dlbayes: Use Dirichlet Laplace Prior to Solve Linear Regression Problem and Do Variable Selection

The Dirichlet Laplace shrinkage prior in Bayesian linear regression and variable selection, featuring: utility functions in implementing Dirichlet-Laplace priors such as visualization; scalability in Bayesian linear regression; penalized credible regions for variable selection.

Version: 0.1.0
Imports: GIGrvg, expm, glmnet, MASS, LaplacesDemon, stats, graphics
Published: 2018-11-14
DOI: 10.32614/CRAN.package.dlbayes
Author: Shijia Zhang; Meng Li
Maintainer: Shijia Zhang <zsj27 at mail.ustc.edu.cn>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: dlbayes results


Reference manual: dlbayes.pdf


Package source: dlbayes_0.1.0.tar.gz
Windows binaries: r-devel: dlbayes_0.1.0.zip, r-release: dlbayes_0.1.0.zip, r-oldrel: dlbayes_0.1.0.zip
macOS binaries: r-release (arm64): dlbayes_0.1.0.tgz, r-oldrel (arm64): dlbayes_0.1.0.tgz, r-release (x86_64): dlbayes_0.1.0.tgz, r-oldrel (x86_64): dlbayes_0.1.0.tgz


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