Package: elrm
Version: 1.2.5
Date: 2021-10-25
Type: Package
Title: Exact Logistic Regression via MCMC
Authors@R: c(person(given="David", family="Zamar", role = c("aut", "cre"), email = "zamar.david@gmail.com"),
             person(given="Jinko", family="Graham", role = "aut"),
             person(given="Brad", family="McNeney", role = "aut"))
Author: David Zamar [aut, cre],
  Jinko Graham [aut],
  Brad McNeney [aut]
Maintainer: David Zamar <zamar.david@gmail.com>
Depends: R(>= 2.7.2), coda, graphics, stats
Description: 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. 
License: GPL (>= 2)
Repository: CRAN
NeedsCompilation: yes
Packaged: 2021-10-25 10:43:14 UTC; zamar
Date/Publication: 2021-10-26 08:30:02 UTC
Built: R 4.0.2; x86_64-apple-darwin17.0; 2021-10-27 10:24:34 UTC; unix
Archs: elrm.so.dSYM
