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 |
| 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: not available |
| OS X binaries: | r-release: islasso_1.0.0.tgz, r-oldrel: islasso_1.0.0.tgz |
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