Author(s): Proença, Isabel
Date: 2006
Persistent ID: http://hdl.handle.net/10400.5/28427
Origin: Repositório da Universidade de Lisboa
Subject(s): Deconvolution; Density Estimation; Errors-In-Variables; Kernel; Simulations
Document details
A simple deconvolving Kernel density estimator when noise is Gaussian
Description
Deconvolving kernel estimators when noise is Gaussian entail heavy calculations. In order to obtain the density estimates numerical evaluation of a specific integral is needed. This work proposes an approximation to the deconvolving kernel which simplifies considerably calculations by avoiding the typical numerical integration. Simulations included indicate that the lost in performance relatively to the true deconvolving kernel, is almost negligible in finite samples
Document Type
Book part
Language English
Contributor(s) Repositório Científico de Acesso Aberto da ULisboa
Language English
Contributor(s) Repositório Científico de Acesso Aberto da ULisboa
