The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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The Maximin Robust Design for the Uncertainty of Parameters of Michaelis-Menten Model

Michaelis-Menten 모형의 모수의 불확실성에 대한 Maximin 타입의 강건 실험

  • Kim, Youngil (School of Business and Economics, Chung-Ang University) ;
  • Jang, Dae-Heung (Department of Statistics, Pukyong National University) ;
  • Yi, Seongbaek (Department of Statistics, Pukyong National University)
  • Received : 2014.10.10
  • Accepted : 2014.11.26
  • Published : 2014.12.31
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Abstract

Despite the D-optimality criterion becomes very popular in designing an experiment for nonlinear models because of theoretical foundations it provides, it is very critical that the criterion depends on the unknown parameters of the nonlinear model. But some nonlinear models turned out to be partially nonlinear in sense that the optimal design depends on the subset of parameters only. It was a strong belief that the maximin approach to find a robust design to protect against the uncertainty of parameters is not guaranteed to be successful in nonlinear models. But the maximin approach could be a success for the partial nonlinear model, because often the optimal design depends on only one unknown value of parameter, easier to handle than the full parameters. We deal with maximin approach for Michaelis-Menten model with respect to D- and $D_s$-optimality.

D-최적 실험은 실험의 이론적인 기초를 제공하는 이유로 비선형모형에 대해 실험설계 시 인기가 있지만 이러한 실험기준은 비선형인 경우 알려져 있지 않은 모수에 의존하는 모순적인 특징이 있다. 그러나 일부 비선형모형은 최적 실험이 비선형 모형의 일부 모수에만 의존하는 특징이 있는 부분비선형모형임 밝혀졌다. 일반적으로 비선형 모형인 경우는 maximin방법은 일반적으로 모수의 불확실성에 강건한 실험을 제공하지 못한다고 알려져 있으나 많은 부분비선형 모형인 경우 하나의 모수에만 최적실험이 의존하는 구조를 갖고 있어 최적실험의 구조를 밝히는데 매우 용이하다. 본 연구에서는 Michaelis-Menten 모형을 대상으로 모수의 불확실성에 대처하기 위한 maximin 방법을 D-최적 및 $D_s$-최적을 기준으로 살펴보았다.

Keywords

References

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