doi:10.1214/12-BA719>).">

reglogit: Simulation-Based Regularized Logistic Regression (original) (raw)

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>).

Version: 1.2-8
Depends: R (≥ 2.14.0), methods, mvtnorm, boot, Matrix
Suggests: plgp
Published: 2025-07-24
DOI: 10.32614/CRAN.package.reglogit
Author: Robert B. Gramacy [cre, aut]
Maintainer: Robert B. Gramacy
License: LGPL-2 | LGPL-2.1 LGPL-3 [expanded from: LGPL]
URL: https://bobby.gramacy.com/r_packages/reglogit/
NeedsCompilation: yes
Materials:
CRAN checks: reglogit results

Documentation:

Reference manual: reglogit.html , <reglogit.pdf>

Downloads:

Package source: reglogit_1.2-8.tar.gz
Windows binaries: r-devel: reglogit_1.2-8.zip, r-release: reglogit_1.2-8.zip, r-oldrel: reglogit_1.2-8.zip
macOS binaries: r-release (arm64): reglogit_1.2-8.tgz, r-oldrel (arm64): reglogit_1.2-8.tgz, r-release (x86_64): reglogit_1.2-8.tgz, r-oldrel (x86_64): reglogit_1.2-8.tgz
Old sources: reglogit archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=reglogitto link to this page.