Parameter Estimation and Stress-Strength Model of Power Lomax Distribution: Classical Methods and Bayesian Estimation

Journal of Data Science

article

Ehab M. Almetwally¹  Hisham. M. Almongy² 

[1] Faculty of Business Administration, Delta University of Science and Technology;Faculty of Commerce, Mansoura University

关键词: Bayesian estimation;    Cramér–von Mises;    maximum likelihood;    maximum product of spacing;    weighted least squares;    stress-strength model;   

DOI  :  10.6339/JDS.202010_18(4).0008

学科分类：土木及结构工程学

来源: JDS

【 摘 要 】

In this paper, parameter estimation for the power Lomax distribution is studied with different methods as maximum likelihood, maximum product spacing, ordinary least squares, weighted least squares, Cramér–von Mises and Bayesian estimation by Markov chain Monte Carlo (MCMC). Robust estimation of the stress-strength model for the Power Lomax distribution is discussed. We propose that the method of maximum product of spacing for reliable estimation of stress-strength model as an alternative method to maximum likelihood and Bayesian estimation methods. A numerical study using real data and Monte Carlo Simulation is performed to compare between different methods.

【 授权许可】

CC BY