Optimal exact designs of experiments via Mixed Integer Nonlinear Programming

Belmiro P.M. Duarte, José F.O. Granjo, Weng Kee Wong

研究成果: Article同行評審

12 引文 斯高帕斯(Scopus)


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.

頁(從 - 到)93-112
期刊Statistics and Computing
出版狀態Published - 2020 2月 1

All Science Journal Classification (ASJC) codes

  • 理論電腦科學
  • 統計與概率
  • 統計、概率和不確定性
  • 計算機理論與數學


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