A categorical-informational approach to the value prediction problem

Authors

  • Gennadii Vyacheslavovich Kondratiev Nizhny Novgorod State Technical University named after R.E. Alekseev, Russia

DOI:

https://doi.org/10.1478/AAPP.912A3

Keywords:

data, multimetric space, fibered category, Lipschitz map, invariance, prediction

Abstract

A non-statistical approach to the problem of estimation of unknown parameters of empirical data is given. It is based on an invariant geometric information associated to the data.

Author Biography

  • Gennadii Vyacheslavovich Kondratiev, Nizhny Novgorod State Technical University named after R.E. Alekseev, Russia
    Professor of the Institute of Radioelectronics and Information Technologies

Downloads

Additional Files

Published

2013-12-14

Issue

Vol. 91 No. 2 (2013)

Section

Articles

License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:
  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).