Dr. Stefanie Biedermann : The optimal weights exchange algorithm – A fast and flexible method to derive optimal designs

Posted by Min Yang , part of the Statistics and Data Science Seminar.

At

Sept. 18, 2013, 4 p.m.

In

SEO 636

Abstract

Finding optimal designs for nonlinear models is challenging in general. Although some recent results allow us to focus on a simple subclass of designs for most problems, deriving a specific optimal design still mainly depends on numerical approaches. There is need for a general and efficient algorithm which is more broadly applicable than the current state of the art methods. We present a new algorithm which can be used to find optimal designs with respect to a broad class of optimality criteria, when the model parameters or functions thereof are of interest, and for both locally optimal and multi-stage design strategies. We prove convergence to the optimal design, and show in various examples that the new algorithm outperforms the current state of the art algorithms.