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) <arXiv:1903.00961>.

Version: 0.1.2
Depends: lars, stats
Imports: Rdpack
Suggests: testthat, roxygen2
Published: 2020-05-26
Author: Yiqi Tang, Ryan Martin
Maintainer: Yiqi Tang <ytang22 at ncsu.edu>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: ebreg results

Downloads:

Reference manual: ebreg.pdf
Package source: ebreg_0.1.2.tar.gz
Windows binaries: r-devel: ebreg_0.1.2.zip, r-release: ebreg_0.1.1.zip, r-oldrel: ebreg_0.1.1.zip
macOS binaries: r-release: ebreg_0.1.1.tgz, r-oldrel: ebreg_0.1.2.tgz
Old sources: ebreg archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ebreg to link to this page.