Methodological considerations for semialgebraic hypothesis testing with incomplete U-statistics
By: David Barnhill , Marina Garrote-López , Elizabeth Gross and more
Potential Business Impact:
Tests science ideas even when rules are tricky.
Recently, Sturma, Drton, and Leung proposed a general-purpose stochastic method for hypothesis testing in models defined by polynomial equality and inequality constraints. Notably, the method remains theoretically valid even near irregular points, such as singularities and boundaries, where traditional testing approaches often break down. In this paper, we evaluate its practical performance on a collection of biologically motivated models from phylogenetics. While the method performs remarkably well across different settings, we catalogue a number of issues that should be considered for effective application.
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