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复发事件下一类加性乘性转移模型

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复发事件下一类加性乘性转移模型 杜彦斌1, 戴家佳2, 金君21. 湖南师范大学数学与统计学院, 长沙 410006;
2. 贵州大学数学与统计学院, 贵阳 550025 A Class of Additive-Multiplicative Transformation Model for Recurrent Events Data DU Yanbin1, DAI Jiajia2, JIN Jun21. College of Mathematics and Statistics, Hunan Normal University, Changsha 410006, China;
2. College of Mathematics and Statistics, Guizhou University, Guiyang 550025
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摘要复发事件数据频繁的出现在纵向研究中,本文基于生物医学中的单类型复发事件数据,提出了一类加性乘性转移模型,该模型包含了一些重要的半参数模型.同时,模型允许协变量具有加性和乘性的影响,且加性影响随时间而变化.利用广义估计方程的思想,对模型中未知参数和非参数函数进行了估计,并证明了所得估计的相合性和渐近正态性.最后,用数值模拟的方法验证了所提估计的可行性.
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收稿日期: 2017-04-10
PACS:O212.7
基金资助:国家自然科学基金(11361015)资助项目.

引用本文:
杜彦斌, 戴家佳, 金君. 复发事件下一类加性乘性转移模型[J]. 应用数学学报, 2018, 41(5): 642-652. DU Yanbin, DAI Jiajia, JIN Jun. A Class of Additive-Multiplicative Transformation Model for Recurrent Events Data. Acta Mathematicae Applicatae Sinica, 2018, 41(5): 642-652.
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http://123.57.41.99/jweb_yysxxb/CN/ http://123.57.41.99/jweb_yysxxb/CN/Y2018/V41/I5/642


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