Performance of Parametric Bayesian Methods for Estimating the Survivor Function in Uncensored Data Using Monte-Carlo Simulation
| المصدر: | المجلة العالمية للاقتصاد والأعمال |
|---|---|
| الناشر: | مركز رفاد للدراسات والأبحاث |
| المؤلف الرئيسي: | Hassan, Mohammed El-Amin (Author) |
| مؤلفين آخرين: | Musa, Fakhereldeen Elhaj Esmial (Co-Author) |
| المجلد/العدد: | مج11, ع3 |
| محكمة: | نعم |
| الدولة: |
الأردن |
| التاريخ الميلادي: |
2021
|
| الشهر: | ديسمبر |
| الصفحات: | 430 - 436 |
| ISSN: |
2519-9285 |
| رقم MD: | 1224891 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | EcoLink |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Bayesian Method | Parametric | Monte Carlo Simulation | Survivor Function | Censoring | Maximum Likelihood Method
|
| رابط المحتوى: |
عدد مرات التحميل
1
| المستخلص: |
The paper aimed to investigate the performance of some parametric survivor function estimators based on Bayesian methodology with respect to bias and efficiency. A simulation was conducted based on Mote Carlo experiments with different sample sizes different (10, 30, 50, 75, 100). The bias and variance of mean square Error V(MSE) were selected as the basis of comparison. The methods of estimation used in this study are Maximum Likelihood, Bayesian with exponential as prior distribution and Bayesian with gamma as prior distribution. A Monte Carlo Simulation study showed that the Bayesian method with gamma as prior distribution was the best performance than the other methods. The study recommended that. |
|---|---|
| ISSN: |
2519-9285 |
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