• Medientyp: E-Artikel
  • Titel: Considering distance measures in Statistics
  • Beteiligte: Kitsos, Christos P.; Nisiotis, Constantinos-Symeon
  • Erschienen: Walter de Gruyter GmbH, 2022
  • Erschienen in: Biometrical Letters
  • Sprache: Englisch
  • DOI: 10.2478/bile-2022-0006
  • ISSN: 2199-577X
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:title>Summary</jats:title> <jats:p>The target of this paper is to offer a compact review of the so called distance methods in Statistics, which cover all the known estimation methods. Based on this fact we propose a new step, to adopt from Information Theory, the divergence measures, as distance methods, to compare two distributions, and not only to investigate if the means or the variances of the distributions are equal. Some useful results towards this line of thought are presented, adopting a compact form for all known divergence measures, and are appropriately analyzed for Biometrical, and not only, applications.</jats:p>