# --------------------------------------------
# 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 "glmbayes" in publications use:'
type: software
license: GPL-2.0-only
title: 'glmbayes: Bayesian Generalized Linear Models (IID Samples)'
version: 0.9.6
identifiers:
- type: doi
  value: 10.32614/CRAN.package.glmbayes
- type: url
  value: https://knygren.r-universe.dev/glmbayes
abstract: Provides Bayesian linear and generalized linear model fitting with independent
  and identically distributed (iid) posterior samples. The main functions mirror R's
  lm() and glm() interfaces while adding prior family specifications for Gaussian,
  Poisson, binomial, and Gamma models with log-concave likelihoods. Sampling for supported
  non-conjugate models uses accept-reject methods based on likelihood subgradients
  as in Nygren and Nygren (2006) <https://doi.org/10.1198/016214506000000357>. The
  package also includes tools for prior setup, posterior summaries, prediction, diagnostics,
  simulation, vignettes, and optional 'OpenCL' acceleration for larger models.
authors:
- family-names: Nygren
  given-names: Kjell
  email: kjell.a.nygren@gmail.com
preferred-citation:
  type: manual
  title: 'glmbayes: Bayesian Generalized Linear Models (IID Samples)'
  authors:
  - family-names: Nygren
    given-names: Kjell
    email: kjell.a.nygren@gmail.com
  year: '2026'
  notes: R package version 0.9.6
  url: https://CRAN.R-project.org/package=glmbayes
repository: https://knygren.r-universe.dev
repository-code: https://github.com/knygren/glmbayes
commit: 385c9748e37c77e864faff0a78a1a2815d8f15c4
url: https://CRAN.R-project.org/package=glmbayes
date-released: '2026-05-18'
contact:
- family-names: Nygren
  given-names: Kjell
  email: kjell.a.nygren@gmail.com
references:
- type: article
  title: Likelihood Subgradient Densities
  authors:
  - family-names: Nygren
    given-names: Kjell N.
  - family-names: Nygren
    given-names: Lan M.
  journal: Journal of the American Statistical Association
  volume: '101'
  issue: '475'
  year: '2006'
  doi: 10.1198/016214506000000357
  start: '1144'
  end: '1156'