Multiple Constrained Optimal Experimental Design

Title & Authors
Multiple Constrained Optimal Experimental Design
Jahng, Myung-Wook; Kim, Young Il;

Abstract
It is unpractical for the optimal design theory based on the given model and assumption to be applied to the real-world experimentation. Particularly, when the experimenter feels it necessary to consider multiple objectives in experimentation, its modified version of optimality criteria is indeed desired. The constrained optimal design is one of many methods developed in this context. But when the number of constraints exceeds two, there always exists a problem in specifying the lower limit for the efficiencies of the constraints because the “infeasible solution” issue arises very quickly. In this paper, we developed a sequential approach to tackle this problem assuming that all the constraints can be ranked in terms of importance. This approach has been applied to the polynomial regression model.
Keywords
$\small{\Phi_{AP}}$-optimality;constrained optimal experimental design;polynomial regression;
Language
Korean
Cited by
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Communications for Statistical Applications and Methods, 2006. vol.13. 1, pp.1-10
2.
Hybrid Approach When Multiple Objectives Exist,;;

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3.
정확최적실험계획법,김영일;

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4.
하이브리드형 제약 외삽실험 계획법,김영일;장대흥;

Communications for Statistical Applications and Methods, 2012. vol.19. 1, pp.65-75
5.
다중 외삽점에서의 최적 실험설계법을 위한 실험설계기준,김영일;장대흥;

응용통계연구, 2014. vol.27. 5, pp.693-703
1.
Hybrid Constrained Extrapolation Experimental Design, Communications for Statistical Applications and Methods, 2012, 19, 1, 65
2.
Some Criteria for Optimal Experimental Design at Multiple Extrapolation Points, Korean Journal of Applied Statistics, 2014, 27, 5, 693
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