| Name : R-EbayesThresh
| |
| Version : 1.4.12
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.2.13
| Date : 2024-06-14 11:01:15
|
| Group : Development/Libraries/Other
| Source RPM : R-EbayesThresh-1.4.12-lp153.2.13.src.rpm
|
| Size : 0.89 MB
| |
| Packager : (none)
| |
| Summary : Empirical Bayes thresholding and related methods
|
Description :
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 heavy-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.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
