Bayesian and Non - Bayesian Inference for Shape Parameter and Reliability Function of Basic Gompertz Distribution
In this paper, some estimators of the unknown shape parameter and reliability function of Basic Gompertz distribution (BGD) have been obtained, such as MLE, UMVUE, and MINMSE, in addition to estimating Bayesian estimators under Scale invariant squared error loss function assuming informative prior...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Baghdad, College of Science for Women
2020-07-01
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| Series: | مجلة بغداد للعلوم |
| Subjects: | |
| Online Access: | http://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/3801 |
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| Summary: | In this paper, some estimators of the unknown shape parameter and reliability function of Basic Gompertz distribution (BGD) have been obtained, such as MLE, UMVUE, and MINMSE, in addition to estimating Bayesian estimators under Scale invariant squared error loss function assuming informative prior represented by Gamma distribution and non-informative prior by using Jefferys prior. Using Monte Carlo simulation method, these estimators of the shape parameter and R(t), have been compared based on mean squared errors and integrated mean squared, respectively |
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| ISSN: | 2078-8665 2411-7986 |