Matthieu MARBAC

Matthieu Marbac
Laboratoire de Mathématiques de Bretagne Atlantique
Université de Bretagne-Sud
Centre de Recherche, Campus de Tohannic, BP 573
F-56017 Vannes, France
Email: matthieu.marbac@univ-ubs.fr

Presentation

Since September 2025, I hold a Chair of Junior Professor (CPJ) position at the Université de Bretagne-Sud, Vannes (LMBA).
Between September 2023 and September 2025, I held a position of Associate Professor in Statistics at ENSAI/CREST (Bruz, France). Between September 2017 and September 2023, I held a position of Assistant Professor in Statistics at ENSAI/CREST (Bruz, France). I defended my habilitation (french qualification required to supervise Ph.D. students) in 2022, here is my manuscript. I was awarded my Ph.D., supervised by Christophe Biernacki and Vincent Vandewalle, in October 2014 at the University of Lille 1. For more information about, please see my academic CV.

Editorial Activity:
Computational Statistics & Data Analysis (Associate Editor, 04/2021 - )
Econometric and Statistics (Associate Editor, 11/2023 - )

Keywords:
Biostatistics; Clustering and classsification; Empirical likelihood; Mixture models.

PhD supervision

December 2023-present: Mohamed El Hasnaoui Model selection for nonparametric mixture models with dependent data
November 2023-present: Koffi Amezouwui Analysis and clustering of soccer game situations in order to populate virtual environments. Jointly supervised with Brigitte Gelein (Irmar-Ensai) and Anthony Sorel (M2S)
September 2022-2025: Antoine Bouvet Analyzing inertial swimming data for automatically monitoring athlete's activity during training. Jointly supervised with Salima El Kolei (CREST-Ensai) and Nicolas Bideau (M2S). Antoine holds now a postdoctoral position at Ecole de Technologie Supérieure (ETS) of Institut National du Sport (INS) du Québec.
December 2021-2022: Camille Méneur Arrhythmia: Statistical modelling for detection and classification of heart defects in racehorses. Jointly supervised with Gilles Stupfler (Univ. of Angers). Stopped before defense. Camille is now data scientist at Caisse nationale des allocations familiales
December 2020-2025: Axel Potier Probabilistic substitution model to determine the optimal stocks. Jointly supervised with Christophe Biernacki (Inria) and Vincent Vandewalle (Univ. of Nice Côte d'Azur)

Collaborations

National:
CREST: Salima El Kolei and Valentin Patilea.
Inria: Christophe Biernacki, Gilles Celeux and Julie Josse.
Irmar: Marie Du Roy de Chaumaray, Marie-Pierre Etienne and Brigitte Gelein.
Inserm: Orianne Dumas, Patricia Dargent and Cécilia Saldanha Gomes.
Institut Pasteur: Étienne Patin.
M2S: Antoine Bouvet and Anthony Sorel.
Université Côte d'Azur: Aude Sportisse and Vincent Vandewalle.
Université de Lille: Mohamed-Salem Ahmed, Camille Frévent and Michaël Genin.
Université Paris-Sud: Mohammed Sedki.
Sorbonne université: Claire Boyer.
International:
HEC Montreal (Canada): Amay Cheam and Marc Fredette.
Purdue University (USA): Michael Levine.
University of McMaster (Canada): Paul McNicholas.

Submitted papers

Amezouwui, K., Gelein, B., Marbac, M. and Sorel, A. Model-Based Clustering of Football Event Sequences: A Marked Spatio-Temporal Point Process Mixture Approach.
Du Roy de Chaumaray, M., Levine, M. and Marbac, M. Rates of Convergence of Maximum Smoothed Log-Likelihood Estimators for Semi-Parametric Multivariate Mixtures.
El Kolei, S. and Marbac, M. Goodness-of-fit testing of the distribution of posterior classification probabilities for validating model-based clustering.

Book chapters (in french)

Marbac, M. Introduction à une étude statistique avec données manquantes, JES 2022, sous la direction de F. Bertrand, G. Saporta, C. Thomas-Agnan.
Marbac, M. Méthodes basées sur la vraisemblance pour données manquantes ayant un mecanisme ignorable, JES 2022, sous la direction de F. Bertrand, G. Saporta, C. Thomas-Agnan.
Marbac, M. Méthodes de pondération pour données manquante, JES 2022, sous la direction de F. Bertrand, G. Saporta, C. Thomas-Agnan.

Journal articles (statistics)

(Most recent first)

Du Roy de Chaumaray, M., El Kolei, S., Etienne, M.P. and Marbac, M. (2024). Estimation of the Order of Non-Parametric Hidden Markov Models using the Singular Values of an Integral Operator. Journal of Machine Learning Research, 25 (415), 1-37.
Sportisse, A., Marbac, M., Biernacki, C., Boyer, C., Celeux, G., Laporte, F. and Josse, J. (2024). Model-based Clustering with Missing Not At Random Data. Statistics and Computing, 34 (4).
Du Roy de Chaumaray, M. and Marbac, M. (2024). Full Model Estimation for Non-Parametric Multivariate Finite Mixture Models.
Journal of the Royal Statistical Society: Series B, 86 (4), 896-921.
Bouvet, A., El Kolei, S. and Marbac. M. (2024). Investigating swimming technical skills by a double partition clustering of multivariate functional data allowing for dimension selection. The Annals of Applied Statistics, 18 (2), 1750-1772.
Cheam, A., Fredette, M., Marbac, M. and Navarro, F. (2023). Translation-invariant functional clustering on COVID-19 deaths adjusted on population risk factors. Journal of the Royal Statistical Society: Series C, 72 (2), 387-413.
Du Roy de Chaumaray M. and Marbac M. (2023). Clustering Data with Nonignorable Missingness using Semi-Parametric Mixture Models. Advances in Data Analysis and Classification, 4, 1-42 ,[R package MNARclust].
Marbac, M., Sedki, M., Biernacki, C. and Vandewalle, V. (2022). Simultaneous semi-parametric estimation of clustering and regression. Journal of Computational and Graphical Statistics, 31 (2), 477-485,[R package ClusPred].
Frévent, C., Ahmed, M.S., Marbac, M. and Genin, M. (2021). Detecting spatial clusters on functional data: a parametric scan statistic approach. Spatial Statistics, 46.
Du Roy de Chaumaray, M., Marbac M. and Patilea, V. (2021). Wilks' theorem for semiparametric regressions with weakly dependent data. The Annals of Statistics, 49 (6), 3228-3254.
Biernacki, C., Marbac, M. and Vandewalle, V. (2021). Gaussian Based Visualization of Gaussian and Non-Gaussian Based Clustering. Journal of Classification, 38, 129-157 [R package ClusVis].
Du Roy de Chaumaray, M., Marbac M. and Navarro, F. (2020). Mixture of hidden Markov models for accelerometre data. The Annals of Applied Statistics, 14 (4), 1834-1855 [R package MHMM].
Marbac, M. and Patin, E. and Sedki, M. (2020). Variable selection for mixed data clustering: Application in human population genomics. Journal of Classification, 37 124-142 [R package VarSelLCM - Package tutorial].
Marbac, M. and Sedki, M. (2019). VarSelLCM: an R/C++ package for variable selection in model-based clustering of mixed-data with missing values. Bioinformatics, 35 (7), 1255-1257 [R package VarSelLCM - Package tutorial]
Marbac, M., and Vandewalle, V. (2019). A tractable Multi-Partitions Clustering. Computational Statistics and Data Analysis, 132, 167-179.
Marbac, M. and Sedki, M. (2017). A Family of Blockwise One-Factor Distributions for Modelling High-Dimensional Binary Data. Computational Statistics and Data Analysis, 114, 130-145 [R package MvBinary - Package tutorial].
Cheam, A.S.M., Marbac, M. and McNicholas, P.D. (2017). Model-based clustering for spatio-temporal data on air quality monitoring. Environmetrics, 8 (3) [R package SpaTimeClus].
Marbac, M., Biernacki, C. and Vandewalle, V. (2017). Model-based clustering of Gaussian Copulas for Mixed Data. Communications in Statistics - Theory and Methods, 46 (23) [R codes].
Marbac, M. and Sedki, M. (2017). Variable selection for model-based clustering using the integrated complete-data likelihood. Statistics and Computing, 27 (4) [R package VarSelLCM - Package tutorial].
Marbac, M., Biernacki, C. and Vandewalle, V. (2016). Finite mixture model of conditional dependencies modes to cluster categorical data. Advances in Data Analysis and Classification, 10 (2), 183-207 [R codes].
Marbac, M. and McNicholas, P.D. (2016). Dimension reduction for clustering. Wiley StatsRef : Statistics Reference Online, 1-7.
Marbac, M., Tubert-Bitter, P. and Sedki, M. (2016). Bayesian model selection in logistic regression for the detection of adverse drug reactions. Biomertical Journal, 58, 1376-1389 [R package MHTrajectoryR].
Marbac, M., Biernacki, C. and Vandewalle, V. (2015). Model-based clustering for conditionally correlated categorical data. Journal of Classification, 32 (2), 145-175, [R codes].

Journal articles (epidemiology)

Dumas, O., Bédard, A., Marbac, M., Sedki, M., Temam, S., Chanoine, S., Severi, G., Boutron-Ruault, M.C., Garcia-Aymerich, J., Siroux, V., Varraso, R., and Le Moual, N. (2021). Household cleaning and poor asthma control among elderly women. Journal of Allergy and Clinical Immunology: In Practice (forthcoming).
Saldanha Gomes, C., Marbac, M., Sedki, M., Cornet, M., Plancoulainr, S., Charles, M.-A., Lioret, S. and Dargent-Molina, P. (2020). Clusters of diet, physical activity, television exposure and sleep habits and their association with adiposity in preschool children: the EDEN mother-child cohort. International Journal of Behavioral Nutrition and Physical Activity, 17 (20).
Marbac, M., Sedki, M., Boutron-Ruault, M.C., and Dumas, O. (2018). Patterns of cleaning product exposures using a novel clustering approach for data with correlated variables. The Annals of Epidemiology, 28 (8), 563-569.e6.