Skip to main content
Article thumbnail
Location of Repository

Dynamics of the Fisher Information Metric

By Xavier Calmet and Jacques Calmet


We present a method to generate probability distributions that correspond to metrics obeying partial differential equations generated by extremizing a functional J[g µν (θ i)], where g µν (θ i) is the Fisher metric. We postulate that this functional of the dynamical variable g µν (θ i) is stationary with respect to small variations of these variables. Our approach enables a dynamical approach to Fisher information metric. It allows to impose symmetries on a statistical system in a systematic way. This work is mainly motivated by the entropy approach to nonmonotonic reasoning

Year: 2004
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • (external link)
  • (external link)
  • Suggested articles

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.