Publications

Submitted papers

• [S5] Estimating distances to tipping points from dryland ecosystem images, B. Pichon, S. Donnet, I. Gounand, S. Kéfi. Submitted

• [S4] The interplay of facilitation and competition drives the emergence of multistability in dryland plant communities, B. Pichon, I. Gounand, S. Donnet, S. Kéfi. Submitted.

• [S3] Auto-encoding GPS data to reveal individual and collective behaviour, S.C. Chabert-Liddell, N. Bez, P. Gloaguen, S. Donnet , S. Mahévas. Submitted

• [S2] Seed circulation networks, the missing link between crop diversity and sustainable agriculture. V. Labeyrie, S. Donnet, S. Caillon, E. Garine, C. Raimond. Submitted

• [S1] Hoeffding-type decomposition for U-statistics on bipartite networks . T. Le Minh, S. Donnet, F. Massol, S. Robin. Submitted

Published or accepted articles

• [A26] Using the multivariate Hawkes process to study interactions between multiple species from camera trap data L. Nicvert, S. Donnet, M. Keith, M. Peel, M.J. Somers, L. H. Swanepoel, J. Venter, H. Fritz, and S. Dray. February 2024, Ecology

• [A25] Learning common structures in a collection of networks. An application to food webs. S.-C. Chabert-Liddell, P. Barbillon, S. Donnet. To appear in Annals of Applied Statistics

• [A24] Linking seed networks and crop diversity contributions to people: a case study in small-scale farming systems in Sahelian Senegal. Vanesse Labeyrie, Sophie Donnet; Rachel S. Friedman; Ndeye Fatou Faye; Océane Cobelli; Jacopo Baggio; Kailin Kroetz; María R. Felipe-Lucia; Jaime Ashander; Christine Raimond. Volume 211, October 2023, 103726, Agricultural Systems

• [A23] Expert elicitation and hierarchical Bayesian approach for parametric survival models: An application to Ixodes ricinus ticks exposed to various temperature and relative humidity. P. Wongnak, S. Bord, S. Donnet, T. Hoch, F. Beugnet , K. Chalvet-Monfray. Ecological Modelling, Volume 464, February 2022

• [A22] Impact of the mesoscale structure of a bipartite ecological interaction network on its robustness through a probabilistic modeling, S.-C. Chabert-Liddell, P. Barbillon, S. Donnet. Published in Environmetrics, Volume 33, Issue 2. DOI: 10.1002/env.2709

• [A21] Coupling ecological network analysis with high-throughput sequencing-based surveys: lessons from the Next-Generation Biomonitoring project, M. Dubart, P. Alonso, D. Barroso-Bergada, N. Becker, K. Bethune, D. A. Bohan, C. Boury, M. Cambon, E. Canard, E. Chancerel, J. Chiquet, P. David, N. de Manincor, S. Donnet, A. Duputié, B. Facon, E. Guichoux, T. Le Minh, S. Ortiz-Martínez, L. Piouceau, A. Sacco–Martret de Préville, M. Plantegenest, C. Poux, V. Ravigné, S. Robin, M. Trillat, C. Vacher, C. Vernière, François Massol. Advances in Ecological Research, Volume 65, 2021, Pages 367-430

• [A20] Accelerating Bayesian estimation for network Poisson models using frequentist variational estimates. Sophie Donnet, Stéphane Robin. JRSSC, 16 April 2021. [Arxiv].

• [A19] A Stochastic Block Model for Multilevel Networks: Application to the Sociology of Organisations. Saint-Clair Chabert-Liddell, Pierre Barbillon, Sophie Donnet & Emmanuel Lazega Computational Statistics and Data Analysis, Volume 158, june 2021. [Arxiv].

• [A18] Block models for multipartite networks. Applications in ecology and ethnobiology. A. Bar-Hen, P. Barbillon & S. Donnet. Statistical Modelling, First Published December 18, 2020. [Arxiv]

• [A17] Nonparametric Bayesian estimation of multivariate Hawkes processes. S. Donnet, V. Rivoirard & J. Rousseau. Annals of Statistics, 2020, Vol. 48, No. 5, 2698-2727. [Arxiv]

• [A16] Effects of competition on collective learning in advice networks. E. Lazega, A. Bar-Hen, P. Barbillon, S. Donnet. Social Networks, Volume 47, October 2016, Pages 1–14 pdf

• [A15] Stochastic block models for multiplex networks: an application ot multilevel network of researchers. P. Barbillon, S. Donnet, E. Lazega, A. Bar-Hen. JRSSA. Volume 180, Issue1, January 2017, Pages 295-314 [Arxiv]

• [A14] * Posterior concentration rates for empirical Bayes procedures with applications to Dirichlet process mixtures.* S. Donnet, V. Rivoirard, J. Rousseau, C. Scricciolo. Bernoulli Journal 24(1): 231-256 (February 2018).

• [A13] S. Donnet, V. Rivoirard, J. Rousseau, C. Scricciolo. Posterior concentration rates for counting processes with Aalen multiplicative intensities. Bayesian Analysis 12(1): 53-87 (March 2017).

• [A12] M. Capistran, A. Christen, S. Donnet. Bayesian Analysis of ODE’s : solver optimal accuracy and Bayes factors. Journal of Uncertainty Quantification, 4, 829-849. pdf

• [A11] S. Donnet, J. Rousseau, J. Bayesian Inference for Partially Observed Branching Processes. Bayesian Analysis Volume 11, Number 1 (2016), 151-190

• [A10] S. Donnet, Bartolo, R., Fernandes J.M., Cunha J.P., Prado, L. and Merchant, H. Monkeys time their movement pauses and not their movement kinematics during a synchronization-continuation rhythmic task. Journal Of Neurophysiology, May 2014 ; 111(10), 2138 pdf

• [A9] S. Donnet, A. Samson. Using PMCMC in EM algorithm for stochastic mixed models : theoretical and practical issues. Journal de la Société Française de Statistique, 155, 49-72, 2014.

• [A8] S. Donnet, A. Samson. A review on estimation of stochastic differential equations for pharmacokinetic/ pharmacodynamic models. Advanced Drug Delivery Reviews pdf

• [A7] I. Albert, S. Donnet, C. Guihenneuc, S. Low-Choy, K. Mengersen, J. Rousseau, Combining expert opinions in prior elicitation (with discussion). Bayesian Analysis, 7(3), 503-546 (2012)

• [A6] S. Donnet, J.-M. Marin . An empirical Bayes procedure for the selection of Gaussian graphical models. Statistics and Computing, 22(5), 1113-1123 (2012) pdf

• [A5] S. Donnet , J-L Foulley, A. Samson. Bayesian analysis of growth curves using mixed models defined by stochastic differential equations . Biometrics, 66(3) :733-741, (2010) pdf

• [A4] P. Ciuciu, T. Vincent, L. Risser, S. Donnet. A joint detection-estimation framework for analysing within-subject fMRI data. Journal de la Société Française de Statistiques, Vol. 151, No 1 (2010)

• [A3] S. Donnet, A. Samson. Parametric inference for mixed models defined by stochastic differential equations. ESAIM P&S, 12 :196-218, (2008) pdf

• [A2] S. Donnet, A. Samson. Estimation of parameters in missing data models defined by differential equations. J. Statist. Plann. Inference 137 (2007), no. 9, 2815–2831 pdf

• [A1] S. Donnet, M. Lavielle, and J.-B. Poline. Are fMRI event related reponses constant across events ?. Neuroimage,Volume 31, Issue 3, 1 (July 2006), 1169 – 1176

Book chapters

• [C1] J. Aubert, P. Barbillon, S. Donnet, V.Miele. Chap Modèles à blocs latents pour la détection de structure dans les réseaux écologiques/Statistical Models for Hidden Variables in Ecology. Available @ ISTE.

Working papers

• [W1] Using deterministic approximations to accelerate SMC for posterior sampling. S. Donnet, S. Robin. Working paper

Book reviews and discussions

• [B3] S. Donnet. Book review of “Stochastic Modelling for Systems Biology (second edition)” by Darren J. Wilkinson. CHANCE 25-4 (Décembre 2012)

• [B2] S. Donnet. Book review of “Statistical Thinking in Epidemiology” by Yu-Kang Tu and Mark S. Gilthorpe. CHANCE 25-4 (Décembre 2012)

• [B1] S. Donnet. Book review of “Monte Carlo Simulation for the Pharmaceutical Industry : Concepts, Algorithms, and Case Studies” by Mark Chang. International Statistical Review (Avril 2012)

• [D1] S. Donnet, A. Samson. Discussion on “Parameter estimation for differential equations : a generalized smoothing approaché” (by Ramsay JO, Hooker G, Campbell D and Cao J), Journal of the Royal Statistical Society : Series B, 69(5) :741-796, (2007)