reglogit (1.2-6)

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Simulation-Based Regularized Logistic Regression.

http://bobby.gramacy.com/r_packages/reglogit
http://cran.r-project.org/web/packages/reglogit

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.

Maintainer: Robert B. Gramacy
Author(s): Robert B. Gramacy <rbg@vt.edu>

License: LGPL

Uses: boot, Matrix, mvtnorm, plgp

Released over 1 year ago.


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