Generalised Linear Mixed Model Selection
Overview
Provides tools for fitting sparse generalised linear mixed models with l0 regularisation. Selects fixed and random effects under the hierarchy constraint that fixed effects must precede random effects. Uses coordinate descent and local search algorithms to rapidly deliver near-optimal estimates. Gaussian and binomial response families are currently supported. For more details see Thompson, Wand, and Wang (2025) doi:10.48550/arXiv.2506.20425.
- Updated citation details
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-04-22
- ERROR13 OK, 1 ERROR2026-04-18
- OK14 OK2026-03-30
Show 1 earlier changeHide 1 earlier change
- ERROR13 OK, 1 ERROR2026-03-10
Documentation
- Help pages
- 14
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 50%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 14%
- Guide to glmmsel HTML
Downloads
Repository
Releases over time
6 development-tooling and community-health practices detected across 5 families in the upstream repository
Checks run against github.com/ryan-thompson/glmmsel on 2026-10-21.
The R CMD check workflow runs on Linux, macOS and Windows
Show all practicesHide 1 practice
Dependencies
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- 1.0.3Latest
- 1.0.22025-05-29
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-05-29
- Total releases
- 2 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 4.1.0
- Download size
- 33 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("glmmsel")The package provides a citation file, so citation() returns the authors' own entry.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.