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Parametric modelling of thresholds across scales in wavelet regression

Antoniadis, Anestis and Fryzlewicz, Piotr (2006) Parametric modelling of thresholds across scales in wavelet regression. Biometrika, 93 (2). pp. 465-471. ISSN 0006-3444

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Identification Number: 10.1093/biomet/93.2.465

Abstract

We propose a parametric wavelet thresholding procedure for estimation in the ‘function plus independent, identically distributed Gaussian noise’ model. To reflect the decreasing sparsity of wavelet coefficients from finer to coarser scales, our thresholds also decrease. They retain the noise-free reconstruction property while being lower than the universal threshold, and are jointly parameterised by a single scalar parameter. We show that our estimator achieves near-optimal risk rates for the usual range of Besov spaces. We propose a crossvalidation technique for choosing the parameter of our procedure. A simulation study demonstrates very good performance of our estimator compared to other state-of-the-art techniques. We discuss an extension to non-Gaussian noise.

Item Type: Article
Official URL: http://biomet.oxfordjournals.org/
Additional Information: © 2006 Biometrika Trust
Subjects: H Social Sciences > HA Statistics
Sets: Departments > Statistics
Date Deposited: 21 Nov 2009 15:39
Last Modified: 25 Nov 2011 11:14
URI: http://eprints.lse.ac.uk/id/eprint/25832

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