Abstract
AbstractThis chapter examines the optimum designs for estimating the optimum mixing proportions in Scheffé’s quadratic mixture model with respect to the A-optimality criterion. By optimum mixing proportion, we refer to the one that maximizes the mean response. Since the dispersion matrix of the estimate depends on the unknown model parameters, a pseudo-Bayesian approach is used in defining the optimality criterion. The optimum designs under this criterion have been obtained for two- and three-component mixtures. Further, using Kiefer’s equivalence theorem, it has been shown that under invariant assumption on prior moments, the optimum design for a \(q\)-component mixture is a \((q, 2)\) simplex lattice design for \(q = 3, 4.\) KeywordsScheffé’s quadratic mixture modelEstimation of optimum mixing proportionsTrace criterionPseudo-Bayesian approachInvariance(\(q\), 2)-simplex lattice designKiefer’s equivalence theorem
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.