Revisiting-Alpha-Investing for Polynomial Regression
Description
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) .