Revistes Publicacions URV: SORT - Statistics and Operations Research Transactions> 2018

Evidence functions: a compositional approach to information

  • Identification data

    Identifier: RP:3068
    Handle: http://hdl.handle.net/20.500.11797/RP3068
  • Authors:

    Pawlowsky-Glahn, Vera
    Egozcue, Juan-José
  • Others:

    URV's Author/s: Pawlowsky-Glahn, Vera Egozcue, Juan-José
    Keywords: Evidence function, Bayes’ formula, Aitchison geometry, compositions, orthonormal basis, simplex, scalar information
    Abstract: The discrete case of Bayes’ formula is considered the paradigm of information acquisition. Prior and posterior probability functions, as well as likelihood functions, called evidence functions, are compositions following the Aitchison geometry of the simplex, and have thus vector character. Bayes’ formula becomes a vector addition. The Aitchison norm of an evidence function is introduced as a scalar measurement of information. A fictitious fire scenario serves as illustration. Two different inspections of affected houses are considered. Two questions are addressed: (a) which is the information provided by the outcomes of inspections, and (b) which is the most informative inspection.
    Journal publication year: 2018
    Publication Type: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article
  • Keywords:

    Evidence function, Bayes’ formula, Aitchison geometry, compositions, orthonormal basis, simplex, scalar information
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