A Fuzzy Logic Framework for Testing Vague Hypotheses with Empirical Data

0404538 - UIVT-O 20010165 RIV GB eng C - Konferenční příspěvek (zahraniční konf.)
Holeňa, Martin
A Fuzzy Logic Framework for Testing Vague Hypotheses with Empirical Data.
Soft Computing and Intelligent Systems for Industry. Canada: ICSINAISO Academic Press, 2001, s. -. ISBN 3-906454-27-4.
[SOCO/ISFI 2001. International ICSC Symposium /4./. Paisley (GB), 26.06.2001-29.06.2001]
Grant CEP: GA ČR GA201/00/1489; GA MŠMT OC 274.001
Grant ostatní: COST(XE) Action 274 TARSKI
Výzkumný záměr: AV0Z1030915
Klíčová slova: data analysis * vague hypotheses * vague significance level * fuzzy predicate calculus * basic fuzzy logic * generalized quantifiers * method Guha
Kód oboru RIV: BA - Obecná matematika

Hypothesis testing consists in checking the null hypothesis that the probability distribution, a priori assumed to belong to some broad set of distributions, actually belongs to some its narrow subset, which must be precisely delimited in advance. However, sometimes there are not enough clues for such a precise delimitation, especially if the purpose of the data analysis is explorative. That is when vague hypotheses need to be tested.
Trvalý link: http://hdl.handle.net/11104/0124787