activity
20192026
most citedNew statistical methodology for second level global sensitivity analysis

13 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

math.ST2026

A Kernel Two-Sample Test Invariant under Group Action with Applications to Functional Data

Madison Giacofci, Anouar Meynaoui, Alex Podgorny

We introduce a kernel-based two-sample test for comparing probability distributions up to group actions. Our construction yields invariant kernels for locally compact -compact g…

math.ST2023

Identifiability of total effects from abstractions of time series causal graphs

Charles K. Assaad, Emilie Devijver, Eric Gaussier +2

We study the problem of identifiability of the total effect of an intervention from observational time series in the situation, common in practice, where one only has access to abs…

stat.ME2022

Second-level global sensitivity analysis of numerical simulators with application to an accident scenario in a sodium-cooled fast reactor

Anouar Meynaoui, Amandine Marrel, Béatrice Laurent

Numerical simulators are widely used to model physical phenomena and global sensitivity analysis (GSA) aims at studying the global impact of the input uncertainties on the simulato…

math.ST2022★ 1 cited

Adaptive nonparametric estimation in the functional linear model with functional output

Gaëlle Chagny, Anouar Meynaoui, Angelina Roche

In this paper, we consider a functional linear regression model, where both the covariate and the response variable are functional random variables. We address the problem of optim…

math.ST2019★ 13 cited

New statistical methodology for second level global sensitivity analysis

Anouar Meynaoui, Amandine Marrel, Béatrice Laurent

Global sensitivity analysis (GSA) of numerical simulators aims at studying the global impact of the input uncertainties on the output. To perform the GSA, statistical tools based o…

math.ST2019

Adaptive test of independence based on HSIC measures

Mélisande Albert, Béatrice Laurent, Amandine Marrel +1

Dependence measures based on reproducing kernel Hilbert spaces, also known as Hilbert-Schmidt Independence Criterion and denoted HSIC, are widely used to statistically decide wheth…