Versatile Descent Algorithms for Group Regularization and Variable Selection in Generalized Linear Models

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-05-31 DOI:10.1080/10618600.2024.2362232

Nathaniel E. Helwig

引用次数: 0

Abstract

This paper proposes an adaptively bounded gradient descent (ABGD) algorithm for group elastic net penalized regression. Unlike previously proposed algorithms, the proposed algorithm adaptively boun...

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通用线性模型中分组正规化和变量选择的多功能后裔算法

本文提出了一种用于组弹性网惩罚回归的自适应有界梯度下降（ABGD）算法。与之前提出的算法不同，本文提出的算法能自适应地约束梯度下降。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computational and Graphical Statistics 数学-统计学与概率论

CiteScore

3.50

自引率

8.30%

发文量

153

审稿时长

>12 weeks

期刊介绍： The Journal of Computational and Graphical Statistics (JCGS) presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. Established in 1992, this journal contains cutting-edge research, data, surveys, and more on numerical graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing. Published in March, June, September, and December.