报告题目：Predicting the multivariate zero-inflated counts: A novel model averaging method under Pearson loss
主讲人：刘寅副教授（中南财经政法越南直播）
时间：2026年6月12日（周五）17:10 p.m.
地点：北院卓远楼305会议室
主办单位：统计与数学学院
摘要：
Excessive zeros in multivariate count data are often observed in scenarios of biomedicine and public health. To provide a better analysis on this type of data, we first develop amarginalized multivariate zero-inflated Poisson (MZIP) regression model to directly interpret the overall exposure effects on marginal means. Then, we define a multiple Pearson residual for our newly developed MZIP regression model by simultaneously taking heterogeneity and correlation into consideration. Furthermore, a newmodel averaging predictionmethod is introduced based on the multiple Pearson residual, and the asymptotical optimality of this model averaging prediction is proved. Simulations and two empirical applications in medicine are used to illustrate the effectiveness of the proposed method.
主讲人简介：
刘寅，中南财经政法越南直播统计与数学学院副教授，硕士生导师。主要研究方向包括复杂数据建模分析，模型平均预测及统计计算。主持国家自然科学基金青年基金1项、教育部人文社会科学基金一般项目1项、国家社会科学基金一般项目1项，相关988pay钱包成果发表在Statistics in Medicine、Statistical Methods in Medical Research、Biometrical Journal、Computational Statistics & Data Analysis、中国科学：数学、数理统计与管理等期刊上。
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