Estimation of the Parameters of the Lomax Distribution using the EM Algorithm and Lindley Approximation

Abstract

Estimation of statistical distribution parameter is one of the important subject of statistical inference. Due to the applications of Lomax distribution in business, economy, statistical science, queue theory, internet traffic modeling and so on, in this paper, the parameters of Lomax distribution under type II censored samples using maximum likelihood and Bayesian methods are estimated. Whereas, selection of prior distribution and loss function plays an important role in Bayesian estimation, therefore the Bayesian estimations are presented by appropriate prior distribution under loss functions, mean square error, Linex and entropy. Whereas the normal equation obtained from estimation methods are not distinct function of parameters, they are estimated using error methods such as EM algorithm and Lindley approximation. At the end, using mean square error criteria, the estimators are compared and the result shows that the Bayesian estimator is better than the maximum likelihood estimator and the accuracy of estimator improves by increasing the sample number while the number of failure is fixed. ./files/site1/files/42/6Abstract.pdf

Keywords

• em algorithm
• censored data
• lindley approximation
• lomax distribution
• methods of estimation
• mean square error.