主题：Growth curve mixture models with unknown covariance structures
主讲人：费宇 云南财经大学
主持人：姜云卢 BETVLCTOR伟德官网下载
时间：2023年4月24日（周一）10：00-11：00
地点：BETVLCTOR伟德官网下载石牌校区伟德BETVlCTOR1946大楼（中惠楼）102室
摘要
Though playing an important role in longitudinal data analysis, the uses of growth curve models are constrained by the crucial assumption that the grouping design matrix is known. In this paper we propose a Gaussian mixture model within the framework of growth curve models which handles the problem caused by the unknown grouping matrix. This allows for a greater degree of flexibility in specifying the model and freeing the response matrix from following a single multivariate normal distribution. The new model is considered under two parsimonious covariance structures together with the unstructured covariance. The maximum likelihood estimation of the proposed model is studied using the ECM algorithm, which clusters growth curve data simultaneously. Data-driving methods are proposed to find various model parameters so as to create an appropriate model for complex growth curve data. Simulation studies are conducted to assess the performance of the proposed methods and real data analysis on gene expression clustering is made, showing that the proposed procedure works well in both, model fitting and growth curve data clustering.
主讲人简介
费宇，二级教授，博士，英国曼彻斯特大学博士后，博士生导师，云南财经大学统计学首席教授，云南省云岭学者，云南省中青年学术技术带头人，云岭教学名师，中国数量经济学会常务理事，云南省统计学会副会长。主要从事统计理论与方法和应用统计方面的研究。在《Technometrics》《Journal of Multivariate Analysis》《Statistical Papers》《Energy》《中国科学》和《统计研究》等杂志发表论文50多篇，出版专著2部，教材4部，主持国家自然科学基金项目3项，获云南省自然科学一等奖1项、三等奖2项，国家统计局科研成果二等奖1项，云南省教学成果一等奖1项、二等奖1项。
编辑|麦嘉杰
初审|王国长
审核|郑贤
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