Bootstrap Bandwidth Selection in Kernel Density Estimation from a Contaminated Sample.

In this paper we consider kernel estimation of a density when the data are contaminated by random noise. More specifically we deal with the problem of how to choose the bandwidth parameter in practice.

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Year of publication:	2001
Authors:	Delaigle, A. ; Gijbels, I.
Institutions:	Catholique de Louvain - Institut de statistique
Subject:	EVALUATION \| BANDWIDTH \| BOOTSTRAP

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Series:	Catholique de Louvain - Institut de statistique.
Type of publication:	Book / Working Paper
Notes:	36 pages
Classification:	C13 - Estimation ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C45 - Neural Networks and Related Topics ; C91 - Laboratory, Individual Behavior
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005661164