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

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Manahel Kh. Awad Huda A. Rasheed

Abstract

     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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How to Cite
AWAD, Manahel Kh.; RASHEED, Huda A.. Bayesian Inference for the Parameter and Reliability Function of Basic Gompertz Distribution under Precautionary loss Function. Ibn AL- Haitham Journal For Pure and Applied Science, [S.l.], v. 33, n. 2, p. 140-148, apr. 2020. ISSN 2521-3407. Available at: <http://jih.uobaghdad.edu.iq/index.php/j/article/view/2435>. Date accessed: 28 may 2020. doi: http://dx.doi.org/10.30526/33.2.2435.
Section
mathematics