Inference for Dependent Competing Risks with Partially Observed Causes from Bivariate Inverted Exponentiated Pareto Distribution Under Generalized Progressive Hybrid Censoring

In this paper, inference under dependent competing risk data is considered with multiple causes of failure. We discuss both classical and Bayesian methods for estimating model parameters under the assumption that data are observed under generalized progressive hybrid censoring. The maximum likelihoo...

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Bibliographic Details
Main Authors: Rani Kumari, Yogesh Mani Tripathi, Rajesh Kumar Sinha, Liang Wang
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Axioms
Subjects:
Online Access:https://www.mdpi.com/2075-1680/14/3/217
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