smurf: Sparse Multi-Type Regularized Feature Modeling

Implementation of the SMuRF algorithm of Devriendt et al. (2018) <arXiv:1810.03136> to fit generalized linear models (GLMs) with multiple types of predictors via regularized maximum likelihood.

Version: 1.0.1
Depends: R (≥ 3.1)
Imports: catdata, glmnet, graphics, MASS, Matrix, methods, mgcv, parallel, RColorBrewer, Rcpp (≥ 0.12.12), speedglm, stats
LinkingTo: Rcpp, RcppArmadillo (≥ 0.8.300.1.0)
Suggests: bookdown, knitr, roxygen2 (≥ 6.0.0), testthat
Published: 2019-05-11
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_1.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: smurf_1.0.1.tgz, r-oldrel: smurf_1.0.1.tgz
Old sources: smurf archive


Please use the canonical form to link to this page.