报告题目：Copula-based models in compositional data analysis

报告人：刘鹏懿

时间：4月25日 15：50-16：40

地点：正妹 106会议室

报告摘要：Multivariate fractional data with unit–sum constraints often occurs in various fields. Both the log-ratio method and the Dirichlet regression rely on assumptions of the same type of marginal distribution. We propose a distribution framework for this class of data by incorporating the Sigmoid transformation of log-ratio coordinates and utilizing Beta,proportional inverse Gaussian (PIG) and simplex marginal distribution with the Gaussian copula function. Simultaneously, we propose a unified model to construct regression models specifically designed for multivariate proportional data subject to unit-sum constraints, with compositional data as a key special case. This framework unifies a large class of new and existing log-ratio type regressions and covers a very flexible class of regression models. The properties of the proposed estimator are assessed numerically through a simulation study and real-data analysis.

报告人简介：刘鹏懿，云南财经大学统计与数学正妹 副教授，统计学博士（毕业于香港大学统计与精算系）。主要从事生物统计、统计计算和分布理论与应用方面的研究。2022年云南省“兴滇英才支持计划”青年人才。