Parameters and Reliability Estimation of Extended Exponential Distribution under Typeii Progressive Hybrid Censoring
| المصدر: | مجلة البحوث التجارية |
|---|---|
| الناشر: | جامعة الزقازيق - كلية التجارة |
| المؤلف الرئيسي: | Salem, Samia Aboul Fotouh (Author) |
| مؤلفين آخرين: | Abo-Kasem, Osama Eraki (Co-Author) , Abu Zaid, Asmaa Abdulaziz (Co-Author) |
| المجلد/العدد: | مج45, ع1 |
| محكمة: | نعم |
| الدولة: |
مصر |
| التاريخ الميلادي: |
2023
|
| الشهر: | يناير |
| الصفحات: | 164 - 193 |
| رقم MD: | 1396804 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | EcoLink |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Extended Exponential Distribution | Reliability and Hazard Rate Functions | Bayesian and Non-Bayesian Estimation | MCMC | Type-II Progressive Hybrid Censoring
|
| رابط المحتوى: |
عدد مرات التحميل
1
| المستخلص: |
The estimating problems of the model parameters, reliability and hazard functions of extended exponential distribution used Type-II progressive hybrid censoring scheme (Type-II PHCS) will be considered. The maximum likelihood estimation (MLE) has been obtained for any function of the model parameters. Based on the normality property of the classical estimators, approximate confidence intervals (ACIs) for the unknown parameters and any function of them are constructed. Further, construct the asymptotic confidence interval of the reliability and hazard rate function. Using independent gamma priors, the Bayes estimators of the unknown parameters are derived based on both the symmetric (squared error (SE)) and asymmetric (LINEX) loss functions. Since the Bayes estimators are obtained in a complex form therefore, Markov Chain Monte Carlo (MCMC) using Metropolis-Hastings (MH) algorithm has been used to carry out the Bayes estimates and also to construct the associate highest posterior density credible intervals. To evaluate the performance of the proposed methods, a Monte Carlo simulation study is carried out. Finally, we consider engineering data to illustrate the applicability of the methods covered in the paper. |
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