EbayesThresh
library is a collection of
MATLAB™ scripts that complements the paper
"Needles and straw in haystacks: Empirical Bayes approaches to thresholding
a possibly sparse sequence" and "Empirical Bayes selection of wavelet thresholds"
by Iain M. Johnstone and Bernard W. Silverman, submitted for publication 2002.
A paper giving a general description of the software and some details both
of the general methodology and of some specific technical matters is available
here. The scripts in this library are a translation of the corresponding R package or S-PLUS library. The ebayesthresh_wavelet function applies the approach to wavelet transforms obtained with the WAVELAB matlab toolbox developed at Stanford by Buckheit, Chen, Donoho, Johnstone & Scargle (1995). If wavelet transforms are obtained using other software, the routine will not be applicable directly, but should still provide a model for the user to write their own wavelet smoothing routine making use of the function ebayesthresh. The software may be downloaded and used freely for academic purposes, provided its use is acknowledged. Commercial use is not allowed without the permission of the authors. Please bring any problems or errors to the author's attention. The entire MATLAB source code,
in compressed zip form, is available for download from:
http://www-lmc.imag.fr/lmc-sms/Anestis.Antoniadis/EBayesThresh/ebayesthreshmlb.zip
The current maintainers of the EBayesThresh matlab library are Anestis Antoniadis and Maarten Jensen.