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Concave Group Selection of Nonparameter Additive Accelerated Failure Time Model

Concave Group Selection of Nonparameter Additive Accelerated Failure Time Model
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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. 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.
作者 Ling Zhu Ling Zhu(Jinan University, Guangzhou, China)
机构地区 Jinan University
出处 《Open Journal of Statistics》 2021年第1期137-161,共25页 统计学期刊(英文)
关键词 Accelerated Failure Time Model Nonparameter Model Group Minimax Concave Penalty Weighted Least Squares Estimation Accelerated Failure Time Model Nonparameter Model Group Minimax Concave Penalty Weighted Least Squares Estimation
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