Package: GLMMselect
Title: Bayesian Model Selection for Generalized Linear Mixed Models
Version: 1.2.0
Authors@R: c(
    person("Shuangshuang", "Xu", email = "xshuangshuang@vt.edu", role = c("aut", "cre")),
    person("Marco", "Ferreira", email = "marf@vt.edu", role = c("aut"),
           comment = c(ORCID = "0000-0002-4705-5661")),
    person("Erica", "Porter", email = "ericamp@vt.edu", role = c("aut")),
    person("Christopher", "Franck", email = "chfranck@vt.edu", role = c("aut")))
Description: 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.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.2.3
Imports: stats (>= 4.2.2)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2023-08-24 00:48:18 UTC; xushu
Author: Shuangshuang Xu [aut, cre],
  Marco Ferreira [aut] (<https://orcid.org/0000-0002-4705-5661>),
  Erica Porter [aut],
  Christopher Franck [aut]
Maintainer: Shuangshuang Xu <xshuangshuang@vt.edu>
Repository: CRAN
Date/Publication: 2023-08-24 22:30:05 UTC
Built: R 4.6.0; ; 2026-04-25 19:17:56 UTC; unix
