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: Cilluffo, G., Sottile, G., La Grutta, S. and Muggeo, V. (2019) The Induced Smoothed lasso: A practical framework for hypothesis testing in high dimensional regression. <doi:10.1177/0962280219842890>, and discussed in a tutorial: Sottile, G., Cilluffo, G., and Muggeo, V. (2019) The R package islasso: estimation and hypothesis testing in lasso regression. <doi:10.13140/RG.2.2.16360.11521>.

Package details

AuthorGianluca Sottile [aut, cre], Giovanna Cilluffo [aut, ctb], Vito MR Muggeo [aut, cre]
MaintainerGianluca Sottile <[email protected]>
LicenseGPL (>= 2)
Version1.1.0
URL https://journals.sagepub.com/doi/abs/10.1177/0962280219842890
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("islasso")

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islasso documentation built on June 25, 2019, 5:03 p.m.