A new approach to select linear and nonparametric predictors simultaneously for generalised partially linear models

Youhan Lu, Juan Hu and Yichao Wu

Journal of Nonparametric Statistics, 2025, vol. 37, issue 4, 1298-1316

Abstract: We introduce a novel approach for variable selection in the generalised partially linear model (GPLM) by building upon the previous research conducted by Lu Dong, Hu, and Wu [(2023), ‘A unified approach to variable selection for partially linear models’, Journal of Computational and Graphical Statistics, 1–11]. Our proposed method expands on their work by incorporating a local scoring algorithm. This approach enables the selection of linear and nonparametric predictors simultaneously by solving a single optimisation problem. To showcase the effectiveness of our method in practice, we provide simulation examples involving logistic regression and Poisson regression models. Additionally, we present a real-world data example and engage in a discussion surrounding its application.

Date: 2025
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DOI: 10.1080/10485252.2025.2556412

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