No Detail Found!

Bayesian and Classical Estimation for the One Parameter Double Lindley Model

Author(s)
Mohamed Ibrahim Department of Applied Statistics and Insurance, Faculty of Commerce, Damietta University, Damietta, Egypt
Wahhab Salim Mohammed Department of Statistics, College of Administration and Economics, Diyala University, Iraq
Haitham M. Yousof Department of Statistics, Mathematics and Insurance, Benha University, Benha, Egypt
Abstract
The main motivation of this paper is to show how the different frequentist estimators of the new distribution perform for different sample sizes and different parameter values and to raise a guideline in choosing the best estimation method for the new model. The unknown parameters of the new distribution are estimated using the maximum likelihood method, ordinary least squares method, weighted least squares method, Cramer-Von-Mises method and Bayesian method. The obtained estimators are compared using Markov Chain Monte Carlo simulations and we observed that Bayesian estimators are more efficient compared to other the estimators.
Publication Details
Page(s) 409-420
DOI 10.18187/pjsor.v16i3.2966
Published Journal: Pakistan Journal of Statistics and Operation Research, Volume: 16, Issue: 3, Year: 2020

Request the full text from PASTIC

Keywords
Clayton Copula, Bayesian estimation, Markov Chain Monte Carlo Simulations, Different Method of Estimations, Farlie Gumbel Morgenstern copula, Renyi's entropy copula
More from Pakistan Journal of Statistics and Operation Research
0

Citations

0

Downloads

38

Views

Copyright ©  PASTIC National Center, Islamabad www.pastic.gov.pk