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Slack-variable models versus Scheffe's mixture models

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  • Andre Khuri

Abstract

Slack-variable models are compared against Scheffe's polynomial model for mixture experiments. The notion of model equivalence and the use of various diagnostic measures provide effective tools in making such comparisons, particularly when the experimental region is highly constrained. It is demonstrated that the choice of the best fitting model, through variable selection, depends on which mixture component is selected as a slack variable, and on the size of the fitted model. In addition, the equivalence of two well-known representations of a complete mixture model is shown to be valid. Two numerical examples are presented.

Suggested Citation

  • Andre Khuri, 2005. "Slack-variable models versus Scheffe's mixture models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(9), pages 887-908.
    • Handle: RePEc:taf:japsta:v:32:y:2005:i:9:p:887-908
    DOI: 10.1080/02664760500163466
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    Cited by:

    1. Javier Cruz-Salgado & Sergio Alonso-Romero & Edgar Augusto Ruelas-Santoyo & Israel Miguel-Andrés & Roxana Zaricell Bautista-López & Amir Hossein Nobil, 2024. "A Numerical Stability Analysis in the Inclusion of an Inverse Term in the Design of Experiments for Mixtures," Mathematics, MDPI, vol. 12(22), pages 1-11, November.

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