reglogit
Simulation-Based Regularized Logistic Regression
Regularized (polychotomous) logistic regression by Gibbs sampling. The package implements subtly different MCMC schemes with varying efficiency depending on the data type (binary v. binomial, say) and the desired estimator (regularized maximum likelihood, or Bayesian maximum a posteriori/posterior mean, etc.) through a unified interface. For details, see Gramacy & Polson (2012 <doi:10.1214/12-BA719>).
- Version1.2-7
- R versionunknown
- LicenseLGPL-2
- LicenseLGPL-2.1
- LicenseLGPL-3
- Needs compilation?Yes
- Last release04/25/2023
Documentation
Team
Robert B. Gramacy
MaintainerShow author details
Insights
Last 30 days
This package has been downloaded 211 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 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 2,911 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 Jul 16, 2024 with 78 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
- Suggests1 package