N. Altman and C. Léger, Bandwidth selection for kernel distribution function estimation, J. Statist. Plann. Inference, vol.46, issue.2, pp.195-214, 1995.

A. Azzalini, A note on the estimation of a distribution function and quantiles by a kernel method, Biometrika, vol.68, issue.1, pp.326-328, 1981.

G. J. Babu, A. J. Canty, and Y. P. Chaubey, Application of Bernstein polynomials for smooth estimation of a distribution and density function, J. Statist. Plann. Inference, vol.105, issue.2, pp.377-392, 2002.

. Billingsley, Convergence of probability measures, Wiley Series in Probability and Statistics: Probability and Statistics, 1999.

D. Bosq, Predicting smoothed Poisson process and regularity for density estimation in the context of an exponential rate, 2017.

A. Bowman, P. Hall, and T. Prvan, Bandwidth selection for the smoothing of distribution functions, Biometrika, vol.85, issue.4, pp.799-808, 1998.

G. Caraux and O. Gascuel, Bounds on distribution functions of order statistics for dependent variates, Statist. Probab. Lett, vol.14, issue.2, pp.103-105, 1992.

M. Cheng and L. Peng, Regression modeling for nonparametric estimation of distribution and quantile functions, Statist. Sinica, vol.12, issue.4, pp.1043-1060, 2002.

H. A. David and H. N. Nagaraja, Order statistics. Wiley Series in Probability and Statistics, 2003.

M. L. Huang and P. H. Brill, A distribution estimation method based on level crossings, J. Statist. Plann. Inference, vol.124, issue.1, pp.45-62, 2004.

P. Janssen, J. S. Marron, N. Veraverbeke, and W. Sarle, Scale measures for bandwidth selection, J. Nonparametr. Statist, vol.5, issue.4, pp.359-380, 1995.

M. C. Jones, The performance of kernel density functions in kernel distribution function estimation, Statist. Probab. Lett, vol.9, issue.2, pp.129-132, 1990.

M. Kaluszka and A. Okolewski, An extension of the Erd? os-Neveu-Rényi theorem with applications to order statistics, Statist. Probab. Lett, vol.55, issue.2, pp.181-186, 2001.

A. Leblanc, On estimating distribution functions using Bernstein polynomials, Ann. Inst. Statist. Math, vol.64, issue.5, pp.919-943, 2012.

M. Lejeune and P. Sarda, Smooth estimators of distribution and density functions, Comput. Statist. Data Anal, vol.14, issue.4, pp.457-471, 1992.

J. S. Marron and M. P. Wand, Exact mean integrated squared error, Ann. Statist, vol.20, issue.2, pp.712-736, 1992.

P. Massart, The tight constant in the Dvoretzky-Kiefer-Wolfowitz inequality, Ann. Probab, vol.18, issue.3, pp.1269-1283, 1990.

W. Maurer and B. H. Margolin, The multivariate inclusion-exclusion formula and order statistics from dependent variates, Ann. Statist, vol.4, issue.6, pp.1190-1199, 1976.

M. Polansky and E. R. Baker, Multistage plug-in bandwidth selection for kernel distribution function estimates, J. Statist. Comput. Simulation, vol.65, issue.1, pp.63-80, 2000.

A. Quintela-del-río and G. Estévez-pérez, Nonparametric kernel distribution function estimation with kerdiest: an R Package for bandwidth choice and applications, Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, vol.50, pp.1-21, 2012.

R. R. Read, The asymptotic inadmissibility of the sample distribution function, Ann. Math. Statist, vol.43, pp.89-95, 1972.

T. Rychlik, Sharp bounds on L-estimates and their expectations for dependent samples, Comm. Statist. Theory Methods, vol.22, issue.4, pp.1053-1068, 1993.

T. Rychlik, Distributions and expectations of order statistics for possibly dependent random variables, J. Multivariate Anal, vol.48, issue.1, pp.31-42, 1994.

P. Sarda, Smoothing parameter selection for smooth distribution functions, J. Statist. Plann. Inference, vol.35, issue.1, pp.65-75, 1993.

D. W. Scott, Frequency polygons: theory and application, J. Amer. Statist. Assoc, vol.80, issue.390, pp.348-354, 1985.

R. Servien, Estimation de la fonction de répartition : revue bibliographique, J. SFdS, vol.150, issue.2, pp.84-104, 2009.

J. S. Simonoff, Smoothing methods in statistics, Springer Series in Statistics, 1996.

J. Swanepoel, Mean integrated squared error properties and optimal kernels when estimating a distribution function, Comm. Statist. Theory Methods, vol.17, issue.11, pp.3785-3799, 1988.

J. Swanepoel and F. Van-graan, A new kernel distribution function estimator based on a non-parametric transformation of the data, Scand. J. Statist, vol.32, issue.4, pp.551-562, 2005.