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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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.