Sequential Probability Ratio Test for Fuzzy Hypotheses Testing with Vague Data

Sequential Probability Ratio Test for Fuzzy Hypotheses Testing with Vague Data

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.

Sequential Probability Ratio Tests for Fuzzy Hypotheses Testing

In hypotheses testing, such as other statistical problems, we may confront imprecise concepts. One case is a situation in which hypotheses are imprecise. In this paper, we redefine some concepts about fuzzy hypotheses testing, and then we introduce the sequential probability ratio test for fuzzy hypotheses testing. Finally, we give some examples. Mathematics Subject Classification: 03E72, 62F03...

Fuzzy hypothesis testing with vague data using likelihood ratio test

Hypothesis testing is one of the most significant facets of statistical inference, which like other situations in the real world is definitely affected by uncertain conditions. The aim of this paper is to develop hypothesis testing based on likelihood ratio test in fuzzy environment, where it is supposed that both hypotheses under study and sample data are fuzzy. The main idea is to employ Zade...

Generalized Sequential Probability Ratio Test for Separate Families of Hypotheses.

In this paper, we consider the problem of testing two separate families of hypotheses via a generalization of the sequential probability ratio test. In particular, the generalized likelihood ratio statistic is considered and the stopping rule is the first boundary crossing of the generalized likelihood ratio statistic. We show that this sequential test is asymptotically optimal in the sense tha...