ebreg: Implementation of the Empirical Bayes Method

Implements a Bayesian-like approach to the high-dimensional sparse linear regression problem based on an empirical or data-dependent prior distribution, which can be used for estimation/inference on the model parameters, variable selection, and prediction of a future response. The method was first presented in Martin, Ryan and Mess, Raymond and Walker, Stephen G (2017) <doi:10.3150/15-BEJ797>. More details focused on the prediction problem are given in Martin, Ryan and Tang, Yiqi (2019) <doi:10.48550/arXiv.1903.00961>.

Version:	0.1.3
Depends:	lars, stats
Imports:	Rdpack
Suggests:	testthat, roxygen2
Published:	2021-05-26
DOI:	10.32614/CRAN.package.ebreg
Author:	Yiqi Tang, Ryan Martin
Maintainer:	Yiqi Tang <ytang22 at ncsu.edu>
License:	GPL-3
NeedsCompilation:	no
Materials:	README
CRAN checks:	ebreg results

Documentation:

Reference manual:

ebreg.pdf

Downloads:

Package source:	ebreg_0.1.3.tar.gz
Windows binaries:	r-devel: ebreg_0.1.3.zip, r-release: ebreg_0.1.3.zip, r-oldrel: ebreg_0.1.3.zip
macOS binaries:	r-release (arm64): ebreg_0.1.3.tgz, r-oldrel (arm64): ebreg_0.1.3.tgz, r-release (x86_64): ebreg_0.1.3.tgz, r-oldrel (x86_64): ebreg_0.1.3.tgz
Old sources:	ebreg archive

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