In a mixture experiment the collinearity problems, implied by the sum to one functional relationship among the factors, have strong consequences for the identification and analysis of regression models for such designs. Here, to address these problems, mixture designs are represented as sets of homogeneous polynomials. Techniques from computational commutative algebra are employed to deduce generalized confounding relationships on power products and to determine families of identifiable models.

On the description and identifiability analysis of mixture designs

RICCOMAGNO, EVA
2007-01-01

Abstract

In a mixture experiment the collinearity problems, implied by the sum to one functional relationship among the factors, have strong consequences for the identification and analysis of regression models for such designs. Here, to address these problems, mixture designs are represented as sets of homogeneous polynomials. Techniques from computational commutative algebra are employed to deduce generalized confounding relationships on power products and to determine families of identifiable models.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/229652
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