A Semismooth Newton-Based Augmented Lagrangian Algorithm for the Generalized Convex Nearly Isotonic Regression Problem

A Semismooth Newton-Based Augmented Lagrangian Algorithm for the Generalized Convex Nearly Isotonic Regression Problem

The generalized convex nearly isotonic regression problem addresses a least squares regression model that incorporates both sparsity and monotonicity constraints on the regression coefficients. In this paper, we introduce an efficient semismooth Newton-based augmented Lagrangian (<span style=&quo...

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Bibliographic Details
Main Authors: Yanmei Xu, Lanyu Lin, Yong-Jin Liu
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Mathematics
Subjects:
generalized convex nearly isotonic regression
augmented Lagrangian algorithm
semismooth Newton method
Online Access:https://www.mdpi.com/2227-7390/13/3/501

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https://www.mdpi.com/2227-7390/13/3/501

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