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Optimum designs for parameter estimation in mixture experiments with group synergism

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  • Manisha Pal
  • Nripes Kumar Mandal

Abstract

Mixture models were first introduced in canonical form of different degrees to represent the response function in a mixture experiment, and designs for the same were suggested. Later, several researchers derived optimum designs for the estimation of parameters and subset of parameters of the models. In this article, a study is carried out to find the D- and A-optimum designs for estimating the parameters of the quadratic mixture model, when the components of the mixture can be divided into two groups such that within a group there is synergism among the components, while the components between groups do not exhibit any synergism.

Suggested Citation

  • Manisha Pal & Nripes Kumar Mandal, 2021. "Optimum designs for parameter estimation in mixture experiments with group synergism," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(9), pages 2001-2014, May.
    • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:9:p:2001-2014
    DOI: 10.1080/03610926.2019.1657455
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