IDEAS home Printed from https://ideas.repec.org/a/srs/jtpref/v8y2017i1p31-46.html
   My bibliography  Save this article

Fuzziness And Statistics – Mathematical Models For Uncertainty

Author

Listed:
  • Owat SUNANTA

    (Institute of Statistics and Mathematical Methods in Economics, Technische Universität Wien, Austria)

  • Reinhard VIERTL

    (Institute of Statistics and Mathematical Methods in Economics, Technische Universität Wien, Austria)

Abstract

Real data from continuous quantities, considered under different models in economic theory, cannot be measured precisely. As a result, measurement results cannot be accurately represented by real numbers, as they contain different kinds of uncertainty. Beside errors and variability, individual measurement results are more or less fuzzy as well. Therefore, real data have to be described mathematically in an adequate way. The best up-to-date models for this are so-called fuzzy numbers, which are special fuzzy subsets of the set of real numbers. Based on this description, statistical analysis methods must be generalized to the situation of fuzzy data. This is possible and will be explained here for descriptive statistics, inferential statistics, objective statistics, and Bayesian inference.

Suggested Citation

  • Owat SUNANTA & Reinhard VIERTL, 2017. "Fuzziness And Statistics – Mathematical Models For Uncertainty," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 8(1), pages 31-46.
    • Handle: RePEc:srs:jtpref:v:8:y:2017:i:1:p:31-46
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    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:srs:jtpref:v:8:y:2017:i:1:p:31-46. 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: Claudiu Popirlan (email available below). General contact details of provider: http://journals.aserspublishing.eu/tpref .

    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.