In this paper, we consider the estimation of the stress-strength reliability of a coherent system. The distributions of stress and strength random variables are the members of a general class of distributions. For a series-parallel system, the reliability of the stress-strength model is estimated using the maximum likelihood estimation, asymptotic confidence interval, uniformly minimum variance unbiased estimation, and Bayes estimation. Also, simulation studies are performed, and two real data sets are analyzed.
Rostami, A., Khanjari Sadegh, M., & Khorashadizadeh, M. (2023). On system reliability estimation in stress-strength setup. Journal of Statistical Modelling: Theory and Applications, 3(1), 103-121. doi: 10.22034/jsmta.2023.19115.1067
MLA
Ali Rostami; Mohammad Khanjari Sadegh; Mohammad Khorashadizadeh. "On system reliability estimation in stress-strength setup". Journal of Statistical Modelling: Theory and Applications, 3, 1, 2023, 103-121. doi: 10.22034/jsmta.2023.19115.1067
HARVARD
Rostami, A., Khanjari Sadegh, M., Khorashadizadeh, M. (2023). 'On system reliability estimation in stress-strength setup', Journal of Statistical Modelling: Theory and Applications, 3(1), pp. 103-121. doi: 10.22034/jsmta.2023.19115.1067
VANCOUVER
Rostami, A., Khanjari Sadegh, M., Khorashadizadeh, M. On system reliability estimation in stress-strength setup. Journal of Statistical Modelling: Theory and Applications, 2023; 3(1): 103-121. doi: 10.22034/jsmta.2023.19115.1067
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