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: 1.2-2
Depends: R (≥ 2.14.0), methods, mvtnorm, boot, Matrix
Suggests: plgp
Published: 2014-01-15
Author: Robert B. Gramacy
Maintainer: Robert B. Gramacy <rbgramacy at chicagobooth.edu>
License: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL]
URL: http://faculty.chicagobooth.edu/robert.gramacy/reglogit.html
NeedsCompilation: yes
Materials: ChangeLog
CRAN checks: reglogit results

Downloads:

Reference manual: reglogit.pdf
Package source: reglogit_1.2-2.tar.gz
MacOS X binary: reglogit_1.2-2.tgz
Windows binary: reglogit_1.2-2.zip
Old sources: reglogit archive