Application of the ADMM Algorithm for a High-Dimensional Partially Linear Model

Aifen Feng (), Xiaogai Chang, Youlin Shang and Jingya Fan
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Aifen Feng: School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471023, China
Xiaogai Chang: School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471023, China
Youlin Shang: School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471023, China
Jingya Fan: School of Mathematics and Statistics, Henan University of Science and Technology, Luoyang 471023, China

Mathematics, 2022, vol. 10, issue 24, 1-13

Abstract: This paper focuses on a high-dimensional semi-parametric regression model in which a partially linear model is used for the parametric part and the B-spline basis function approach is used to estimate the unknown function for the non-parametric part. Within the framework of this model, the constrained least squares estimation is investigated, and the alternating-direction multiplier method (ADMM) is used to solve the model. The convergence is proved under certain conditions. Finally, numerical simulations are performed and applied to workers’ wage data from CPS85. The results show that the ADMM algorithm is very effective in solving high-dimensional partially linear models.

Keywords: partially linear model; B-spline interpolation; ADMM; variational inequality (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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