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Yue, M., Li, J.L. and Ma, S.G. (2018) Sparse Boosting for High-Dimensional Survival Data with Varying Coefficients. Statistics in Medicine, 37, 789-800.
https://doi.org/10.1002/sim.7544

has been cited by the following article:

• TITLE: Concave Group Selection of Nonparameter Additive Accelerated Failure Time Model

  AUTHORS: Ling Zhu

  KEYWORDS: Accelerated Failure Time Model, Nonparameter Model, Group Minimax Concave Penalty, Weighted Least Squares Estimation

  JOURNAL NAME: Open Journal of Statistics, Vol.11 No.1, February 5, 2021

  ABSTRACT: In this paper, we have studied the nonparameter accelerated failure time (AFT) additive regression model, whose covariates have a nonparametric effect on high-dimensional censored data. We give the asymptotic property of the penalty estimator based on GMCP in the nonparameter AFT model.