On the description and identifiability analysis of experiments with mixtures

In a mixture experiment the collinearity problems, implied by the sum to one functional relationship among the factors, have strong consequences on 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.