Concave Group Selection of Nonparameter Additive Accelerated Failure Time Model

• 作者: Ling Zhu
• 来源期刊: 统计学期刊(英文)
• 学科: 数学
• 关键词: Accelerated Failure Time Model Nonparameter Model Group Minimax Concave Penalty Weighted Least Squares Estimation
• 年，卷（期）: 2021,（1）
• 页码范围: 137-161
• 页数: 25页
• 分类号: O17

摘要

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.