Work

Evaluating the Performance of Bayesian Estimates for Burr XII Inverse Rayleigh Parameters Using MCMC

Year: 2025

Type: article

Abstract: This work applied multiple Bayesian approaches to estimate the parameters of the Burr XII Inverse Rayleigh (BXII-IR) Distribution. For Bayesian estimators, needed priors distribution for the parameters and certain loss functions such squared error, general entropy, and linear-exponential, owing to the unavailability of closed-form solutions for Bayesian estimates with these loss functions. Bayesian estimate employing the Markov Chain Monte Carlo (MCMC) approach were assessed for performance. The simulation results for Bayesian methods indicate that all methods consistently estimate the parameters, with the LN2 loss function estimator demonstrating the highest efficiency as assessed by mean squared error (MSE), root mean squared error (RMSE), bias, Highest Posterior Density Intervals (HPD), average interval length (AIL), and coverage probability (CP).

Source: Iraqi statisticians journal.

DOI: 10.62933/z56q8971

Authors: Alaa A. Khalaf, Mundher A. Khaleel, Danial Mazarei, Ahlam H. Tolba, Akeem A. Adepoju

Institutions: Ministry of Education, University of Tikrit, Persian Gulf University, Mansoura University

Language: English

Topic: Statistical Distribution Estimation and Applications

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4412705143

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