Nonparametric Interaction Selection




RE 104

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Yichao Wu, Department of Mathematics, Statistics and Computer Science, University of Illinois at Chicago



Interaction selection has gained much interest recently. Yet most of the existing interaction methods are parametric. In this talk, I will present a new method to perform nonparametric interaction selection. Our method is based on the estimation framework of coupling backfitting algorithm with local constant smoothing for the additive interaction model. In this framework, it is observed that an interaction term is unimportant if it favors an infinity smoothing bandwidth. Based on this observation, we propose to solve an optimization problem to estimate which interaction terms favor an infinity smoothing bandwidth, thus achieving nonparametric interaction selection. We will provide both numerical evidence and theoretical justification for the proposed nonparametric interaction selection method.