1. Parameter estimation in nonlinear multivariate stochastic differential equations based on splitting schemes, Pilipovic P, Samson A, Ditlevsen S, to appear in Annals of Statistics.
  2. Remote monitoring of positive airway pressure data: Challenges, Pitfalls and Strategies to consider for optimal data science applications, G Bottaz-Bosson G, Midelet A, Mendelson M, Borel JC, Martinot JB, Le Hy R, Schaeffer MC, Samson A, Hamon A, Tamisier R, Malhotra A,  Pépin JL, Bailly S, Chest, Dec 2:S0012-3692(22)04204-0, 2022.
  3. Rheological identification of jetted fluid using machine learning, Maitrejean G, Samson A, Roux D, Physics of Fluid, 34, 093103, 2022.
  4. A splitting method for SDEs with locally Lipschitz drift: Illustration on the FitzHugh-Nagumo model, Buckwar E, Samson A, Tamborrino M, Tubikanec I, Applied Numerical Mathematics, 2022, 179, 191-220.
  5. Dataset of numerically-generated interfaces of Newtonian jets in CIJ regime, Maitrejean G, Samson A, Roux D, Data in Brief, 2022, 42, 108215.
  6. Optimal control for parameter estimation in partially observed hypoelliptic stochastic differential equations, Clairon Q, Samson A, Computational Statistics, 2022, 37, 2471-2491.
  7. Narwhals react to ship noise and airgun pulses embedded in background noise. Tervo, O.M., Blackwell, S.B., Ditlevsen, S., Conrad, A., Samson, A., Garde, E. and Heide-Jørgensen, M.P. Biology Letters, 2021.
  8. CPAP adherence trajectories in sleep apnea: clustering with summed discrete Fréchet and dynamic time warping dissimilarities, Bottaz-Bosson G, Hamon A, Pepin JL, Bailly S, Samson A, Statistics in Medicine, 2021, 40, 5373-5396.
  9. Behavioral response study on seismic airgun and vessel exposures in narwhals. Heide-Jørgensen MP,  Blackwell SB, Tervo O,  Samson A, Garde E, Hansen RG, Ngo MC, Conrad AS,  Trinhammer P,  Schmidt HC, Sinding MHS, Williams T, Ditlevsen S, Frontiers in Marine Science, section Marine Megafauna, 2021.
  10. Parameter estimation and treatment optimization in a stochastic model for immunotherapy of cancer, Diabate M, Coquille L, Samson A, J Theo Biology, 7, 502:110359, 2020.
  11. Inference for biomedical data using diffusion models with covariates and mixed effects, Grosse Ruse M, Samson A, Ditlevsen S, J Royal Statistical Society C, 69, 167-193, 2020.
  12. Optimal control for estimation in partially observed elliptic and hypoelliptic stochastic differential equations, Clairon Q, Samson A, Statistical Inference Stochastic Processes, 23, 105-127, 2020.
  13. Long-term effects of cochlear implantation on the intelligibility of speec in French-speaking children, Grandon B, Martinez MJ, Samson A, Vilain A, Journal of Child Language, 47-881-892, 202.
  14. Hypoelliptic diffusions: discretization, filtering and inference from complete and partial observations, Ditlevsen S, Samson A, J Royal Statistical Society B, 81, 361-384, 2019.
  15. Mixedsde: an R package to fit mixed stochastic differential equations, Dion C, Hermann S, Samson A, R Journal, 11, 44-66, 2019.
  16. Stochastic Proximal Gradient Algorithms for Penalized Mixed Models, Fort G, Ollier E, Samson A, Statistics and Computing, 29, 231-253, 2019.
  17. Humans are able to self-paced constant running accelerations until exhaustion, Billat V, Brunel N, Carbillet T, Labbé S, Samson A, Physica A, 506, 290-304, 2018
  18. Hypoelliptic stochastic FitzHugh-Nagumo neuronal model: mixing, up-crossing and estimation of the spike rate, Leòn JR, Samson A, Annals of Applied Probability, 28, 2243-2274, 2018.
  19. Coupling stochastic EM and Approximate Bayesian Computation for parameter inference in state-space models, Picchini U, Samson A, Computational Statistics, 33, 179-212, 2018.
  20. Statistical methodology for the analysis of repeated duration data in speech, language and hearing research, Letué F, Martinez MJ, Samson A, Vilain A, Vilain C, Journal of Speech, Language, and Hearing Research, 61, 561-582, 2018.
  21. Hazard estimation for censored data contaminated with additive measurement error: Application to length of pregnancy, Comte F, Samson A, Stirnemann J, TEST, 27, 338-359, 2018
  22. Population parametrization of costly black box models using iterations between SAEM algorithm and kriging,Grenier E, Helbert C, Louvet V, Samson A, Vigneaux P, Computational and Applied Mathematics, 37, 161-173, 2018.
  23. Adaptive estimation for stochastic damping hamiltonian systems under partial observation, Comte F, Prieur C, Samson A, Stochastic Processes and Their Applications, 127, 3689-3718, 2017.
  24. Spline regression for hazard rate estimation when data are censored and measured with error, Comte F, Mabon G, Samson A, Statistica Neerlandica, 71, 115-140, 2017.
  25. Analysis of Temozolomide resistance in low-grade gliomas by using a mechanistic mathematical model Ollier E, Mazzocco P, Ricard D, Kaloshi G, Idbaih A, Alentorn A, Psimaras D, Honnorat J, Delattre JY, Grenier E, Ducray F, Samson, A, Fundamental & Clinical Pharmacology, 31, 347-358, 2017.
  26. A comparative study of the precision of Carstens and NDI electromagnetic articulographs Savariaux C, Badin P, Samson A, Gerber S, Journal of Speech, Language, and Hearing Research, 60, 322-340, 2017.
  27. Parametric estimation of complex mixed models based on meta-model approach, Barbillon P, Barthelemy C, Samson A, Statistics and Computing, 27, 1111-1128, 2017.
  28. Unified approach for extrapolation and bridging of adult information in early-phase dose-finding paediatric studies Petit C, Samson A, Morita S, Ursino M, Guedj J, Jullien V, Comets E, Zohar S, Statistical Methods in Medical Research, 2016.
  29. Physiological and acoustic characteristics of the male music theatre voice Bourne T, Garnier M, Samson A, Journal of Acoustical Society of America, 140, 610, 2016.
  30. Mixtures of stochastic differential equations with random effects: application to data clustering,Delattre M, Genon-Catalot V, Samson A, Journal of Statistical Planning and Inference, 173:109-124, 2016.
  31. A SAEM Algorithm for Fused Lasso Penalized Non Linear Mixed Effect Models: Application to Group Comparison in Pharmacokinetic Ollier E, Samson A, Delavenne X, Viallon V, Computational Statistics and Data Analysis, 96:207-221, 2016.
  32. Designing a paediatric study for an antimalarial drug including prior information from adultsPetit C, Jullien V, Samson A, Guedj J, Kiechel JR,Zohar S, Comets E, Antimicrobial Agents and Chemotherapy, 60:1481-1491, 2016.
  33. Parameter estimation in neuronal stochastic differential equation models from intracellular recordings of membrane potentials in single neurons: a Review Ditlevsen S, Samson A, Journal de la SFdS, 157:6-21, 2016.
  34. Estimation of population parameters in stochastic differential equations with random effects in the diffusion coefficient Delattre M, Genon-Catalot V, Samson A, ESAIM P&S, 19, 2015.
  35. Estimation in the partially observed stochastic Morris-Lecar neuronal model with particle filter and stochastic approximation methods. Ditlevsen S, Samson A, Annals of Applied Statistics, 2, 674-702, 2014.
  36. Using PMCMC in EM algorithm for stochastic mixed models: theoretical and practical issues, Donnet S, Samson A, Journal de la Société Francaise de Statistique, 155, 49-72, 2014.
  37. Deconvolution estimation of onset of pregnancy with replicate observations. Comte F, Samson A, Stirnemann J, Scandinavian Journal of Statistics, 41, 325-345, 2014.
  38. Estimation in autoregressive model with measurement error. Dedecker J, Samson A, Taupin ML. ESAIM P&S, 18 227-307, 2014.
  39. Routine OGTT: a robust model including incretin effect for precise identification of insulin sensitivity and secretion in a single individual. De Gaetano A, Panunzi S, Matone A, Samson A, Kautzky-Willer A, Vrbikova J, Bendlova B, Pacin G.,PLOS ONE, 8(8): e70875.
  40. Nonparametric estimation for stochastic differential equations with random effects. Comte F, Genon-Catalot V, Samson A. Stochastic Processes and Their Applications, 123(7): 2522-2551, 2013
  41. Day-specific probabilities of conception in spontaneous pregnancies. Stirnemann J, Samson A, Bernard JP, Thalabard JC. Human Reproduction, 28(4):1110-1116, 2013.
  42. Maximum likelihood estimation for stochastic differential equations with random effects. Delattre M, Genon-Catalot V, Samson A, Scandinavian Journal of Statistics, 40(2): 322-343, 2013
  43. A review on estimation of stochastic differential equations for pharmacokinetic – pharmacodynamic models . Donnet S, Samson A, Advanced Drug Delivery Reviews, 65(7): 929-939, 2013
  44. Density estimation of a biomedical variable subject to measurement error using an auxiliary set of replicate observations. Stirnemann J, Comte F, Samson A, Statistics in Medicine, 31(30): 4154-4163, 2012.
  45. Nonparametric estimation of random effects densities in linear mixed-effects model. Comte F, Samson A, Journal of Nonparametric Statistics, 24: 951-975, 2012.
  46. Contrast estimator for completely or partially observed hypoelliptic diffusion. Samson A, Thieullen M, Stochastic Processes and Their Applications, 122:2521-2552, 2012
  47. Multiple treatment comparisons in a series of anti-malarials trials with an ordinal primary outcome and repeated treatment evaluations. Whegang SY, Samson A, Basco L, Thalabard JC,Malaria Journal, 3;11(1):147, 2012.
  48. Individual predictions based on population nonlinear mixed modeling: application to prenatal twin growth. Stirnemann J, Samson A, Thalabard JC, Statistics in Medicine, 31:1986-1999, 2012.
  49. Parameter estimation and change-point detection from Dynamic Contrast Enhanced MRI data using stochastic differential equations. Cuenod CA, Favetto B, Genon-Catalot V, Rozenholc Y, Samson A, Mathematical Biosciences, 233(1):68-76, 2011.
  50. Maximum likelihood estimation of long term HIV dynamic models and antiviral response. Lavielle M, Samson A, Fermin AK, Mentre F, Biometrics, 67(1):250-259, 2011
  51. Bayesian analysis of growth curves using mixed models defined by stochastic differential equations. Donnet S, Foulley JL, Samson A, Biometrics, 66(3):733-741, 2010
  52. Parameter estimation for a bidimensional partially observed Ornstein-Uhlenbeck process with biological application. Favetto B, Samson A, Scandinavian Journal of Statistics, 37(2):200-220, 2010
  53. Phenomenological modeling of tumor diameter growth based on a mixed effects model. Bastogne T, Samson A, Vallois P, Wantz-Mézières S, Pinel S, Bechet D, Barberi-Heyob M, Journal of Theoretical Biology, 262:544-552, 2010.
  54. A SAEM algorithm for the estimation of template and deformation parameters in medical image sequences. Richard F, Samson A, Cuenod CA, Statistics and Computing, 19:465-478, 2009.
  55. Extension of the SAEM algorithm for the nonlinear mixed models with two levels of random effects. Panhard X, Samson A, Biostatistics, 10:121-35, 2009
  56. Parametric inference for mixed models defined by stochastic differential equations. Donnet S, Samson A, ESAIM P&S, 12:196-218, 2008.
  57. Missing data in randomized controlled trials of rheumatoid arthritis with radiographic outcomes: a simulation study. Baron G, Ravaud P, Samson A, Giraudeau B, Arthritis Care & Research, 59(1):25-31, 2008.
  58. Design in nonlinear mixed effects models: optimization using the Fedorov-Wynn algorithm and power of the Wald test for binary covariates. Retout S, Comets E, Samson A, Mentré F, Statistics in Medicine, 26(28):5162-5179, 2007.
  59. Estimation of parameters in incomplete data models defined by dynamical systems. Donnet S, Samson A, Journal of Statistical Planning and Inference, 137(9):2815-31, 2007.
  60. The SAEM algorithm for group comparison tests in longitudinal data analysis based on non-linear mixed-effects model. Samson A, Lavielle M, Mentré F, Statistics in Medicine, 26(27):4860-4875, 2007.
  61. Discussion on « Parameter estimation for differential equations: a generalized smoothing approach » (by Ramsay JO, Hooker G, Campbell D and Cao J), Donnet S, Samson A, Journal of the Royal Statistical Society: Series B, 69(5):741-796, 2007
  62. Extension of the SAEM algorithm to left-censored data in non-linear mixed-effects model: application to HIV dynamics model. Samson A, Lavielle M, Mentré F, Computational Statistics and Data Analysis, 51(3):1562-74, 2006.

Book chapter

  1. Introduction to stochastic models in biology. Ditlevsen S, Samson A. In Bachar, Batzel and Ditlevsen (Eds.), Stochastic Methods and Neuron Modeling. Springer. 2012


  1. Non-asymptotic statistical test of the diffusion coefficient of stochastic differential equations, Melnykova A, Reynaud-Bouret P, Samson A, submitted.
  2. Nowhere else to go: anthropogenic noise threatens narwhals in their once pristine Artic habitat, Tervo O, Blackwell S, Ditlevsen S, Garde E, Hansen R, Samson A, Conrad A, Heide-Jorgensen MP, submitted.
  3. The Early NUmerical DIdactical Test (ENUDIT): A French-language monitoring scale to assess early numerical abilities of children from 3 to 6, Gardes ML, Croset MC, Samson A, Prado J, submitted
  4. Determinants of the response to a multicomponent therapy Program in Fibromyalgia, Guinot M, Bernard AC, Dumolard A, Samson A, Gaudin P, Submitted.
  5. EM algorithm coupled with particle filter for maximum likelihood parameter estimation of stochastic differential mixed-effects models . Donnet S, Samson A. Prepublication MAP5 2010-24

Publications in Proceedings

  1. System identification of tumor growth described by a mixed effects model. Bastogne T, Samson A, Mézières-Wantz S, Vallois P, Pinel S, Barberi-Heyob M, Proceedings of IFAC Symposium on system identification, 2009.
  2. Metropolis-Hasting techniques for finite element-based registration . Richard F, Samson A, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2007.