# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "elrm" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'elrm: Exact Logistic Regression via MCMC'
version: 1.2.5
identifiers:
- type: doi
  value: 10.32614/CRAN.package.elrm
abstract: 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) <https://doi.org/10.18637/jss.v021.i03> for more details.
authors:
- family-names: Zamar
  given-names: David
  email: zamar.david@gmail.com
- family-names: Graham
  given-names: Jinko
- family-names: McNeney
  given-names: Brad
preferred-citation:
  type: article
  title: 'elrm: Software Implementing Exact-like Inference for Logistic Regression
    Models'
  authors:
  - family-names: Zamar
    given-names: David
    email: zamar.david@gmail.com
  - family-names: McNeney
    given-names: Brad
  - family-names: Graham
    given-names: Jinko
  journal: Journal of Statistical Software
  volume: '21'
  issue: '3'
  year: '2007'
  url: https://doi.org/10.18637/jss.v021.i03
  start: 1-18
repository: https://cranhaven.r-universe.dev
commit: e4b947b62984f7f33d74537eddea16d5696b0511
date-released: '2021-10-25'
contact:
- family-names: Zamar
  given-names: David
  email: zamar.david@gmail.com