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| author | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2021-01-09 15:03:07 +0000 |
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| committer | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2021-01-09 15:03:07 +0000 |
| commit | d0261f4b979d4457f98363fccc4f84aa3318c61f (patch) | |
| tree | c60041a7d001baf05913d865a497464009626b35 | |
| parent | update description after cran submission failure (diff) | |
| download | sparsestep-d0261f4b979d4457f98363fccc4f84aa3318c61f.tar.gz sparsestep-d0261f4b979d4457f98363fccc4f84aa3318c61f.zip | |
Change arXiv identifier to preferred format
| -rw-r--r-- | DESCRIPTION | 20 |
1 files changed, 10 insertions, 10 deletions
diff --git a/DESCRIPTION b/DESCRIPTION index 9956dbd..3fa1ed2 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -7,15 +7,15 @@ Authors@R: c(person("Gertjan", "van den Burg", role=c("aut", "cre"), person("Patrick", "Groenen", email="groenen@ese.eur.nl", role="ctb"), person("Andreas", "Alfons", email="alfons@ese.eur.nl", role="ctb")) Description: Implements the SparseStep model for solving regression - problems with a sparsity constraint on the parameters. The SparseStep - regression model was proposed in Van den Burg, Groenen, and Alfons (2017) - <https://arxiv.org/abs/1701.06967>. In the model, a regularization term is - added to the regression problem which approximates the counting norm of - the parameters. By iteratively improving the approximation a sparse - solution to the regression problem can be obtained. In this package both - the standard SparseStep algorithm is implemented as well as a path - algorithm which uses golden section search to determine solutions with - different values for the regularization parameter. + problems with a sparsity constraint on the parameters. The SparseStep + regression model was proposed in Van den Burg, Groenen, and Alfons (2017) + <arxiv:1701.06967>. In the model, a regularization term is added to the + regression problem which approximates the counting norm of the parameters. + By iteratively improving the approximation a sparse solution to the + regression problem can be obtained. In this package both the standard + SparseStep algorithm is implemented as well as a path algorithm which uses + golden section search to determine solutions with different values for the + regularization parameter. License: GPL (>= 2) Imports: graphics Depends: @@ -25,4 +25,4 @@ Classification/MSC: 62J05, 62J07 URL: https://github.com/GjjvdBurg/SparseStep, https://arxiv.org/abs/1701.06967 BugReports: https://github.com/GjjvdBurg/SparseStep -RoxygenNote: 5.0.1 +RoxygenNote: 7.1.0 |