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.

Version: 1.2-6
Depends: R (≥ 2.14.0), methods, mvtnorm, boot, Matrix
Suggests: plgp
Published: 2018-09-14
Author: Robert B. Gramacy
Maintainer: Robert B. Gramacy <rbg at vt.edu>
License: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL]
URL: http://bobby.gramacy.com/r_packages/reglogit
NeedsCompilation: yes
Materials: ChangeLog
CRAN checks: reglogit results

Downloads:

Reference manual: reglogit.pdf
Package source: reglogit_1.2-6.tar.gz
Windows binaries: r-devel: reglogit_1.2-6.zip, r-release: reglogit_1.2-6.zip, r-oldrel: reglogit_1.2-6.zip
macOS binaries: r-release: reglogit_1.2-6.tgz, r-oldrel: reglogit_1.2-6.tgz
Old sources: reglogit archive

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