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>.
|Author||Kory D. Johnson [aut, cre], Robert A. Stine [aut]|
|Maintainer||Kory D. Johnson <[email protected]>|
|Package repository||View on CRAN|
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