应数学系概率统计与运筹控制研究所田波平教授邀请，上海财经大学教授王绍立老师将于7月24日-7月28日来公司进行讲学活动，欢迎感兴趣的师生参加！

        报告题目：Nonparametric Mixture of Regression Models.

报告时间： 7月27日下午15:30-17:00          

报告地点：格物楼503

报告摘要：Motivated by an analysis of U.S. house price index (HPI) data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the ascent property of the EM algorithm in an asymptotic sense. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed estimation procedure. An empirical analysis of the U.S. HPI data is illustrated for the proposed methodology.

   报告人简介: 2005年获美国宾夕法尼亚州立大学统计学博士学位，2004年美国耶鲁大学博士后。长期从事高维数据的降维与分析、非参数和半参数模型，混合模型等统计学领域的研究，并取得多项富有价值的科研成果。在《The Annals of Statistics》、《Journal of The American Statistical Association》和《Journal of Statistical Planning and Inference》等学术杂志上发表学术论文多篇。其中SCI索引论文近10篇，被SCI他引数十次。曾多次应邀在国际学术会议上作报告。 2009 -现在上海财经大学统计与管理学院教授，主要从事数量金融与风险管理、数理统计研究工作；讲授时间序列、试验设计、概率论、风险管理与金融建模等课程。