reglogit: Simulation-Based Regularized Logistic Regression
Version 1.2-4

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 <rbgramacy@chicagobooth.edu>
Date of publication2015-06-22 20:26:49
MaintainerRobert B. Gramacy <rbgramacy@chicagobooth.edu>
LicenseLGPL
Version1.2-4
URL http://faculty.chicagobooth.edu/robert.gramacy/reglogit.html
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("reglogit")

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reglogit documentation built on May 29, 2017, 11:48 a.m.