Please use this identifier to cite or link to this item: http://ir.mu.ac.ke:8080/jspui/handle/123456789/2822
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dc.contributor.authorMwaniki, Wambua Alex-
dc.contributor.authorNjoroge, Elizabeth-
dc.contributor.authorKoske, Joseph-
dc.contributor.authorMutiso, John-
dc.contributor.authorGikonyo, Joseph Kuria-
dc.contributor.authorGitunga, Muriungi Robert-
dc.contributor.authorKipkoech, Cheruiyot-
dc.date.accessioned2020-03-03T09:08:03Z-
dc.date.available2020-03-03T09:08:03Z-
dc.date.issued2017-
dc.identifier.urihttp://ir.mu.ac.ke:8080/jspui/handle/123456789/2822-
dc.description.abstractThe aim of this paper is to investigate some optimal slope mixture designs in the second degree Kronecker model for mixture experiments. The study is restricted to weighted centroid designs, with the second degree Kronecker model. For the selected maximal parameter subsystem in the model, a method is devised for identifying the ingredients ratio that leads to an optimal response. The study also seeks to establish equivalence relations for the existence of optimal designs for the various optimality criteria. To achieve this for the feasible weighted centroid designs the information matrix of the designs is obtained. Derivations of D-, A- and E-optimal weighted centroid designs are then obtained from the information matrix. Basically this would be limited to classical optimality criteria. Results on a quadratic subspace of H-invariant symmetric matrices containing the information matrices involved in the design problem was used to obtain optimal designs for mixture experiments analytically. The discussion is based on Kronecker product algebra which clearly reflects the symmetries of the simplex experimental region.en_US
dc.language.isoenen_US
dc.publisherSciencePGen_US
dc.subjectSlope Mixture designs Kronecker producten_US
dc.subjectOptimal Designsen_US
dc.subjectWeighted Centroid Designsen_US
dc.subjectE-Optimalityen_US
dc.subjectH- invariant Symmetric Matricesen_US
dc.titleOptimal Slope Designs for Second Degree Kronecker Model Mixture Experimentsen_US
dc.typeArticleen_US
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