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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). {\it Frontier estimation with kernel regression on high order moments}. It is shown that this estimator is strongly uniformly consistent, 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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Preprints, Working Papers, ...
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https://hal.archives-ouvertes.fr/hal-00764425
Contributor : Stephane Girard <>
Submitted on : Thursday, December 13, 2012 - 9:03:33 AM
Last modification on : Tuesday, February 9, 2021 - 3:20:20 PM
Long-term archiving on: : Thursday, March 14, 2013 - 3:46:10 AM

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  • HAL Id : hal-00764425, version 1
  • ARXIV : 1212.3111

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Stéphane Girard, Armelle Guillou, Gilles Stupfler. Uniform strong consistency of a frontier estimator using kernel regression on high order moments. 2012. ⟨hal-00764425v1⟩

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