A robust and efficient variable selection method for linear regression-Reference-Cited by-同舟云学术

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A robust and efficient variable selection method for linear regression

Published:2021-08-06 Issue: Volume: Page:1-16
ISSN:0266-4763
Container-title:Journal of Applied Statistics
language:en
Short-container-title:Journal of Applied Statistics

Author:

Yang Zhuoran¹,Fu Liya¹,Wang You-Gan²,Dong Zhixiong¹,Jiang Yunlu³

Affiliation:

1. School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, People's Republic of China

2. School of Mathematical Science, Queensland University of Technology, Brisbane, Australia

3. Department of Statistics, College of Economics, Jinan University, Guangzhou, People's Republic of China

Funder

National Natural Science Foundation of China

Australian Research Council

Fundamental Research Funds for the Central Universities

Natural Science Basic Research Plan in ShaanxiProvince of China

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/02664763.2021.1962259

Reference23 articles.

1. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems

2. On Estimating Variances of Robust Estimators When the Errors are Asymmetric

3. Robust Lasso Regression Using Tukey's Biweight Criterion

4. Extended Bayesian information criteria for model selection with large model spaces

5. Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Nonasymptotic analysis of robust regression with modified Huber's loss;Journal of Complexity;2023-06

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