Optimal design under complete class with ancillary functions

Abstract

AbstractNonlinear models are challenging in optimal designs due to their complexity and lack of canonical forms. The complete class strategy provides a unified framework for studying optimal designs for nonlinear models. However, the current strategy does not apply to many models under this framework. In this article, we propose a tool called ancillary functions as an extension to the complete class strategy. We also provide results on minimally supported designs with proper conditions. We demonstrate this tool with two‐parameter dose–response models, which include the Beta‐Poisson model, the complementary log–log model, and the skewed logit model. The results of this article add to the previous complete class framework and make the minimally supported design available for more nonlinear models that were previously not feasible.