Name
Abstract | ||
|---|---|---|
A new approach for testing fuzzy parametric hypotheses based on fuzzy test statistic is introduced. First, we define some models representing the extended versions of the simple, the one-sided and the two-sided crisp hypotheses to the fuzzy ones. Then, we provide a confidence interval for interested parameter, and using α-cuts of the fuzzy null hypothesis, we construct the related fuzzy test statistic. Finally, by introducing a credit level, we can decide to accept or reject the fuzzy hypothesis. The method is applied to test the fuzzy hypotheses for the mean of a normal distribution, the variance of a normal distribution, and the mean of a Poisson distribution. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s00500-008-0339-3 | Soft Comput. |
Keywords | Field | DocType |
Credit level,Fuzzy hypothesis,Fuzzy test statistic,Testing hypothesis | Test statistic,F-test,p-value,Fuzzy logic,Fuzzy measure theory,One- and two-tailed tests,Z-test,Statistics,Membership function,Mathematics | Journal |
Volume | Issue | ISSN |
13 | 6 | 1432-7643 |
Citations | PageRank | References |
18 | 1.00 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| S. Mahmoud Taheri | 1 | 90 | 10.84 |
| Mohsen Arefi | 2 | 24 | 3.82 |