smurf: Sparse Multi-Type Regularized Feature Modeling

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.

Version: 1.1.5
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
Published: 2023-03-22
DOI: 10.32614/CRAN.package.smurf
Author: Tom Reynkens ORCID iD [aut, cre], Sander Devriendt [aut], Katrien Antonio [aut]
Maintainer: Tom Reynkens <tomreynkens at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: NEWS
CRAN checks: smurf results


Reference manual: smurf.pdf
Vignettes: Introduction to the smurf package


Package source: smurf_1.1.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): smurf_1.1.5.tgz, r-oldrel (arm64): smurf_1.1.5.tgz, r-release (x86_64): smurf_1.1.5.tgz, r-oldrel (x86_64): smurf_1.1.5.tgz
Old sources: smurf archive

Reverse dependencies:

Reverse imports: airpart


Please use the canonical form to link to this page.