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k ‐sample median test for vague data
Author(s) -
Grzegorzewski Przemysław
Publication year - 2009
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.20345
Subject(s) - generalization , nonparametric statistics , statistical hypothesis testing , mathematics , statistics , test (biology) , sample (material) , computer science , artificial intelligence , paleontology , chemistry , chromatography , biology , mathematical analysis
Classical statistical tests may be sensitive to violations of the fundamental model assumptions inherent in the derivation and construction of these tests. It is obvious that such violations are much more probable in the presence of vague data. Thus nonparametric tests seem to be promising statistical tools. In the present paper, a distribution‐free statistical test for the so‐called “many‐one problem” with vague data is suggested. This test is a generalization of the k ‐sample median test. In our approach, we utilize the necessity index of strict dominance, suggested by Dubois and Prade. © 2009 Wiley Periodicals, Inc.