Inferences on the means of two log-normal distributions: a computational approach test. (English) Zbl 1327.62088
Summary: In this article, we propose a novel approach for testing the equality of two log-normal populations using a computational approach test (CAT) that does not require explicit knowledge of the sampling distribution of the test statistic. Simulation studies demonstrate that the proposed approach can perform hypothesis testing with satisfying actual size even at small sample sizes. Overall, it is superior to other existing methods. Also, a CAT is proposed for testing about reliability of two log-normal populations when the means are the same. Simulations show that the actual size of this new approach is close to nominal level and better than the score test. At the end, the proposed methods are illustrated using two examples.
MSC:
| 62F03 | Parametric hypothesis testing |
| 62F30 | Parametric inference under constraints |
| 62F40 | Bootstrap, jackknife and other resampling methods |
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