Y. Baraud, Model selection for regression on a random design, ESAIM Probab. Statist, vol.6, pp.127-146, 2002.
DOI : 10.1051/ps:2002007

URL : https://www.esaim-ps.org/articles/ps/pdf/2002/01/psVol6-7.pdf

A. Barron, L. Birgé, and P. Massart, Risk bounds for model selection via penalization, Probab. Theory Related Fields, vol.113, pp.301-413, 1999.
DOI : 10.1007/s004400050210

H. C. Berbee, Random walks with stationary increments and renewal theory, Math. Tracts. Mathematisch Centrum, p.112, 1979.

L. Birgé and P. Massart, Minimum contrast estimators on sieves: exponential bounds and rates of convergence. Bernoulli, vol.4, pp.329-375, 1998.

A. Cohen, M. A. Davenport, and D. Leviatan, On the stability and acuracy of least squares approximations, Found. Comput. math, vol.13, pp.819-834, 2013.

F. Comte and V. Genon-catalot, Regression funtion estimation on non compact support as a partly inverse problem, 2018.

F. Comte, V. Genon-catalot, and Y. Rozenholc, Penalized nonparametric mean square estimation of the coefficients of diffusion processes, Bernoulli, vol.13, pp.514-543, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00748947

A. Dalalyan, Sharp adaptive estimation of the drift function for ergodic diffusions, Ann. Statist, vol.33, issue.6, pp.2507-2528, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00022066

S. Efromovich, Nonparametric curve estimation. Methods, theory, and applications. Springer Series in Statistics, 1999.

E. Gobet, M. Hoffmann, and M. Reiss, Nonparametric estimation of scalar diffusions based on low frequency data, Ann. Statist, vol.32, pp.2223-2253, 2004.

M. Hoffmann, Adaptive estimation in diffusion processes, Stochastic Process. Appl, vol.79, pp.135-163, 1999.
DOI : 10.1016/s0304-4149(98)00074-x

URL : https://doi.org/10.1016/s0304-4149(98)00074-x

M. Kessler, A. Lindner, and M. Sørensen, Statistical methods for stochastic differential equations, 2012.

T. Klein and E. Rio, Concentration around the mean for maxima of empirical processes, Ann. Probab, vol.33, issue.3, pp.1060-1077, 2005.
DOI : 10.1214/009117905000000044

URL : http://doi.org/10.1214/009117905000000044

Y. A. Kutoyants, Statistical inference for ergodic diffusion processes, Springer Series in Statistics, 2004.

E. Pardoux, A. Veretennikov, and . Yu, On the Poisson equation and diffusion approximation, I. Ann. Probab, vol.29, pp.1061-1085, 2001.
DOI : 10.1214/009117905000000062

URL : https://doi.org/10.1214/009117905000000062

V. G. Spokoiny, Adaptive drift estimation for nonparametric diffusion model, Ann. Statist, vol.28, pp.815-836, 2000.

G. Szegö, Orthogonal polynomials, vol.XXIII, 1975.

J. A. Tropp, An introduction to matrix concentration inequalities, Found. Trends Mach. Learn, vol.8, issue.1-2, pp.1-230, 2015.
DOI : 10.1561/2200000048

URL : http://arxiv.org/pdf/1501.01571

A. B. Tsybakov, Introduction to nonparametric estimation, Springer Series in Statistics, 2009.

A. Y. Veretennikov, Bounds for the mixing rate in the theory of stochastic differential equation, Theory Probab. Appl, vol.32, pp.273-281, 1988.

G. Viennet, Inequalities for absolutely regular processes: application to density estimation, Probab. Theory Relat. Fields, vol.107, pp.467-492, 1997.