Dr. Jiming Jiang, University of California, Davis

Dr. Jiming Jiang, University of California, Davis

Amazing Journey: The Conquest of Asymptotic Analysis of Maximum Likelihood Estimator in Generalized Linear Mixed Models with Crossed Random Effects

Generalized linear mixed models (GLMM) with crossed random effects are well known not only for the computational challenges involved in numerically evaluating the maximum likelihood estimator (MLE) but also for the theoretical challenges in studying asymptotic behavior of the MLE under these models. In fact, not until 2012 has consistency of the MLE been established for GLMM with crossed random effects (Jiang 2013). Now, another part of the asymptotic behavior, that is, asymptotic normality of the MLE for GLMM with crossed random effects has also been established (Jiang 2025). This talk provides an overview of this “amazing journey”, focusing on the methodology developments for overcoming the theoretical challenges.

Bio

Jiming Jiang is a Professor of Statistics and Chair of the Department of Statistics at the University of California, Davis. He received his Ph.D. in Statistics in 1995 from the University of California, Berkeley. His research interests include mixed effects models, model selection, small area estimation, longitudinal data analysis, Big Data intelligence, statistical genetics/bioinformatics, and asymptotic theory.