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-====== Publications ======+{{ :fr:logo_i2m_color-seul-72dpi.png?nolink&200|}} {{:fr:saf.png?nolink&200|}}===== Research topics ===== 
 + 
 +  * 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.  
 + 
 + 
 +---- 
 + 
 + 
 +ArXiV / HAL: 
 + 
 +  * Fuchs, R., Pommeret, D., Viroli, C. (2020) "Mixed data Deep Gaussian Mixture Model: A clustering model for mixed datasets". [[https://arxiv.org/abs/2010.06661]] 
 +  * Pommeret, D., Reboul, L., Yao, A.F. (2020) "Testing the equality of the laws of two strictly stationary processes". [[https://hal.em-lyon.com/IML/hal-02490333v1]] 
 +  * Milhaud, X., Pommeret, D., Salhi, Y., Vandekerkhove, P. (2020) "Semiparametric two-sample mixture components comparison test". [[https://hal.archives-ouvertes.fr/hal-02491127]] 
 +  * Ngounou, Y., Pommeret, D. (2020) "Nonparametric estimation of copulas and copula densities by orthogonal projections". [[https://arxiv.org/abs/2010.15351]] 
 + 
 + 
 + 
 +---- 
 + 
 +===== Liens utiles ===== 
 + 
 +  * Chaire d'Excellence DAMI [[http://chaire-dami.fr/]] 
 +  * Chaire d'Excellence DIALOG [[https://hal.archives-ouvertes.fr/CHAIRE-DIALOG]] 
 +  * Chaire d'Excellence NINA 
 +  * ANR DREAMES [[https://sites.google.com/view/anr-dreames]] 
 +  * https://sites.google.com/view/denys-pommeret/home 
 +  * Projet RODEO (Ordre et Désordre dans un Océan Turbulent) [[https://rodeo-ocean.mio.osupytheas.fr/]] 
 + 
 + 
 + 
 +