Robust and efficient factorial designs under baseline parametrization

Abstract

Factorial designs, traditionally based on orthogonal parametrization, are widely used to study the effects of factors on responses. While the baseline parametrization has more applicability in many cases compared to the orthogonal parametrization, constructing baseline parametrization design is still challenging. This article presents a method based on approximation theory to search for highly efficient baseline parametrization designs, enhancing the accuracy of factor effect estimations. In addition, this article employs the D-optimal minimax criterion to ensure the robustness of the design. The examples and simulation show that the constructed designs have high efficiency.