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. , and discussed in a tutorial: Sottile, G., Cilluffo, G., and Muggeo, V. (2019) The R package islasso: estimation and hypothesis testing in lasso regression. .


Reference manual

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1.4.2 by Gianluca Sottile, 2 months ago

Browse source code at

Authors: Gianluca Sottile [aut, cre] , Giovanna Cilluffo [aut, ctb] , Vito MR Muggeo [aut, cre]

Documentation:   PDF Manual  

Task views: Machine Learning & Statistical Learning

GPL (>= 2) license

Depends on glmnet, Matrix

Suggests knitr, lars, xfun, rmarkdown

See at CRAN