Package: EbayesThresh
Title: Empirical Bayes thresholding and related methods
Version: 1.3.0
Date: 2005-03-24
Author: Bernard W. Silverman <bernard.silverman@spc.ox.ac.uk>
Maintainer: Bernard W. Silverman <bernard.silverman@spc.ox.ac.uk>
Description: This package carries out Empirical Bayes thresholding
        using the methods developed by I. M. Johnstone and B. W.
        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.
License: GPL version 2 or newer
URL: http://www.bernardsilverman.com
Packaged: Thu Mar 24 16:46:17 2005; Administrator
Built: R 2.0.1; ; 2005-04-18 21:29:40; unix
