Bayesian Estimation of The unknown parameter of Inverse Rayleigh Distribution (IRD) based on GELF

Jinan A. Naser Al-obedy

doi:10.30526/37.3.3294

PDF

Published: Jul 20, 2024

DOI: https://doi.org/10.30526/37.3.3294

Keywords:

The inverse Rayleigh distribution, MLE, Bayes estimation, GELF, MSE

Jinan A. Naser Al-obedy

Department of Quality Management Techniques, Technical College of Management-Baghdad, Middle Technical University, Baghdad, Iraq.

https://orcid.org/0000-0001-8486-3273

Abstract

In this paper, we investigated the Bayesian estimation of the unknown parameter of the Inverse Rayleigh Distribution (IRD) under different priors, represented by the inverse gamma distribution, the inverse chi-squared distribution, and the standard Levy distribution as priors. We obtained the posterior distributions for the unknown parameter of IRD under the different priors based on the general entropy loss function (GELF). We assumed different values for the shape parameter of GELF. Also, the maximum likelihood estimator (MLE) is used to estimate the scale parameter of IRD. Then, a study is conducted to obtain the results, based on the different parameters of Inverse Rayleigh distribution and sample sizes. We found that Bayes estimators perform better than MLE according to the least mean square error (MSE) Criterion

How to Cite

[1]

Al-obedy, J.A.N. 2024. Bayesian Estimation of The unknown parameter of Inverse Rayleigh Distribution (IRD) based on GELF. Ibn AL-Haitham Journal For Pure and Applied Sciences. 37, 3 (Jul. 2024), 354–368. DOI:https://doi.org/10.30526/37.3.3294.

Issue

Vol. 37 No. 3 (2024)

Section

Mathematics

This work is licensed under a Creative Commons Attribution 4.0 International License.

licenseTerms

Publication Dates

Received

2023-02-25

Accepted

2023-03-30

Published Online First

2023-07-20

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