Event Date
Joint UC Berkeley / UC Davis Symposium
This is our annual joint symposium with our colleagues at the UC Berkeley Department of Statistics. This year, the event is hosted at Berkeley.
Speaker: Jiming Jiang (Chair and Professor, Department of Statistics, UC Davis)
Title: Amazing Journey: The Conquest of Asymptotic Analysis of Maximum Likelihood Estimator in Generalized Linear Mixed Models with Crossed Random Effects
Abstract: 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.
References
- Jiang, J. (2013), The subset argument and consistency of MLE in GLMM: Answer to an open problem and
beyond, Ann. Statist. 41, 177-195. - Jiang, J. (2025), Asymptotic distribution of maximum likelihood estimator in generalized linear mixed models
with crossed random effects, Ann. Statist., in press.
Short Bio of Speaker
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.
He is author/coauthor of over 100 peer-reviewed publications and six books and monographs, including
Linear and Generalized Linear Mixed Models and Their Applications (Springer 2007, 2nd ed. 2021), Large
Sample Techniques for Statistics (Springer 2010, 2nd ed. 2022), The Fence Methods (World Scientific 2015;
joint with Nguyen), Asymptotic Analysis of Mixed Effects Models: Theory, Application, and Open Problems
(Chapman & Hall/CRC, 2017), Robust Mixed Model Analysis (World Scientific 2019), and Robust Small Area
Estimation: Methods, Theory, Applications and Open Problems (Chapman & Hall/CRC, in press; joint with
Rao).
He has served editorial boards of several major statistical journals including The Annals of Statistics and
Journal of the American Statistical Association. He is a Fellow of the American Association for the
Advancement of Science (AAAS), a Fellow of the American Statistical Association (ASA), a Fellow of the
Institute of Mathematical Statistics (IMS), and an Elected Member of the International Statistical Institute
(ISI). He is a co-recipient of Outstanding Statistical Application Award (ASA, 1998), a co-recipient of the first
Distinguished Alumni Award (National Institute of Statistical Sciences, 2015), a Yangtze River Scholar
(Chaired Professor, 2017-2020), widely regarded as the highest academic honor awarded to a foreigner by
the People's Republic of China, a Primary Speaker of the Morris Hansen Lecture (Washington Statistical
Society, 2023), and the recipient of the 2023-24 Award for Outstanding Contribution to Small Area Estimation
(the SAE Award; 2024).
Event Details (links to UC Berkeley): https://events.berkeley.edu/stat/event/292981-berkeley-davis-colloquium-with-jiming-jiang