学术报告：李纯净 长春工业大学

主讲人：李纯净 长春工业大学

题 目： Bayesian variable selection in a binary quantile regression model for longitudinal data

时间：2025年10月18日 14:00-15:30

地点：VSport体育官网新校园 B514

摘要：In this paper, we construct a Bayesian hierarchical model with regression coefficients following a spike-and-slab prior. This model is used for high-dimensional binary quantile regression models with longitudinal data, which fills the gap in literature research. We employ the EM algorithm and Gibbs algorithm to generate posterior samples. Subsequently, we develop a threshold rule to identify important independent variables in the model while eliminating redundant ones. Through simulations in various scenarios, we validate the effectiveness and robustness of our proposed Bayesian model. Finally, we apply our method to the Add Health dataset.