Parameters and Reliability Estimation of Alpha Power Exponential Distribution under Type-II Progressive Hybrid Censoring with Applications of Engineering and Management Fields
| المصدر: | مجلة البحوث التجارية |
|---|---|
| الناشر: | جامعة الزقازيق - كلية التجارة |
| المؤلف الرئيسي: | Abo-Kasem, Osama Eraki (Author) |
| مؤلفين آخرين: | Elhadidy, Omnia Ibrahim Abdelrhman Ali (Co-Author) |
| المجلد/العدد: | مج45, ع2 |
| محكمة: | نعم |
| الدولة: |
مصر |
| التاريخ الميلادي: |
2023
|
| الشهر: | أبريل |
| الصفحات: | 171 - 208 |
| ISSN: |
1110-7731 |
| رقم MD: | 1531045 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | EcoLink |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Maximum Likelihood | Alpha Power Exponential Distribution | Type-II Progressive Hybrid Censoring | Bayesian Estimations
|
| رابط المحتوى: |
عدد مرات التحميل
1
| المستخلص: |
The mixture of Type-I and Type-II censoring schemes, called the hybrid censoring scheme (HCS) is quite common in life testing or reliability experiments. Recently Type-II progressive censoring scheme (Type-II PCS) becomes quite popular for analyzing highly reliable data. One drawback of the Type-II PCS is that the length of the experiment can be quite large. In this paper we introduce the estimating problems of the unknown parameters of alpha power exponential distribution (APED) using Type-II progressive hybrid censoring scheme (Type-II PCS) will be considered. The maximum likelihood estimation (MLE) and Bayesian estimations of the unknown parameters based on both squared error loss (SE) and LINEX loss functions are obtained. We propose to apply the Markov Chain Monte Carlo (MCMC) technique to carry out a Bayes estimation procedure. The approximate and credible confidence intervals for the unknown parameters are obtained. Also, we introduced the estimating problems of reliability and hazard rate function of the APED under Type-II PHCS and the corresponding approximate confidence intervals. Finally, all the theoretical results obtained are assessed and compared using two real datasets, coming from engineering and management fields. |
|---|---|
| ISSN: |
1110-7731 |
عناصر مشابهة
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