• DocumentCode
    3021933
  • Title

    The principle of possibility maximum specificity as a basis for measurement uncertainty expression

  • Author

    Mauris, Gilles

  • Author_Institution
    LISTIC, Univ. de Savoie, Annecy Le Vieux, France
  • fYear
    2009
  • fDate
    6-7 July 2009
  • Firstpage
    5
  • Lastpage
    9
  • Abstract
    This paper deals with the foundations of a possibility/fuzzy expression of measurement uncertainty. Indeed the notion of possibility distribution is clearly identified to a family of probability distributions whose coverage intervals are included in the level cuts of the possibility distribution Thus the fuzzy inclusion ordering, dubbed specificity ordering, constitutes the basis of a maximal specificity principle. The latter is sounder than the maximal entropy principle to deal with cases of partial or incomplete information in a measurement context. The two approaches can be compared on some common practical measurement cases thanks to the respective coverage intervals they provide.
  • Keywords
    maximum entropy methods; measurement uncertainty; statistical distributions; measurement uncertainty expression; possibility maximum specificity; probability distributions; Constraint theory; Entropy; Gaussian distribution; Measurement uncertainty; Possibility theory; Probability density function; Probability distribution; Testing; coverage intervals; maximum entropy principle; maximum specificity principle; measurement uncertainty; possibility theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Methods for Uncertainty Estimation in Measurement, 2009. AMUEM 2009. IEEE International Workshop on
  • Conference_Location
    Bucharest
  • Print_ISBN
    978-1-4244-3593-7
  • Electronic_ISBN
    978-1-4244-3593-7
  • Type

    conf

  • DOI
    10.1109/AMUEM.2009.5207599
  • Filename
    5207599