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 |
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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