题目：Random Forest Estimation of Generalized Quantile Regression

主讲人：姜荣

讲座时间：2026年7月12日(周日)  10：00-11：00

地点：综合楼644会议室

报告人简介：姜荣，博士，上海对外经贸大学统计与数据科学学院教授，中国现场统计研究会旅游大数据分会常务理事。在《Journal of Machine Learning Research》、《Journal of Business & Economic Statistics》、《Journal of the Royal Statistical Society: SeriesC》、《Journal of Financial Econometrics》和《Journal of Multivariate Analysis》等国际期刊上发表SCI和SSCI论文30余篇。主持国家自然科学基金、教育部人文社科基金和上海市扬帆计划等项目。

讲座摘要：In this talk, I will introduce a novel nonparametric estimation framework for Generalized Quantile Regression (GQR) based on random forests. The framework overcomes the limitations faced by traditional kernel-based methods in high-dimensional settings. By integrating the bootstrap-based random forest conditional distribution estimator into the GQR framework, we establish the strong consistency of the random forest GQR estimator under realistic assumptions that account for the full bootstrap aggregation and data-dependent tree construction. Our findings contribute to bridging the gap between the practical implementation of random forests in risk management and their rigorous asymptotic theory. Both simulation studies and real data analyses demonstrate the finitesample performance of our proposed methods.