fbrglm: Safe Formula-Based Regularized Generalized Linear Models

A formula-based wrapper around 'glmnet' that brings the 'glm()'-compatible modeling workflow to regularized generalized linear models. Training-time 'terms', 'xlevels', and 'contrasts' are stored on the fit object and reused at predict time, so the design matrix is reconstructed consistently across sessions. Complete-case bookkeeping is exposed via 'nobs_info', and linearly dependent columns are detected by a QR pivot and reported as 'NA' in 'coef()' and 'summary()' (the 'stats::glm()' convention), distinguishing "not identifiable" from "shrunk to zero by the penalty". Novel factor levels at predict time raise the same error 'stats::predict.glm()' does by default, with 'on_new_levels = "na"' as a production-style opt-in. Accepts character family strings ('gaussian', 'binomial', 'poisson', 'cox', 'multinomial', 'mgaussian') and any 'glm' family object the underlying 'glmnet' itself accepts, including 'Gamma' and fixed-theta negative binomial via 'MASS::negative.binomial'.

Version: 0.0.1
Imports: glmnet, stats, graphics
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, survival, MASS
Published: 2026-06-22
DOI: 10.32614/CRAN.package.fbrglm (may not be active yet)
Author: Koki Tsuyuzaki [aut, cre]
Maintainer: Koki Tsuyuzaki <k.t.the-answer at hotmail.co.jp>
BugReports: https://github.com/dsc-chiba-u/fbrglm/issues
License: MIT + file LICENSE
URL: https://github.com/dsc-chiba-u/fbrglm
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: fbrglm results

Documentation:

Reference manual: fbrglm.html , fbrglm.pdf
Vignettes: Families and model types in fbrglm (source, R code)
Getting started with fbrglm (source, R code)

Downloads:

Package source: fbrglm_0.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): fbrglm_0.0.1.tgz, r-oldrel (arm64): fbrglm_0.0.1.tgz, r-release (x86_64): fbrglm_0.0.1.tgz, r-oldrel (x86_64): fbrglm_0.0.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=fbrglm to link to this page.