S. Arlot and P. Massart, 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/inria-00287631

I. V. Basawa and J. Zhou, Non-Gaussian bifurcating models and quasi-likelihood estimation, Journal of Applied Probability, pp.41-55, 2004.
DOI : 10.1239/jap/1082552190

M. Bec and C. Lacour, Adaptive pointwise estimation for pure jump L??vy processes, Statistical Inference and Stochastic Processes, pp.229-256, 2015.
DOI : 10.1080/0094965021000015477
URL : http://arxiv.org/abs/1205.4692

I. Benjamini and Y. Peres, Markov chains indexed by trees. The Annals of Probability, pp.219-243, 1994.
DOI : 10.1214/aop/1176988857

K. Bertin, C. Lacour, and V. Rivoirard, Adaptive pointwise estimation of conditional density function, Annales de l'Institut Henri Poincaré Probabilités et Statistiques, pp.52-939, 2016.
DOI : 10.1214/14-AIHP665
URL : https://hal.archives-ouvertes.fr/hal-00922555

L. Birgé and P. Massart, Minimum Contrast Estimators on Sieves: Exponential Bounds and Rates of Convergence, Bernoulli, vol.4, issue.3, pp.329-375, 1998.
DOI : 10.2307/3318720

S. V. Bitseki-penda, H. Djellout, and A. Guillin, Deviation inequalities, moderate deviations and some limit theorems for bifurcating Markov chains with application, The Annals of Applied Probability, vol.24, issue.1, pp.235-291, 2014.
DOI : 10.1214/13-AAP921
URL : https://hal.archives-ouvertes.fr/hal-00646588

S. V. Bitseki-penda, M. Hoffmann, and A. Olivier, Adaptive estimation for bifurcating Markov chains, Bernoulli, vol.23, issue.4B, 2016.
DOI : 10.3150/16-BEJ859
URL : https://hal.archives-ouvertes.fr/hal-01251594

S. V. Bitseki-penda and A. Olivier, Autoregressive functions estimation in nonlinear bifurcating autoregressive models, Statistical Inference for Stochastic Processes, pp.179-210, 2017.
DOI : 10.1007/b13794
URL : https://hal.archives-ouvertes.fr/hal-01159255

G. Chagny, Adaptive Warped Kernel Estimators, Scandinavian Journal of Statistics, vol.76, issue.375, pp.336-360, 2015.
DOI : 10.1080/01621459.1981.10477700
URL : https://hal.archives-ouvertes.fr/hal-00715184

G. Chagny and A. Roche, Adaptive and minimax estimation of the cumulative distribution function given a functional covariate, Electronic Journal of Statistics, vol.8, issue.2, pp.2352-2404, 2014.
DOI : 10.1214/14-EJS956
URL : https://hal.archives-ouvertes.fr/hal-00931228

G. Chagny and A. Roche, Adaptive estimation in the functional nonparametric regression model, Journal of Multivariate Analysis, vol.146, pp.105-118, 2016.
DOI : 10.1016/j.jmva.2015.07.001
URL : https://hal.archives-ouvertes.fr/hal-01099520

M. Chichignoud and S. Loustau, Bandwidth selection in kernel empirical risk minimization via the gradient, The Annals of Statistics, vol.43, issue.4, pp.1617-1646, 2015.
DOI : 10.1214/15-AOS1318
URL : https://hal.archives-ouvertes.fr/hal-00937026

F. Comte and C. Lacour, Anisotropic adaptive kernel deconvolution, Annales de l'Institut Henri Poincaré Probabilités et Statistiques, pp.569-609, 2013.
DOI : 10.1214/11-AIHP470
URL : https://hal.archives-ouvertes.fr/hal-00579608

R. Cowan and R. G. Staudte, The Bifurcating Autoregression Model in Cell Lineage Studies, Biometrics, vol.42, issue.4, pp.769-783, 1986.
DOI : 10.2307/2530692

C. Dion and V. Genon-catalot, Bidimensional random effect estimation in mixed stochastic differential model, Statistical Inference for Stochastic Processes, vol.47, issue.2, pp.131-158, 2016.
DOI : 10.1007/b13794
URL : https://hal.archives-ouvertes.fr/hal-01103303

M. Doumic, M. Hoffmann, N. Krell, and L. Robert, Statistical estimation of a growth-fragmentation model observed on a genealogical tree, Bernoulli, vol.21, issue.3, pp.1760-1799, 2015.
DOI : 10.3150/14-BEJ623
URL : https://hal.archives-ouvertes.fr/hal-01102799

A. Goldenshluger and O. Lepski, 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

A. Goldenshluger and O. Lepski, On adaptive minimax density estimation on R d . Probability Theory and Related Fields, pp.479-543, 2014.
DOI : 10.1007/s00440-013-0512-1
URL : https://hal.archives-ouvertes.fr/hal-01265245

A. Guilloux, S. Lemler, and M. Taupin, Adaptive kernel estimation of the baseline function in the Cox model with high-dimensional covariates, Journal of Multivariate Analysis, vol.148, pp.141-159, 2016.
DOI : 10.1016/j.jmva.2016.03.002
URL : https://hal.archives-ouvertes.fr/hal-01171775

J. Guyon, Limit theorems for bifurcating Markov chains. Application to the detection of cellular aging, The Annals of Applied Probability, vol.17, issue.5/6, pp.1538-1569, 2007.
DOI : 10.1214/105051607000000195

C. Lacour and P. Massart, Minimal penalty for Goldenshluger???Lepski method, Stochastic Processes and their Applications, pp.3774-3789, 2016.
DOI : 10.1016/j.spa.2016.04.015
URL : https://hal.archives-ouvertes.fr/hal-01121989

O. Lepski, Adaptive estimation over anisotropic functional classes via oracle approach. The Annals of Statistics, pp.1178-1242, 2015.
DOI : 10.1214/14-aos1306
URL : https://hal.archives-ouvertes.fr/hal-01265235

T. Patschkowski and A. Rohde, Adaptation to lowest density regions with application to support recovery. The Annals of Statistics, pp.255-287, 2016.
DOI : 10.1214/15-aos1366
URL : http://arxiv.org/abs/1408.4057

M. K. Pitt, C. Chatfield, and S. G. , Constructing First Order Stationary Autoregressive Models via Latent Processes, Scandinavian Journal of Statistics, vol.27, issue.4, pp.657-663, 2002.
DOI : 10.1239/jap/1032192553

G. Rebelles, $\mathbb{L}_{p}$ adaptive estimation of an anisotropic density under independence hypothesis, Electronic Journal of Statistics, vol.9, issue.1, pp.106-134, 2015.
DOI : 10.1214/15-EJS986

A. Tsybakov, Introduction to Nonparametric Estimation. Springer series in statistics, 2009.

S. Vaì-ere-bitseki-penda, I. , and C. , Université Bourgogne Franche-Comté, 9 avenue Alain Savary, 21078 Dijon Cedex, France. E-mail address: simeon-valere.bitseki-penda@u-bourgogne