elrm: Exact Logistic Regression via MCMC

Implements a Markov Chain Monte Carlo algorithm to approximate exact conditional inference for logistic regression models. Exact conditional inference is based on the distribution of the sufficient statistics for the parameters of interest given the sufficient statistics for the remaining nuisance parameters. Using model formula notation, users specify a logistic model and model terms of interest for exact inference. See Zamar et al. (2007) <doi:10.18637/jss.v021.i03> for more details.

Getting started

Package details

AuthorDavid Zamar [aut, cre], Jinko Graham [aut], Brad McNeney [aut], Techsoft Pvt. Ltd [ctb]
MaintainerDavid Zamar <zamar.david@gmail.com>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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elrm documentation built on Aug. 31, 2019, 1:04 a.m.