islasso: The Induced Smoothed Lasso

An implementation of the induced smoothing (IS) idea to lasso regularization models to allow estimation and inference on the model coefficients (currently hypothesis testing only). Linear, logistic, Poisson and gamma regressions with several link functions are implemented. The algorithm is described in the original paper; see <doi:10.1177/0962280219842890> and discussed in a tutorial <doi:10.13140/RG.2.2.16360.11521>.

Version: 1.5.2
Depends: glmnet (≥ 4.0), Matrix (≥ 1.0-6), R (≥ 4.0.0)
Imports: stats, utils, graphics
Suggests: knitr, lars, xfun, rmarkdown
Published: 2024-01-23
DOI: NA
Author: Gianluca Sottile [aut, cre], Giovanna Cilluffo [aut, ctb], Vito MR Muggeo [aut, ctb]
Maintainer: Gianluca Sottile <gianluca.sottile at unipa.it>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: islasso citation info
Materials: NEWS
In views: MachineLearning
CRAN checks: islasso results

Documentation:

Reference manual: islasso.pdf

Downloads:

Package source: islasso_1.5.2.tar.gz
Windows binaries: r-devel: islasso_1.5.2.zip, r-release: islasso_1.5.2.zip, r-oldrel: islasso_1.5.2.zip
macOS binaries: r-release (arm64): islasso_1.5.2.tgz, r-oldrel (arm64): islasso_1.5.2.tgz, r-release (x86_64): islasso_1.5.2.tgz, r-oldrel (x86_64): islasso_1.5.2.tgz
Old sources: islasso archive

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