Log-Density Deconvolution by Wavelet Thresholding

Bigot, Jérôme and Van Bellegem, Sébastien (2009) Log-Density Deconvolution by Wavelet Thresholding. TSE Working Paper, n. 09-011

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Official URL: http://tse-fr.eu/pub/22136

Abstract

This paper proposes a new wavelet-based method for deconvolving a
density. The estimator combines the ideas of nonlinear wavelet thresholding with periodised Meyer wavelets and estimation by information projection. It is guaranteed to be in the class of density functions, in particular it is positive everywhere by construction. The asymptotic optimality of the estimator is established in terms of rate of convergence of the Kullback-Leibler discrepancy over Besov classes. Finite sample properties is investigated in detail, and show the excellent empirical performance of the estimator, compared with other recently introduced estimators.

Item Type: Monograph (Working Paper)
Language: French
Date: 11 February 2009
Uncontrolled Keywords: deconvolution, wavelet thresholding, adaptive estimation
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 18 Jan 2012 05:59
Last Modified: 07 Mar 2018 13:22
OAI ID: oai:tse-fr.eu:22136
URI: http://publications.ut-capitole.fr/id/eprint/3194

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