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It is known in the literature that maximum likelihood estimation of the Emax model parameters often encounters computational problems. Our contribution provides a new understanding and control of all the experimental situations. In particular, exact MLE for a three-point experimental design is shown, and we identify the two scenarios where the MLE fails. We show that the D-optimal design generally yields a favorable response for the existence of the Maximum Likelihood Estimation (MLE).

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On the Maximum Likelihood Estimator of the Emax Model

  • 会议论文

  • 发表日期：

    2025年

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  • Giacomo Aletti,
  • Caterina May,
  • Chiara Tommasi

摘要

It is known in the literature that maximum likelihood estimation of the Emax model parameters often encounters computational problems. Our contribution provides a new understanding and control of all the experimental situations. In particular, exact MLE for a three-point experimental design is shown, and we identify the two scenarios where the MLE fails. We show that the D-optimal design generally yields a favorable response for the existence of the Maximum Likelihood Estimation (MLE).