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Variable selection for recurrent event data with broken adaptive ridge regression

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成果类型:
期刊论文
作者:
Zhao, Hui;Sun, Dayu;Li, Gang;Sun, Jianguo*
通讯作者:
Sun, Jianguo
作者机构:
[Zhao, Hui] Cent China Normal Univ, Sch Math & Stat, Wuhan, Hubei, Peoples R China.
[Zhao, Hui] Cent China Normal Univ, Hubei Key Lab Math Sci, Wuhan, Hubei, Peoples R China.
[Sun, Dayu; Sun, Jianguo] Univ Missouri, Dept Stat, Columbia, MO 65211 USA.
[Li, Gang] Univ Calif Los Angeles, Dept Biostat, Los Angeles, CA USA.
通讯机构:
[Sun, Jianguo] U
Univ Missouri, Dept Stat, Columbia, MO 65211 USA.
语种:
英文
关键词:
Additive rate model;event history study;recurrent event data;variable selection
期刊:
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
ISSN:
0319-5724
年:
2018
卷:
46
期:
3
页码:
416-428
基金类别:
The authors wish to thank the Editor, Dr. Yi, the Associate Editor, and two referees for their many helpful comments and suggestions. This work was partly supported by the US National Institutes of Health grants (R03 CA219450, R21 CA198641), the National Nature Science Foundation of China (Nos. 11471135, 11571133), and the self-determined research funds of CCNU from the college’s basic research of MOE (CCNU15ZD011, CCNU18ZDPY08).
机构署名:
本校为第一机构
院系归属:
数学与统计学学院
摘要:
Recurrent event data occur in many areas such as medical studies and social sciences and a great deal of literature has been established for their analysis. On the other hand, only limited research exists on the variable selection for recurrent event data, and the existing methods can be seen as direct generalizations of the available penalized procedures for linear models and may not perform as well as expected. This article discusses simultaneous parameter estimation and variable selection and presents a new method with a new penalty function, which will be referred to as the broken adaptive...

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