Jordan algebras, generating pivot variables and orthogonal normal models

Jordan algebras are used to present normal orthogonal models in a canonical form. It is shown that the usual factor based formulation of such models may, many times, be obtained imposing restrictions on the parameters of the canonical formulation, and examples are presented. The canonical model formulation is interesting since it leads to complete sufficient statistics. These statistics may be used to obtain pivot variables that induce probability measures in the parameter space. Monte Carlo generated samples, of arbitrary size, may be obtained having the induced probability measures. These samples may be screened so that the restrictions corresponding to the direct model formulations hold. Inference is presented using such samples.