• Office hours:
  • T 2:00 - 3:00
    R 2:30 - 3:30
    
• Courses:
  • Spring 2025
    
    

    Math 553	Section 01 :	Nonparametric Inference
    	TR 9:00 - 11:00	WH-100E

• Ph. D. Students:
  • Mengyu Chen, Spring, 2022
    Thesis: An Empirical Likelihood Approach with Bivariate Data
  • Xiaojie Du, Spring, 2018
    Thesis: Inference in Linear Regression with Symmetric Errors: An Empirical Likelihood Approach
  • Ruiqi Liu, Spring, 2018
    Thesis: Identification and estimation in panel models with over specified number of groups
  • Nan Bi, Fall, 2016
    Thesis: Empirical Likelihood for a Class of Semiparametric Regression Models
  • Yilin Zhu, Spring, 2016
    Thesis: Estimation of the Error Distribution in a Varying Coefficient Regression Model
  • Peng Zhang, Fall, 2010
    Thesis: Prediction in heteroskedastic autoregressive models
  • Jichang Du, Fall, 2007
    Thesis: Covariate-matched estimator of the error variance in nonparametric regression
  • Jeffrey Forrester, Summer, 2001
    Thesis: Efficient Estimation of the Regression Parameter in a Heteroscedastic Regression Model Where Heteroscedasticity is Modeled as a function of the mean response
  • William Hooper, Summer, 2001
    Thesis: Efficient Estimation of Transformation Parameters in Nonparametric Regression
  • Hanxiang Peng, Summer, 2001
    Thesis: Efficient Estimation of Linear Functionals of a Bivariate Probability with Equal Marginals

Here's a link to my personal web page.