  Information geometry and inductive inference methods can be used to model
dynamical systems in terms of their probabilistic description on curved
statistical manifolds.
  In this article, we present a formal conceptual reexamination of the
information geometric construction of entropic indicators of complexity for
statistical models. Specifically, we present conceptual advances in the
interpretation of the information geometric entropy (IGE), a statistical
indicator of temporal complexity (chaoticity) defined on curved statistical
manifolds underlying the probabilistic dynamics of physical systems.
