Estimating the Parameters of Burr Type XII Distribution with Fuzzy Observations

• Autor(a) principal: Abdul Hussein , Abbas
• Data de Publicação: 2023
• Outros Autores: Al-Mosawi , Riyadh
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.57805/revstat.v21i3.174
• topic: Bayesian estimation; Burr type XII distribution; expectation-maximization algorithm; fuzzy observations; Lindley’s approximation; maximum likelihood estimation; Tierney-Kadane approximation

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.