Data-driven resistant kernel regression

Jianhua Zhou and Christopher F. Parmeter

Journal of Nonparametric Statistics, 2025, vol. 37, issue 1, 33-59

Abstract: We investigate data-driven bandwidth selection within the confines of robust (resistant) kernel smoothing. While several approaches presently exist, they require user defined robustness parameters. We discuss identification issues within this setting and propose several tractable avenues to fully operationalise this approach. Simulations reveal that the proposed selection methods perform well relative to competing approaches and a small empirical example illustrates its usefulness.

Date: 2025
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DOI: 10.1080/10485252.2024.2335494

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