P. Tseng, An Analysis of the EM Algorithm and Entropy-Like Proximal Point Methods, Mathematics of Operations Research, vol.29, issue.1, pp.27-44, 2004.
DOI : 10.1287/moor.1030.0073

S. Chrétien and A. Hero, Generalized Proximal Point Algorithms and Bundle Implementations Available online, 2016.

A. Goldstein, How good are the proximal point algorithms?, Numerical Functional Analysis and Optimization, vol.9, issue.7-8, pp.709-724, 1987.
DOI : 10.1080/01630568208816109

S. Chrétien and A. Hero, Acceleration of the EM algorithm via proximal point iterations, Proceedings. 1998 IEEE International Symposium on Information Theory (Cat. No.98CH36252), pp.16-21, 1998.
DOI : 10.1109/ISIT.1998.709049

I. Csiszár, Eine informationstheoretische Ungleichung und ihre anwendung auf den Beweis der ergodizität von Markoffschen Ketten, Publ. Math. Inst. Hung. Acad. Sci, vol.8, pp.95-108, 1963.

M. Broniatowski and A. Keziou, Parametric estimation and tests through divergences and the duality technique, Journal of Multivariate Analysis, vol.100, issue.1, pp.16-36, 2009.
DOI : 10.1016/j.jmva.2008.03.011

N. Cressie and T. R. Read, Multinomial goodness-of-fit tests, J. R. Stat. Soc. Ser. B, vol.46, pp.440-464, 1984.

M. Broniatowski and A. Keziou, Minimization of ??-divergences on sets of signed measures, Studia Scientiarum Mathematicarum Hungarica, vol.43, issue.4, pp.403-442, 2006.
DOI : 10.1556/SScMath.43.2006.4.2
URL : https://hal.archives-ouvertes.fr/hal-00467649

F. Liese, On Divergences and Informations in Statistics and Information Theory, IEEE Transactions on Information Theory, vol.52, issue.10, pp.4394-4412, 2006.
DOI : 10.1109/TIT.2006.881731

A. Mohamad and D. , Towards a better understanding of the dual representation of phi divergences, Statistical Papers, vol.5, issue.1, 2016.
DOI : 10.1007/s00362-016-0812-5

A. Toma and M. Broniatowski, Dual divergence estimators and tests: Robustness results, Journal of Multivariate Analysis, vol.102, issue.1, pp.20-36, 2011.
DOI : 10.1016/j.jmva.2010.07.010
URL : https://hal.archives-ouvertes.fr/hal-00441124

R. T. Rockafellar and R. J. Wets, Variational Analysis, 1998.
DOI : 10.1007/978-3-642-02431-3

A. Basu, I. R. Harris, N. L. Hjort, and M. C. Jones, Robust and efficient estimation by minimising a density power divergence, Biometrika, vol.85, issue.3, pp.549-559, 1998.
DOI : 10.1093/biomet/85.3.549

A. P. Dempster, N. M. Laird, and D. B. Rubin, Maximum likelihood from incomplete data via the EM algorithm, J. R. Stat. Soc. B, vol.39, pp.1-38, 1977.

C. F. Wu, On the Convergence Properties of the EM Algorithm, The Annals of Statistics, vol.11, issue.1, pp.95-103, 1983.
DOI : 10.1214/aos/1176346060

A. Ostrowski, Solution of Equations and Systems of Equations, 1966.

S. Chrétien and A. Hero, On EM algorithms and their proximal generalizations. ESAIM Probabil, pp.308-326, 2008.

C. Berge, Topological Spaces: Including a Treatment of Multi-valued Functions, Vector Spaces, and Convexity, 1963.

A. Meister, Deconvolution Problems in Nonparametric Statistics, 2009.
DOI : 10.1007/978-3-540-87557-4

R. Jiménz and Y. Shao, On robustness and efficiency of minimum divergence estimators, Test, vol.1, issue.2, pp.241-248, 2001.
DOI : 10.1007/BF02595695

J. A. Nelder and R. Mead, A Simplex Method for Function Minimization, The Computer Journal, vol.7, issue.4, pp.308-313, 1965.
DOI : 10.1093/comjnl/7.4.308

R. The and . Team, R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2013. c 2016 by the authors This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http