Safe Formula-Based Regularized Generalized Linear Models R package fbrglm version 0.1.0 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'. Software Imports: glmnet, stats, graphics, generics, tibble Suggests: testthat (>= 3.0.0), knitr, rmarkdown, survival, MASS Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp> Comprehensive R Archive Network (CRAN) Koki Tsuyuzaki [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=fbrglm/LICENSE) 2026-07-14 application/tgz https://CRAN.R-project.org/package=fbrglm doi:10.32614/CRAN.package.fbrglm