Process Variables in the Mixture Problem for Categorized Components

John A. Cornell

31 citations0/0 files storedJournal of the American Statistical Association

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Optimal Experimental Design Methods Statistical Methods and Applications Bayesian Methods and Mixture Models

Abstract

A method is presented for the design of experiments and the fitting of polynomial models where the experimentation involves not only mixture components but process variables as well. The experimentation is performed in a region of operation comprised of an ellipsoidal region in the mixture components and an ndimensional rectangular region in the process variables. The designs discussed are standard designs for factorial experiments.

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References

1957Multi-Factor Experimental Designs for Exploring Response Surfaces 1958Experiments with Mixtures 1959A Basis for the Selection of a Response Surface Design 1963The Simplex-Centroid Design for Experiments with Mixtures 1961The 2k—pFractional Factorial Designs 2000The 2 k-p Fractional Factorial Designs Part I 1961The 2 k-p Fractional Factorial Designs Part I 1962Simplex Lattice Designs for Multicomponent Systems

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