Sparse Multi-Type Regularized Feature Modeling R package smurf version 1.1.8 Implementation of the SMuRF algorithm of Devriendt et al. (2021) <doi:10.1016/j.insmatheco.2020.11.010> to fit generalized linear models (GLMs) with multiple types of predictors via regularized maximum likelihood. Software Depends: R (>= 3.4) Imports: catdata, glmnet (>= 4.0), graphics, MASS, Matrix, methods, mgcv, parallel, RColorBrewer, Rcpp (>= 0.12.12), stats LinkingTo: Rcpp, RcppArmadillo (>= 0.8.300.1.0) Suggests: bookdown, knitr, rmarkdown, roxygen2 (>= 6.0.0), testthat Tom Reynkens <tomreynkens.r@gmail.com> Comprehensive R Archive Network (CRAN) Tom Reynkens [aut, cre] (ORCID: <https://orcid.org/0000-0002-5516-5107>), Sander Devriendt [aut], Katrien Antonio [aut] GPL (>= 2) 2025-09-19 application/tgz https://CRAN.R-project.org/package=smurf doi:10.32614/CRAN.package.smurf