User Tools

Site Tools


members:mtaupin:welcome

This is an old revision of the document!


Marie-Luce Taupin

Professeur des Universités (UEVE)
Université d'Évry Val d'Essonne
Laboratoire de Mathématiques et Modélisation d'Évry (UMR 8071)
I.B.G.B.I., 23 Bd. de France, 91037 Évry Cedex
☎ +33 (0) 1 64 85 35 28
📠: +33 1 64 85 36 01
email : marie-luce.taupin “AT”@univ-evry.fr>

A la Une

Actual position

Since 2009, I am a full professor at the university of Evry, member of the team “Statistics and Genome” in the lab LaMME.

Since 2013, I am the director of the mathematics department of the University of Evry.
Since September 2018, I am responsible of the first year of Master Mathematics and Interactions ( M1 MINT, Evry) in the Master of Mathematics and Applications in University Paris Saclay.

Research Interest

  • Semiparametric models
  • Nonparametric estimation
  • Survival analysis
  • Dimension reduction / variable selection
  • Model selection
  • Mixture models
  • Deconvolution
  • Measurement errors models
  • Sensitivity Analysis
  • Meta-modeling
  • Statistics for genomics and genetics

PhD Students

Current

  • Halala Kamari started his thesis in september, 2016, under the supervision of Sylvie Huet, MaIAGE Unit in INRA, Jouy-En-Josas. She is working half time at our laboratory, spending the rest of the time in INRA. She is working on meta-modelling and sensitivity. She is receiving a 3-year financial support from the EDMH.

Past

  • Marius Kwemou started his thesis in July, 2010, under the supervision of Jean-Yves Lehesran, Abdou Kâ Diongue from University Gaston Berger at Saint-Louis in Senegal and myself. He is working half time at our laboratory, spending the rest of the time in University Gaston Berger at Saint-Louis in Senegal. He is working on dimension reduction in logistic regression with an application to ACTU-PALU Data (ANR n°07-SEST-001). He is receiving a 3-year financial support from the IRD. He has presented his Phd defense on september, the 29th, 2014.
  • Sarah Lemler started her thesis in september, 2011, under the supervision of Agathe Guilloux and myself. She is receiving a 3-year financial support from the french minister of Education and Research and Evry University. She is working on variable selection and dimension reduction in high-dimensional survival analysis. She has presented her Phd defense on december, the 9th, 2014.

Teachings

Groupe de travail de Statistique de Paris 5

Séminaire Parisien de Statistique

SSB Group

Unité MIA-Jouy, INRA

GdR MASCOT-NUM

Réseau Mexico

Réseau REM

Linear Models and R

Logistic Regression. A self learning Text

Generalized Linear Models

2024
[1]
Dedecker, J., Guedj, O. & Taupin, M.L. Asymptotic confidence interval for R2 in multiple linear regression. , 2024., (working paper or preprint). implementation
2023
[2]
Frioux, C., Huet, S., Labarthe, S., Martinelli, J., Malou, T., Sherman, D., Taupin, M.L. & Ugalde-Salas, P. Accelerating metabolic models evaluation with statistical metamodels: application to Salmonella infection models. , 73:187-217, EDP Sciences, 2023. implementation
2022
[3]
Kamari, H., Huet, S. & Taupin, M.L. RKHSMetaMod: An R Package to Estimate the Hoeffding Decomposition of a Complex Model by Solving RKHS Ridge Group Sparse Optimization Problem. The R Journal, 14(1):101-122, R Foundation for Statistical Computing, 2022. implementation
[4]
Frioux, C., Huet, S., Labarthe, S., Martinelli, J., Malou, T., Sherman, D.J., Taupin, M.L. & Salas, P.U. Dynamic Flux Balance Analysis with Metamodels. , 2022., (Poster). implementation
[5]
Frioux, C., Huet, S., Labarthe, S., Martinelli, J., Malou, T., Sherman, D.J., Taupin, M.L. & Ugalde-Salas, P. Dynamic Flux Balance Analysis with Metamodels. , 2022., (Poster). implementation
2019
[6]
Huet, S. & Taupin, M.L. Metamodel construction for sensitivity analysis. , 2019., (working paper or preprint). implementation
[7]
2017
[8]
Huet, S. & Taupin, M.L. Metamodel construction for sensitivity analysis. ESAIM: Proceedings and Surveys, 60:27-69, EDP Sciences, 2017. implementation
[9]
Huet, S. & Taupin, M.L. Metamodel construction for sensitivity analysis. ESAIM: Proceedings and Surveys, 60-2017:27-69, EDP Sciences, 2017. implementation
2016
[10]
Guilloux, A., Lemler, S. & Taupin, M.L. Adaptive kernel estimation of the baseline function in the Cox model with high-dimensional covariates. Journal of Multivariate Analysis, 148:141-159, Elsevier, 2016. implementation
2015
[11]
Guilloux, A., Lemler, S. & Taupin, M.L. Adaptive estimation of the baseline hazard function in the Cox model by model selection, with high-dimensional covariates. Journal of Statistical Planning and Inference, 171:38-62, Elsevier, 2015. implementation
[12]
[13]
Guilloux, A., Lemler, S. & Taupin, M.L. Adaptive kernel estimation of the baseline function in the Cox model with high-dimensional covariates. , 2015., (working paper or preprint). implementation
[14]
Kwemou, M., Taupin, M.L. & Tocquet, A.S. MODEL SELECTION IN LOGISTIC REGRESSION. , 2015., (working paper or preprint). implementation
2014
[15]
Dedecker, J., Samson, A. & Taupin, M.L. Estimation in autoregressive model with measurement error. ESAIM Probab. \& Stat., 18():277-307, 2014., (http://dx.doi.org/10.1051/ps/2013037). implementation
[16]
Dedecker, J., Samson, A. & Taupin, M.L. Estimation in autoregressive model with measurement error. ESAIM: Probability and Statistics, 18:277-307, EDP Sciences, 2014. implementation
[17]
2010
[18]
Taupin, M.L. Comment on : Identification and estimation of nonlinear models using two samples with nonclassical measurement errors. Journal of nonparametric statistics, 22():409-414, 2010.
2009
[19]
Martin-Magniette, M.L. & Taupin, M.L. Semi-parametric estimation of the hazard function in a model with covariate measurement error.. ESAIM: Proba. and Stat., 13():87-114, 2009. implementation
2008
[20]
[21]
Butucea, C. & Taupin, M.L. New M-estimators in semiparametric regression with errors-in-variables.. Annales de l'Institut Henri Poincaré, 44(3):393-421, 2008. implementation
[22]
Comte, F., Dedecker, J. & Taupin, M.L. Adaptive density deconvolution with dependent inputs.. Math. Methods Statist., 17(2):87-112, 2008. implementation
[23]
Comte, F., Dedecker, J. & Taupin, M.L. Adaptive density estimation for general ARCH models.. Econometric Theory, 24(6):1628-1662, 2008., (http://journals.cambridge.org/action/displayJournal?jid=ECT). implementation
2007
[24]
Comte, F. & Taupin, M.L. Adaptive estimation in a nonparametric regression model with errors-in-variables. Statist. Sinica, 17(3):1065-1090, 2007.
[25]
Comte, F., Rozenholc, Y. & Taupin, M.L. Finite sample penalization in adaptive density deconvolution.. Journal of Statistical Computation and Simulation, 77():977-1000, 2007. implementation
2006
[26]
Comte, F., Rozenholc, Y. & Taupin, M.L. Penalized contrast estimator for adaptive density deconvolution. Canad. J. Statist., 34(3):431-452, 2006. implementation
2004
[27]
Matias, C. & Taupin, M.L. Minimax estimation of linear functionals in the convolution model. Math. Methods Statist., 13(3):282-328, 2004.
2001
[28]
Comte, F. & Taupin, M.L. Semiparametric estimation in the (auto)-regressive \beta-mixing model with errors-in-variables. Math. Methods Statist., 10(2):121-160, 2001.
[29]
Taupin, M.L. Semi-parametric estimation in the nonlinear structural errors-in-variables model. Ann. Statist., 29():66-93, 2001.
1998
[30]
Taupin, M.L. Estimation in the nonlinear errors-in-variables model.. C. R. Acad. Sci. Paris Se\́r. I Math. 326, 7():885-890, 1998.
[31]
members/mtaupin/welcome.1544798348.txt.gz · Last modified: 2018/12/14 15:39 by Marie Luce Taupin

Page Tools