Robust and sparse learning of varying coefficient models with high-dimensional features-Reference-Cited by-同舟云学术

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Robust and sparse learning of varying coefficient models with high-dimensional features

Published:2022-08-09 Issue: Volume: Page:1-25
ISSN:0266-4763
Container-title:Journal of Applied Statistics
language:en
Short-container-title:Journal of Applied Statistics

Author:

Xiong Wei¹,Tian Maozai²^ORCID,Tang Manlai³,Pan Han¹

Affiliation:

1. School of Statistics, University of International Business and Economics, Beijing, People's Republic of China

2. Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, People's Republic of China

3. Department of Mathematics, College of Engineering, Design and Physical Sciences, Brunel University London, London, UK

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/02664763.2022.2109129

Reference39 articles.

1. Nonparametric Quantile Estimations for Dynamic Smooth Coefficient Models

2. Smoothing Spline Estimation for Varying Coefficient Models With Repeatedly Measured Dependent Variables

3. Feature screening for time-varying coefficient models with ultrahigh-dimensional longitudinal data

4. Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis

5. Local Linear Regression Smoothers and Their Minimax Efficiencies

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