NewsNew version of VarSelLCM is available on This package performs cluster analysis of mixed-type data with missing values. Algorithm for variable selection is implemented. Results can be easily interpreted by using the Shiny application.
Marbac, M. and Patin, E. and Sedki, M. (2018). Variable selection for mixed data clustering: Application in human population genomics Journal of Classification (to appear) [R package VarSelLCM.2.1 - Package tutorial].
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 [Journal - R package MvBinary.1.0 - Package tutorial].
Marbac, M. and Sedki, M. (2017). Variable selection for model-based clustering using the integrated complete-data likelihood. Statistics and Computing, 27 (4), 1049–1063 [Journal - 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 [Journal - R codes].
Marbac, M. and McNicholas, P.D. (2016). Dimension reduction for clustering. Wiley StatsRef : Statistics Reference Online, 1–7, [Journal]
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, [Journal - R package MHTrajectoryR.1.0].
Marbac, M., and Vandewalle, V. A tractable Multi-Partitions Clustering.
Marbac, M., Sedki, M., Boutron-Ruault, M.C., and Dumas, O. Patterns of cleaning product exposures using a novel clustering approach for data with correlated variables.
Marbac, M. and Sedki, M. VarSelLCM: an R/C++ package for variable selection in model-based clustering of mixed-data with missing values
Works in progress
Empirical likelihood for conditional estimating equations (with Patilea, V.)
Gaussian-Based Visualization of Gaussian and Non-Gaussian Model-Based Clustering (with Biernacki, C. and Vandewalle, V.)
Multiple model-based clustering to improve model-based prediction (with Biernacki, C., Sedki, M., and Vandewalle, V.)
M. Marbac, C. Biernacki and V. Vandewalle (2014). Mixture model of Gaussian copulas to cluster mixed-type data, Proceedings CompStat2014. [Pdf].
M. Marbac (2014). Model-based clustering for categorical and mixed variables. Thèse de doctorat [Pdf].