Package: ebayesthresh
Title: Empirical Bayes thresholding and related methods
Version: 1.02
Author: Bernard Silverman (with major intellectual input from Iain
        Johnstone)
Description: Carries out Empirical Bayes thresholding using the methods
	developed by Johnstone and Silverman.  The basic problem is to estimate a mean
	vector given a vector of observations of the mean vector plus white noise, taking
	advantage of possible sparsity in the mean vector.  Within a Bayesian formulation, the
	elements of the mean vector are modelled as having, independently, a distribution that
	is a mixture of an atom of probability at zero and a suitable hevay-tailed distribution.
	The mixing parameter can be estimated by a marginal maximum likelihood approach.
	This leads to an adaptive thresholding approach on the original data.  Extensions of
	the basic method, in particular to wavelet thresholding, are also implemented
	within the package.
Maintainer: Bernard Silverman <bernard.silverman@spc.ox.ac.uk>
License: GPL version 2 or newer
Date: 2004-09-04
URL: http://www.bernardsilverman.com
Packaged: Sun Sep  5 22:48:58 2004; silverma
