Bayesian and Non - Bayesian Inference for Shape Parameter and Reliability Function of Basic Gompertz Distribution

Authors

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

Abstract

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 functionassuming 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

Keywords

Basic Gompertz distribution, MinMSE estimator, MLE, Scale invariant squared error loss function, UMVUE.

Article Type

Article

How to Cite this Article

Kh. Awad, Manahel and A. Rashed, Huda (2020) "Bayesian and Non - Bayesian Inference for Shape Parameter and Reliability Function of Basic Gompertz Distribution," Baghdad Science Journal: Vol. 17: Iss. 3, Article 15.
DOI: https://doi.org/10.21123/bsj.2020.17.3.0854