Estimating the Inverted Kumaraswamy Parameters With Competing Risks Under Type-II Generalized Hybrid Censoring Scheme

Gamal M. Ismail, Afrah Al-Bossly, Manal M. Alloqmani and Samah M. Ahmed

Journal of Mathematics, 2026, vol. 2026, 1-21

Abstract: This research develops frequentist and Bayesian estimation procedures for the inverted Kumaraswamy distribution under a Type-II generalized hybrid censoring scheme with competing risks. Key contributions include the derivation of the maximum likelihood estimator via the Newton–Raphson algorithm and the construction of asymptotic and bootstrap confidence intervals. Additionally, a Bayesian approach using Markov chain Monte Carlo (MCMC) and gamma priors is introduced to provide Bayesian estimates and credible intervals under different loss functions. The performance of these methods is rigorously assessed through Monte Carlo simulations and a real-data application, providing practical guidelines for analyzing complex lifetime data.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:4330595

DOI: 10.1155/jom/4330595

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