Song-Xi Chen (Iowa State University): High Dimensional Empirical Likelihood for Generalized Estimating Equations with Dependent Data
Speaker Song-Xi Chen, Iowa State University
Date Sep 20, 2012
Time 3:30 pm – 4:30 pm
Location 122 Illini Hall
Sponsor Statistics Department
Event type Seminar
This paper studies the maximum empirical likelihood estimation (MELE) and inference on parameters identified by generalized estimating equations with weakly dependent data when the dimensions of the estimating equations and the parameters are diverging. Our theory greatly extends a wide range of existing results to the new time series framework of growing dimensions of the parameters, the estimating equations and the observed covariates. We obtain the consistency with rates and the asymptotic normality of the MELE by properly restricting the growth rates of the dimensions of the parameters and the estimating equations, as well as the degree of dependence. We also show that, even in this high dimensional nonlinear time series setting, the empirical likelihood ratio still behaves like a Chi-square random variable asymptotically. (Note that time and location are different from usual)