A New Type of LASSO Regression Model with Cauchy Noise

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2023-11-28 DOI:10.1007/s13253-023-00583-w

Amir Hossein Ghatari, Mina Aminghafari, Adel Mohammadpour

引用次数: 0

Abstract

Many datasets have heavy-tailed behavior, and classical penalized models are not appropriate for them. To treat this problem, we propose a penalized regression that handles model selection and outliers issues simultaneously. We provide a LASSO regression for models with Cauchy distributed noises using the negative log-likelihood loss function. To select the regularization parameter, we define AIC and BIC type criteria. We study the distribution of the regression coefficients estimator in the simulation experiments. In addition, simulation study and real datasets analysis confirm the superiority of the proposed method.

Abstract Image

查看原文本刊更多论文

一类新的柯西噪声LASSO回归模型

许多数据集具有重尾行为，经典的惩罚模型不适用于它们。为了解决这个问题，我们提出了一个惩罚回归，同时处理模型选择和异常值问题。我们使用负对数似然损失函数为具有柯西分布噪声的模型提供LASSO回归。为了选择正则化参数，我们定义了AIC和BIC类型准则。在仿真实验中研究了回归系数估计量的分布。仿真研究和实际数据集分析验证了该方法的优越性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.