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DONNET Sophie

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Current Position - Status

Department of attachment : MIDO

Centre of Research : Mathématiques (CEREMADE)

Former positions

* Sept 2006 - Aug 2007 University Paris-Descartes :
Teaching assistant in Statistic and Probabilities
* Sept 2003 - Aug 2006 University Paris-xi (Orsay - France) :
Teaching assistant in Mathematics
Resarch fellow of Laboratory of Mathematics
Preparation of my thesis in statistics

Education and qualification

Aggregation

  • Mathematics (2002)

Ph.D.

Mathématiques appliquées et applications (2006 - Université Paris XI- Orsay)

Master (Search) specialty : Modélisation Stochastique et Statistique (2003 - Université Paris XI- Orsay)

Fields of teaching, research and professionnal competence

Fields of teaching

  • Mathematics ans Statistics
  • Bayesian Statistics
  • Mathematical Statistics
  • Applied Statistics
  • Statistics and Decision theory

Fields of research

  • Applied mathematics and applications
  • Bayesian Statistics
  • Statistics

Areas of Expertise

  • Bayesian Statistics
  • Stochastic Algorithms
  • Biostatisitics and stochastic differential equations

Publications of DONNET Sophie

2013

Articles

  • Samson, Adeline ; Donnet, Sophie . A review on estimation of stochastic differential equations for pharmacokinetic/pharmacodynamic models. Advanced Drug Delivery Reviews. 2013. Elsevier. DOI http://dx.doi.org/10.1016/j.addr.2013.03.005.

Working Papers

  • Rousseau, Judith ; Donnet, Sophie . Bayesian Inference for Partially Observed Branching Processes. Université Paris-Dauphine . 2013 .

2012

Articles

  • Donnet, Sophie . Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies by Mark Chang. Synthese. Volume 80. n° 1. 2012. pages 186-187. Wiley. DOI http://dx.doi.org/10.1111/j.1751-5823.2012.00179_10.x.
  • Marin, Jean-Michel ; Donnet, Sophie . An empirical Bayes procedure for the selection of Gaussian graphical models. Statistics and Computing. Volume 22. n° 5. 2012. pages 1113-1123. Springer. DOI http://dx.doi.org/10.1007/s11222-011-9285-5.

2010

Articles

  • Vincent, Thomas ; Risser, Laurent ; Ciuciu, Pierre ; Donnet, Sophie . A joint detection-estimation framework for analysing within-subject fMRI data. Journal de la Société Française de Statistique. Volume 151. n° 1. 2010. pages 58-89. Société française de statistique et Société mathématique de France.
  • Foulley, Jean-Louis ; Samson, Adeline ; Donnet, Sophie . Bayesian analysis of growth curves using mixed models defined by stochastic differential equations. Biometrics. Volume 66. n° 3. 2010. pages 733-741. International Biometric Society. DOI http://dx.doi.org/10.1111/j.1541-0420.2009.01342.x.

Conference Contributions

  • Donnet, Sophie ; Foulley, Jean-Louis ; Samson, Adeline . Bayesian Analysis of Growth Curves Using Mixed Models Defined by Stochastic Differential Equations. 9th Valencia International Meeting on Bayesian Statistics - 2010 World Meeting of the International Society for Bayesian Analysis. Benidorm. Espagne. 2010.

Working Papers

  • Samson, Adeline ; Donnet, Sophie . EM algorithm coupled with particle filter for maximum likelihood parameter estimation of stochastic differential mixed-effects models. Université Paris-Dauphine . 2010 .

2009

Conference Contributions

  • Samson, Adeline ; Foulley, Jean-Louis ; Donnet, Sophie . Analyse bayésienne de courbes de croissance par des modèles à effets mixtes définis par équations différentielles stochastiques.. 41èmes Journées de Statistique, SFdS, Bordeaux. Bordeaux, France. France. 2009.

2008

Articles

  • Samson, Adeline ; Donnet, Sophie . Parametric inference for mixed models defined by diffusion processes. ESAIM: Probability and Statistics (P&S). Volume 12. 2008. pages 196-218. EDP Sciences. DOI http://dx.doi.org/10.1051/ps:2007045.

2007

Articles

  • Samson, Adeline ; Donnet, Sophie . Discussion on "Parameter estimation for differential equations: a generalized smoothing approach" (by Ramsay JO, Hooker G, Campbell D and Cao J),. Journal of the Royal Statistical Society: Series B (Statistical Methodology). Volume 69. n° 5. 2007. pages 778. Wiley. DOI http://dx.doi.org/10.1111/j.1467-9868.2007.00610.x.

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