elrm: Exact Logistic Regression via MCMC

elrm 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.

Version: 1.2.2
Depends: R (≥ 2.7.2), coda, graphics, stats
Published: 2013-12-07
Author: David Zamar, Jinko Graham, Brad McNeney
Maintainer: David Zamar <zamar.david at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://stat-db.stat.sfu.ca:8080/statgen/research/elrm
NeedsCompilation: yes
Citation: elrm citation info
Materials: ChangeLog
In views: SocialSciences
CRAN checks: elrm results


Reference manual: elrm.pdf
Vignettes: elrm
Package source: elrm_1.2.2.tar.gz
Windows binaries: r-devel: elrm_1.2.2.zip, r-release: elrm_1.2.2.zip, r-oldrel: elrm_1.2.2.zip
OS X Snow Leopard binaries: r-release: elrm_1.2.2.tgz, r-oldrel: elrm_1.2.2.tgz
OS X Mavericks binaries: r-release: elrm_1.2.2.tgz
Old sources: elrm archive