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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "GLMMselect" in publications use:'
type: software
license: GPL-3.0-only
title: 'GLMMselect: Bayesian Model Selection for Generalized Linear Mixed Models'
version: 1.2.0
doi: 10.32614/CRAN.package.GLMMselect
abstract: A Bayesian model selection approach for generalized linear mixed models.
  Currently, 'GLMMselect' can be used for Poisson GLMM and Bernoulli GLMM. 'GLMMselect'
  can select fixed effects and random effects simultaneously. Covariance structures
  for the random effects are a product of a unknown scalar and a known semi-positive
  definite matrix. 'GLMMselect' can be widely used in areas such as longitudinal studies,
  genome-wide association studies, and spatial statistics. 'GLMMselect' is based on
  Xu, Ferreira, Porter, and Franck (202X), Bayesian Model Selection Method for Generalized
  Linear Mixed Models, Biometrics, under review.
authors:
- family-names: Xu
  given-names: Shuangshuang
  email: xshuangshuang@vt.edu
- family-names: Ferreira
  given-names: Marco
  email: marf@vt.edu
  orcid: https://orcid.org/0000-0002-4705-5661
- family-names: Porter
  given-names: Erica
  email: ericamp@vt.edu
- family-names: Franck
  given-names: Christopher
  email: chfranck@vt.edu
repository: https://xss55.r-universe.dev
commit: 8e700a93b2364e0243f2b74b6c10a004b1c6db17
date-released: '2023-08-24'
contact:
- family-names: Xu
  given-names: Shuangshuang
  email: xshuangshuang@vt.edu