8 citations · 22 across the 5 of their papers we have counts for
10 papers
Global Sensitivity Analysis: a novel generation of mighty estimators based on rank statistics
Fabrice Gamboa, Pierre Gremaud, Thierry Klein +1
We propose a new statistical estimation framework for a large family of global sensitivity analysis indices. Our approach is based on rank statistics and uses an empirical correlat…
Variance-based sensitivity of Bayesian inverse problems to the prior distribution
John E. Darges, Alen Alexanderian, Pierre A. Gremaud
The formulation of Bayesian inverse problems involves choosing prior distributions; choices that seem equally reasonable may lead to significantly different conclusions. We develop…
Multiscale global sensitivity analysis for stochastic chemical systems
Michael Merritt, Alen Alexanderian, Pierre A. Gremaud
Sensitivity analysis is routinely performed on simplified surrogate models as the cost of such analysis on the original model may be prohibitive. Little is known in general about t…
Global Sensitivity Analysis: a new generation of mighty estimators based on rank statistics
Fabrice Gamboa, Pierre Gremaud, Thierry Klein +1
We propose a new statistical estimation framework for a large family of global sensitivity analysis methods. Our approach is based on rank statistics and uses an empirical correlat…
Global Sensitivity Analysis of High Dimensional Neuroscience Models: An Example of Neurovascular Coupling
J. L. Hart, P. A. Gremaud, T. David
The complexity and size of state-of-the-art cell models have significantly increased in part due to the requirement that these models possess complex cellular functions which are t…
Robustness of the Sobol' indices to distributional uncertainty
Joseph Hart, Pierre Gremaud
Global sensitivity analysis (GSA) is used to quantify the influence of uncertain variables in a mathematical model. Prior to performing GSA, the user must specify (or implicitly as…