Bayesian Estimation for Two Parameters of Gamma Distribution under Generalized Weighted Loss Function

Loaiy F. Naji; Huda A. Rasheed

doi:10.24996/ijs.2019.60.5.24

Bayesian Estimation for Two Parameters of Gamma Distribution under Generalized Weighted Loss Function

Authors

Loaiy F. Naji 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.2019.60.5.24

Keywords:

Gamma distribution, Maximum likelihood estimator, Hessian matrix, Generalized Weighted loss function, Lindleyâ€™s approximation

Abstract

This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindleyâ€™s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSEâ€™s).

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Published

2019-05-26

Issue

Vol. 60 No. 5 (2019)

Section

Mathematics

How to Cite

Bayesian Estimation for Two Parameters of Gamma Distribution under Generalized Weighted Loss Function. (2019). Iraqi Journal of Science, 60(5), 1161-1171. https://doi.org/10.24996/ijs.2019.60.5.24