Information matrices for non-maximal parameter subsystems for second-degree mixture experiments

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Date
2012-12Author
Kinyanjui, Josphat k.
Koske, Joseph K.
Mutiso, John M.
Cherutich, Mike R.
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Many practical problems are associated with the investigation of mixture of m factors, assumed to influence the response
through the proportions in which they are blended together. More often, the primary concern of the experimenter is to learn
more about the subsystems of interest. This study adopts the second-degree Kronecker model put forward by Draper and
Pukelsheim (1998) to derive the information matrices desired. The parameter subspace of interest in this study is nonmaximal parameter subsystem which is subspace of the full parameter space. This subspace is consistent with the estimability
and feasibility conditions. Information matrices are obtained by employing the Kronecker model approach and applying the
canonical unit vector definitions. Results for fro information matrices for m � 2 ingredients are obtained.