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. .


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install.packages("islasso")

1.3.1 by Gianluca Sottile, 5 days ago


https://journals.sagepub.com/doi/abs/10.1177/0962280219842890


Browse source code at https://github.com/cran/islasso


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


Documentation:   PDF Manual  


GPL (>= 2) license


Depends on glmnet, Matrix

Suggests knitr, lars, xfun, rmarkdown


See at CRAN