國立政治大學統計學系
學 術 演 講
主講人：陳瑞彬教授(清華大學統計與數據科學研究所)學 術 演 講
題 目：Bayesian Selection Approach for Categorical Responses via Multinomial
Probit Models
時 間：民國114年5月19日 (星期一) 下午1：30
地 點：國立政治大學逸仙樓050101教室
摘 要：
In this paper, a multinomial probit model is proposed to examine a categorical response variable, with the main objective being the identification of the influential variables in the model. To this end, a Bayesian selection technique is employed featuring two hierarchical indicators. The first indicator denotes a variable's relevance to the categorical response, and the subsequent indicator relates to the variable's importance at a specific categorical level, which aids in assessing its impact at that level. The selection process relies on the posterior indicator samples generated through an MCMC algorithm. The efficacy of our Bayesian selection strategy is demonstrated through both simulation and an application to a real-world example.
