This study focuses on estimating the stress-strength parameter R, utilizing two independent Type-I progressively hybrid censored samples derived from populations governed by the proportional hazard rate model. The maximum likelihood and Bayes estimators are obtained under some well-known loss functions and the assumption that the priors are independently gamma-distributed. The asymptotic confidence interval and Bayesian and highest posterior density credible intervals are also presented. A Monte Carlo simulation study is used to evaluate the performances of the obtained point estimators and confidence and credible intervals. Finally, a pair of real data sets is analyzed for illustrative purposes.
Estabraqi, J. and Nadeb, H. (2024). Stress-strength reliability of the proportional hazard rate models under Type-I progressively hybrid censored samples. Journal of Statistical Modelling: Theory and Applications, 5(1), 181-202. doi: 10.22034/jsmta.2025.22030.1151
MLA
Estabraqi, J. , and Nadeb, H. . "Stress-strength reliability of the proportional hazard rate models under Type-I progressively hybrid censored samples", Journal of Statistical Modelling: Theory and Applications, 5, 1, 2024, 181-202. doi: 10.22034/jsmta.2025.22030.1151
HARVARD
Estabraqi, J., Nadeb, H. (2024). 'Stress-strength reliability of the proportional hazard rate models under Type-I progressively hybrid censored samples', Journal of Statistical Modelling: Theory and Applications, 5(1), pp. 181-202. doi: 10.22034/jsmta.2025.22030.1151
CHICAGO
J. Estabraqi and H. Nadeb, "Stress-strength reliability of the proportional hazard rate models under Type-I progressively hybrid censored samples," Journal of Statistical Modelling: Theory and Applications, 5 1 (2024): 181-202, doi: 10.22034/jsmta.2025.22030.1151
VANCOUVER
Estabraqi, J., Nadeb, H. Stress-strength reliability of the proportional hazard rate models under Type-I progressively hybrid censored samples. Journal of Statistical Modelling: Theory and Applications, 2024; 5(1): 181-202. doi: 10.22034/jsmta.2025.22030.1151