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Identification of local sparsity and variable selection for varying coefficient additive hazards models

  • Published:2018-09 Issue: Volume:125 Page:119-135
  • ISSN:0167-9473
  • Container-title:Computational Statistics & Data Analysis
  • language:en
  • Short-container-title:Computational Statistics & Data Analysis

Author:

Qu Lianqiang,Song Xinyuan,Sun Liuquan

Funder

Research Grant Council of the Hong Kong Special Administration Region

Chinese University of Hong Kong

National Natural Science Foundation of China

Key Laboratory of RCSDS, CAS

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference42 articles.

1. Efficient estimation for the Cox model with varying coefficients;Chen;Biometrika,2012

2. Varying coefficient transformation models with censored data;Chen;Biometrika,2010

3. Variable selection via nonconcave penalized likelihood and its oracle properties;Fan;J. Amer. Statist. Assoc.,2001

4. Variable selection for Cox’s proportional hazards model and frailty model;Fan;Ann. Statist.,2002

5. Local partial likelihood estimation for lifetime data;Fan;Ann. Statist.,2006

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1. Feature Selection for High-Dimensional Varying Coefficient Models via Ordinary Least Squares Projection;Communications in Mathematics and Statistics;2023-03-31

2. Functional concurrent hidden Markov model;Statistics and Computing;2023-03-28

3. Additive hazards model with time-varying coefficients and imaging predictors;Statistical Methods in Medical Research;2022-11-30

4. Variable screening for varying coefficient models with ultrahigh-dimensional survival data;Computational Statistics & Data Analysis;2022-08

5. Time-varying coefficient additive hazards model with latent variables;Statistical Methods in Medical Research;2022-01-24
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