Volume 4, Issue 2 (Vol. 4, No. 2 2018)                   mmr 2018, 4(2): 201-210 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Zaman R, Nasiri P. Estimation of the Parameters of the Lomax Distribution using the EM Algorithm and Lindley Approximation. mmr 2018; 4 (2) :201-210
URL: http://mmr.khu.ac.ir/article-1-2651-en.html
1- Faculty of Mathematical Sciences and Statistics, Payame Noor University, Tehran, Iran
Abstract:   (2768 Views)

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  

Full-Text [PDF 485 kb]   (1153 Downloads)    
Type of Study: Original Manuscript | Subject: stat
Received: 2017/07/14 | Revised: 2019/08/27 | Accepted: 2018/02/19 | Published: 2019/01/14 | ePublished: 2019/01/14

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Mathematical Researches

Designed & Developed by : Yektaweb