期刊
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
卷 -, 期 -, 页码 -出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/03610918.2021.2023180
关键词
Bayes estimation; credible interval; EM algorithm; joint progressive censoring; Lindley's approximation; maximum likelihood estimation
This article investigates the joint Type-II progressive censoring scheme for two populations with lifetimes following Topp-Leone models, but with unknown parameters. Classical and Bayesian inferences are used to estimate the parameters, and Monte Carlo simulation is conducted to compare the performance of the methods.
Recently, the progressive Type-II censoring has been extended to a more general censoring scheme, called joint progressive Type-II censoring, which studies the lifetimes of two or more populations simultaneously. In this article, we consider the joint Type-II progressive censoring scheme for two populations when their lifetimes follow Topp-Leone models with unknown common scale parameter but different shape parameters. Classical and Bayesian inferences are studied. Expectation-Maximization (EM) algorithm is implemented for obtaining the maximum likelihood estimators (MLEs) and the associated asymptotic confidence intervals of the unknown parameters. Bayesian inferences are discussed based on a beta-gamma prior for the shape parameters and an incomplete inverse gamma prior for the scale parameter. Importance sampling method is proposed to approximate the Bayes estimates. The associated Bayesian credible intervals are also established. Monte Carlo simulation study is performed to compare the performance of the proposed methods. Finally, a real data set representing two different algorithms for estimating unit capacity factors is analyzed for illustrative purposes.
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