On the Problem of Structure Selection for the Identification of Stationary Stochastic Processes

Abstract

Several "overlapping" but uniquely identifiable parametrizations can usually be fitted to the same multivariate stationary stochastic process. We show that these parametrizations are defined by a finite set of intrinsic invariants, and that they all give the same value to the determinant of the Fisher information matrix.