Bayesian Estimation for the Parameters and Reliability Function of Basic Gompertz Distribution under Squared Log Error Loss Function

Authors

  • Manahel Kh. Awad Department of Mathematics, College of Science, Mustansiriyah University, Baghdad, Iraq
  • Huda A. Rasheed Department of Mathematics, College of Science, Mustansiriyah University, Baghdad, Iraq

DOI:

https://doi.org/10.24996/ijs.2020.61.6.22

Keywords:

Basic Gompertz distribution, Maximum likelihood estimator, Bayes estimator, Squared log error loss function, Reliability function, Mean squared errors

Abstract

In this paper, some estimators for the unknown shape parameters and reliability function of Basic Gompertz distribution were obtained, such as Maximum likelihood estimator and some Bayesian estimators under Squared log error loss function by using Gamma and Jefferys priors. Monte-Carlo simulation was conducted to compare the performance of all estimates of the shape parameter and Reliability function, based on mean squared errors (MSE) and integrated mean squared errors (IMSE's), respectively. Finally, the discussion is provided to illustrate the results that are summarized in tables.

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Published

2020-06-27

How to Cite

Awad, M. K. ., & Rasheed, H. A. . (2020). Bayesian Estimation for the Parameters and Reliability Function of Basic Gompertz Distribution under Squared Log Error Loss Function. Iraqi Journal of Science, 61(6), 1433–1439. https://doi.org/10.24996/ijs.2020.61.6.22

Issue

Section

Mathematics