rai: Revisiting-Alpha-Investing for Polynomial Regression

A modified implementation of stepwise regression that greedily searches the space of interactions among features in order to build polynomial regression models. Furthermore, the hypothesis tests conducted are valid-post model selection due to the use of a revisiting procedure that implements an alpha-investing rule. As a result, the set of rejected sequential hypotheses is proven to control the marginal false discover rate. When not searching for polynomials, the package provides a statistically valid algorithm to run and terminate stepwise regression. For more information, see Johnson, Stine, and Foster (2019) <arXiv:1510.06322>.

Version: 1.0.0
Imports: stats, dplyr, ggplot2, readr, rlang
Suggests: testthat
Published: 2019-07-02
Author: Kory D. Johnson [aut, cre], Robert A. Stine [aut]
Maintainer: Kory D. Johnson <korydjohnson at gmail.com>
BugReports: https://github.com/korydjohnson/rai/issues
License: GPL-3
URL: https://github.com/korydjohnson/rai
NeedsCompilation: no
Materials: NEWS
CRAN checks: rai results

Documentation:

Reference manual: rai.pdf

Downloads:

Package source: rai_1.0.0.tar.gz
Windows binaries: r-devel: rai_1.0.0.zip, r-release: rai_1.0.0.zip, r-oldrel: rai_1.0.0.zip
macOS binaries: r-release (arm64): rai_1.0.0.tgz, r-oldrel (arm64): rai_1.0.0.tgz, r-release (x86_64): rai_1.0.0.tgz

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