Testing hypotheses with fuzzy data: The fuzzy p-value

Peter Filzmoser and R. Viertl

Metrika: International Journal for Theoretical and Applied Statistics, 2004, vol. 59, issue 1, 29 pages

Abstract: Statistical hypothesis testing is very important for finding decisions in practical problems. Usually, the underlying data are assumed to be precise numbers, but it is much more realistic in general to consider fuzzy values which are non-precise numbers. In this case the test statistic will also yield a non-precise number. This article presents an approach for statistical testing at the basis of fuzzy values by introducing the fuzzy p-value. It turns out that clear decisions can be made outside a certain interval which is determined by the characterizing function of the fuzzy p-values. Copyright Springer-Verlag 2004

Keywords: Fuzzy data; Non-precise numbers; p-value; Hypothesis testing (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:metrik:v:59:y:2004:i:1:p:21-29

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DOI: 10.1007/s001840300269

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