Comment on “A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression”,Journal of the American Statistical Association

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Comment on “A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression”
Journal of the American Statistical Association ( IF 3.0 ) Pub Date : 2020-10-01 , DOI: 10.1080/01621459.2020.1837138
Jianqing Fan ₁ , Cong Ma ₂ , Kaizheng Wang ₃

Affiliation

ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/uasa20 Comment on “A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression” Jianqing Fan , Cong Ma & Kaizheng Wang To cite this article: Jianqing Fan , Cong Ma & Kaizheng Wang (2020) Comment on “A TuningFree Robust and Efficient Approach to High-Dimensional Regression”, Journal of the American Statistical Association, 115:532, 1720-1725, DOI: 10.1080/01621459.2020.1837138 To link to this article: https://doi.org/10.1080/01621459.2020.1837138

中文翻译：

评论“一种无需调整的稳健高效的高维回归方法”

ISSN: (Print) (Online) 期刊主页: https://www.tandfonline.com/loi/uasa20 Comment on “A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression” 范建清 , Cong Ma & Kaizheng Wang To引用本文：Jianqing Fan , Cong Ma & Kaizheng Wang (2020) Comment on “A TuningFree Robust and Efficient Approach to High-Dimensional Regression”, Journal of the American Statistical Association, 115:532, 1720-1725, DOI: 10.1080/ 01621459.2020.1837138 本文链接：https://doi.org/10.1080/01621459.2020.1837138

更新日期：2020-10-01

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