Journal of Advanced Statistics

Download PDF (299 KB) PP. 9 - 12 Pub. Date: June 28, 2019

DOI: 10.22606/jas.2019.42001

• Owat Sunanta^*
  Department of Business and Management, Webster Vienna Private University, Vienna, Austria
• Reinhard Viertl
  Institute of Statistics and Mathematical Methods in Economics, Technische Universität Wien, Vienna, Austria

Information and its quality are essential for effective decision making, which often takes into account the statistical knowledge of the condition under consideration. Information in form of collected data from continuous quantities is always uncertain, i.e. more or less fuzzy. However, such data can be further described by so-called fuzzy numbers for better understanding. In applied statistics, a more general form of distributions (so-called fuzzy densities) is suitable to model uncertain stochastic information. The combination of fuzziness and stochastic uncertainty calls for a generalization of mathematical models for decision making. As a result, models must be generalized to handle this situation. This is possible and will be explained via decision model and utility.

Characterizing function, decision model, fuzzy data, fuzzy density, fuzzy information

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