reglogit: Simulation-Based Regularized Logistic Regression
Version 1.2-5

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.

Package details

AuthorRobert B. Gramacy <[email protected]>
Date of publication2017-11-19 18:22:50 UTC
MaintainerRobert B. Gramacy <[email protected]>
Package repositoryView on CRAN
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reglogit documentation built on Nov. 20, 2017, 1:06 a.m.