[1] M. Debbarh. Loi du logarithme itéré pour les composantes du modèle additif de régression. C. R. Math. Acad. Sci. Paris, 339(10):717–720, 2004.
[2] M. Debbarh. Normalité asymptotique de l’estimateur par ondelettes des composantes d’un modèle additif de régression. C. R. Math. Acad. Sci. Paris, 343(9):601–606, 2006.
[3] M. Debbarh. Some uniform limit results in additive regression model. Communications in Statistics - Theory and
Methods, Volume 37, Issue 19 January 2008, pages 3090 - 3114.
[4] M. Debbarh and B. Maillot. Additive Regression Model For Continuous Time Processes. Communications in Statistics - Theory and Methods, Volume 37, Issue 15 September 2008, pages 2416 - 2432.
[5] M. Debbarh and B. Maillot.Asymptotic Normality of the Additive Regression Components for Continuous Time Processes. Comptes Rendus Mathématique, Volume 346, Issues 15-16, August 2008, Pages 901-906.
[6] M. Debbarh and V. Viallon. Asymptotic normality of the additive regression model components under random censorship. Submitted to J. Nonparametric Stat.(http://arxiv.org), 2006.
[7] M. Debbarh and V. Viallon. Testing additivity in nonparametric regression under random censorship. Statistics & Probability Letters, Volume 78, Issue 16, November 2008, Pages 2584-2591.
[8] M. Debbarh and V. Viallon. Uniform convergence for an estimator of the additive regression function under random censorhsip. Comptes Rendus Mathématique, Volume 345, Issue 2, 15 July 2007, Pages 97-100 (in French).
[9] M. Debbarh and V. Viallon. Uniform limit laws of the logarithm for estimators of the additive regression function in the presence of right censored data. Electron. J. Statist. Volume 2 (2008), 516-541.
[10] M. Debbarh and V. Viallon. Mean square convergence for an estimator of the additive regression function under random censorship. C. R., Math., Acad. Sci. Paris. Ser. I, 344:205–210, 2007.
[11] R. Bergel-Hayat, M.Debbarh, C. Antoniou, G. Yannis Explaining the road accident risk: Weather effects.
[14] Thèse de doctorat de l'université Paris 6, Quelques propriétés asymptotiques dans les modèles additifs de régression.