Piste : • recherche

Research topics

Table des matières

  • Statistique actuarielle (construction de tests, modélisation de la mortalité, théorie de la ruine, approximation)
  • Statistique bayésienne (sélection de variables, approximation)
  • Processus à courte et longue mémoire (comparaison et tests)
  • Copules et indicateurs de dépendance (estimation et tests)
  • Mélanges et clustering (mélanges gaussiens, comparaison de mélanges)

Doctorants

  • Samuel Stocksieker : “Modélisation des distributions déséquilibrées en assurance” (co-encadrement : Arthur Charpentier)
  • Eléonore Blanchard : “Détection de régimes de marché en gestion d’actifs” (co-encadrement : Anne Eyraud-Loisel, Pierre-Olivier Goffard)
  • Maxime Dotta : “Sciences des données et détection de fraude santé” (co-encadrement : Xavier Milhaud)

Anciens doctorants

Yves Ngounou-Bakam (2022), Robin Fuchs (2022), Mathilde Dugenne (2017), Pierre-Olivier Goffard (2015), Meïli Baragatti (2011)

Publications

  
* Ngounou-Bakam, Y., Pommeret, D. (2023) "Nonparametric estimation of copulas and copula densities by orthogonal projections". Econometrics and Statistics. 
* Milhaud, X., Pommeret, D., Salhi, Y. Vandekerkhove, P. (2023) "Two sample contamination model test". Bernoulli.
* Stocksieker, S., Pommeret, D., Charpentier, A. (2023) "Data Augmentation for Imbalanced Regression". Proceedings of the 25th International Conference on Artificial Intelligence and Statistics. 
* Fuchs, R., Thyssen, M., Creach, V., Dugenne, M., Izard, L., Latimier, M., Louchart, A., Marrec, P.,  Rijkeboer, M., Grégori, G., Pommeret, D. (2022) "Automatic recognition of flow cytometric phytoplankton functional groups using convolutional neural networks". Limnology and Oceanography Methods. 
* Pommeret, D., Reboul, L., Yao, A.F. (2022) "Testing the equality of the  laws of two strictly stationary processes". Statistical Inference for Stochastic Processes
* Fuchs, R., Pommeret, D., Stocksieker, S. (2022) "MIAMI: MIxed data Augmentation MIxture". ICCSA Proceedings – Lecture Notes in Computer Science.
* Fuchs, R., Pommeret, D., Stocksieker, S. (2022) "MI2AMI: Missing data imputation using Mixed Deep Gaussian Mixture Models". LOD Proceedings – Lecture Notes in Computer Science.
* Fuchs, R., Pommeret, D., Viroli, C. (2021) "Mixed Deep Gaussian Mixture Model: a clustering model for mixed datasets". Advances in Data Analysis and Classification.
* Milhaud, X., Pommeret, D., Salhi, Y., Vandekerkhove, P. (2022) "Semiparametric two-sample admixture components comparison test: The symmetric case". Journal of Statistical Planning and Inference. 
* Soubeyrand, S., Ribaud, M., Baudrot, V., Allard, D., Pommeret. D, Roques, L. (2020) "COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s)" PLOS ONE. https://doi.org/10.1371/journal.pone.0238410
* Pommeret, D., Vandekerkhove, P. (2019) " Semiparametric density testing in the contamination model". Electronic Journal of Statistics. 
* Doukhan, P., Grublit, I., Pommeret, D., Reboul, L. (2019) "Comparing the marginal densities of two strictly stationary linear processes". Annals of the Institute of Statistical Mathematics.
* Pommeret, D., Reboul, L. (2018) "Approximating the Probability Density Function of a Transformation of Random Variables". Methodology and Computing in Applied Probability.
* Doukhan, P., Joseph Rynkiewicz, J., Pommeret, D., Salhi, Y. (2017) "A Class of Random Field Memory Models for Mortality Forecasting". Insurance Mathematics and Economics
* Boutahar, M., Pommeret, D. (2016) "A test for the equality of transformations of two random variables". ESAIM P&S.
* Goffard, P.O., Loisel, S., Pommeret, D. (2015) "Polynomial approximation for bivariate aggregate claims amount probability distributions". Methodology and Computing in Applied Probability. 
* Goffard, P.O., Loisel, S., Pommeret, D. (2014) "A polynomial expansion to approximate the ultimate ruin probability in the compound Poisson ruin model". Journal of Computational and Applied Mathematics.
* Doukhan, P., Pommeret, D., Reboul, L. (2015) "Data Driven Smooth Test of Comparison of Dependent Sequences". Journal of Multivariate Analysis.
* Pommeret, D. (2015) "Comparing two mixing densities in nonparametric mixtures". Sankhya
* Pommeret, D. (2013) "A two-sample test when data are contaminated". Statistical Methods and Applications.
* Boutahar, M. Ghattas, B., Pommeret, D. (2013) "Nonparametric comparison of several transformations of distribution functions". Journal of Nonparametric Statistics.
* Baragatti, M., Grimaud, A., Pommeret, D. (2013) "Parallel tempering with Equi-Energy moves". Statistics and Computing. 
* Baragatti, A. Grimaud, A., Pommeret, D. (2012) "Likelihood-free parallel tempering". Statistics and Computing. 
* Druilhet, P., Pommeret, D. (2012) "Invariant conjugate analysis for exponential families". Bayesian Analysis. 
* Baragatti, M., Pommeret, D. (2011) "A study of variable selection using g-prior distribution with ridge parameter". Computational Statistics and Data Analysis. 
* Guyon, E., Pommeret, D. (2011) "Imputation by PLS regression for linear mixed models". Journal de la Societe Francaise de Statistique. 
* Pommeret, D. (2011) "Data driven smooth test for contaminated data". Journal of Statistical Theory and Practice. 
* Ghattas, B., Pommeret, D., Reboul, L., Yao, A.F. (2011) "Data driven smooth test for paired populations". Journal of Statistical Planning and Inference. 
* Baragatti, M., Pommeret, D. (2011) Comments on "Bayesian variable selection for disease classification using gene expression data". Bioinformatics. 
* Pommeret (2010) "Testing Mixed Distributions when the Mixing Distribution Is Known". Advances in Data Analysis, Data Handling and Business Intelligence. Studies in Classification,Data Analysis, and Knowledge Organization.

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