It is known in the literature that maximum likelihood esti- mation 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 Estima- tion (MLE).
On the Maximum Likelihood Estimator of the Emax Model / G. Aletti, C. May, C. Tommasi (ITALIAN STATISTICAL SOCIETY SERIES ON ADVANCES IN STATISTICS). - In: Methodological and Applied Statistics and Demography II / [a cura di] A. Pollice, P. Mariani. - [s.l] : Springer, 2025. - ISBN 978-3-031-64349-1. - pp. 379-385 (( 52. SIS Bari 2024 [10.1007/978-3-031-64350-7].
On the Maximum Likelihood Estimator of the Emax Model
G. Aletti;C. Tommasi
2025
Abstract
It is known in the literature that maximum likelihood esti- mation 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 Estima- tion (MLE).
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