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

Autor:	Aifen Feng, Xiaogai Chang, Youlin Shang, Jingya Fan
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	partially linear model B-spline interpolation ADMM variational inequality Mathematics QA1-939
Zdroj:	Mathematics, Vol 10, Iss 24, p 4767 (2022)
Druh dokumentu:	article
ISSN:	2227-7390
DOI:	10.3390/math10244767
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/388b7c2095ca41cd91e77ca6b5d3d05b Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
Nepřihlášeným uživatelům se plný text nezobrazuje	K zobrazení výsledku je třeba se přihlásit.