Research shows R-optimality designs improve confidence regions in linear log contrast models, suggesting enhanced experimental effectiveness.
The R-optimality criterion is proposed in the literature as an alternative to the most frequently used D-optimality criterion. This criterion can be used in the experimental design when the main objective is to construct a rectangular confidence region. The present work investigates the R-optimal designs of the linear log contrast model supported on the general q-mixture components. The necessary and sufficient conditions of R-optimality have been examined by the equivalence theorem.
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Panda et al. (2022) studied this question.
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