Package: glmmsel 1.0.3

Ryan Thompson

glmmsel: Generalised Linear Mixed Model Selection

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>.

Authors:Ryan Thompson [aut, cre]

glmmsel_1.0.3.tar.gz
glmmsel_1.0.3.tar.gz(r-4.7-arm64)glmmsel_1.0.3.tar.gz(r-4.7-x86_64)glmmsel_1.0.3.tar.gz(r-4.6-arm64)glmmsel_1.0.3.tar.gz(r-4.6-x86_64)
glmmsel_1.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
glmmsel/json (API)
NEWS

# Install 'glmmsel' in R:
install.packages('glmmsel', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ryan-thompson/glmmsel/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

2.70 score 7 scripts 154 downloads 4 exports 19 dependencies

Last updated from:3a4658fff8. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK187
linux-devel-x86_64OK190
source / vignettesOK255
linux-release-arm64OK184
linux-release-x86_64OK192
wasm-releaseOK164

Exports:cv.glmmselfixefglmmselranef

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerRcppRcppArmadillorlangS7scalesvctrsviridisLitewithr

Guide to glmmsel

Ryan Thompson

Rendered fromvignette.Rmdusingknitr::rmarkdownon Jun 13 2026.

Last update: 2025-05-29
Started: 2025-05-29