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September 5, 2025Iraqi Journal of Science2 citationsOpen Access

Approximate Estimation Methods for Exponential Rayleigh Distribution

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SAShurooq A.K. Al-SultanyLHLamyaa Khalid Hussein

Key Points

  • Approximate estimators for scale parameters are derived using Modified Maximum Likelihood and Bayesian methods.
  • The study utilizes modified Newton–Raphson method due to the lack of closed-form solutions in Modified Maximum Likelihood.
  • Bayesian estimators are calculated with both symmetric and asymmetric loss functions using Lindley's approximation method.
  • Monte Carlo simulation is employed to compare the performance of the derived estimators effectively.

Abstract

This paper introduces approximate estimators for the scale parameters, reliability, and hazard rate functions of the exponential Rayleigh distribution using Modified Maximum Likelihood and Bayesian method. The Modified Maximum Likelihood estimator requires iterative techniques such as the modified Newton–Raphson method due to the unavailability of closed-form expressions. Bayesian estimators are derived using both symmetric and asymmetric loss functions, and Lindley's approximation method is employed for integrals that lack closed-form solutions. Finally, the estimators obtained are compared through Monte Carlo simulation study.

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Cite This Study

Al-Sultany et al. (2025) studied this question.

synapsesocial.com/papers/68bb46a86d6d5674bccfe4a4https://doi.org/10.24996/ijs.2025.66.8.21
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