Contact

Email: Sylvie.Huet AT jouy.inra.fr Mailing address: INRA UNITÉ MAIAGE Domaine de Vilvert 78352 Jouy-en-Josas Cedex - FRANCE - Tél: (+33) (0)1 34 65 22 24 Fax: (+33) (0)1 34 65 22 17 Secretary: (+33) (0)1 34 65 22 31

Research Topics

I am working on statistical models usefull for analysing data observed by biologists working at INRA.

• More particularly I studied nonlinear regression models with heteroscedastic variances and non parametric regression models proposing methods for inference based on bootstrap. These models are widely used for estimating dose response relationships.
• I also proposed goodness of fit tests for testing the validity of a regression model.
• I worked on model selection procedures for detecting non-zero components in a gaussian vector, for estimating change points in a signal or for selecting variables among a large set of variables. I also considered procedures for selecting estimators in the context of estimating graphical gaussian models, and in the Gaussian regression model.
• I am now interested in the application of this machinery to metamodels estimation and sensitivity indices estimation.
• I also consider estimation of shape-constrained discrete density, and application to estimating the number of species in a population.

Applications

• Analysis of "omic" data : comparison of protein abundance, estimating relations between phenotypes and "omic" data, ...
• Statistical analysis of data coming from Citizen Sciences

Publications

Book

Technical reports

Graph selection with GGMselect : with C. Giraud and N. Verzelen

Estimator selection in the Gaussian setting : with Y. Baraud and C. Giraud.

Software

NLS2 : A set of Splus (or R) functions and programs to estimate the parameters of a non-linear regression model over a given set of observations.

GGMselect : A R package dedicated to graph estimation in Gaussian Graphical Models. The main functions return the adjacency matrix of an undirected graph estimated from a data matrix.

LINSelect : R functions for choosing an estimator in Gaussian regression model according to the method proposed by Baraud et al. 2010. See also LINselect.pdf, and Giraud et al. 2012.

ConvDiscr : R functions for the non parametric estimation of a convex discrete distribution. Durot et al. 2013, CSDA, 67, 282-298. The functions are available in a zip file.

NConv : R functions for estimating the number of species under the hypothesis that the abundance distribution is a convex abundance distribution. Durot et al. 2014. The functions are available in a zip file.