IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v496y2018icp384-398.html
   My bibliography  Save this article

Towards an information geometric characterization/classification of complex systems. I. Use of generalized entropies

Author

Listed:
  • Ghikas, Demetris P.K.
  • Oikonomou, Fotios D.

Abstract

Using the generalized entropies which depend on two parameters we propose a set of quantitative characteristics derived from the Information Geometry based on these entropies. Our aim, at this stage, is to construct first some fundamental geometric objects which will be used in the development of our geometrical framework. We first establish the existence of a two-parameter family of probability distributions. Then using this family we derive the associated metric and we state a generalized Cramer–Rao Inequality. This gives a first two-parameter classification of complex systems. Finally computing the scalar curvature of the information manifold we obtain a further discrimination of the corresponding classes. Our analysis is based on the two-parameter family of generalized entropies of Hanel and Thurner (2011).

Suggested Citation

  • Ghikas, Demetris P.K. & Oikonomou, Fotios D., 2018. "Towards an information geometric characterization/classification of complex systems. I. Use of generalized entropies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 384-398.
  • Handle: RePEc:eee:phsmap:v:496:y:2018:i:c:p:384-398
    DOI: 10.1016/j.physa.2017.12.069
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117313183
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2017.12.069?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. López-Picón, J.L. & López-Vega, J. Manuel, 2021. "Information geometry for the strongly degenerate ideal Bose–Einstein fluid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:496:y:2018:i:c:p:384-398. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.