Empirical Bayes Selection of Wavelet Thresholds (2005)
by
Iain M. Johnstone
,
Bernard W. Silverman
| Venue: | ANN. STATIST |
| Citations: | 53 - 3 self |
BibTeX
@ARTICLE{Johnstone05empiricalbayes,
author = {Iain M. Johnstone and Bernard W. Silverman},
title = {Empirical Bayes Selection of Wavelet Thresholds},
journal = {ANN. STATIST},
year = {2005},
volume = {33},
number = {4},
pages = {1700--1752}
}
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Abstract
This paper explores a class of empirical Bayes methods for level-dependent threshold selection in wavelet shrinkage. The prior considered for each wavelet coefficient is a mixture of an atom of probability at zero and a heavy-tailed density. The mixing weight, or sparsity parameter, for each level of the transform is chosen by marginal maximum likelihood. If estimation
