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Package: sparsestep
Version: 1.0.1
Date: 2021-01-10
Title: SparseStep Regression
Authors@R: c(person("Gertjan", "van den Burg", role=c("aut", "cre"),
email="gertjanvandenburg@gmail.com"),
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)
<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:
R (>= 3.0.0),
Matrix (>= 1.0-6)
Classification/MSC: 62J05, 62J07
URL: https://github.com/GjjvdBurg/SparseStep,
https://arxiv.org/abs/1701.06967
BugReports: https://github.com/GjjvdBurg/SparseStep
RoxygenNote: 7.1.0
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