Confidence Intervals for Common Coefficient of Variation of Several Birnbaum–Saunders Distributions
نویسندگان
چکیده
The Birnbaum–Saunders (BS) distribution, also known as the fatigue life is right-skewed and used to model failure times of industrial components. It has received much attention due its attractive properties relationship normal distribution (which symmetric). Furthermore, coefficient variation (CV) commonly analyze within a dataset. In some situations, independent samples are collected from different instruments or laboratories. Consequently, it importance make inference for common CV. To this end, confidence intervals based on generalized interval (GCI), method variance estimates recovery (MOVER), large-sample (LS), Bayesian credible (BayCrI), highest posterior density (HPDI) methods proposed herein estimate CV several BS distributions. Their performances in terms their coverage probabilities average lengths were investigated by using Monte Carlo simulation. simulation results indicate that HPDI-based outperformed others all scenarios. Finally, efficacies illustrated applying them real datasets PM10 (particulate matter ? 10 ?m) concentrations three pollution monitoring stations Chiang Mai, Thailand.
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ژورنال
عنوان ژورنال: Symmetry
سال: 2022
ISSN: ['0865-4824', '2226-1877']
DOI: https://doi.org/10.3390/sym14102101