, Data-driven calibration of penalties for least-squares regression, Journal of Machine Learning Research, vol.10, pp.245-279, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00243116
, Adaptive non-parametric estimation in the presence of dependence, 2016.
, Random walks with stationary increments and renewal theory Mathematical Centre Tracts 112, 1979.
, Pointwise adaptive estimation of the marginal density of a weakly dependent process, Journal of Statistical Planning and Inference, vol.187, 2016.
DOI : 10.1016/j.jspi.2017.03.003
, Basic properties of strong mixing conditions. a survey and some open questions, Probability surveys, pp.107-144, 2005.
, Estimation for stochastic damping hamiltonian systems under partial observation. ii. drift term, ALEA, vol.11, pp.359-384, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01044611
, Estimation for stochastic damping hamiltonian systems under partial observation. i. invariant density. Stochastic Process, Appl, vol.124, pp.1236-1260, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01044611
, Adaptive estimation of the stationary density of discrete and continuous time mixing processes, ESAIM: Probability and Statistics, vol.107, pp.211-238, 2001.
DOI : 10.1007/s004400050094
URL : https://hal.archives-ouvertes.fr/hal-00170768
, Super optimal rates for nonparametric density estimation via projection estimators. Stochastic Process, Appl, vol.115, issue.5, pp.797-826, 2005.
DOI : 10.1016/j.spa.2004.12.004
URL : https://hal.archives-ouvertes.fr/hal-00138764
, Penalized nonparametric mean square estimation of the coefficients of diffusion processes, Bernoulli, vol.13, issue.2, pp.514-54307, 2007.
DOI : 10.3150/07-BEJ5173
URL : https://hal.archives-ouvertes.fr/hal-00748947
, Nonparametric adaptive estimation for integrated diffusions, Stochastic Processes and their Applications, vol.119, issue.3, pp.811-834, 2009.
DOI : 10.1016/j.spa.2008.04.009
URL : https://hal.archives-ouvertes.fr/hal-00110510
, Adaptive density estimation under weak dependence, ESAIM: Probability and Statistics, vol.110, pp.151-172, 2010.
DOI : 10.1007/BF02808180
URL : https://hal.archives-ouvertes.fr/hal-00591694
, Stochastic Volatility Models as Hidden Markov Models and Statistical Applications, Bernoulli, vol.6, issue.6, pp.1051-1079, 2000.
DOI : 10.2307/3318471
URL : https://hal.archives-ouvertes.fr/hal-00693752
, Parameter estimation for a discretely observed integrated diffusion process. Scand, J. Statist, vol.33, issue.1, pp.83-104, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00404901
, Bandwidth selection in kernel density estimation: Oracle inequalities and adaptive minimax optimality, The Annals of Statistics, vol.39, issue.3, pp.1608-1632, 2011.
DOI : 10.1214/11-AOS883
URL : https://hal.archives-ouvertes.fr/hal-01265258
, Nonlinear estimation in anisotropic multi-index denoising. Probab. Theory Related Fields, pp.137-170, 2001.
DOI : 10.1007/pl00008800
URL : http://www.proba.jussieu.fr/mathdoc/textes/PMA-810.pdf
, mpirical processes and concentration around the mean. The Annals of Probability, pp.1060-1077, 2005.
, Explicit parametrix and local limit theorems for some degenerate diffusion processes, Annales de l'Institut Henri Poincar??, Probabilit??s et Statistiques, vol.46, issue.4, pp.908-923, 2010.
DOI : 10.1214/09-AIHP207
URL : https://hal.archives-ouvertes.fr/hal-00559448
, Solution of Fokker-Planck equation by finite element and finite difference methods for nonlinear systems, Sadhana, vol.19, issue.EM2, pp.445-461, 2006.
DOI : 10.1007/978-3-642-61544-3
, Estimator Selection: a New Method with Applications to Kernel Density Estimation, Sankhya A, vol.58, issue.2
DOI : 10.1007/978-1-4899-3324-9
URL : https://hal.archives-ouvertes.fr/hal-01346081
, Optimal model selection for density estimation of stationary data under various mixing conditions, The Annals of Statistics, vol.39, issue.4, pp.1852-187711, 2011.
DOI : 10.1214/11-AOS888SUPP
URL : https://hal.archives-ouvertes.fr/hal-00656405
, Optimal model selection in density estimation, Annales de l'Institut Henri Poincar??, Probabilit??s et Statistiques, vol.48, issue.3, pp.884-90811, 2012.
DOI : 10.1214/11-AIHP425
URL : https://hal.archives-ouvertes.fr/hal-00422655
, Parameter estimation for partially observed hypoelliptic diffusions, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.2, issue.1, pp.49-73, 2009.
DOI : 10.1007/978-1-4757-3071-5
URL : http://arxiv.org/pdf/0710.5442v2.pdf
, Random vibration and statistical linearization, 2003.
, A contrast estimator for completely or partially observed hypoelliptic diffusion, Stochastic Processes and their Applications, 2012.
DOI : 10.1016/j.spa.2012.04.006
URL : https://hal.archives-ouvertes.fr/hal-00714352
, Penalized nonparametric drift estimation for a multidimensional diffusion process, Statistics, vol.29, issue.3, pp.61-84, 2013.
DOI : 10.1214/aos/1009210692
URL : https://hal.archives-ouvertes.fr/hal-00358410
, Nonparametric estimation of the derivatives of the stationary density for stationary processes. ESAIM Probab, Stat, vol.17, pp.33-69, 2011102.
URL : https://hal.archives-ouvertes.fr/hal-00507025
, Introduction to nonparametric estimation Springer Series in Statistics, 2009.
, Inequalities for absolutely regular sequences: application to density estimation, Probability Theory and Related Fields, vol.107, issue.4, pp.467-492, 1997.
DOI : 10.1007/s004400050094
, Some Limit Theorems for Random Functions. I, Theory of Probability & Its Applications, vol.4, issue.2, pp.178-197, 1960.
DOI : 10.1137/1104015
, Large and moderate deviations and exponential convergence for stochastic damping Hamiltonian systems, Stochastic Processes and their Applications, pp.205-238, 2001.
DOI : 10.1016/S0304-4149(00)00061-2
URL : https://doi.org/10.1016/s0304-4149(00)00061-2