Three and Four Component R-, A- and D-optimal Allocations for an Additive Quadratic Mixture Model
Keywords:
Mixture experiments, optimal designs, R-optimal design, A-optimal design, D-optimal designAbstract
Optimal mixture experiments are a powerful tool for systematically exploring and optimizing the composition of mixtures. In this paper, we have presented a new additive quadratic mixture model and have obtained R-, A- and D-optimal allocations for three and four component mixtures. The obtained designs have been checked for optimality using the equivalence theorem.
References
Becker NG. Models for the response of a mixture. J Roy Stat Soc B Met. 1968; 30(2): 349-358.
Cornell JA. Experiments with mixtures: Designs, models, and the analysis of mixture data. 3rd ed. New York: Wiley; 2002.
Darroch JN, Waller J. Additivity and interaction in three-component experiments with mixtures. Biometrika. 1985; 72(1): 153-163.
Dette H. Designing experiments with respect to ‘standardized’optimality criteria. J Roy Stat Soc B. 1997;59(1): 97-110.
Draper NR, Pukelsheim F. Mixture models based on homogeneous polynomials. J Stat Plan Infer. 1998; 71(1-2): 303-311.
Husain B, Parveen S. F-Square based four component D-, A-and E-optimal orthogonal designs for an additive quadratic mixture model. J Indian Soc Probab Stat. 2016; 17(1): 95-109.
Scheffé H. Experiments with mixtures. J Roy Stat Soc B Met. 1958; 20(2): 344-360.
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
