期刊名称：Pakistan Journal of Statistics and Operation Research
印刷版ISSN：2220-5810
出版年度：2020
卷号：16
期号：2
页码：357-372
DOI：10.18187/pjsor.v16i2.2442
语种：English
出版社：College of Statistical and Actuarial Sciences
摘要：This paper develops Bayesian estimation and prediction, for a mixture of Weibull and Lomax distributions, in the context of the new life test plan called progressive first failure censored samples. Maximum likelihood estimation and Bayes estimation, under informative and non-informative priors, are obtained using Markov Chain Monte Carlo methods, based on the symmetric square error Loss function and the asymmetric linear exponential (LINEX) and general entropy loss functions. The maximum likelihood estimates and the different Bayes estimates are compared via a Monte Carlo simulation study. Finally, Bayesian prediction intervals for future observations are obtained using a numerical example.
关键词：Mixture model;Progressive First Failure Censored Scheme;Loss Function;Maximum Likelihood Estimation;Bayesian Estimation and Prediction;Markov Chain Monte Carlo
