THE OPTIMALITY OF PERMUTATION MIXTURE DESIGNS UNDER DIFFERENT $q$-MIXTURE COMPONENTS
Keywords:
log models, mixture components, linear constraints, permutation mixture designs, the theory of optimalityDOI:
https://doi.org/10.17654/0972361723041Abstract
Experiments with mixture settings are conducted in different areas. In such experiments, the response depends on the proportions of the components and not the amount of the mixtures. The need for finding the optimum designs for empirical or mechanistic models under consideration arises. Under optimality procedures, the main researchers’ interest is to allow model’s parameters to be estimated with minimum variance according to some statistical criteria functions. Thus, construction of an optimum design under different scenarios is the basis of the design methodology. In the literature, the special nature of the factors under such experiments necessitates specific types of experimental designs. Apart from illustrated designs for such experiments provided in the literature, the present work constructs and investigates different optimum designs when a permutation process under whether a log model of degree one or two is appropriate incorporating with some pre-chosen statistical criteria functions. Under this study, we assume some different q mixture components. Afterward, we seek for the designs which are optimum under some consideration under different forms of log models.
Received: February 12, 2023
Accepted: March 31, 2023
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