Estimation in quantile regression models for correlated data with diverging number of covariates and large cluster sizes-Reference-Cited by-同舟云学术

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Estimation in quantile regression models for correlated data with diverging number of covariates and large cluster sizes

Published:2021-06-08 Issue: Volume: Page:1-27
ISSN:0361-0926
Container-title:Communications in Statistics - Theory and Methods
language:en
Short-container-title:Communications in Statistics - Theory and Methods

Author:

Zhao Weihua¹,Zhang Xiaoyu²,Yuen Kam Chuen²,Li Rui³,Lian Heng⁴^ORCID

Affiliation:

1. School of Science, Nantong University, Nantong, China

2. Department of Statistics, University of Hong Kong, Pok Fu Lam, Hong Kong

3. School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China

4. Department of Mathematics, City University of Hong Kong, Kowloon Tong, Hong Kong

Funder

National Social Science Fund of China

Publisher

Informa UK Limited

Subject

Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610926.2021.1922701

Reference42 articles.

1. Penalized quadratic inference functions for single-index models with longitudinal data

2. ℓ1-penalized quantile regression in high-dimensional sparse models

3. Binary quantile regression: a Bayesian approach based on the asymmetric Laplace distribution

4. Standard errors and covariance matrices for smoothed rank estimators

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