accelerated failure time model;
classification;
discriminant analysis;
fixed censoring;
median regression;
proportional hazard model;
quantile regression;
robustness;
D O I:
10.1198/016214502388618663
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
This article suggests very simple three-step estimators for censored quantile regression models with a separation restriction on the censoring probability. The estimators are theoretically attractive (i.e.. asymptotically as efficient as the celebrated Powell's censored least absolute deviation estimator). At the same time, they are conceptually simple and have trivial computational expenses. They are especially useful in samples of small size or models with many regressors. with desirable finite-sample properties and small bias. The separation restriction costs a small reduction of generality relative to the canonical censored regression quantile model, yet its main plausible features remain intact. The estimator can also be used to estimate a large class of traditional models. including the normal Amemiya-Tobin model and many accelerated failure and proportional hazard models. We illustrate the approach with an extramarital affairs example and contrast our findings with those of Fair.
机构:
Univ Hong Kong, Dept Stat & Actuarial Sci, Pokfulam, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Pokfulam, Hong Kong, Peoples R China
Jiang, Fei
Cheng, Qing
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h-index: 0
机构:
Duke NUS Med Sch, Ctr Quantitat Med, Singapore, SingaporeUniv Hong Kong, Dept Stat & Actuarial Sci, Pokfulam, Hong Kong, Peoples R China
Cheng, Qing
Yin, Guosheng
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机构:
Univ Hong Kong, Dept Stat & Actuarial Sci, Stat & Actuarial Sci, Pokfulam, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Pokfulam, Hong Kong, Peoples R China
Yin, Guosheng
Shen, Haipeng
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机构:
Univ Hong Kong, Innovat & Informat Management, Pokfulam, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Pokfulam, Hong Kong, Peoples R China
机构:
Shanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R China
Southern Univ Sci & Technol, Dept Stat & Data Sci, Shenzhen 518055, Peoples R ChinaShanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R China
Tang, Yuanyuan
Wang, Xiaorui
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R China
Southern Univ Sci & Technol, Dept Stat & Data Sci, Shenzhen 518055, Peoples R ChinaShanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R China
Wang, Xiaorui
Zhu, Jianming
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R ChinaShanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R China
Zhu, Jianming
Lin, Hongmei
论文数: 0引用数: 0
h-index: 0
机构:
Shanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R ChinaShanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R China
Lin, Hongmei
Tang, Yanlin
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h-index: 0
机构:
East China Normal Univ, Sch Stat, MOE, KLATASDS, Shanghai 200062, Peoples R China
Hong Kong Baptist Univ, Dept Math, Hong Kong 519087, Peoples R ChinaShanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R China
Tang, Yanlin
Tong, Tiejun
论文数: 0引用数: 0
h-index: 0
机构:
East China Normal Univ, Sch Stat, MOE, KLATASDS, Shanghai 200062, Peoples R China
Hong Kong Baptist Univ, Dept Math, Hong Kong 519087, Peoples R ChinaShanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R China