Fuzzy Hypotheses Testing by Vague Response Data with Reflected Correlation

Testing fuzzy hypotheses with vague data

The problem of testing fuzzy hypotheses in the presence of vague data is considered. A new method based on the necessity index of strict dominance (NSD) is suggested. An example hoe to apply the proposed test in statistical quality control is shown.

Fuzzy decision in testing hypotheses by fuzzy data: Two case studies

In testing hypotheses, we may confront with cases where data are recorded as non-precise (fuzzy) rather than crisp. In such situations, the classical methods of testing hypotheses are not capable and need to be generalized. In solving the problem of testing hypotheses based on fuzzy data, the fuzziness of the observed data leads to the fuzzy p-value. This paper has been focused to calculate fuz...

Sequential Probability Ratio Test for Fuzzy Hypotheses Testing with Vague Data

The Most Powerful Tests for Fuzzy Hypotheses Testing with Vague Data

In hypotheses testing, such as other statistical problems, we may confront imprecise concepts. One case is a situation in which both hypotheses and observations are imprecise. In this paper, we redefine some concepts about fuzzy hypotheses testing, and then we give the Neyman-Pearson lemma for fuzzy hypotheses testing with fuzzy observations. Finally, we give some applied examples. Mathematics ...

Testing Hypotheses with Fuzzy Data: The Fuzzy p-value

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 o...