General Blending Models for Data From Mixture Experiments

Abstract

We propose a new class of models providing a powerful unification and extension of existing statistical methodology for analysis of data obtained in mixture experiments. These models, which integrate models proposed by Scheffé and Becker, extend considerably the range of mixture component effects that may be described. They become complex when the studied phenomenon requires it, but remain simple whenever possible. This article has supplementary material online.

• Becker’s models
• Model selection
• Nonlinear models
• Scheffé polynomials.

ACKNOWLEDGMENTS

We were fortunate to have our article been refereed by an Editor, Associate Editor, and the two referees who understand well the theory and practice of mixture experiments. Their extensive and constructive suggestions were invaluable to us in the revisions of this article.