The Fuzzy Representation of Prior Information for Separating Outliers in Statistical Experiments
The paper presents a new fuzzy set based description which helps to distinguish the expected values of the statistical experiment from the outliers. Since the Neyman-Pearson criterion is not adequate in some real applications for such purpose, we propose to use triangular norms for conjuction of two propositions about typical and non-typical values and describe both of them as a fuzzy set that is called the typical transform. We also investigate such a property of the typical transform as stability.
Keywordsdistortion function triangular norm fuzzy set Neyman-Pearson criterion outliers Lipschitz continuity
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