MATH Club
Jie Yang
UIC
Analytic solutions for D-optimal factorial designs under generalized linear models
Abstract: In order to find D-optimal designs in statistics, we
often need to maximize a homogeneous polynomial as a function of
proportions. We introduce two analytic approaches to solve
D-optimal approximate designs under generalized linear models. The
first approach provides analytic D-optimal allocations for
generalized linear models with two factors. The second approach
leads to explicit solutions for a class of generalized linear
models with more than two factors. There are many other similar
optimization problems of homogenous polynomials that are open and
have potential applications in statistics.
Wednesday March 7, 2018 at 5:00 PM in seo 300