islasso: The Induced Smoothed Lasso

An implementation of the induced smoothing idea that focuses on hypothesis testing in lasso regularization models (IS-lasso). Linear, logistic, Poisson and gamma regressions with several link functions are already implemented. The algorithm uses the steps as described in the original paper. See: The Induced Smoothed lasso: A practical framework for hypothesis testing in high dimensional regression. Cilluffo, G., Sottile, G., La Grutta, S. and Muggeo, V. (2019) <doi:10.1177/0962280219842890>.

Version: 1.0.0
Depends: glmnet, Matrix, R (≥ 2.10)
Published: 2019-04-29
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)]
URL: https://journals.sagepub.com/doi/abs/10.1177/0962280219842890
NeedsCompilation: yes
Citation: islasso citation info
CRAN checks: islasso results

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Reference manual: islasso.pdf
Package source: islasso_1.0.0.tar.gz
Windows binaries: r-devel: islasso_1.0.0.zip, r-release: islasso_1.0.0.zip, r-oldrel: islasso_1.0.0.zip
OS X binaries: r-release: islasso_1.0.0.tgz, r-oldrel: islasso_1.0.0.tgz

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