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- Title
Reliability Estimation for Dependent Left-Truncated and Right-Censored Competing Risks Data with Illustrations.
- Authors
Zuo, Zhiyuan; Wang, Liang; Lio, Yuhlong
- Abstract
In this paper, a competing risks model with dependent causes of failure is considered under left-truncated and right-censoring scenario. When the dependent failure causes follow a Marshall–Olkin bivariate exponential distribution, estimation of model parameters and reliability indices are proposed from classic and Bayesian approaches, respectively. Maximum likelihood estimators and approximate confidence intervals are constructed, and conventional Bayesian point and interval estimations are discussed as well. In addition, E-Bayesian estimators are proposed and their asymptotic behaviors have been investigated. Further, another objective-Bayesian analysis is also proposed when a noninformative probability matching prior is used. Finally, extensive simulation studies are carried out to investigate the performance of different methods. Two real data examples are presented to illustrate the applicability.
- Subjects
COMPETING risks; DISTRIBUTION (Probability theory); MAXIMUM likelihood statistics; FIX-point estimation; BIVARIATE analysis; FAILURE time data analysis; BAYESIAN analysis; RELIABILITY in engineering
- Publication
Energies (19961073), 2023, Vol 16, Issue 1, p62
- ISSN
1996-1073
- Publication type
Article
- DOI
10.3390/en16010062