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
Built: R 1.9.1; ; 2004-10-06 23:47:12; unix
