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In this paper, we study the D- and A-optimal assignment problems for regression models with experimental cost constraints. To solve these two problems, we propose two multiplicative algorithms for obtaining… Click to show full abstract
In this paper, we study the D- and A-optimal assignment problems for regression models with experimental cost constraints. To solve these two problems, we propose two multiplicative algorithms for obtaining optimal designs and establishing extended D-optimal (ED-optimal) and A-optimal (EA-optimal) criteria. In addition, we give proof of the convergence of the ED-optimal algorithm and draw conjectures about some properties of the EA-optimal algorithm. Compared with the classical D- and A-optimal algorithms, the ED- and EA-optimal algorithms consider not only the accuracy of parameter estimation, but also the experimental cost constraint. The proposed methods work well in the digital example.
Journal Title: Mathematics
Year Published: 2023
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