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Uniform strong consistency of a frontier estimator using kernel regression on high order moments

Stéphane Girard 1 Armelle Guillou 2 Gilles Stupfler 3
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
Abstract : We consider the high order moments estimator of the frontier of a random pair introduced by Girard, S., Guillou, A., Stupfler, G. (2012). Frontier estimation with kernel regression on high order moments. In the present paper, we show that this estimator is strongly uniformly consistent on compact sets and its rate of convergence is given when the conditional cumulative distribution function belongs to the Hall class of distribution functions.
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Stéphane Girard, Armelle Guillou, Gilles Stupfler. Uniform strong consistency of a frontier estimator using kernel regression on high order moments. ESAIM: Probability and Statistics, EDP Sciences, 2014, 18, pp.642--666. ⟨10.1051/ps/2013050⟩. ⟨hal-00764425v2⟩

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