编号 | 时间 | 类型 | 题目 | 讲者 | 单位 |
---|---|---|---|---|---|
1 | 13:30-13:50 | 贡献报告 |
共同富裕促进代际收入流动吗——基于微观家庭数据的经验研究 |
黄赛洪 | 安徽财经大学 |
Contributed Talk |
共同富裕促进代际收入流动吗——基于微观家庭数据的经验研究 |
Saihong Huang | Anhui University of Finance and Economics | ||
2 | 13:50-14:10 | 贡献报告 |
AI智能体能否成为智能投顾新助手 |
Zhanye Luo | University of Chicago |
Contributed Talk |
AI智能体能否成为智能投顾新助手 |
Zhanye Luo | University of Chicago | ||
3 | 14:10-14:30 | 贡献报告 |
数据要素市场化配置对企业新质生产力的影响研究 ——基于A股上市公司的经验证据 |
李竹萌 | 吉林财经大学 |
Contributed Talk |
数据要素市场化配置对企业新质生产力的影响研究 ——基于A股上市公司的经验证据 |
Zhumeng Li | Jilin University of Finance and Economics | ||
4 | 14:30-14:50 | 贡献报告 |
具有长记忆性的时变回归模型 (Time-varying Regression with Long Memory) |
柯书尧 | 暨南大学经济学院 |
Contributed Talk |
Time-varying Regression with Long Memory |
Shuyao Ke | School of Economics,Jinan University | ||
5 | 14:50-15:10 | 贡献报告 |
基于协变量自适应随机化的多重政策分位数处理效应模型及其应用 |
许格芳 | 郑州大学商学院 |
Contributed Talk |
基于协变量自适应随机化的多重政策分位数处理效应模型及其应用 |
Gefang Xu | School of Business, Zhengzhou University |
编号 | 时间 | 类型 | 题目 | 讲者 | 单位 |
---|---|---|---|---|---|
1 | 15:30-15:50 | 贡献报告 |
High-dimensional graphical inference via partially penalised regression |
赵 妮 | 中国科学技术大学 |
Contributed Talk |
High-dimensional graphical inference via partially penalised regression |
Ni Zhao | University of Science and Technology of China | ||
2 | 15:50-16:10 | 贡献报告 |
Bayesian Grouping-Gibbs Sampling Estimation of High-dimensional Linear Model with Non-sparsity |
秦珊珊 | 天津财经大学 |
Contributed Talk |
Bayesian Grouping-Gibbs Sampling Estimation of High-dimensional Linear Model with Non-sparsity |
Shanshan Qin | Tianjin University of Finance and Economics | ||
3 | 16:10-16:30 | 贡献报告 |
Regret Minimization and Statistical Inference in Online Decision Making with High-dimensional Covariates |
段聪原 | 香港科技大学 |
Contributed Talk |
Regret Minimization and Statistical Inference in Online Decision Making with High-dimensional Covariates |
Congyuan Duan | The Hong Kong University of Science and Technology | ||
4 | 16:30-16:50 | 贡献报告 |
Group Sparse $\beta$-Model: Multi-Magnitude Core Node Influence |
王中含 | 北京师范大学统计学院 |
Contributed Talk |
Group Sparse $\beta$-Model: Multi-Magnitude Core Node Influence |
Zhonghan Wang | Beijing Normal University | ||
5 | 16:50-17:10 | 贡献报告 |
Robust Model Averaging Prediction of Longitudinal Response with Ultrahigh-dimensional Covariates |
吕 晶 | 西南大学 |
Contributed Talk |
Robust Model Averaging Prediction of Longitudinal Response with Ultrahigh-dimensional Covariates |
Jing Lv | Southwest University |