Compare Some Shrinkage Bayesian Estimators for Kumaraswamy Distribution with Simulation
DOI:
https://doi.org/10.62933/615r0s12Keywords:
Kumaraswamy distribution, , parameter estimation, , MLE, , Shrinkage Bayesian Estimators,, square loss function, , LINEX loss function,, Simulation Experiments, , Mean Square Error.Abstract
The Kumaraswamy distribution, a flexible probability distribution with wide applications in various fields, has attracted significant attention in statistical research.
This study focuses on the comparison of shrinkage Bayesian estimators for the parameters of the Kumaraswamy distribution through simulations experiments.We explore and evaluate different shrinkage Bayesian estimation methods, aiming to enhance the accuracy and efficiency of parameter estimation for the Kumaraswamy distribution with deffrent loss functions. Through a comprehensive simulation study, we assess the performance of these estimators in terms of mean squared error under varying sample sizes and parameter values .Our findings provide valuable insights into the robustness and efficiency of the considered shrinkage Bayesian estimators for the Kumaraswamy distribution. The simulation results contribute to the understanding of the efficiency, aiding practitioners in choosing appropriate estimation methods for specific scenarios. Additionally, the study discusses the implications of these findings for real-world applications where the Kumaraswamy distribution is commonly employed.
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