bayesreg
Bayesian Regression Models with Global-Local Shrinkage Priors
Fits linear or generalized linear regression models using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) doi:10.1093/acprof:oso/9780199694587.003.0017. Provides an efficient implementation of ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace, Student-t, Poisson or geometric distributed targets using the algorithms summarized in Makalic and Schmidt (2016) doi:10.48550/arXiv.1611.06649.
- Version1.3
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release09/30/2024
Team
Daniel F. Schmidt
Enes Makalic
Insights
Last 30 days
This package has been downloaded 664 times in the last 30 days. Not bad! The download count is somewhere between 'small-town buzz' and 'moderate academic conference'. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 25 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 5,296 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Mar 12, 2025 with 70 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
Binaries
Dependencies
- Depends3 packages
- Reverse Imports1 package