Nonparametric independence screening for ultra-high dimensional generalized varying coefficient models with longitudinal data-Reference-Cited by-同舟云学术

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Nonparametric independence screening for ultra-high dimensional generalized varying coefficient models with longitudinal data

Published:2019-05 Issue: Volume:171 Page:37-52
ISSN:0047-259X
Container-title:Journal of Multivariate Analysis
language:en
Short-container-title:Journal of Multivariate Analysis

Author:

Zhang Shen,Zhao Peixin,Li Gaorong,Xu Wangli

Funder

National Social Science Foundation of China

Chongqing Research Program of Basic Theory and Advanced Technology, China

National Natural Science Foundation of China

Beijing Natural Science Foundation, China

Publisher

Elsevier BV

Subject

Statistics, Probability and Uncertainty,Numerical Analysis,Statistics and Probability

Reference46 articles.

1. A Practical Guide to Splines;de Boor,1978

2. The Dantzig selector: Statistical estimation when p is much larger than n;Candès;Ann. Statist.,2007

3. Nonparametric independence screening and structure identification for ultra-high dimensional longitudinal data;Cheng;Ann. Statist.,2014

4. Forward variable selection for sparse ultra-high dimensional varying coefficient models;Cheng;J. Amer. Statist. Assoc.,2016

5. Feature screening for time-varying coefficient models with ultrahigh dimensional longitudinal data;Chu;Ann. Appl. Statist.,2016

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1. Recent advances in longitudinal data analysis;Handbook of Statistics;2024

2. Sure Joint Screening for High Dimensional Cox's Proportional Hazards Model Under the Case-Cohort Design;Journal of Computational Biology;2023-05-01

3. Double Penalized Regularization Estimation for Semiparametric Instrumental Variable Models with Ultrahigh Dimensional Data;Advances in Applied Mathematics;2022

4. Double penalized regularization estimation for partially linear instrumental variable models with ultrahigh dimensional instrumental variables;Communications in Statistics - Simulation and Computation;2021-09-09

5. Feature screening of quadratic inference functions for ultrahigh dimensional longitudinal data;Journal of Statistical Computation and Simulation;2020-06-23

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