n-uniformly consistent density estimation in nonparametric regression models

The paper introduces a n-consistent estimator of the probability density function of the response variable in a nonparametric regression model. The proposed estimator is shown to have a (uniform) asymptotic normal distribution, and it is computationally very simple to calculate. A Monte Carlo experiment confirms our theoretical results. The results derived in the paper adapt general U-processes theory to the inclusion of infinite dimensional nuisance parameters.

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Year of publication:	2012
Authors:	Escanciano, Juan Carlos ; Jacho-Chávez, David T.
Published in:	Journal of Econometrics. - Elsevier, ISSN 0304-4076. - Vol. 167.2012, 2, p. 305-316
Publisher:	Elsevier
Subject:	Density estimation \| Kernel smoothing \| U-processes

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011052204