数理学院第三周学术报告的通知
2016-03-08      阅读次数: 2203

时间:2016311日下午1400-1500

地点:图书馆报告厅南厅

主讲人:朱仲义,复旦大学统计系教授,博士研究生导师;曾任中国概率统计学会第八、九届副理事长,国际著名杂志”Statistica Sinica 副主编;现任“应用概率统计”,”数理统计与管理”杂志编委, 中国现场统计研究会常务理事,中国统计教材编审委员会委员。研究方向为:保险精算;非参数和半参数统计模型;纵向数据(面板数据)模型;分位数回责人完成国家自然科学基金重点项目1项。目前主持国家自然科学基金1.自从归模型等。主持完成国家自然科学基金3项、国家社会科学基金1项,作为子项目负1999年至今多次访问香港大学统计与精算学系、八次访问美国著名大学。近几年发表论文80多篇(其中包括在国际顶级刊物:J.R.Stat.Soc B, J.A.S.A., Ann. Statist. BiometrikaSCI论文四十多篇) SCI论文引用400多次,最高单篇论文被SCI论文引用近200.作为第一完成人研究成果获得教育部自然科学二等奖一次。

 

内容简介:

Missing responses and measurement errors are very common to be seen in practice. We develop new estimating equations, which can simultaneously estimate the mean and covariance under the partially linear model for longitudinal data with missing responses and covariate measurement errors. Specifically, we propose a novel approach to handle measurement errors by using the independence among replicated measures.  Comparing with the existing methods, the proposed method needs less  assumptions, such as those conditions in classical structural approaches or correction methods for measurement errors, and estimating the probability of being observed or imputing missing responses based on assumed models for missing responses. Additionally, the estimating equations of the proposed method is easy to implement in  most popular statistical softwares by applying existing algorithms for the standard generalized estimating equations. We establish the asymptotic properties of proposed estimators under regularity conditions, and the simulation studies demonstrate desired properties. Finally, we investigate the Lifestyle Education for Activity and Nutrition (LEAN) study and confirm the effective of intervention in producing weight loss after nine month.

 

   欢迎全校感兴趣的师生积极参加! 

                                          数理学院

                                 2016年3月8


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