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Classical and Bayesian Inference for the Weibull-Poisson Distribution under Progressive Type-II Censoring with Informative Removals
Alaa Falah Hasan , Maryam Sharafi *
Abstract:   (9 Views)
Unlike traditional methods that assume removals are independent of the failure process, this paper presents a novel approach for classical and Bayesian inference under progressive Type-II censoring with informative random removals. Under a Weibull-Poisson lifetime model, two removal distributions—the truncated Poisson and truncated discrete Weibull—are introduced. Due to their structural dependence on the model parameters, these distributions enhance estimation accuracy under heavy censoring. Finally, the superiority of the proposed methods is evaluated through Monte Carlo simulations and the analysis of real data on remission times of bladder cancer patients.
Keywords: Binomial random removals, Censoring, Informative removals, Weibull-Poisson distribution.
Full-Text [PDF 814 kb]   (4 Downloads)    
Type of Study: Research | Subject: Statistical Inference
Received: 2026/08/18 | Accepted: 2027/03/1
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