Information Covid Recherche

MARBAC LOURDELLE Matthieu

Enseignant-chercheur en statistique DOMAINES DE RECHERCHE
  • Model-based clustering
  • Computational statistics
  • Biostatistics
  • Empirical likelihood
Bureau 259 Téléphone +33 (0)2 99 05 32 15 Email matthieu.marbac-lourdelle@ensai.fr Adresse ENSAI
Campus de Ker Lann
51 Rue Blaise Pascal
BP 37203
35172 BRUZ Cedex

Preprints

  1. Cheam, A., Fredette, M., Marbac, M. and Navarro, F. Translation-invariant functional clustering on COVID-19 deaths adjusted on population risk factors.
  2. Frévent, C., Ahmed, M.S., Marbac, M. and Genin, M. Detecting spatial clusters on functional data: a parametric scan statistic approach.
  3. 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. Household cleaning and poor asthma control among elderly women.
  4. Du Roy de Chaumaray M. and Marbac M. Clustering Data with Nonignorable Missingness using Semi-Parametric Mixture Models.
  5. Marbac, M., Sedki, M., Biernacki, C. and Vandewalle, V. Simultaneous semi-parametric estimation of clustering and regression.
  6. Du Roy de Chaumaray, M., Marbac M. and Patilea, V. Wilks' theorem for semiparametric regressions with weakly dependent data.

Journal articles

(Most recent first)

  1. Biernacki, C., Marbac, M. and Vandewalle, V. Gaussian Based Visualization of Gaussian and Non-Gaussian Based Clustering. Journal of Classification, forthcoming [R package ClusVis].
  2. Du Roy de Chaumaray, M., Marbac M. and Navarro, F. (2020). Mixture of hidden Markov models for accelerometre data. Annals of Applied Statistics, 14 (4), 1834-1855 [R package MHMM].
  3. 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].
  4. 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).
  5. 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]
  6. Marbac, M., and Vandewalle, V. (2019). A tractable Multi-Partitions Clustering. Computational Statistics and Data Analysis, 132, 167-179.
  7. 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. Annals of Epidemiology, 28 (8), 563-569.e6.
  8. 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].
  9. 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].
  10. 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].
  11. 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].
  12. 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].
  13. Marbac, M. and McNicholas, P.D. (2016). Dimension reduction for clustering. Wiley StatsRef : Statistics Reference Online, 1–7.
  14. 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].
  15. 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].