Robust designs with high projection efficiency

摘要

Alphabetic optimality criteria, such as the D, A, and I criteria, require specifying a model to select optimal designs. They are not model-free, and the designs obtained by them may not be robust. Recently, many extensions of the D and A criteria have been proposed for selecting robust designs with high estimation efficiency. However, approaches for finding robust designs with high prediction efficiency are rarely studied in the literature. In this paper, we propose a compound criterion and apply the coordinate-exchange 2-phase local search algorithm to generate robust designs with high estimation, high prediction, or balanced estimation and prediction efficiency for projective submodels. Examples demonstrate that the designs obtained by our method have better projection efficiency than many existing designs.