%0 Journal Article
%T Pivotal and Bayesian inference in exponential coherent systems under progressive censoring
%J Journal of Advanced Mathematical Modeling
%I Shahid Chamran University of Ahvaz
%Z 2251-8088
%A Fallah, Adeleh
%A Asgharzadeh, Akbar
%D 2021
%\ 09/23/2021
%V 11
%N 3
%P 496-514
%! Pivotal and Bayesian inference in exponential coherent systems under progressive censoring
%K Coherent system
%K System signature
%K Exponential distribution
%K Estimation based on pivotal quantity
%K Bayesian estimation
%R 10.22055/jamm.2021.36145.1888
%X In this paper, statistical inference is considered for k-component coherent systems, when the system lifetime data is progressively type-II censored. In these coherent systems, it is assumed that the system structure and system signature are known and the component lifetime distribution is exponential. Pivotal and Bayesian methods are introduced for point estimation of the component lifetime parameter, and these methods are compared with the maximum likelihood and the least squares methods existing in the literature. Pivotal confidence interval, Bayesian confidence interval and confidence interval based on the likelihood ratio test are computed. Using Monte Carlo simulations, different point and interval estimates are compared and it is observed that pivotal and Bayesian methods perform better than other existing estimation methods.
%U https://jamm.scu.ac.ir/article_16975_b187128c3022b751d0ba30e1db249210.pdf