Estimation of the Weibull Distribution Parameters and Reliability Using Kernel and Bayes Approaches

Authors

M. Maswadah, Department of Mathematics, Faculty of Science,Aswan University, Aswan, EgyptFollow
M. Seham, Department of Mathematics, Faculty of Science,Aswan University, Aswan, EgyptFollow

Abstract

A new estimation technique based on the non-parametric kernel density estimation is introduced as an alternative and reliable technique for estimation in life testing models. This technique estimates the density functions of the parameters and reliability directly from the data without any prior assumptions about the underlying distribution parameters. The efficiency of this technique has been studied comparing to the Bayesian estimation of the parameters and reliability of the Weibull distribution based on the non-informative, informative and the informative conjugate priors, via Monte Carlo simulations, which indicated the robustness of the proposed method than the Bayesian approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper.

Recommended Citation

Maswadah, M. and Seham, M. (2023) "Estimation of the Weibull Distribution Parameters and Reliability Using Kernel and Bayes Approaches," Information Sciences Letters: Vol. 12 : Iss. 3 , PP -.
Available at: https://digitalcommons.aaru.edu.jo/isl/vol12/iss3/4