract

The method of derivative based global sensitivity measures (DGSM) has recently become popular among practitioners. It has a strong link with the Morris screening method and Sobol' sensitivity indices and has several advantages over them. DGSM are very easy to implement and evaluate numerically. The computational time required for numerical evaluation of DGSM is generally much lower than that for estimation of Sobol' sensitivity indices. This paper presents a survey of recent advances in DGSM concerning lower and upper bounds on the values of Sobol' total sensitivity indices $S\_{i}^{tot}$. Using these bounds it is possible in most cases to get a good practical estimation of the values of $S\_{i}^{tot} $. Several examples are used to illustrate an application of DGSM.