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