Bayesian Inference for the Parameter and Reliability Function of Basic Gompertz Distribution under Precautionary loss Function

     In this paper, some estimators for the unknown shape parameter and reliability function of Basic Gompertz distribution have been obtained, such as Maximum likelihood estimator and Bayesian estimators under Precautionary loss function using Gamma prior and Jefferys prior. Monte-Carlo simulation...

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Main Authors: Manahel Kh. Awad, Huda A. Rasheed
Format: Article
Language:English
Published: University of Baghdad 2020-04-01
Series:Ibn Al-Haitham Journal for Pure and Applied Sciences
Subjects:
Online Access:https://jih.uobaghdad.edu.iq/index.php/j/article/view/2435
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author Manahel Kh. Awad
Huda A. Rasheed
author_facet Manahel Kh. Awad
Huda A. Rasheed
author_sort Manahel Kh. Awad
collection DOAJ
description      In this paper, some estimators for the unknown shape parameter and reliability function of Basic Gompertz distribution have been obtained, such as Maximum likelihood estimator and Bayesian estimators under Precautionary loss function using Gamma prior and Jefferys prior. Monte-Carlo simulation is conducted to compare mean squared errors (MSE) for all these estimators for the shape parameter and integrated mean squared error (IMSE's) for comparing the performance of the Reliability estimators. Finally, the discussion is provided to illustrate the results that summarized in tables.
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spelling doaj.art-062dbdfe9d114f29a6707c50fb2282172022-12-22T00:12:39ZengUniversity of BaghdadIbn Al-Haitham Journal for Pure and Applied Sciences1609-40422521-34072020-04-0133210.30526/33.2.2435Bayesian Inference for the Parameter and Reliability Function of Basic Gompertz Distribution under Precautionary loss FunctionManahel Kh. AwadHuda A. Rasheed      In this paper, some estimators for the unknown shape parameter and reliability function of Basic Gompertz distribution have been obtained, such as Maximum likelihood estimator and Bayesian estimators under Precautionary loss function using Gamma prior and Jefferys prior. Monte-Carlo simulation is conducted to compare mean squared errors (MSE) for all these estimators for the shape parameter and integrated mean squared error (IMSE's) for comparing the performance of the Reliability estimators. Finally, the discussion is provided to illustrate the results that summarized in tables. https://jih.uobaghdad.edu.iq/index.php/j/article/view/2435Basic Gompertz distribution, Maximum likelihood estimator, Bayes estimator, Precautionary loss function, Mean squared errors.
spellingShingle Manahel Kh. Awad
Huda A. Rasheed
Bayesian Inference for the Parameter and Reliability Function of Basic Gompertz Distribution under Precautionary loss Function
Ibn Al-Haitham Journal for Pure and Applied Sciences
Basic Gompertz distribution, Maximum likelihood estimator, Bayes estimator, Precautionary loss function, Mean squared errors.
title Bayesian Inference for the Parameter and Reliability Function of Basic Gompertz Distribution under Precautionary loss Function
title_full Bayesian Inference for the Parameter and Reliability Function of Basic Gompertz Distribution under Precautionary loss Function
title_fullStr Bayesian Inference for the Parameter and Reliability Function of Basic Gompertz Distribution under Precautionary loss Function
title_full_unstemmed Bayesian Inference for the Parameter and Reliability Function of Basic Gompertz Distribution under Precautionary loss Function
title_short Bayesian Inference for the Parameter and Reliability Function of Basic Gompertz Distribution under Precautionary loss Function
title_sort bayesian inference for the parameter and reliability function of basic gompertz distribution under precautionary loss function
topic Basic Gompertz distribution, Maximum likelihood estimator, Bayes estimator, Precautionary loss function, Mean squared errors.
url https://jih.uobaghdad.edu.iq/index.php/j/article/view/2435
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AT hudaarasheed bayesianinferencefortheparameterandreliabilityfunctionofbasicgompertzdistributionunderprecautionarylossfunction