SparseStep R Package

Paper: SparseStep: Approximating the Counting Norm for Sparse Regularization by G.J.J. van den Burg, P.J.F. Groenen, and A. Alfons (Arxiv preprint arXiv:1701.06967 [stat.ME], 2017).

GitHub: https://github.com/GjjvdBurg/SparseStep.

Introduction

This R package implements the SparseStep method for solving the regression problem with a sparsity constraint on the parameters. The package is extensively documented through the builtin R documentation. See:

?'sparsestep-package'
?sparsestep
?path.sparsestep

for more information.

Installation

This package can be installed through CRAN:

install.packages('sparsestep')

Reference

If you use SparseStep in any of your projects, please cite the paper using the information available through the R command:

citation('sparsestep')

or use the following BibTeX code:

@article{van2017sparsestep,
  title = {{SparseStep}: Approximating the Counting Norm for Sparse Regularization},
  author = {Gerrit J.J. {van den Burg} and Patrick J.F. Groenen and Andreas Alfons},
  journal = {arXiv preprint arXiv:1701.06967},
  archiveprefix = {arXiv},
  year = {2017},
  eprint = {1701.06967},
  url = {https://arxiv.org/abs/1701.06967},
  primaryclass = {stat.ME},
  keywords = {Statistics - Methodology, 62J05, 62J07},
}

License

Copyright 2016, G.J.J. van den Burg.

SparseStep is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

SparseStep is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with SparseStep. If not, see <http://www.gnu.org/licenses/>.

For more information please contact:

G.J.J. van den Burg
email: gertjanvandenburg@gmail.com