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.
- Version0.1.0
- R versionunknown
- LicenseMIT
- Needs compilation?No
- Last release11/14/2018
Documentation
Team
Shijia Zhang
Meng Li
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Insights
Last 30 days
This package has been downloaded 144 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,827 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 21 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
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Dependencies
- Imports5 packages