The Annals of Statistics

Wavelet thresholding for non-necessarily Gaussian noise: idealism

R. Averkamp and C. Houdré

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For various types of noise (exponential, normal mixture, compactly supported, ...) wavelet thresholding methods are studied. Problems linked to the existence of optimal thresholds are tackled, and minimaxity properties of the methods also analyzed. A coefficient dependent method for choosing thresholds is also briefly presented.

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Ann. Statist., Volume 31, Number 1 (2003), 110-151.

First available in Project Euclid: 26 February 2003

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Zentralblatt MATH identifier

Primary: 62G07: Density estimation 62C20: Minimax procedures
Secondary: 60G70: Extreme value theory; extremal processes 41A25: Rate of convergence, degree of approximation

Wavelets thresholding minimax


Averkamp, R.; Houdré, C. Wavelet thresholding for non-necessarily Gaussian noise: idealism. Ann. Statist. 31 (2003), no. 1, 110--151. doi:10.1214/aos/1046294459.

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