K. Antonio and J. Beirlant, Actuarial statistics with generalized linear mixed models, Insurance: Mathematics and Economics, vol.40, issue.1, pp.58-76, 2007.
DOI : 10.1016/j.insmatheco.2006.02.013

D. Belomestny, Statistical inference for time-changed L??vy processes via composite characteristic function estimation, The Annals of Statistics, vol.39, issue.4, pp.2205-2242, 2011.
DOI : 10.1214/11-AOS901

L. Birgé and P. Massart, Minimal Penalties for Gaussian Model Selection, Probability Theory and Related Fields, vol.6, issue.1-2, pp.33-73, 2007.
DOI : 10.1007/s00440-006-0011-8

M. Bogsted and S. M. Pitts, Decompounding random sums: a nonparametric approach, Annals of the Institute of Statistical Mathematics, vol.26, issue.5, pp.855-872, 2010.
DOI : 10.1007/s10463-008-0200-6

C. Butucea and A. B. Tsybakov, Sharp optimality in density deconvolution with dominating bias. I. Theory Probab, Appl, vol.52, pp.24-39, 2008.

C. Butucea and A. B. Tsybakov, Sharp optimality in density deconvolution with dominating bias. II. Theory Probab, Appl, vol.52, pp.237-249, 2008.

C. Chesneau, F. Comte, and F. Navarro, Fast nonparametric estimation for convolutions of densities, Canadian Journal of Statistics, vol.51, issue.4, pp.617-636, 2013.
DOI : 10.1002/cjs.11191

URL : https://hal.archives-ouvertes.fr/hal-00798766

F. Comte, C. Duval, and V. Genon-catalot, Nonparametric density estimation in compound Poisson processes using convolution power estimators, Metrika, vol.153, issue.1, pp.163-183, 2014.
DOI : 10.1007/s00184-013-0475-3

F. Comte and . Genon-catalot, Nonparametric estimation for pure jump L??vy processes based on high frequency data, Stochastic Processes and their Applications, pp.4088-4123, 2009.
DOI : 10.1016/j.spa.2009.09.013

M. Davidian and D. M. Giltinan, Nonlinear Models for Repeated Measurement Data, 1995.

C. Duval, Density estimation for compound Poisson processes from discrete data, Stochastic Processes and their Applications, vol.123, issue.11, 2013.
DOI : 10.1016/j.spa.2013.06.006

P. Embrechts, C. Klüppelberg, and T. Mikosch, Modelling extremal events, 1997.
DOI : 10.1007/978-3-642-33483-2

B. Van-es, S. Gugushvili, and P. Spreij, A kernel type nonparametric density estimator for decompounding, Bernoulli, vol.13, issue.3, p.672694, 2007.
DOI : 10.3150/07-BEJ6091

J. E. Figueroa-lópez, Nonparametric estimation of Lévy models based on discrete-sampling. Optimality, IMS Lecture Notes Monogr. Ser. Inst. Math. Statist, vol.57, pp.117-146, 2009.

J. Grandell, Mixed Poisson processes, Monographs on Statistics and Applied Probability, 1997.
DOI : 10.1007/978-1-4899-3117-7

S. Gugushvili, Nonparametric inference for discretely sampled L??vy processes, Annales de l'Institut Henri Poincar??, Probabilit??s et Statistiques, vol.48, issue.1, pp.282-307, 2012.
DOI : 10.1214/11-AIHP433

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

T. Mikosch, Non-life insurance mathematics. An introduction with the Poisson process, 2009.

M. H. Neumann, On the effect of estimating the error density in nonparametric deconvolution, Journal of Nonparametric Statistics, vol.46, issue.4, pp.307-320, 1997.
DOI : 10.1214/aos/1176348768

M. H. Neumann and M. Reiss, Nonparametric estimation for L??vy processes from low-frequency observations, Bernoulli, vol.15, issue.1, pp.223-248, 2009.
DOI : 10.3150/08-BEJ148

J. C. Pinheiro and D. M. Bates, Mixed-Effects Models in S and S-PLUS, 2000.
DOI : 10.1007/978-1-4419-0318-1

H. Tuckwell, Introduction to Theoretical Neurobiology Nonlinear and stochastic theories. Cambridge studies in biology 8, 1998.

F. A. Ueltzhöfer and C. Klüppelberg, An oracle inequality for penalised projection estimation of L??vy densities from high-frequency observations, Journal of Nonparametric Statistics, vol.36, issue.4, pp.967-989, 2011.
DOI : 10.1080/0094965021000015477

C. Fabienne and . Umr, rue des Saints-P` eres, 75006 PARIS, FRANCE email. fabienne.comte@parisdescartes.fr Supporting information Additional supporting information may be found in the online version of this article at the publishers web site

A. Appendix, Additional proofs A.1. Proof of Lemma 1

B. Appendix, Additional simulation results