8 citations · 18 across the 18 of their papers we have counts for
11 papers · 1 filter
Asymptotic efficiency for Sobol' and Cram{é}r-von Mises indices under two designs of experiments
Thierry Klein, Agnès Lagnoux, Paul Rochet +1
A variety of indices aim to quantify the impact of input variables on a response, typically the output from a complex computer code or black-box model. Most commonly used, the Sobo…
Contraction rates and projection subspace estimation with Gaussian process priors in high dimension
Elie Odin, François Bachoc, Agnès Lagnoux
This work explores the dimension reduction problem for Bayesian nonparametric regression and density estimation. More precisely, we are interested in estimating a functional parame…
Sensitivity analysis from a single input/output sample
Sébastien Da Veiga, Fabrice Gamboa, Thierry Klein +2
The main objective of this paper is to estimate optimally Sobol' indices at any order when a unique input/output i.i.d.\ sample is available. Our approach stands on three main ingr…
Posterior contraction rates for constrained deep Gaussian processes in density estimation and classication
François Bachoc, Agnès Lagnoux
We provide posterior contraction rates for constrained deep Gaussian processes in non-parametric density estimation and classication. The constraints are in the form of bounds on t…
Global sensitivity analysis and Wasserstein spaces
Jean-Claude Fort, Thierry Klein, Agnès Lagnoux
Sensitivity indices are commonly used to quantity the relative inuence of any specic group of input variables on the output of a computer code. In this paper, we focus both on comp…
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…
Sensitivity analysis in general metric spaces
Fabrice Gamboa, Thierry Klein, Agnès Lagnoux +1
In this paper, we introduce new indices adapted to outputs valued in general metric spaces. This new class of indices encompasses the classical ones; in particular, the so-called S…
Semi-parametric estimation of the variogram of a Gaussian process with stationary increments
Jean-Marc Azaïs, François Bachoc, Agnès Lagnoux +1
We consider the semi-parametric estimation of a scale parameter of a one-dimensional Gaussian process with known smoothness. We suggest an estimator based on quadratic variations a…
Maximum likelihood estimation for Gaussian processes under inequality constraints
François Bachoc, Agnès Lagnoux, Andrés F. López-Lopera
We consider covariance parameter estimation for a Gaussian process under inequality constraints (boundedness, monotonicity or convexity) in fixed-domain asymptotics. We address the…
On the Bickel-Rosenblatt test of goodness-of-fit for the residuals of autoregressive processes
Agnès Lagnoux, Thi Mong Ngoc Nguyen, Frédéric Proïa
We investigate in this paper a Bickel-Rosenblatt test of goodness-of-fit for the density of the noise in an autoregressive model. Since the seminal work of Bickel and Rosenblatt, i…
Cross-validation estimation of covariance parameters under fixed-domain asymptotics
Francois Bachoc, Agnes Lagnoux, Thi Mong Ngoc Nguyen
We consider a one-dimensional Gaussian process having exponential covariance function. Under fixed-domain asymptotics, we prove the strong consistency and asymptotic normality of a…