In traditional statistics all parameters of the mathematical model and possible observations should be well defined. Sometimes such assumption appears too rigid for the real-life problems, especially while dealing with linguistic data or imprecise requirements. To relax this rigidity fuzzy methods are incorporated into statistics. We review hitherto existing achievements in testing statistical hypotheses in fuzzy environment, point out their advantages or disadvantages and practical problems. We propose also a formalization of that decision problem and indicate the directions of further investigations in order to construct a more general theory.
@article{urn:eudml:doc:39109,
title = {Testing statistical hypotheses in fuzzy environment.},
journal = {Mathware and Soft Computing},
volume = {4},
year = {1997},
pages = {203-217},
zbl = {0893.68139},
language = {en},
url = {http://dml.mathdoc.fr/item/urn:eudml:doc:39109}
}
Grzegorzewski, Przemyslaw; Hryniewicz, Olgierd. Testing statistical hypotheses in fuzzy environment.. Mathware and Soft Computing, Tome 4 (1997) pp. 203-217. http://gdmltest.u-ga.fr/item/urn:eudml:doc:39109/