glmbayes: Bayesian Generalized Linear Models (IID Samples)

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) <doi:10.1198/016214506000000357>. The package also includes tools for prior setup, posterior summaries, prediction, diagnostics, simulation, vignettes, and optional 'OpenCL' acceleration for larger models.

Version:	0.9.3
Depends:	MASS, R (≥ 3.5.0)
Imports:	stats, coda, Rcpp (≥ 1.1.1), RcppParallel, Rdpack (≥ 0.11-0)
LinkingTo:	Rcpp, RcppArmadillo, RcppParallel
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0), spelling
Published:	2026-05-04
DOI:	10.32614/CRAN.package.glmbayes (may not be active yet)
Author:	Kjell Nygren [aut, cre], The R Core Team [ctb, cph] (R Mathlib sources, R stats modeling code, and derived/adapted routines), The R Foundation [cph] (Portions of R Mathlib and R source code), Ross Ihaka [ctb, cph] (R Mathlib and original R modeling infrastructure), Robert Gentleman [ctb, cph] (Portions of R Mathlib), Simon Davies [ctb] (Original R glm implementation), Morten Welinder [ctb, cph] (Portions of R Mathlib), Martin Maechler [ctb] (Portions of R Mathlib)
Maintainer:	Kjell Nygren <kjell.a.nygren at gmail.com>
BugReports:	https://github.com/knygren/glmbayes/issues
License:	GPL-2
Copyright:	see file COPYRIGHTS
URL:	https://github.com/knygren/glmbayes, https://knygren.r-universe.dev/glmbayes
NeedsCompilation:	yes
SystemRequirements:	Optional OpenCL support. If available, GPU acceleration will be used; otherwise, computation runs on CPU.
Language:	en-US
Citation:	glmbayes citation info
Materials:	README, NEWS
CRAN checks:	glmbayes results

Documentation:

Reference manual:

glmbayes.html , glmbayes.pdf

Vignettes:

Chapter 00: Introduction (source, R code) Chapter 02: Estimating Bayesian Linear Models (source, R code) Chapter 03: Tailoring Priors - Leveraging the Prior_Setup Function (source, R code) Chapter 04: Reviewing Model Predictions, Deviance Residuals and Model Statistics (source, R code) Chapter 05: Foundations of GLMs – Families, Links, and Log-Concave Likelihoods (source) Chapter 06: Estimating Bayesian Generalized Linear Models (source, R code) Chapter 07: Models for the Binomial Family (source, R code) Chapter 08: Models for the Poisson Family (source, R code) Chapter 09: Models for the Gamma Family (source, R code) Chapter 10: Informative Priors: Centering and priors with differentiated prior weights (source, R code) Chapter 11: Estimating Models with unknown dispersion parameters (source, R code) Chapter 12: Large Models: GPU Acceleration using OpenCL (source, R code) Chapter 13: Hierarchical Linear Models (source, R code) Chapter 14: Hierarchical Generalized Linear Models (source, R code) Chapter A01: A detailed overview of the glmbayes package (source, R code) Chapter A02: Overview of Estimation Procedures (source, R code) Chapter A03: Methods available in glmbayes (source, R code) Chapter A04: Directional Tail Diagnostics for Prior-Posterior Disagreement (source, R code) Chapter A05: Simulation Methods - Likelihood Subgradient Densities (source, R code) Chapter A06: Accept–Reject Sampling for Dispersion in Gamma Regression (source, R code) Chapter A07: Accept–Reject Sampling for gaussian Regression models with independent normal-gamma priors (source, R code) Chapter A08: Overview of Envelope Related Functions (source, R code) Chapter A09: Parallel Sampling Implementation using RcppParallel (source, R code) Chapter A10: Accelerated EnvelopeBuild Implementation using OpenCL (source, R code) Chapter A11: Implementation Companion for Independent Normal-Gamma (source, R code) Chapter A12: Technical Derivations for Priors Returned by 'Prior_Setup() (source, R code) Chapter 01: Getting started with glmbayes (source)

Downloads:

Package source:	glmbayes_0.9.3.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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