Publications in Scientific Journals:
O. Sunanta, R. Viertl:
"Fuzzy Models in Regional Statistics";
Journal of the Hungarian Central Statistical Office,
Volume 6
(2016),
No 1 Online ISSN 2064-8243;
104
- 118.
English abstract:
Many regional data are not provided as precise numbers, but they are frequently non-precise (fuzzy). In order to provide realistic statistical information, the imprecision must be described quantitatively. This is po
ssible using special fuzzy subsets of the set of real numbers ℝ, called fuzzy numbers, together with their characterising functions. In this study, the uncertainty of measured
data is highlighted through an example of
environmental data from a regional study. The generalised statistical methods, through the characterising function and the δ-cut, that are suitable for the situations of fuzzy uni- and multivariate data are described. In addition, useful generalised descriptive statistics and predictive models frequently applicable for analysis of fuzzy data in regional studies as well as the concept of fuzzy data in databases are presented.
Keywords:
fuzzy data in regional studies characterising function statistics with fuzzy data fuzz y data in databases
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.15196/RS06106
Created from the Publication Database of the Vienna University of Technology.