Maud DELATTRE Liste de publications

Identifiants chercheurs

IdHAL :

madelattre

ORCID :

0000-0002-3775-9278

IdRef :

162348576

Publications

Article dans une revue (28)

Posterior contraction rates in a sparse non-linear mixed-effects model Marion Naveau,Maud Delattre,Laure Sansonnet Electronic Journal of Statistics , 2025, 19 (2), pp.4725-4757. ⟨10.48550/arXiv.2405.01206⟩ Article dans une revue hal-04561040v3
Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm Marion Naveau,Guillaume Kon Kam King,Renaud Rincent,Laure Sansonnet,Maud Delattre Statistics and Computing, 2024, 34 (1), pp.53. ⟨10.1007/s11222-023-10367-4⟩ Article dans une revue hal-04395282v1
Computing an empirical Fisher information matrix estimate in latent variable models through stochastic approximation Maud Delattre,Estelle Kuhn Computo, 2023, ⟨10.57750/r5gx-jk62⟩ Article dans une revue hal-04347257v1
Modeling soybean growth: A mixed model approach Maud Delattre,Yusuke Toda,Hiroyoshi Iwata,Jessica Tressou PLoS Computational Biology, 2023, 20 (7), pp.e1011258. ⟨10.1371/journal.pcbi.1011258⟩ Article dans une revue hal-04220837v1
Inference in Gaussian state-space models with mixed effects for multiple epidemic dynamics Romain Narci,Maud Delattre,Catherine Larédo,Elisabeta Vergu Journal of Mathematical Biology, 2022, 85, pp.40. ⟨10.1007/s00285-022-01806-3⟩ Article dans une revue hal-03347365v1
Inference for partially observed epidemic dynamics guided by Kalman filtering techniques Romain Narci,Maud Delattre,Catherine Larédo,Elisabeta Vergu Computational Statistics and Data Analysis, 2021, 164, ⟨10.1016/j.csda.2021.107319⟩ Article dans une revue hal-02475936v4
A review on asymptotic inference in stochastic differential equations with mixed-effects Maud Delattre Japanese Journal of Statistics and Data Science , 2021, ⟨10.1007/s42081-021-00105-3⟩ Article dans une revue (article de synthèse) hal-02938697v1
A novel modelling approach to quantify the response of dairy goats to a high-concentrate diet Masoomeh Taghipoor,Maud Delattre,Sylvie Giger-Reverdin Scientific Reports, 2020, 10 (1), pp.20376. ⟨10.1038/s41598-020-77353-y⟩ Article dans une revue hal-03132771v1
Patterns of amino acids intake are strongly associated with cardiovascular mortality, independently of the sources of protein Marion Tharrey,François Mariotti,Andrew Mashchak,Pierre Barbillon,Maud Delattreet al. International Journal of Epidemiology, 2020, 49 (1), pp.312 - 321. ⟨10.1093/ije/dyz194⟩ Article dans une revue hal-02366516v1
Floral trait functional diversity is related to soil characteristics and positively influences pollination function in semi-natural grasslands Jérémie Goulnik,Sylvain Plantureux,Marc Thery,Mathilde Baude,Maud Delattreet al. Agriculture, Ecosystems & Environment, 2020, 301, pp.107033. ⟨10.1016/j.agee.2020.107033⟩ Article dans une revue hal-02915375v1
An iterative algorithm for joint covariate and random effect selection in mixed effects models Maud Delattre,Marie-Anne Poursat The international journal of biostatistics, 2020, 16 (2), ⟨10.1515/ijb-2019-0082⟩ Article dans une revue hal-03144783v1
Patterns of plant and animal protein intake are strongly associated with cardiovascular mortality: the Adventist Health Study-2 cohort Marion Tharrey,François Mariotti,Andrew Mashchak,Pierre M Barbillon,Maud Delattreet al. International Journal of Epidemiology, 2018, 47 (5), pp.1603-1612. ⟨10.1093/ije/dyy030⟩ Article dans une revue hal-01766695v1
Approximate maximum likelihood estimation for stochastic differential equations with random effects in the drift and the diffusion Maud Delattre,Valentine Genon-Catalot,Catherine Laredo Metrika, 2018, 81 (4), pp.953-983. ⟨10.1007/s00184-018-0666-z⟩ Article dans une revue hal-02621496v1
Parametric inference for discrete observations of diffusion processes with mixed effects Maud Delattre,Valentine Genon-Catalot,Catherine Laredo Stochastic Processes and their Applications, 2018, 128 (6), pp.1929-1957. ⟨10.1016/j.spa.2017.08.016⟩ Article dans une revue hal-02622519v1
An escalation for bivariate binary endpoints controlling the risk of overtoxicity (EBE-CRO ): managing efficacy and toxicity in early oncologyvClinical trials Pierre Colin,Maud Delattre,P. Minini,S. Micallef Journal of Biopharmaceutical Statistics, 2017, 27 (6), pp.1-19. ⟨10.1080/10543406.2017.1295248⟩ Article dans une revue hal-01533853v1
Estimating the number of block boundaries from diagonal blockwise matrices without penalization Vincent Brault,Maud Delattre,Tristan Mary-Huard,Céline Leduc Scandinavian Journal of Statistics, 2017, 44 (2), pp.563-580. ⟨10.1111/sjos.12266⟩ Article dans une revue hal-01533843v1
Mixtures of stochastic differential equations with random effects: Application to data clustering Maud Delattre,Valentine Genon-Catalot,Adeline Samson Journal of Statistical Planning and Inference, 2016, 173, pp.109-124. ⟨10.1016/j.jspi.2015.12.003⟩ Article dans une revue hal-01218612v1
Estimation of population parameters in stochastic differential equations with random effects in the diffusion coefficient Maud Delattre,Valentine Genon-Catalot,Adeline Samson ESAIM: Probability and Statistics, 2015, 19, pp.671-688. ⟨10.1051/ps/2015006⟩ Article dans une revue hal-01056917v2
Towards using a full spectrum of early clinical trial data: a retrospective analysis to compare potential longitudinal categorical models for molecular targeted therapies in oncology Pierre Colin,Sandrine Micallef,Maud Delattre,Pierre Mancini,Éric Parent Statistics in Medicine, 2015, Special Issue: Papers from the Seventh International French Society of Statistics Meeting on Statistical Methods in Biopharmacy: Emerging Topics for Statistical Methodology in Clinical Drug Development, 34 (2), pp.2999-3016. ⟨10.1002/sim.6548⟩ Article dans une revue hal-01197648v1
Two-dimensional segmentation for analyzing Hi-C data Celine Lévy-Leduc,Maud Delattre,T. Mary-Huard,S. Robin Bioinformatics, 2014, 30 (17), pp.i386-i392. ⟨10.1093/bioinformatics/btu443⟩ Article dans une revue hal-04083798v1
A note on BIC in mixed-effects models Maud Delattre,Marc Lavielle,Marie-Anne Poursat Electronic Journal of Statistics , 2014, 8, pp.456--475. ⟨10.1214/14-EJS890⟩ Article dans une revue hal-00991708v1
Coupling the SAEM algorithm and the extended Kalman filter for maximum likelihood estimation in mixed-effects diffusion models Maud Delattre,Marc Lavielle Statistics and Its Interface, 2013, 6 (4), pp.519--532. ⟨10.4310/sii.2013.v6.n4.a10⟩ Article dans une revue hal-00916803v1
Maximum likelihood estimation for stochastic differential equations with random effects Maud Delattre,Valentine Genon-Catalot,Adeline Samson Scandinavian Journal of Statistics, 2013, 40 (2), pp.322-343. ⟨10.1111/j.1467-9469.2012.00813.x/abstract⟩ Article dans une revue hal-00650844v1
The recruitment of p47phox and Rac2G12V at the phagosome is transient and phosphatidylserine-dependent Marie-Cécile Faure,Jean-Claude Sulpice,Maud Delattre,Marc Lavielle,Magali Prigentet al. Biology of the Cell, 2013, 105, pp.1--18. ⟨10.1111/boc.201300010⟩ Article dans une revue hal-01555264v2
Analysis of exposure–response of CI-945 in patients with epilepsy: application of novel mixed hidden Markov modeling methodology Maud Delattre,Radojka M. Savic,Raymond Miller,Mats O. Karlsson,Marc Lavielle Journal of Pharmacokinetics and Pharmacodynamics, 2012, 39 (3), pp.263 - 271. ⟨10.1007/s10928-012-9248-2⟩ Article dans une revue istex hal-01560511v1
Maximum likelihood estimation in discrete mixed hidden Markov models using the SAEM algorithm Maud Delattre,Marc Lavielle Computational Statistics and Data Analysis, 2012, 56 (6), pp.2073-2085. ⟨10.1016/j.csda.2011.12.017⟩ Article dans une revue istex hal-00756599v1
Analysis of exposure-response of CI-945 in patients with epilepsy: application of novel Mixed Hidden Markov Modelling Methodology Maud Delattre,Radojka M. Savic,Raymond Miller,Mats O. Karlsson,Marc Lavielle Journal of Pharmacokinetics and Pharmacodynamics, 2012, 39 (3), pp.263-271 Article dans une revue hal-00756603v1
Inference in Mixed Hidden Markov Models and Applications to Medical Studies Maud Delattre Journal de la Société Française de Statistique, 2010, 151 (1), pp.90-105 Article dans une revue hal-00637419v1

HDR (1)

Etudes de modèles markoviens à variables latentes avec applications à la pharmacologie et à l’épidémiologie. Maud Delattre Statistiques [math.ST]. Université Paris-Saclay, 2020 HDR tel-03202055v1

Communication dans un congrès (24)

A new preconditioned stochastic gradient descent for estimation in latent variable models Maud Delattre Journées Statistiques du Sud 2024, Jun 2024, Toulouse, France Communication dans un congrès hal-05213349v1
High-dimensional variable selection in non-linear mixed-effects models using a stochastic EM spike-and-slab Marion Naveau,Guillaume Kon Kam King,Renaud Rincent,Laure Sansonnet,Maud Delattre European Meeting of Statisticians, Bernoulli Society, Jul 2023, Warsaw, Poland Communication dans un congrès hal-04248037v1
Sélection de variables bayésienne en grande dimension dans les modèles non-linéaires à effets mixtes Maud Delattre Journées de statistiques de Rennes, Apr 2023, Rennes, France Communication dans un congrès hal-04210257v1
Efficient preconditioned stochastic gradient descent for estimation in latent variable models Charlotte Baey,Maud Delattre,Estelle Kuhn,Jean-Benoist Leger,Sarah Lemler 40th International Conference on Machine Learning (ICML 2023), Jul 2023, Honolulu, United States Communication dans un congrès hal-04131641v1
Selection consistency in non-linear mixed-effects models under spike-and-slab prior Marion Naveau,Laure Sansonnet,Maud Delattre Colloque Jeunes Probabilistes et Statisticiens, Oct 2023, Saint Pierre d'Oleron, France Communication dans un congrès hal-04248058v1
Bayesian high-dimensional variable selection in non-linear mixed-effects models using the SAEM algorithm Marion Naveau,Guillaume Kon Kam King,Laure Sansonnet,Maud Delattre Journée APPLIBUGS, Jun 2022, Lyon, France Communication dans un congrès hal-04247984v1
Modelling soybean growth: a nonlinear mixed model approach Maud Delattre,Hiroyoshi Iwata,Jessica Tressou EcoSta, Jun 2022, Kyoto, Japan Communication dans un congrès hal-04083815v1
Sélection de variables en grande dimension dans les modèles non linéaires à effets mixtes Marion Naveau,Guillaume Kon Kam King,Laure Sansonnet,Maud Delattre 9ème Rencontre des Jeunes Statisticiens, Apr 2022, Porquerolles, France Communication dans un congrès hal-04247947v1
Bayesian high-dimensional variable selection in non-linear mixed-effects models using the SAEM algorithm Marion Naveau,Guillaume Kon Kam King,Laure Sansonnet,Maud Delattre 53ème Journées de Statistique de la Société Française de Statistique, Jun 2022, Lyon, France Communication dans un congrès hal-04247962v1
Statistical analysis of stochastic processes and applications in life science Maud Delattre Journées MAS 2022, Aug 2022, Rouen, France Communication dans un congrès hal-04083875v1
Pollination function is positively influenced by floral traits functional diversity in semi-natural grasslands Jérémie Goulnik,Sylvain Plantureux,Marc Théry,Mathilde Baude,Maud Delattreet al. 28th General Meeting of the European Grassland Federation - 2020 EGF, Oct 2020, Helsinki, Finland Communication dans un congrès hal-02974143v1
Estimating Fisher information matrix in latent variable models based on the score function Maud Delattre,Estelle Kuhn 32. European Meeting of Statisticians -EMS, May 2019, Palermo, Italy Communication dans un congrès hal-02735033v1
Estimation for partially observed epidemic dynamics with measurement errors Maud Delattre,Romain Narci,Catherine Larédo,Elisabeta Vergu Dynstoch, Jun 2018, Porto, Portugal Communication dans un congrès hal-04083830v1
Un nouvel estimateur pour l'information de Fisher dans les modèles à variables latentes Estelle Kuhn,Maud Delattre SFdS- 50ème Journées de Statistique de la SFdS (JdS'2018), May 2018, Pallaiseau, France Communication dans un congrès hal-02735037v1
Estimating the Fisher information matrix in latent variable models Estelle Kuhn,Maud Delattre ERCIM WG on computational and methodological statistics, Dec 2017, Londres, United Kingdom. pp.272 Communication dans un congrès hal-02735038v1
On BIC for mixed-effects models Maud Delattre,Marie-Anne Poursat CMStatistics, 2016, Séville, Spain Communication dans un congrès hal-04083845v1
Estimating variability from capture-recapture data using the SAEM algorithm Maud Delattre,Rémi Choquet Isec (International Statistical Ecology Conference), 2014, Montpellier, France Communication dans un congrès hal-04083859v1
Two-dimensional segmentation for analyzing HiC data Celine Levy Leduc,Maud Delattre,Tristan Mary-Huard,Stephane Robin ECCB 2014: The 13th European Conference on Computational Biology, Sep 2014, Strasbourg, France. pp.386-392, ⟨10.1093/bioinformatics/btu443⟩ Communication dans un congrès hal-01148580v1
Validation data: keystone to move state-space models for movements to operational models for fisheries and marine ecology Stéphanie Mahevas,Nicolas Bez,Sophie Bertrand,Manuela Capello,Maud Delattreet al. ISEC'2014 : International Statistical Ecology Conference, Jul 2014, Montpellier, France Communication dans un congrès hal-01865154v1
Equations diférentielles stochastiques en pharmacocinétique de population : modèles et méthodologie Maud Delattre,Marc Lavielle 45e Journées de Statistique de la SfDS, May 2013, Toulouse, France Communication dans un congrès hal-01589553v1
Population pharmacokinetics and stochastic differential equations : Models and methods Maud Delattre,Marc Lavielle Dynstoch 2013, Apr 2013, Copenhagen, Denmark Communication dans un congrès hal-01586993v1
Maximum likelihood estimation for stochastic differential equations with random effects Maud Delattre,Valentine Genon-Catalot,Adeline Samson Dynstoch, 2012, Paris, France Communication dans un congrès hal-04083864v1
Sélection de variables dans les modèles non-linéaires mixtes Marie-Anne Poursat,Maud Delattre 44e Journées de Statistiques - JdS'2012, May 2012, Bruxelles, Belgique Communication dans un congrès hal-01631001v1
Les modèles de Markov cachés à effets mixtes Maud Delattre 42èmes Journées de Statistique, 2010, Marseille, France, France Communication dans un congrès inria-00494812v1

Poster de conférence (1)

High-dimensional variable selection in non-linear mixed effects models using a stochastic EM spike-and-slab Marion Naveau,Guillaume Kon Kam King,Laure Sansonnet,Maud Delattre ISBA World Meeting, Jun 2022, Montréal, Canada. Poster de conférence hal-04248003v1