M. Abramowitz and I. A. Stegun, Handbook of mathematical functions with formulas, graphs, and mathematical tables, National Bureau of Standards Applied Mathematics Series, 55 For sale by the Superintendent of Documents, U.S. Government Printing Office, 1964.

O. E. Barndorff-nielsen, Processes of normal inverse Gaussian type, Finance and Stochastics, vol.2, issue.1, p.4168, 1998.
DOI : 10.1007/s007800050032

O. E. Barndorff-nielsen and N. Shephard, Non-Gaussian Ornstein-Uhlenbeck-based models and some of their uses in financial economics, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.2, pp.167-241, 2001.
DOI : 10.1111/1467-9868.00282

A. Barron, L. Birgé, and P. Massart, Risk bounds for model selection via penalization. Probab. Theory Related Fields, pp.301-413, 1999.

L. Birgé and P. Massart, From model selection to adaptive estimation, in Festschrift for Lucien Le Cam: Research Papers in Probability and Statistics, pp.55-87, 1997.

C. Butucea, Exact adaptive pointwise estimation on Sobolev classes of densities, ESAIM: Probability and Statistics, vol.5, p.131, 2001.
DOI : 10.1051/ps:2001100

L. Evroye, The double kernel method in density estimation, Ann. Inst. H. Poincar Probab. Statist, vol.25, issue.4, p.533580, 1989.

L. Devroye and G. Lugosi, A universally acceptable smoothing factor for kernel density estimates, The Annals of Statistics, vol.24, issue.6, pp.2499-2512, 1996.
DOI : 10.1214/aos/1032181164

D. L. Donoho, I. M. Johnstone, G. Kerkyacharian, and D. Picard, Density estimation by wavelet thresholding, The Annals of Statistics, vol.24, issue.2, pp.508-539, 1996.
DOI : 10.1214/aos/1032894451

W. Feller, An introduction to probability theory and its applications, 1971.

A. Goldenshluger and O. Lepski, Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality (preprint) ArXiv:1009, 1016.

P. Hall and C. C. Heyde, Martingale limit theory and its application. Probability and Mathematical Statistics, 1980.

A. Juditsky, Wavelet estimators: adapting to unknown smoothness, Math. Methods Statist, vol.6, issue.1, p.125, 1997.

M. Kendall and A. O. Stuart, J. Keith Kendall's advanced theory of statistics Distribution theory. Fifth edition, 1987.

G. Kerkyacharian, O. Lepski, and D. Picard, Nonlinear estimation in anisotropic multi-index denoising, Probability Theory and Related Fields, vol.121, issue.2, pp.137-170, 2001.
DOI : 10.1007/PL00008800

G. Kerkyacharian, D. Picard, and K. Tribouley, L p Adaptive Density Estimation, Bernoulli, vol.2, issue.3, pp.229-247, 1996.
DOI : 10.2307/3318521

M. Ledoux, On Talagrand's deviation inequalities for product measures, ESAIM: Probability and Statistics, vol.1, pp.63-87, 1997.
DOI : 10.1051/ps:1997103

P. Massart, Concentration inequalities and model selection. Lectures from the 33rd Summer School on Probability Theory held in Saint-Flour, Lecture Notes in Mathematics, p.1896, 2003.

K. Sato, Lévy processes and infinitely divisible distributions, Cambridge Studies in Advanced Mathematics, vol.68, 1999.

C. J. Stone, Optimal Rates of Convergence for Nonparametric Estimators, The Annals of Statistics, vol.8, issue.6, pp.1348-1360, 1980.
DOI : 10.1214/aos/1176345206

M. Talagrand, New concentration inequalities in product spaces, Inventiones Mathematicae, vol.126, issue.3, pp.505-563, 1996.
DOI : 10.1007/s002220050108

A. B. Tsybakov, Introduction to nonparametric estimation. Revised and extended from the 2004 French original. Translated by Vladimir Zaiats, 2009.