Premium
On the propagation of fuzziness of data
Author(s) -
Schnatter Sylvia
Publication year - 1991
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.3770020209
Subject(s) - statistical inference , object (grammar) , sample space , sample (material) , mathematics , function (biology) , fuzzy logic , computer science , inference , data mining , algorithm , statistics , artificial intelligence , chemistry , chromatography , evolutionary biology , biology
Abstract The object of this paper is to discuss how fuzziness of data is propagated when statistical inference for samples of non‐precise data is carried out. The method of propagation of fuzziness as introduced by Schnatter (1989) is reviewed. This method may be applied to any statistical method which leads to a result that may be expressed as a function f ( x 1 ,…, x n ) of the data x 1 ,…, x n . It is outlined that practical application of this method is equal to determining the images of a family of compact subsets of the sample space under the function f (·). An illustrative example from environmetrics is discussed. The general approach is used to formulate a fuzzy sample mean and a fuzzy valued empirical distribution function.