【专家简介】：胡雪梅，重庆工商大学数学与统计学院教授，长江上游经济中心(教育部人文社科重点研究基地)博士生导师，中南大学理学博士，中科院数学与系统科学研究院控制论国家重点实验室系统科学博士后，美国《数学评论》评议员， “第五批重庆市高等学校优秀人才支持计划”人选。重庆市“统计学”研究生导师团队负责人，《随机过程》市级一流线下课程负责人。目前已对半变系数模型的统计推断、半参数模型的经验似然、随机扩散方程的稳健推断、高维数据模型的统计学习等展开了系统研究，在Journal of Multivariate Analysis、Statistical Papers、North American Journal of Economics and Finance、Soft Computing、Journal of Forecasting等学术期刊上发表论文40多篇，其中SCI/SSCI收录27篇，主持完成1项国家自然科学基金青年项目、1项教育部人文社科青年项目、5项重庆市科委项目、2项重庆市教委项目， 参与获得重庆市科学技术奖二等奖。出版专著2部（《高维统计模型的估计理论与模型识别》和《高维数据模型的统计学习方法与预测精度评估》）。目前主持在研1项重庆市教委科学技术研究计划重大项目和1项重庆市社科规划项目。
【报告摘要】：Multinomial logit model(MLM) has been proposed as the most frequently regression model for multi-category response and the widely used functional form for discrete choice probabilities. To deal with correlated data, in this paper we propose G-LASSO/G-SCAD/G-MCP penalized MLM model to exert class discovery and class prediction for multi-category classification problems. Firstly, we develop a group coordinate descent algorithm to simultaneously complete group selection and group estimation, and prove its convergence under mild conditions. Secondly, we apply the training set and group estimations to obtain class probability estimators, choose the Bayes classifier to identify class index information, and introduce the testing set and a few measures to assess multi-category prediction performance. Simulations show that the proposed methods outperform LASSO/SCAD/MCP penalized MLM, 3 deep learning methods and 3 machine learning methods in terms of Kappa, PDI, Optimal or Average Accuracy. Finally, we combine group penalized MLM with 58 technical indicators to predict up trends, sideways trends and down trends for stock returns, and show that the proposed methods outperform the other 9 methods in terms of Accuracy, PDI, Kappa and HUM. Therefore, the proposed method can not only accommodate the correlation information, but also improve multi-category prediction performance by shrinking group coefficients.
时 间：2023年9月13日 8:40
地 点：位育楼417
