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超高维II型区间删失数据的非参数变量筛选法

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超高维II型区间删失数据的非参数变量筛选法 张婧1, 靳韶佳2, 陈丹丹21. 中南财经政法大学统计与数学学院, 武汉 430073;
2. 武汉大学数学与统计学院, 武汉 430072 Nonparametric Feature Screening for Ultrahigh-dimensional Case II Interval-censored Failure Time Data ZHANG Jing1, JIN Shaojia2, CHEN Dandan21. School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan 430073, China;
2. School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China
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摘要在定期随访的医学研究或临床实验中,人们经常会收集到高维区间删失数据,如何对这类数据进行降维是一个非常有意义的问题.本文基于Kolmogorov-Smirnov检验统计量,利用分割和融合的技巧,把独立特征筛选方法推广到区间删失数据中,提出了一种可以处理超高维II型区间删失数据且不依赖于任何模型假设的变量筛选方法.此方法的适用范围很广,可以有效地处理各种生存模型下的超高维II型区间删失数据,而且可以处理离散型,连续型等多种类型的协变量.在估计生存函数时,本文采用EM-ICM算法,极大地提高了计算效率.大量的数值模拟实验验证了此方法在有限样本下的有效性.
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收稿日期: 2020-06-04
PACS:O212.1
基金资助:国家自然科学基金青年项目(No.11901581),中南财经政法大学中央高校基本科研业务费专项资金(No.2722020JCG064)资助.

引用本文:
张婧, 靳韶佳, 陈丹丹. 超高维II型区间删失数据的非参数变量筛选法[J]. 应用数学学报, 2021, 44(5): 690-702. ZHANG Jing, JIN Shaojia, CHEN Dandan. Nonparametric Feature Screening for Ultrahigh-dimensional Case II Interval-censored Failure Time Data. Acta Mathematicae Applicatae Sinica, 2021, 44(5): 690-702.
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http://123.57.41.99/jweb_yysxxb/CN/ http://123.57.41.99/jweb_yysxxb/CN/Y2021/V44/I5/690


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