Interpretable and predictive models based on high-dimensional data in ecology and evolution
Joshua P. Jahner, C. Alex Buerkle, Dustin G. Gannon, Eliza M. Grames, S. Eryn McFarlane, Andrew Siefert, Katherine L. Bell, Victoria L. DeLeo, Matthew L. Forister, Joshua G. Harrison, Daniel C. Laughlin, Amy C. Patterson, Breanna F. Powers, Chhaya M. Werner, Isabella A. Oleksy
The paper evaluates nine methods for variable selection and prediction in high-dimensional ecological and evolutionary data, finding that overfitting is common but prediction accuracy improves with more observations and stronger effects.
Molecular Ecology Resources · Aug 1, 2026Peer-reviewedGenomics