Multiplication Algorithms for Approximate Optimal Distributions with Cost Constraints

Lianyan Fu (), Faming Ma, Zhuoxi Yu () and Zhichuan Zhu
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Lianyan Fu: School of Mathematics and Statistics, Liaoning University, Shenyang 110036, China
Faming Ma: School of Economics, Liaoning University, Shenyang 110036, China
Zhuoxi Yu: School of Mathematics and Statistics, Liaoning University, Shenyang 110036, China
Zhichuan Zhu: School of Mathematics and Statistics, Liaoning University, Shenyang 110036, China

Mathematics, 2023, vol. 11, issue 8, 1-14

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 ( E D -optimal) and A -optimal ( E A -optimal) criteria. In addition, we give proof of the convergence of the E D -optimal algorithm and draw conjectures about some properties of the E A -optimal algorithm. Compared with the classical D - and A -optimal algorithms, the E D - and E A -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.

Keywords: D-optimal; A-optimal; experimental design; Kuhn–Tucker method; experimental cost (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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