Forthcoming

Estimating the Parameters of Burr Type XII Distribution with Fuzzy Observations

Accepted - January 2022

Authors

Keywords:

Bayesian estimation, Burr type XII distribution, expectation-maximization algorithm, fuzzy observations, Lindley’s approximation, maximum likelihood estimation, Tierney-Kadane approximation

Abstract

In this article, the classical as well as the Bayesian estimation problems of two-parameter Burr type XII distribution based on fuzzy data are considered. The maximum likelihood estimators via two methods, namely, Newton-Raphson and Expectation-Maximization algorithms are computed. The standard errors of the estimates are computed using the observed information matrix. For computing the Bayes estimators, three methods viz Lindley’s approximation, Tierney-Kadane approximation and highest posterior density method are obtained. Monte-Carlo simulation experiments are conducted to investigate the performance of the proposed methods. Finally, the proposed methods are illustrated by using three different real data sets.

Published

2022-01-19

How to Cite

Abdul Hussein , A., & Al-Mosawi , R. (2022). Estimating the Parameters of Burr Type XII Distribution with Fuzzy Observations: Accepted - January 2022. REVSTAT-Statistical Journal. Retrieved from https://revstat.ine.pt/index.php/REVSTAT/article/view/174

Issue

Section

Forthcoming Paper