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

O. V. Besov, V. P. Il-'in, and S. M. Nikol-'ski?-i, Integral Representations of Functions and Imbedding Theorems, 1979.

L. D. Brown and M. G. Low, A constrained risk inequality with applications to nonparametric functional estimation, The Annals of Statistics, vol.24, issue.6, pp.2524-2535, 1996.
DOI : 10.1214/aos/1032181166

C. Chesneau, Regression with random design: A minimax study, Statistics & Probability Letters, vol.77, issue.1, pp.40-53, 2007.
DOI : 10.1016/j.spl.2006.05.010

URL : https://hal.archives-ouvertes.fr/hal-00014248

B. Delyon and A. Juditsky, On Minimax Wavelet Estimators, Applied and Computational Harmonic Analysis, vol.3, issue.3, pp.215-228, 1995.
DOI : 10.1006/acha.1996.0017

S. Ga¨?ffasga¨?ffas, On pointwise adaptive curve estimation based on inhomogeneous data, ESAIM: Probability and Statistics, vol.11, pp.344-364, 2007.
DOI : 10.1051/ps:2007023

S. Ga¨?ffasga¨?ffas and G. Lecué, Optimal rates and adaptation in the single-index model using aggregation, Electronic Journal of Statistics, vol.1, issue.0, pp.538-573, 2007.
DOI : 10.1214/07-EJS077

A. Goldenshluger, O. Lepski, A. Goldenshluger, and O. Lepski, Universal pointwise selection rule in multivariate function estimation, Bernoulli, vol.14, issue.4, pp.1150-1190, 2008.
DOI : 10.3150/08-BEJ144

G. K. Golubev and J. L. Horowitz, Asymptotically minimax estimation of a regression function in an additive model. (In Russian) Problemy Peredachi Informatsii 28 3?15; translation in Probl Semiparametric Methods in Econometrics, Inf. Transm. Lecture Notes in Statistics, vol.28, issue.131, pp.101-112, 1992.

R. I. Jennrich, G. Kerkyacharian, O. Lepski, and D. Picard, Asymptotic Properties of Non-Linear Least Squares Estimators, The Annals of Mathematical Statistics, vol.40, issue.2, pp.633-643, 1969.
DOI : 10.1214/aoms/1177697731

G. Kerkyacharian, O. Lepski, and D. Picard, Nonlinear Estimation in Anisotropic Multi-Index Denoising. Sparse Case, Theory of Probability & Its Applications, vol.52, issue.1, pp.58-77, 2008.
DOI : 10.1137/S0040585X97982864

G. Kerkyacharian and D. Picard, Regression in random design and warped wavelets, Bernoulli, vol.10, issue.6, pp.1053-1105, 2004.
DOI : 10.3150/bj/1106314850

URL : https://hal.archives-ouvertes.fr/hal-00103448

R. Kulik and M. Raimondo, Wavelet regression in random design with heteroscedastic dependent errors, The Annals of Statistics, vol.37, issue.6A, pp.3396-3430, 2009.
DOI : 10.1214/09-AOS684

O. Lepski, Upper functions for positive random functionals. I. General setting and Gaussian random functions, Mathematical Methods of Statistics, vol.22, issue.1, pp.1-27, 2013.
DOI : 10.3103/S1066530713010018

URL : https://hal.archives-ouvertes.fr/hal-01265252

O. V. Lepski, E. Mammen, and V. G. Spokoiny, Optimal spatial adaptation to inhomogeneous smoothness: An approach based on kernel estimates with variable bandwidth selectors, Ann. Statist, vol.25, pp.929-947, 1997.

O. V. Lepski?-i, A problem of adaptive estimation in Gaussian white noise. Theory Probab, Appl, vol.35, pp.459-466, 1990.

O. Lepski and N. Serdyukova, Supplement to Adaptive estimation under single-index constraint in a regression model, pp.10-1214, 2013.

G. S. Maddala, Limited-Dependent and Qualitative Variables in Econometrics Econometric Society Monographs in Quantitative Economics 3, 1983.

R. L. Wheeden, A. Zygmund, M. Wong, and Z. Zheng, Measure and Integral: An Introduction to Real Analysis. Pure and Applied Mathematics 43. Dekker Wavelet threshold estimation of a regression function with random design, J. Multivariate Anal, vol.80, pp.256-284, 1977.

F. Aix-marseille-rue, Joliot Curie 13453 Marseille France E-mail: Oleg.Lepski@cmi.univ-mrs