iilasso: Independently Interpretable Lasso

Efficient algorithms for fitting linear / logistic regression model with Independently Interpretable Lasso. Takada, M., Suzuki, T., & Fujisawa, H. (2018). Independently Interpretable Lasso: A New Regularizer for Sparse Regression with Uncorrelated Variables. AISTATS. <http://proceedings.mlr.press/v84/takada18a/takada18a.pdf>.

Version: 0.0.2
Imports: Rcpp, Matrix
LinkingTo: Rcpp, BH
Suggests: testthat, knitr, rmarkdown, MASS, parallel
Published: 2018-06-21
Author: Masaaki Takada
Maintainer: Masaaki Takada <tkdmah at gmail.com>
License: MIT + file LICENSE
URL: http://proceedings.mlr.press/v84/takada18a/takada18a.pdf
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: iilasso results


Reference manual: iilasso.pdf
Vignettes: Introduction to iilasso package
Package source: iilasso_0.0.2.tar.gz
Windows binaries: r-devel: iilasso_0.0.2.zip, r-devel-gcc8: iilasso_0.0.2.zip, r-release: iilasso_0.0.2.zip, r-oldrel: iilasso_0.0.2.zip
OS X binaries: r-release: iilasso_0.0.2.tgz, r-oldrel: iilasso_0.0.2.tgz
Old sources: iilasso archive


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