Uniform strong consistency of a frontier estimator using kernel regression on high order moments - Archive ouverte HAL Access content directly
Journal Articles ESAIM: Probability and Statistics Year : 2014

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

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.
Fichier principal
Vignette du fichier
Frontier_beta_final.pdf (256.15 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00764425 , version 1 (13-12-2012)
hal-00764425 , version 2 (16-07-2013)

Identifiers

Cite

Stéphane Girard, Armelle Guillou, Gilles Stupfler. Uniform strong consistency of a frontier estimator using kernel regression on high order moments. ESAIM: Probability and Statistics, 2014, 18, pp.642--666. ⟨10.1051/ps/2013050⟩. ⟨hal-00764425v2⟩
462 View
183 Download

Altmetric

Share

Gmail Facebook X LinkedIn More