Maud DELATTRE

Liste de publications
54
Documents
Identifiants chercheurs

Domaines de recherche

Statistiques [stat]

Compétences

Modèles à variables latentes Estimation par maximum de vraisemblance Sélection de variables Algorithmes d'optimisation stochastiques Méthodes bayésiennes Applications en sciences du vivant

Publications

Publications

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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
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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
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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
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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
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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
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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 Delattre et al.

International Journal of Epidemiology, 2020, 49 (1), pp.312 - 321. ⟨10.1093/ije/dyz194⟩

Article dans une revue hal-02366516v1
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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

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 Delattre et 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

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
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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 Delattre et al.

International Journal of Epidemiology, 2018, 47 (5), pp.1603-1612. ⟨10.1093/ije/dyy030⟩

Article dans une revue hal-01766695v1

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
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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
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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
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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
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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
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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
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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
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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
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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 Prigent et 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
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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

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

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
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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
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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
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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
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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
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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
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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 Delattre et 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
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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

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 Delattre et al.

ISEC'2014 : International Statistical Ecology Conference, Jul 2014, Montpellier, France

Communication dans un congrès hal-01865154v1
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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

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

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

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

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
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Les modèles de Markov cachés à effets mixtes

Maud Delattre

42èmes Journées de Statistique, 2010, Marseille, France, France

Communication dans un congrès inria-00494812v1