Estimation of global sensitivity indices for models with dependent variables

By Sergei S. Kucherenko, Stefano Tarantola, Paola Annoni. Computer Physics Communications, 2012

337 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Mechanics of Materials, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d0959c8ed9403de0334b5ecac1ba2728c5ff095a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Thorsten Wagener
2. Francesca Pianosi
3. Clémentine Prieur
4. Bertrand Iooss
5. Elmar Plischke
6. Keith Beven
7. Jim W. Hall
8. David B. Stephenson

In Mechanics of Materials

1. Curtis L. Smith
2. Emanuele Borgonovo
3. Elmar Plischke
4. Clémentine Prieur
5. Francesca Pianosi
6. Bertrand Iooss
7. Thorsten Wagener

In Statistics and Probability

1. Thorsten Wagener
2. Francesca Pianosi
3. Clémentine Prieur
4. Bertrand Iooss
5. Elmar Plischke
6. Keith Beven
7. Jim W. Hall
8. David B. Stephenson

Citations in the corpus

• The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020, neutral): “…extensions of the Hoeffding--Sobol ’ decomposition (Chastaing et al., 2012), regression-based methods (Xu and Gertner, 2008), copula-based methods (Kucherenko, 2012; Do and Razavi, 2020; Sheikholeslami et al., 2020) and game-theory concepts (Owen, 2014; Owen and Prieur, 2017; Iooss and Prieur,…”
• Global sensitivity measures from given data (2013, background): “In the presence of input dependencies, the computational cost increases (Kucherenko et al., 2012).”
• Generalized Hoeffding-Sobol Decomposition for Dependent Variables -Application to Sensitivity Analysis (2011, neutral): “[19] proposed to use first order and total sensitivity indices based on the classical decomposition of total variance.”
• SHAPLEY EFFECTS FOR SENSITIVITY ANALYSIS WITH CORRELATED INPUTS: COMPARISONS WITH SOBOL' INDICES, NUMERICAL ESTIMATION AND APPLICATIONS (2017, positive): “The numerical tests of [16] have inspired the ones proposed in this section.”
• A Generalized ANOVA Dimensional Decomposition for Dependent Probability Measures (2014, neutral): “[12], and Chastaing et al [3], are available for models with dependent or correlated input.”
• The Complexities of Agent-Based Modeling Output Analysis (2015, methodology): “While recent methods addressing these dependencies have been developed (Kucherenko et al. 2012; Mara & Tarantola 2012; Zuniga et al. 2013), they still require elaborate DOE coupled with a very large sample size and algorithmic complexity.”
• Sensitivity analysis of environmental models: A systematic review with practical workflow (2014, background): “For example one might observe total-order indices smaller than fi rst-order ones for negative correlations or total-order indices tending to zero as correlation grows to unity (Kucherenko et al., 2012).”
• Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications (2015, neutral): “Many techniques have been proposed to generalize variance-based SA methods to correlated or dependent variables (Kucherenko et al., 2012; Xu, 2013), but have been very few successful applications in hydrological modeling.”