Title: Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models

Keynote Speaker: Lin Huazhen

Abstract:

The efficiency of estimation for the parameters in semiparametric models has been widely studied in the literature. In this paper, we study efficient estimators for both parameters and nonparametric functions in a class of generalized semi/non-parametric regression models, which cover commonly used semiparametric models such as partially linear models, partially linear single index models, and two-sample semiparametric models. We propose a maximum likelihood principle combined with the local linear technique for estimating the parameters and nonparametric functions. The proposed estimators of the parameters and a linear functional of the nonparametric functions are consistent and asymptotically normal and are further shown to be semiparametrically efficient. An efficient computational algorithm to achieve the maximization is proposed. Extensive simulation experiments show the superiority of the proposed methods. Three real data examples are analyzed and presented as an illustration.

Introduction to the Speaker:

Lin Huazhen, Professor, Doctoral Supervisor, is the Director of Center of Statistical Research, Southwestern University of Finance and Economics, distinguished professor of Chang Jiang Scholars Program of the Ministry of Education, winner of National Science Fund for Distinguished Young Scholars, winner of Hundred-Thousand-Ten Thousand Talent Project, expert enjoying special government allowance of the State Council, member of the Program for New Century Excellent Talents in University of the Ministry of Education, leader of the 11^th batch of academic and technical talents in Sichuan and excellent expert of the 10^th batch of talents making great contributions to Chengdu. She mainly studies transformation model, non-parametric method, survival data analysis, functional data analysis, latent variable analysis, ROC method, skew data analysis, capture-recapture data analysis. She has published over 40 academic papers, including several papers published in top international journals of statistics and econometrics, such as AoS, JASA, JoE, JRSSB, Biometrika and Biometrcs, and presided over National Natural Science Foundation Program of China for six times. Besides, Prof. Lin Huazhen is also a member of IMS-China, IBS-CHINA and ICSA-China, Vice President of the 9^th National Industrial Statistics Teaching and Research Association, and Vice Chairman of the Environment and Resources Branch, High Dimensional Data Analysis Branch, Society of Biomedical Statistics and Survival Analysis Branch of China Field Statistics Research Association. And she has successively been the Associate Editor of international statistical journals such as Biometrics, Scandinavian Journal of Statistics, Canadian Journal of Statistics, Statistics and Its Interface, Statistical Theory and Related Fields, and the editorial board member of Chinese Journal of Applied Probability and Statistics, Journal of System Science and Mathematical Science and Journal of Applied Statistics and Management.

Inviter:

Lin Lu Professor

Time:

16:00-17:00 on October 13 (Tuesday)

Location:

Tencent Conference, conference ID: 867 628 840

Sponsored by: School of Mathematics, Shandong University