A0624
Title: Uniform inference near the boundary, with mixed models examples
Authors: Karl Oskar Ekvall - University of Florida (United States) [presenting]
Abstract: The focus is on new advances and open problems in the theory and methods for uniform inference on parameters near the boundary of the parameter set. The general theory is motivated and illustrated using linear mixed models examples. For example, recent results show that score-based confidence regions can have asymptotically correct uniform coverage probability, while uniform inference based on Wald and likelihood ratio statistics is more difficult and, in some cases, impossible. Connections between boundary problems and settings are also outlined with singular Fisher information.
