Optimal exact designs of experiments via Mixed Integer Nonlinear Programming(Article)

Statistics and Computing

Journal Article

Optimal exact designs are problematic to find and study because there is no unified theory for determining them and studying their properties. Each has its own challenges and when a method exists to confirm the design optimality, it is invariably applicable to the particular problem only. We propose a systematic approach to construct optimal exact designs by incorporating the Cholesky decomposition of the Fisher Information Matrix in a Mixed Integer Nonlinear Programming formulation. As examples, we apply the methodology to find D- and A-optimal exact designs for linear and nonlinear models using global or local optimizers. Our examples include design problems with constraints on the locations or the number of replicates at the optimal design points. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

B.P.M.a,b Duarte

W.K.c Wong


Year of publication: 2020


ISSN: 09603174


DOI: 10.1007/s11222-019-09867-z

Alternative Titles